“A characterization of Gaucher iPS-derived astrocytes: Potential implications for Parkinson’s disease” (2020) Neurobiology of Disease
A characterization of Gaucher iPS-derived astrocytes: Potential implications for Parkinson’s disease
(2020) Neurobiology of Disease, 134, art. no. 104647, .
Aflaki, E.a , Stubblefield, B.K.a , McGlinchey, R.P.b , McMahon, B.a , Ory, D.S.c , Sidransky, E.a
a Section of Molecular Neurogenetics, National Human Genome Research Institute, NIH, Bethesda, MD 20892, United States
b Laboratory of Protein Conformation and Dynamics, National Heart Lung and Blood Institute, NIH, Bethesda, MD 20892, United States
c Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
Abstract
While astrocytes, the most abundant cells found in the brain, have many diverse functions, their role in the lysosomal storage disorder Gaucher disease (GD) has not been explored. GD, resulting from the inherited deficiency of the enzyme glucocerebrosidase and subsequent accumulation of glucosylceramide and its acylated derivative glucosylsphingosine, has both non-neuronopathic (GD1) and neuronopathic forms (GD2 and 3). Furthermore, mutations in GBA1, the gene mutated in GD, are an important risk factor for Parkinson’s disease (PD). To elucidate the role of astrocytes in the disease pathogenesis, we generated iAstrocytes from induced pluripotent stem cells made from fibroblasts taken from controls and patients with GD1, with and without PD. We also made iAstrocytes from an infant with GD2, the most severe and progressive form, manifesting in infancy. Gaucher iAstrocytes appropriately showed deficient glucocerebrosidase activity and levels and substrate accumulation. These cells exhibited varying degrees of astrogliosis, Glial Fibrillary Acidic Protein (GFAP) up-regulation and cellular proliferation, depending on the level of residual glucocerebrosidase activity. Glutamte uptake assays demonstrated that the cells were functionally active, although the glutamine transporter EEAT2 was upregulated and EEAT1 downregulated in the GD2 samples. GD2 iAstrocytes were morphologically different, with severe cytoskeletal hypertrophy, overlapping of astrocyte processes, pronounced up-regulation of GFAP and S100β, and significant astrocyte proliferation, recapitulating the neuropathology observed in patients with GD2. Although astrocytes do not express α-synuclein, when the iAstrocytes were co-cultured with dopaminergic neurons generated from the same iPSC lines, excessive α-synuclein released from neurons was endocytosed by astrocytes, translocating into lysosomes. Levels of aggregated α-synuclein increased significantly when cells were treated with monomeric or fibrillar α-synuclein. GD1-PD and GD2 iAstrocytes also exhibited impaired Cathepsin D activity, leading to further α-synuclein accumulation. Cytokine and chemokine profiling of the iAstrocytes demonstrated an inflammatory response. Thus, in patients with GBA1-associated parkinsonism, astrocytes appear to play a role in α-synuclein accumulation and processing, contributing to neuroinflammation. © 2019 Elsevier Inc.
Author Keywords
Alpha-synuclein; Astrocytes; Gaucher disease; GBA1; Glucocerebrosidase; Induced pluriopotent stem cells; Parkinson’s disease
Document Type: Article
Publication Stage: Final
Source: Scopus
“Intramuscular blood flow in Duchenne and Becker Muscular Dystrophy: Quantitative power Doppler sonography relates to disease severity” (2020) Clinical Neurophysiology
Intramuscular blood flow in Duchenne and Becker Muscular Dystrophy: Quantitative power Doppler sonography relates to disease severity
(2020) Clinical Neurophysiology, 131 (1), pp. 1-5.
Dietz, A.R.a b , Connolly, A.d , Dori, A.b c , Zaidman, C.M.b
a Blue Sky Neurology, Englewood, CO, United States
b Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
c Department of Neurology, Talpiot Medical Leadership Program, Chaim Sheba Medical Center, Tel HaShomer, and Joseph Sagol Neuroscience Center, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
d Department of Pediatrics, Division of Neurology, Nationwide Children’s Hospital, Columbus, OH, United States
Abstract
Objective: Absent or truncated dystrophin in Duchenne (DMD) and Becker (BMD) muscular dystrophies results in impaired vasodilatory pathways and exercise induced muscle ischemia. Here, we used power Doppler sonography to quantify changes in intramuscular blood flow immediately following exercise in boys with D/BMD. Method: We quantified changes in intramuscular blood flow following exercise using power Doppler sonography in 14 boys with D/BMD and compared changes in muscle blood flow to disease severity and to historic controls. Result: Post exercise blood flow change in the anterior forearm muscles is lower in (1) DMD (median 0.25%; range −0.47 to 2.19%) than BMD (2.46%; 2.02–3.38%, p < 0.05) and historical controls (6.59%; 2.16–12.40%, p < 0.01); (2) in non-ambulatory (0.04%; −0.47 to 0.10%) than ambulatory DMD boys (0.71%; 0.07–2.19%, p < 0.05); and (3) in muscle with higher echointensity (rs = −0.7253, p = 0.005). The tibialis anterior showed similar findings. We estimate that a single sample clinical trial would require 19 subjects to detect a doubling of blood flow to the anterior forearm after the intervention. Conclusion: Post-exercise blood flow is reduced in D/BMD and relates to disease severity. Significance: Our protocol for quantifying post-exercise intramuscular blood flow is feasible for clinical trials in D/BMD. © 2019
Author Keywords
Blood flow; Doppler; Dystrophy; Exercise; Muscle; Ultrasound
Document Type: Article
Publication Stage: Final
Source: Scopus
“Changes in alcohol and cigarette consumption in response to medical and recreational cannabis legalization: Evidence from U.S. state tax receipt data” (2020) International Journal of Drug Policy
Changes in alcohol and cigarette consumption in response to medical and recreational cannabis legalization: Evidence from U.S. state tax receipt data
(2020) International Journal of Drug Policy, 75, art. no. 102585, .
Veligati, S.a , Howdeshell, S.a b , Beeler-Stinn, S.a b , Lingam, D.a , Allen, P.C.b , Chen, L.-S.c , Grucza, R.A.c
a Master of Population Health Sciences Program, Washington University, St. Louis, MO, United States
b Brown School, Washington University, St. Louis, MO, United States
c Department of Psychiatry, School of Medicine, Washington University, 660 South Euclid Avenue, Box 8134, St. Louis, MO 63110, United States
Abstract
Background: Whether medical or recreational cannabis legalization impacts alcohol or cigarette consumption is a key question as cannabis policy evolves, given the adverse health effects of these substances. Relatively little research has examined this question. The objective of this study was to examine whether medical or recreational cannabis legalization was associated with any change in state-level per capita alcohol or cigarette consumption. Methods: Dependent variables included per capita consumption of alcohol and cigarettes from all 50 U.S. states, estimated from state tax receipts and maintained by the Centers for Disease Control and National Institute for Alcohol Abuse and Alcoholism, respectively. Independent variables included indicators for medical and recreational legalization policies. Three different types of indicators were separately used to model medical cannabis policies. Indicators for the primary model were based on the presence of active medical cannabis dispensaries. Secondary models used indicators based on either the presence of a more liberal medical cannabis policy (“non-medicalized”) or the presence of any medical cannabis policy. Difference-in-difference regression models were applied to estimate associations for each type of policy. Results: Primary models found no statistically significant associations between medical or recreational cannabis legalization policies and either alcohol or cigarette sales per capita. In a secondary model, both medical and recreational policies were associated with significantly decreased per capita cigarette sales compared to states with no medical cannabis policy. However, post hoc analyses demonstrated that these reductions were apparent at least two years prior to policy adoption, indicating that they likely result from other time-varying characteristics of legalization states, rather than cannabis policy. Conclusion: We found no evidence of a causal association between medical or recreational cannabis legalization and changes in either alcohol or cigarette sales per capita. © 2019 Elsevier B.V.
Author Keywords
Alcohol; Cannabis; Complementarity; Legalization; Marijuana; Medical cannabis; Substitution; Tobacco
Document Type: Article
Publication Stage: Final
Source: Scopus
“Focal left prefrontal lesions and cognitive impairment: A multivariate lesion-symptom mapping approach” (2020) Neuropsychologia
Focal left prefrontal lesions and cognitive impairment: A multivariate lesion-symptom mapping approach
(2020) Neuropsychologia, 136, art. no. 107253, .
Arbula, S.a b , Ambrosini, E.a c , Della Puppa, A.d , De Pellegrin, S.e , Anglani, M.f , Denaro, L.a g , Piccione, F.h , D’Avella, D.a g , Semenza, C.i j , Corbetta, M.i k , Vallesi, A.h i
a Department of Neuroscience, University of Padova, Italy
b Area of Neuroscience, SISSA, Trieste, Italy
c Department of General Psychology, University of Padova, Padova, Italy
d Department of Neurosurgery, University of Florence, Careggi Hospital, Florence, Italy
e Department of Neuroscience, University Hospital of Padova, Padova, Italy
f Neuroradiology Unit, University Hospital of Padova, Padova, Italy
g Academic Neurosurgery, Department of Neuroscience, University of Padova Medical School, Italy
h Brain Imaging & Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
i Department of Neuroscience & Padua Neuroscience Center, University of Padova, Italy
j Cognitive Neuroscience Research Group, IRCCS San Camillo Hospital, Venice, Italy
k Washington University School of Medicine, St. Louis, United States
Abstract
Despite network studies of the human brain have brought consistent evidence of brain regions with diverse functional roles, the neuropsychological approach has mainly focused on the functional specialization of individual brain regions. Relatively few neuropsychological studies try to understand whether the severity of cognitive impairment across multiple cognitive abilities can be related to focal brain injuries. Here we approached this issue by applying a latent variable modeling of the severity of cognitive impairment in brain tumor patients, followed by multivariate lesion-symptom methods identifying brain regions critically involved in multiple cognitive abilities. We observed that lesions in confined left lateral prefrontal areas including the inferior frontal junction produced the most severe cognitive deficits, above and beyond tumor histology. Our findings support the recently suggested integrated albeit modular view of brain functional organization, according to which specific brain regions are highly involved across different sub-networks and subserve a vast range of cognitive abilities. Defining such brain regions is relevant not only theoretically but also clinically, since it may facilitate tailored tumor resections and improve cognitive surgical outcomes. © 2019 Elsevier Ltd
Author Keywords
Brain tumor; Cognitive dysfunction; Dorsolateral prefrontal cortex; Frontal lobe; Multivariate lesion-symptom mapping; Principal component analysis
Document Type: Article
Publication Stage: Final
Source: Scopus
“A regulatory variant of CHRM3 is associated with cannabis-induced hallucinations in European Americans” (2019) Translational Psychiatry
A regulatory variant of CHRM3 is associated with cannabis-induced hallucinations in European Americans
(2019) Translational Psychiatry, 9 (1), art. no. 309, .
Cheng, Z.a , Phokaew, C.a , Chou, Y.-L.b , Lai, D.c , Meyers, J.L.d , Agrawal, A.b , Farrer, L.A.e , Kranzler, H.R.f , Gelernter, J.a g
a Division of Human Genetics, Department of Psychiatry, VA CT Healthcare Center, Yale University School of Medicine, New Haven, CT, United States
b Department of Psychiatry, Washington University School of Medicine, St. Louis, MI, United States
c Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
d Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, United States
e Departments of Neurology, Ophthalmology, Genetics & Genomics, Epidemiology and Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, United States
f Department of Psychiatry, Center for Studies of Addiction and Crescenz Veterans Affairs Medical Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
g Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, United States
Abstract
Cannabis, the most widely used illicit drug, can induce hallucinations. Our understanding of the biology of cannabis-induced hallucinations (Ca-HL) is limited. We used the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA) to identify cannabis-induced hallucinations (Ca-HL) among long-term cannabis users (used cannabis ≥1 year and ≥100 times). A genome-wide association study (GWAS) was conducted by analyzing European Americans (EAs) and African Americans (AAs) in Yale-Penn 1 and 2 cohorts individually, then meta-analyzing the two cohorts within population. In the meta-analysis of Yale-Penn EAs (n = 1917), one genome-wide significant (GWS) signal emerged at the CHRM3 locus, represented by rs115455482 (P = 1.66 × 10−10), rs74722579 (P = 2.81 × 10−9), and rs1938228 (P = 1.57 × 10−8); signals were GWS in Yale-Penn 1 EAs (n = 1092) and nominally significant in Yale-Penn 2 EAs (n = 825). Two SNPs, rs115455482 and rs74722579, were available from the Collaborative Study on the Genetics of Alcoholism data (COGA; 3630 long-term cannabis users). The signals did not replicate, but when meta-analyzing Yale-Penn and COGA EAs, the two SNPs’ association signals were increased (meta-P-values 1.32 × 10−10 and 2.60 × 10−9, respectively; n = 4291). There were no significant findings in AAs, but in the AA meta-analysis (n = 3624), nominal significance was seen for rs74722579. The rs115455482*T risk allele was associated with lower CHRM3 expression in the thalamus. CHRM3 was co-expressed with three psychosis risk genes (GABAG2, CHRNA4, and HRH3) in the thalamus and other human brain tissues and mouse GABAergic neurons. This work provides strong evidence for the association of CHRM3 with Ca-HL and provides insight into the potential involvement of thalamus for this trait. © 2019, The Author(s).
Document Type: Article
Publication Stage: Final
Source: Scopus
“Whole-cortex mapping of common genetic influences on depression and a social deficits dimension” (2019) Translational Psychiatry
Whole-cortex mapping of common genetic influences on depression and a social deficits dimension
(2019) Translational Psychiatry, 9 (1), art. no. 299, .
Hatoum, A.S.a b , Reineberg, A.E.a , Smolker, H.R.a c , Hewitt, J.K.a c , Friedman, N.P.a c
a Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, United States
b Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
c Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, United States
Abstract
Social processes are associated with depression, particularly understanding and responding to others, deficits in which can manifest as callousness/unemotionality (CU). Thus, CU may reflect some of the genetic risk to depression. Further, this vulnerability likely reflects the neurological substrates of depression, presenting biomarkers to capture genetic vulnerability of depression severity. However, heritability varies within brain regions, so a high-resolution genetic perspective is needed. We developed a toolbox that maps genetic and environmental associations between brain and behavior at high resolution. We used this toolbox to estimate brain areas that are genetically associated with both depressive symptoms and CU in a sample of 258 same-sex twin pairs from the Colorado Longitudinal Twin Study (LTS). We then overlapped the two maps to generate coordinates that allow for tests of downstream effects of genes influencing our clusters. Genetic variance influencing cortical thickness in the right dorsal lateral prefrontal cortex (DLFPC) sulci and gyri, ventral posterior cingulate cortex (PCC), pre-somatic motor cortex (PreSMA), medial precuneus, left occipital-temporal junction (OTJ), parietal–temporal junction (PTJ), ventral somatosensory cortex (vSMA), and medial and lateral precuneus were genetically associated with both depression and CU. Split-half replication found support for both DLPFC clusters. Meta-analytic term search identified “theory of mind”, “inhibit”, and “pain” as likely functions. Gene and transcript mapping/enrichment analyses implicated calcium channels. CU reflects genetic vulnerability to depression that likely involves executive and social functioning in a distributed process across the cortex. This approach works to unify neuroimaging, neuroinformatics, and genetics to discover pathways to psychiatric vulnerability. © 2019, The Author(s).
Document Type: Article
Publication Stage: Final
Source: Scopus
“Validation of the Disabilities of the Arm, Shoulder, and Hand in Patients Undergoing Cervical Spine Surgery” (2019) Spine
Validation of the Disabilities of the Arm, Shoulder, and Hand in Patients Undergoing Cervical Spine Surgery
(2019) Spine, 44 (23), pp. 1676-1684.
Khalifeh, J.M., Akbari, S.H.A., Khandpur, U., Johnston, W., Wright, N.M., Hawasli, A.H., Dorward, I., Santiago, P., Ray, W.Z.
Department of Neurological Surgery, Washington University School of Medicine, MO, Saint Louis, Seychelles
Abstract
STUDY DESIGN: Retrospective cohort study. OBJECTIVE: To evaluate the performance and convergent validity of the disabilities of the arm, shoulder, and hand (DASH) in comparison with the visual analog scale (VAS) for pain, and neck disability index (NDI) in patients undergoing cervical spine surgery. SUMMARY OF BACKGROUND DATA: Neck-specific disability scales do not adequately assess concurrent upper extremity involvement in patients with cervical spine disorders. The DASH is a patient-reported outcomes (PRO) instrument designed to measure functional disability due to upper extremity conditions but has additionally been shown to perform well in patients with neck disorders. METHODS: We identified patients who underwent cervical spine surgery at our institution between 2013 and 2016. We collected demographic information, clinical characteristics, and PRO measures-DASH, VAS, NDI-preoperatively, as well as early and late postoperatively. We calculated descriptive statistics and changes from baseline in PROs. Correlation coefficients were used to quantify the association between PRO measures. The analysis was stratified by radiculopathy and myelopathy diagnoses. RESULTS: A total of 1046 patients (52.8% male) with PROs data at baseline were included in the analysis. The mean age at surgery ± SD was 57.2 ± 11.3 years, and postoperative follow-up duration 12.7 ± 10.7 months. The most common surgical procedure was anterior cervical discectomy and fusion (71.1%). Patients experienced clinically meaningful postoperative improvements in all PRO measures. The DASH showed moderate positive correlations with VAS preoperatively (Spearman rho = 0.43), as well as early (rho = 0.48) and late postoperatively (rho = 0.60). DASH and NDI scores were strongly positively correlated across operative states (Preoperative rho = 0.74, Early Postoperative rho = 0.78, Late Postoperative rho = 0.82). Stratified analysis by preoperative diagnosis showed similar within-groups trends and pairwise correlations. However, radiculopathy patients experienced larger magnitude early and late change scores. CONCLUSION: The DASH is a valid and responsive PRO measure to evaluate disabling upper extremity involvement in patients undergoing cervical spine surgery.3.
Document Type: Article
Publication Stage: Final
Source: Scopus
“A neural network for information seeking” (2019) Nature Communications
A neural network for information seeking
(2019) Nature Communications, 10 (1), art. no. 5168, .
White, J.K.a , Bromberg-Martin, E.S.a , Heilbronner, S.R.b , Zhang, K.c , Pai, J.a d , Haber, S.N.e , Monosov, I.E.a c
a Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
b Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States
c Department of Biomedical Engineering, Washington University, St. Louis, MO, United States
d Center for Neural Science, New York University, New York, NY, United States
e Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, United States
Abstract
Humans and other animals often show a strong desire to know the uncertain rewards their future has in store, even when they cannot use this information to influence the outcome. However, it is unknown how the brain predicts opportunities to gain information and motivates this information-seeking behavior. Here we show that neurons in a network of interconnected subregions of primate anterior cingulate cortex and basal ganglia predict the moment of gaining information about uncertain rewards. Spontaneous increases in their information prediction signals are followed by gaze shifts toward objects associated with resolving uncertainty, and pharmacologically disrupting this network reduces the motivation to seek information. These findings demonstrate a cortico-basal ganglia mechanism responsible for motivating actions to resolve uncertainty by seeking knowledge about the future. © 2019, The Author(s).
Document Type: Article
Publication Stage: Final
Source: Scopus
“Cognitive Decline Over Time in Patients With Systolic Heart Failure: Insights From WARCEF” (2019) JACC: Heart Failure
Cognitive Decline Over Time in Patients With Systolic Heart Failure: Insights From WARCEF
(2019) JACC: Heart Failure, 7 (12), pp. 1042-1053. Cited 1 time.
Lee, T.C.a , Qian, M.a , Liu, Y.a , Graham, S.b , Mann, D.L.c , Nakanishi, K.a , Teerlink, J.R.d , Lip, G.Y.H.e f , Freudenberger, R.S.g , Sacco, R.L.h , Mohr, J.P.a , Labovitz, A.J.i , Ponikowski, P.j , Lok, D.J.k , Matsumoto, K.a , Estol, C.l , Anker, S.D.m n , Pullicino, P.M.o , Buchsbaum, R.a , Levin, B.a , Thompson, J.L.P.a , Homma, S.a , Di Tullio, M.R.a , WARCEF Investigatorsp
a Columbia University Medical Center, New York, NY, United States
b Department of Medicine, State University of New York at Buffalo, Buffalo, NY, United States
c Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
d Section of Cardiology, San Francisco Veterans Affairs Medical Center and School of Medicine, University of California San Francisco, San Francisco, CA, United States
e Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart and Chest Hospital, Liverpool, United Kingdom
f Aalborg Thrombosis Research Unit, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
g Lehigh Valley Hospital, Allentown, PA, United States
h Department of Neurology, University of Miami, Miami, FL, United States
i Department of Medicine, University of South Florida, Tampa, FL, United States
j Military Hospital, Wroclaw, Poland
k Deventer Hospital, Deventer, Netherlands
l Stroke Unit, Sanatorio Guemes, Buenos Aires, Argentina
m Division of Cardiology and Metabolism, Department of Cardiology, and Berlin-Brandenburg Center for Regenerative Therapies, Deutsches Zentrum für Herz-Kreislauf-Forschung partner site Berlin; Charité Universitätsmedizin Berlin, Germany
n Department of Cardiology and Pneumology, University Medicine Göttingen, Göttingen, Germany
o Kent Institute of Medicine and Health Science, Canterbury, United Kingdom
Abstract
Objectives: This study sought to characterize cognitive decline (CD) over time and its predictors in patients with systolic heart failure (HF). Background: Despite the high prevalence of CD and its impact on mortality, predictors of CD in HF have not been established. Methods: This study investigated CD in the WARCEF (Warfarin versus Aspirin in Reduced Ejection Fraction) trial, which performed yearly Mini-Mental State Examinations (MMSE) (higher scores indicate better cognitive function; e.g., normal score: 24 or higher). A longitudinal time-varying analysis was performed among pertinent covariates, including baseline MMSE and MMSE scores during follow-up, analyzed both as a continuous variable and a 2-point decrease. To account for a loss to follow-up, data at the baseline and at the 12-month visit were analyzed separately (sensitivity analysis). Results: A total of 1,846 patients were included. In linear regression, MMSE decrease was independently associated with higher baseline MMSE score (p < 0.0001), older age (p < 0.0001), nonwhite race/ethnicity (p < 0.0001), and lower education (p < 0.0001). In logistic regression, CD was independently associated with higher baseline MMSE scores (odds ratio [OR]: 1.13; 95% confidence interval [CI]: 1.07 to 1.20]; p < 0.001), older age (OR: 1.37; 95% CI: 1.24 to 1.50; p < 0.001), nonwhite race/ethnicity (OR: 2.32; 95% CI: 1.72 to 3.13 for black; OR: 1.94; 95% CI: 1.40 to 2.69 for Hispanic vs. white; p < 0.001), lower education (p < 0.001), and New York Heart Association functional class II or higher (p = 0.03). Warfarin and other medications were not associated with CD. Similar trends were seen in the sensitivity analysis (n = 1,439). Conclusions: CD in HF is predicted by baseline cognitive status, demographic variables, and NYHA functional class. The possibility of intervening on some of its predictors suggests the need for the frequent assessment of cognitive function in patients with HF. (Warfarin versus Aspirin in Reduced Cardiac Ejection Fraction [WARCEF]; NCT00041938) © 2019 American College of Cardiology Foundation
Author Keywords
cognitive function; comorbidities; dementia; longitudinal analysis; Mini-Mental State Examination
Document Type: Article
Publication Stage: Final
Source: Scopus
“Mapping infant neurodevelopmental precursors of mental disorders: How synthetic cohorts & computational approaches can be used to enhance prediction of early childhood psychopathology” (2019) Behaviour Research and Therapy
Mapping infant neurodevelopmental precursors of mental disorders: How synthetic cohorts & computational approaches can be used to enhance prediction of early childhood psychopathology
(2019) Behaviour Research and Therapy, 123, art. no. 103484, .
Luby, J.a , Allen, N.b , Estabrook, R.b , Pine, D.S.c , Rogers, C.a , Krogh-Jespersen, S.b , Norton, E.S.d , Wakschlag, L.b
a Washington University School of Medicine, 4444 Forest Park Avenue, St. Louis, MO 63108, United States
b Northwestern University Feinberg School of Medicine & Institute for Innovations in Developmental Sciences, 633 N. St Clair, 19th Floor, Chicago, IL 60611, United States
c National Institute of Mental Health (NIMH) Intramural Research Program, Building 15K, Room 110, MSC 2670, Bethesda, MD 20814, United States
d Northwestern University, Department of Communication Sciences and Disorders, 2240 Campus Drive, Evanston, IL 60208, United States
Abstract
Bridging advances in neurodevelopmental assessment and the established onset of common psychopathologies in early childhood with epidemiological data science and computational methods holds much promise for identifying risk for mental disorders as early as infancy. In particular, we propose the development of a mental health risk algorithm for the early detection of mental disorders with the potential for high public health impact that applies and adapts methods innovated in and successfully applied to early detection of cardiovascular risk. Specifically, we propose methods to advance risk prediction of early developmental psychopathology by creating synthetic cohorts that contain complete behavioral and neural data in the first years of life, as the basis for a robust and generalizable risk algorithm. The application of computational approaches within synthetic cohorts, an approach increasingly applied in psychiatry, may be particularly well suited to advancing risk prediction in early childhood mental health. We propose new research directions using these methods to generate an early childhood mental health risk calculator that could significantly advance early mental health risk detection to direct preventive intervention and/or need for more intensive assessment within a pragmatic framework for maximal clinical utility. The availability of such a tool in early childhood, a period of high neuroplasticity, holds promise to reduce the burden of mental disorder by identifying risk early in the clinical sequence and delivering prevention that targets the neurodevelopmental vulnerability phase. © 2019
Author Keywords
Child characteristics; Computational methods; Developmental psychopathology; Risk prediction
Document Type: Article
Publication Stage: Final
Source: Scopus
“Associations between polygenic risk for tobacco and alcohol use and liability to tobacco and alcohol use, and psychiatric disorders in an independent sample of 13,999 Australian adults” (2019) Drug and Alcohol Dependence
Associations between polygenic risk for tobacco and alcohol use and liability to tobacco and alcohol use, and psychiatric disorders in an independent sample of 13,999 Australian adults
(2019) Drug and Alcohol Dependence, 205, art. no. 107704, .
Chang, L.-H.a b , Whitfield, J.B.a , Liu, M.c , Medland, S.E.a , Hickie, I.B.d , Martin, N.G.a , Verhulst, B.f , Heath, A.C.g , Madden, P.A.g , Statham, D.J.h , Gillespie, N.A.e , GSCAN Consortiumi
a Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, QLD 4006, Australia
b Faculty of Medicine, the University of Queensland, 20 Weightman St, Herston QLD 4006, Australia
c Department of Psychology, University of Minnesota Twin Cities, 75 E River Rd, Minneapolis, MN 55455, United States
d Brain and Mind Centre, University of Sydney, 94 Mallett St, Camperdown, NSW 2050, United States
e Virginia Institute for Psychiatric and Behavioural Genetics, Virginia Commonwealth University, Richmond, VA 23298, United States
f Department of psychology, Michigan State University, 316 Physics Road #262, East Lansing, MI 48824, United States
g Department of Psychiatry, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63110, United States
h School of Health and Life Sciences, Federation University, Federation University Australia, PO Box 663, Ballarat, VIC 3353, Australia
Abstract
Background: Substance use, substance use disorders (SUDs), and psychiatric disorders commonly co-occur. Genetic risk common to these complex traits is an important explanation; however, little is known about how polygenic risk for tobacco or alcohol use overlaps the genetic risk for the comorbid SUDs and psychiatric disorders. Methods: We constructed polygenic risk scores (PRSs) using GWAS meta-analysis summary statistics from a large discovery sample, GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN), for smoking initiation (SI; N = 631,564), age of initiating regular smoking (AI; N = 258,251), cigarettes per day (CPD; N = 258,999), smoking cessation (SC; N = 312,273), and drinks per week (DPW; N = 527,402). We then estimated the fixed effect of these PRSs on the liability to 15 phenotypes related to tobacco and alcohol use, substance use disorders, and psychiatric disorders in an independent target sample of Australian adults. Results: After adjusting for multiple testing, 10 of 75 combinations of discovery and target phenotypes remained significant. PRS-SI (R2 range: 1.98%–5.09 %) was positively associated with SI, DPW, and with DSM-IV and FTND nicotine dependence, and conduct disorder. PRS-AI (R2: 3.91 %) negatively associated with DPW. PRS-CPD (R2: 1.56 %–1.77 %) positively associated with DSM-IV nicotine dependence and conduct disorder. PRS-DPW (R2: 3.39 %–6.26 %) positively associated with only DPW. The variation of DPW was significantly influenced by sex*PRS-SI, sex*PRS-AI and sex*PRS-DPW. Such interaction effect was not detected in the other 14 phenotypes. Conclusions: Polygenic risks associated with tobacco use are also associated with liability to alcohol consumption, nicotine dependence, and conduct disorder. © 2019 Elsevier B.V.
Author Keywords
Alcohol dependence; Conduct disorder; Genetics; Genotype by sex interaction; Nicotine dependence; Polygenic risk score; Twins
Document Type: Article
Publication Stage: Final
Source: Scopus
“Cortical Circuit Dynamics Are Homeostatically Tuned to Criticality In Vivo” (2019) Neuron, 104 (4), pp. 655-664.e4
Cortical Circuit Dynamics Are Homeostatically Tuned to Criticality In Vivo
(2019) Neuron, 104 (4), pp. 655-664.e4. Cited 1 time.
Ma, Z.a , Turrigiano, G.G.b , Wessel, R.a , Hengen, K.B.c
a Department of Physics, Washington University in St. Louis, St. Louis, MO 63130, United States
b Department of Biology, Brandeis University, Waltham, MA 02453, United States
c Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, United States
Abstract
Homeostatic mechanisms stabilize neuronal activity in vivo, but whether this process gives rise to balanced network dynamics is unknown. Here, we continuously monitored the statistics of network spiking in visual cortical circuits in freely behaving rats for 9 days. Under control conditions in light and dark, networks were robustly organized around criticality, a regime that maximizes information capacity and transmission. When input was perturbed by visual deprivation, network criticality was severely disrupted and subsequently restored to criticality over 48 h. Unexpectedly, the recovery of excitatory dynamics preceded homeostatic plasticity of firing rates by >30 h. We utilized model investigations to manipulate firing rate homeostasis in a cell-type-specific manner at the onset of visual deprivation. Our results suggest that criticality in excitatory networks is established by inhibitory plasticity and architecture. These data establish that criticality is consistent with a homeostatic set point for visual cortical dynamics and suggest a key role for homeostatic regulation of inhibition. © 2019 Elsevier Inc.
Ma et al. evaluate long-term computational dynamics in the visual cortex. Cortical circuits exhibit criticality, a regime that maximizes information processing. Using monocular deprivation, the authors demonstrate that criticality is consistent with a homeostatic set point of emergent dynamics. © 2019 Elsevier Inc.
Author Keywords
computation; cortex; criticality; dynamics; homeostasis; homeostatic plasticity; modeling; visual cortex
Document Type: Article
Publication Stage: Final
Source: Scopus
“Economic Decisions through Circuit Inhibition” (2019) Current Biology
Economic Decisions through Circuit Inhibition
(2019) Current Biology, 29 (22), pp. 3814-3824.e5.
Ballesta, S.a , Padoa-Schioppa, C.a b c
a Department of Neuroscience, Washington University in St. Louis, St. Louis, MO 63110, United States
b Department of Economics, Washington University in St. Louis, St. Louis, MO 63110, United States
c Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, United States
Abstract
Ballesta and Padoa-Schioppa show that similar groups of neurons in the primate orbitofrontal cortex engage in choices between goods offered simultaneously or in sequence. Their results suggest that economic decisions rely on mechanisms of circuit inhibition whereby each offer value indirectly inhibits cells encoding the opposite choice outcome. © 2019 The Author(s)
Economic choices between goods are thought to rely on the orbitofrontal cortex (OFC), but the decision mechanisms remain poorly understood. To shed light on this fundamental issue, we recorded from the OFC of monkeys choosing between two juices offered sequentially. An analysis of firing rates across time windows revealed the presence of different groups of neurons similar to those previously identified under simultaneous offers. This observation suggested that economic decisions in the two modalities are formed in the same neural circuit. We then examined several hypotheses on the decision mechanisms. OFC neurons encoded good identities and values in a juice-based representation (labeled lines). Contrary to previous assessments, our data argued against the idea that decisions rely on mutual inhibition at the level of offer values. In fact, we showed that previous arguments for mutual inhibition were confounded by differences in value ranges. Instead, decisions seemed to involve mechanisms of circuit inhibition, whereby each offer value indirectly inhibited neurons encoding the opposite choice outcome. Our results reconcile a variety of previous findings and provide a general account for the neuronal underpinnings of economic choices. © 2019 The Author(s)
Author Keywords
attention; decision making; good-based model; monkey; mutual inhibition; neuroeconomics; neurophysiology; orbitofrontal cortex; sequential offers; subjective value
Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access
“Chronic Opioid Therapy and Sleep: An American Academy of Sleep Medicine Position Statement” (2019) Journal of Clinical Sleep Medicine : JCSM : Official Publication of the American Academy of Sleep Medicine
Chronic Opioid Therapy and Sleep: An American Academy of Sleep Medicine Position Statement
(2019) Journal of Clinical Sleep Medicine : JCSM : Official Publication of the American Academy of Sleep Medicine, 15 (11), pp. 1671-1673.
Rosen, I.M.a , Aurora, R.N.b , Kirsch, D.B.c , Carden, K.A.d , Malhotra, R.K.e , Ramar, K.f , Abbasi-Feinberg, F.g , Kristo, D.A.h , Martin, J.L.i j , Olson, E.J.f , Rosen, C.L.k , Rowley, J.A.l , Shelgikar, A.V.m , American Academy of Sleep Medicine Board of Directorsn
a Division of Sleep Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
b Department of Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey
c Sleep Medicine, Atrium Health, Charlotte, North Carolina
d Saint Thomas Medical Partners – Sleep Specialists, Nashville, TN, United States
e Sleep Medicine Center, Washington University School of Medicine, St. Louis, MO, United States
f Division of Pulmonary and Critical Care Medicine, Center for Sleep Medicine, Mayo Clinic, Rochester, MN
g Millennium Physician Group, Fort Myers, FL, United States
h University of Pittsburgh, Pittsburgh, PA, United States
i Veteran Affairs Greater Los Angeles Healthcare System, North HillsCA
j David Geffen School of Medicine at the University of California, Los Angeles, CA, Mexico
k Department of Pediatrics, Case Western Reserve University, University Hospitals – Cleveland Medical Center, Cleveland, OH, United States
l Wayne State University, Detroit, MI, United States
m University of Michigan Sleep Disorders Center, University of Michigan, Ann Arbor, MI, United States
Abstract
None: There is a complex relationship among opioids, sleep and daytime function. Patients and medical providers should be aware that chronic opioid therapy can alter sleep architecture and sleep quality as well as contribute to daytime sleepiness. It is also important for medical providers to be cognizant of other adverse effects of chronic opioid use including the impact on respiratory function during sleep. Opioids are associated with several types of sleep-disordered breathing, including sleep-related hypoventilation, central sleep apnea (CSA), and obstructive sleep apnea (OSA). Appropriate screening, diagnostic testing, and treatment of opioid-associated sleep-disordered breathing can improve patients’ health and quality of life. Collaboration among medical providers is encouraged to provide high quality, patient-centered care for people who are treated with chronic opioid therapy. © 2019 American Academy of Sleep Medicine.
Document Type: Article
Publication Stage: Final
Source: Scopus
“Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration” (2019) Nature Communications
Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration
(2019) Nature Communications, 10 (1), p. 5121.
Noordam, R.a , Bos, M.M.a , Wang, H.b , Winkler, T.W.c , Bentley, A.R.d , Kilpeläinen, T.O.e f , de Vries, P.S.g , Sung, Y.J.h , Schwander, K.h , Cade, B.E.b , Manning, A.i j , Aschard, H.k l , Brown, M.R.g , Chen, H.g m , Franceschini, N.n , Musani, S.K.o , Richard, M.p , Vojinovic, D.q , Aslibekyan, S.r , Bartz, T.M.s , de Las Fuentes, L.h t , Feitosa, M.u , Horimoto, A.R.v , Ilkov, M.w , Kho, M.x , Kraja, A.u , Li, C.y , Lim, E.z , Liu, Y.aa , Mook-Kanamori, D.O.ab ac , Rankinen, T.ad , Tajuddin, S.M.ae , van der Spek, A.q , Wang, Z.g , Marten, J.af , Laville, V.l , Alver, M.ag ah , Evangelou, E.ai aj , Graff, M.E.n , He, M.ak , Kühnel, B.al am , Lyytikäinen, L.-P.an ao , Marques-Vidal, P.ap , Nolte, I.M.aq , Palmer, N.D.ar , Rauramaa, R.as , Shu, X.-O.at , Snieder, H.aq , Weiss, S.au , Wen, W.at , Yanek, L.R.av , Adolfo, C.o , Ballantyne, C.aw ax , Bielak, L.x , Biermasz, N.R.ay az , Boerwinkle, E.g ba , Dimou, N.aj , Eiriksdottir, G.w , Gao, C.bb , Gharib, S.A.bc , Gottlieb, D.J.b j bd , Haba-Rubio, J.be , Harris, T.B.bf , Heikkinen, S.bg bh , Heinzer, R.be , Hixson, J.E.g , Homuth, G.au , Ikram, M.A.q bi , Komulainen, P.as , Krieger, J.E.v , Lee, J.b , Liu, J.bj , Lohman, K.K.bk , Luik, A.I.q , Mägi, R.ag , Martin, L.W.bl , Meitinger, T.bm , Metspalu, A.ag ah , Milaneschi, Y.bl , Nalls, M.A.bn bo , O’Connell, J.bp bq , Peters, A.am br , Peyser, P.x , Raitakari, O.T.bs bt , Reiner, A.P.bj , Rensen, P.C.N.ay az , Rice, T.K.h , Rich, S.S.bu , Roenneberg, T.bv , Rotter, J.I.bw , Schreiner, P.J.bx , Shikany, J.by , Sidney, S.S.bz , Sims, M.o , Sitlani, C.M.ca , Sofer, T.b cb , Strauch, K.cc cd , Swertz, M.A.ce , Taylor, K.D.bw , Uitterlinden, A.G.q cf , van Duijn, C.M.q cg , Völzke, H.ch , Waldenberger, M.al am br , Wallance, R.B.ci , van Dijk, K.W.ay az cj , Yu, C.ak , Zonderman, A.B.ck , Becker, D.M.av , Elliott, P.ah cl cm cn , Esko, T.ag co , Gieger, C.al cp , Grabe, H.J.cq , Lakka, T.A.as bh cr , Lehtimäki, T.an ao , North, K.E.n , Penninx, B.W.J.H.cs , Vollenweider, P.ap , Wagenknecht, L.E.ct , Wu, T.ak , Xiang, Y.-B.cu , Zheng, W.at , Arnett, D.K.cv , Bouchard, C.ad , Evans, M.K.ae , Gudnason, V.w cw , Kardia, S.x , Kelly, T.N.cx , Kritchevsky, S.B.cy , Loos, R.J.F.cz da , Pereira, A.C.v , Province, M.u , Psaty, B.M.db dc , Rotimi, C.d , Zhu, X.dd , Amin, N.q , Cupples, L.A.z de , Fornage, M.p , Fox, E.F.df , Guo, X.bw , Gauderman, W.J.dg , Rice, K.dh , Kooperberg, C.bj , Munroe, P.B.di dj , Liu, C.-T.z , Morrison, A.C.g , Rao, D.C.h , van Heemst, D.a , Redline, S.b dk
a Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, Netherlands
b Division of Sleep and Circadian Disorders, Harvard Medical School, Brigham and Women’s Hospital, MA, Boston, United States
c Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
d Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, MD, Bethesda, United States
e Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, 2200, Denmark
f Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount SinaiNY, United States
g Human Genetics Center, Department of Epidemiology, Human Genetics, Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, TX, Houston, United States
h Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
i Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, MA, Boston, United States
j Department of Medicine, Harvard Medical School, MA, Boston, United States
k Department of Epidemiology, MA, Harvard School of Public Health, Boston, United States
l Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Institut Pasteur, Paris, France
m Center for Precision Health, School of Public Health & School of Biomedical Informatics, University of Texas Health Science Center at Houston, TX, Houston, United States
n Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, United States
o Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, MS, Jackson, United States
p Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, TX, Houston, United States
q Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
r Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
s Cardiovascular Health Research Unit, Biostatistics and Medicine, University of Washington, Seattle, WA, USA
t Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
u Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
v Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, Brazil
w Icelandic Heart Association, Kopavogur, Iceland
x Department of Epidemiology, School of Public Health, University of Michigan, MI, Ann Arbor, United States
y Epidemiology and Biostatistics, University of Georgia at Athens College of Public Health, Athens, United States
z Department of Biostatistics, Boston University School of Public Health, MA, Boston, United States
aa Public Health Sciences, Epidemiology and Prevention, Wake Forest University Health Sciences, Winston-Salem, United States
ab Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands
ac Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands
ad Human Genomics Laboratory, Pennington Biomedical Research Center, LA, Baton Rouge, United States
ae Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, MD, Baltimore, United States
af Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
ag Estonian Genome Center, Institute of Genomics, University of TartuTartu, Estonia
ah Department of Biotechnology, Institute of Molecular and Cell Biology, University of TartuTartu, Estonia
ai Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
aj Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
ak Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
al Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, Helmholtz Zentrum MünchenNeuherberg, Germany
am Institute of Epidemiology, German Research Center for Environmental Health, Helmholtz Zentrum MünchenNeuherberg, Germany
an Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
ao Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
ap Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
aq University of Groningen, University Medical Center Groningen, Department of EpidemiologyGroningen, Netherlands
ar Biochemistry, Wake Forest School of Medicine, Winston-Salem, United States
as Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
at Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, TN, Nashville, United States
au Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, Greifswald, University Medicine Greifswald, Germany
av Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, MD, Baltimore, United States
aw Section of Cardiovascular Research, Baylor College of Medicine, TX, Houston, United States
ax Houston Methodist Debakey Heart and Vascular Center, TX, Houston, United States
ay Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, Netherlands
az Einthoven Laboratory for Experimental Vascular Medicine, Leiden, Netherlands
ba Human Genome Sequencing Center, Baylor College of Medicine, TX, Houston, United States
bb Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, United States
bc Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Medicine, University of Washington, Seattle, WA, USA
bd VA Boston Healthcare System, MA, Boston, United States
be Medicine, Sleep Laboratory, Lausanne University Hospital, Lausanne, Switzerland
bf Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, MD, Bethesda, United States
bg Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
bh Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Finland
bi Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, Netherlands
bj Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle, WA, USA
bk Public Health Sciences, Biostatistical Sciences, Wake Forest University Health Sciences, Winston-Salem, United States
bl Cardiology, School of Medicine and Health Sciences, George Washington University, D.C.WA, United States
bm Institute of Human Genetics, German Research Center for Environmental Health, Helmholtz Zentrum MünchenNeuherberg, Germany
bn Laboratory of Neurogenetics, National Institute on Aging, MD, Bethesda, United States
bo Data Tecnica International, MD, Glen Echo, United States
bp Division of Endocrinology, Diabetes, Nutrition, University of Maryland School of Medicine, MD, Baltimore, United States
bq Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, MD, Baltimore, United States
br DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance ,Neuherberg, Germany
bs Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
bt University of Turku, Turku, Finland
bu Center for Public Health Genomics, University of Virginia, VA, Charlottesville, United States
bv Institute of Medical Psychology, Ludwig-Maximilians-Universitat Munchen, Munich, Germany
bw Department of Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, CC, Torrance, United States
bx Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, MN, Minneapolis, United States
by Division of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
bz Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
ca Cardiovascular Health Research Unit, Medicine, University of Washington, Seattle, WA, USA
cb Institute of Human Genetics, Technische Universität München, Munich, Germany
cc Institute of Genetic Epidemiology, German Research Center for Environmental Health, Helmholtz Zentrum MünchenNeuherberg, Germany
cd Institute for Medical Informatics Biometry and Epidemiology, Ludwig-Maximilians-Universitat Munchen, Munich, Germany
ce University of Groningen, University Medical Center Groningen, Department of GeneticsGroningen, Netherlands
cf Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands
cg Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
ch Institute for Community Medicine, Greifswald, University Medicine Greifswald, Germany
ci Department of Epidemiology, University of Iowa College of Public Health, IA, Iowa City, United States
cj Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
ck Behavioral Epidemiology Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, MD, Baltimore, United States
cl MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
cm National Institute of Health Research Imperial College London Biomedical Research Centre, London, United Kingdom
cn UK-DRI Dementia Research Institute at Imperial College London, London, United Kingdom
co Broad Institute of the Massachusetts Institute of Technology and Harvard University, MA, Boston, United States
cp German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
cq Department Psychiatry and Psychotherapy, Greifswald, University Medicine Greifswald, Germany
cr Department of Clinical Phsiology and Nuclear Medicine, Kuopia University Hospital, Kuopio, Finland
cs Department of Psychiatry, Amsterdam Neuroscience and Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, Netherlands
ct Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, United States
cu SKLORG & Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of MedicineShanghai, China
cv Dean’s Office, University of Kentucky College of Public Health, Lexington, United States
cw Faculty of Medicine, University of Iceland, Reykjavik, Iceland
cx Epidemiology, Tulane University School of Public Health and Tropical Medicine, LA, New Orleans, United States
cy Sticht Center for Healthy Aging and Rehabilitation, Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, United States
cz Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, NY, NY, United States
da Mindich Child Health Development Institute, Icahn School of Medicine at Mount Sinai, NY, NY, United States
db Cardiovascular Health Research Unit, Epidemiology, Medicine and Health Services, University of Washington, Seattle, WA, USA
dc Kaiser Permanente Washington, Health Research Institute, Seattle, WA, USA
dd Department of Population Quantitative and Health Sciences, Case Western Reserve University, Cleveland, OH, USA
de NHLBI Framingham Heart Study, MA, Framingham, United States
df Cardiology, Medicine, University of Mississippi Medical Center, MS, Jackson, United States
dg Biostatistics, Preventive Medicine, University of Southern California, Los Angeles, CA, USA
dh Department of Biostatistics, University of Washington, Seattle, WA, USA
di Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, Barts and The London School of Medicine and Dentistry, London, United Kingdom
dj NIHR Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, United Kingdom
dk Division of Pulmonary Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, MA, Boston, United States
Abstract
Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access
“Mild chronic perturbation of inhibition severely alters hippocampal function” (2019) Scientific Reports
Mild chronic perturbation of inhibition severely alters hippocampal function
(2019) Scientific Reports, 9 (1), p. 16431.
Sun, M.-Y.a , Ziolkowski, L.a , Lambert, P.a b , Shu, H.-J.a , Keiser, M.a , Rensing, N.c , Warikoo, N.a , Martinek, M.a , Platnick, C.a , Benz, A.a , Bracamontes, J.d , Akk, G.d e , Steinbach, J.H.d e , Zorumski, C.F.a e f , Wong, M.c , Mennerick, S.g h i
a Department of Psychiatry, Washington University School of Medicine, St. Louis, United States
b MSTP Training Program, Washington University School of Medicine, St. Louis, United States
c Department of Neurology, Washington University School of Medicine, St. Louis, United States
d Department of Anesthesiology, Washington University School of Medicine, St. Louis, United States
e Taylor Family Institute for Innovative Psychiatric Research, St. Louis, United States
f Department of Neuroscience, Washington University School of Medicine, St. Louis, United States
g Department of Psychiatry, Washington University School of Medicine, St. Louis, United States
h Department of Neuroscience, Washington University School of Medicine, St. Louis, United States
i Taylor Family Institute for Innovative Psychiatric Research, St. Louis, United States
Abstract
Pentameric GABAA receptors mediate a large share of CNS inhibition. The γ2 subunit is a typical constituent. At least 11 mutations in the γ2 subunit cause human epilepsies, making the role of γ2-containing receptors in brain function of keen basic and translational interest. How small changes to inhibition may cause brain abnormalities, including seizure disorders, is unclear. In mice, we perturbed fast inhibition with a point mutation T272Y (T6’Y in the second membrane-spanning domain) to the γ2 subunit. The mutation imparts resistance to the GABAA receptor antagonist picrotoxin, allowing verification of mutant subunit incorporation. We confirmed picrotoxin resistance and biophysical properties in recombinant receptors. T6’Y γ2-containing receptors also exhibited faster deactivation but unaltered steady-state properties. Adult T6’Y knockin mice exhibited myoclonic seizures and abnormal cortical EEG, including abnormal hippocampal-associated theta oscillations. In hippocampal slices, picrotoxin-insensitive inhibitory synaptic currents exhibited fast decay. Excitatory/inhibitory balance was elevated by an amount expected from the IPSC alteration. Partial pharmacological correction of γ2-mediated IPSCs with diazepam restored total EEG power toward baseline, but had little effect on the abnormal low-frequency peak in the EEG. The results suggest that at least part of the abnormality in brain function arises from the acute effects of truncated inhibition.
Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access
“Visual Field Loss in Patients With Diabetes in the Absence of Clinically-Detectable Vascular Retinopathy in a Nationally Representative Survey” (2019) Investigative Ophthalmology & Visual Science
Visual Field Loss in Patients With Diabetes in the Absence of Clinically-Detectable Vascular Retinopathy in a Nationally Representative Survey
(2019) Investigative Ophthalmology & Visual Science, 60 (14), pp. 4711-4716.
Bao, Y.K.a , Yan, Y.b , Gordon, M.c , McGill, J.B.d , Kass, M.c , Rajagopal, R.c
a Department of Medicine, University of Missouri-Kansas City School of Medicine, Kansas City, MO, United States
b Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, United States
c Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, United States
d Division of Metabolism, Endocrinology and Lipid Research, Department of Medicine, Washington University School of MedicineMO, United States
Abstract
Purpose: Neuroretinopathy is increasingly being recognized as an independent cause of vision loss in diabetes. Visual field loss, as detected by frequency doubling technology (FDT)-based visual perimetry, is a sign of neuroretinopathy and occurs in early stages of diabetic retinopathy (DR). Here, we hypothesized that FDT visual field testing could identify patients with diabetic neuroretinopathy in the absence of clinically detectable microvascular DR. Methods: All National Health and Nutrition Examination Survey (NHANES) 2005-2008 participants receiving fundus photography and visual field screening by FDT were included in this study. Participants with self-reported glaucoma, use of glaucoma medications, or determination of glaucoma based on disk features were excluded. Visual fields were screened using FDT protocol in which participants underwent a 19-subfield suprathreshold test. Results: Patients with diabetes but no DR were more likely to have ≥1 subfield defects at 5%, 2%, and 1% probability levels than patients without diabetes (41.3% vs. 28.6%; 27.4% vs. 17.5%; 15.9% vs. 9.4%; all P < 0.0008). Multivariable regression showed that each additional glycated hemoglobin % (HbA1c) was associated with 19% greater odds of having ≥1 visual subfield defects in those with diabetes without DR (odds ratio: 1.19, 95% confidence interval: 1.07-1.33; P = 0.0020). Conclusions: Patients with diabetes have visual field defects in the absence of clinically detectable DR, suggesting neuroretinopathy precedes classical microvascular disease. These defects become more frequent with the onset of visible retinopathy and worsen as the retinopathy becomes more severe. Longitudinal studies are required to understand the pathogenesis of diabetic neuroretinopathy in relation to classic DR.
Document Type: Article
Publication Stage: Final
Source: Scopus
“Impact of Pharmacogenomics on Clinical Outcomes for Patients Taking Medications With Gene-Drug Interactions in a Randomized Controlled Trial” (2019) The Journal of Clinical Psychiatry
Impact of Pharmacogenomics on Clinical Outcomes for Patients Taking Medications With Gene-Drug Interactions in a Randomized Controlled Trial
(2019) The Journal of Clinical Psychiatry, 80 (6), .
Thase, M.E.a b , Parikh, S.V.c , Rothschild, A.J.d , Dunlop, B.W.e , DeBattista, C.f , Conway, C.R.g , Forester, B.P.h , Mondimore, F.M.i , Shelton, R.C.j , Macaluso, M.k , Li, J.l , Brown, K.m , Jablonski, M.R.l , Greden, J.F.c
a Perelman School of Medicine of the University of Pennsylvania, Room 689, 3535 Market Street, Philadelphia, PA 19104, United States
b Perelman School of Medicine of the University of Pennsylvania and the Corporal Michael Crescenz VAMC, Philadelphia, PA, United States
c University of Michigan Comprehensive Depression Center and Department of Psychiatry, National Network of Depression Centers, Ann Arbor, MI, United States
d University of Massachusetts Medical School and UMass Memorial Healthcare, Worcester, MA, United States
e Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
f Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
g Department of Psychiatry, Washington University School of Medicine, the John Cochran Veteran’s Administration Hospital, St Louis, MO, United States
h Division of Geriatric Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, United States
i Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
j Department of Psychiatry and School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
k Department of Psychiatry and Behavioral Sciences, University of Kansas School of Medicine-Wichita, Wichita, KS, United States
l Assurex Health, Inc, Mason, OH, United States
m Myriad Genetics, Inc, Salt Lake City, UT, United States
Abstract
OBJECTIVE: The objective of the Genomics Used to Improve DEpression Decisions (GUIDED) trial was to evaluate the utility of pharmacogenomic testing to improve outcomes among patients with major depressive disorder (MDD) who had not responded to at least 1 prior medication trial. The objective of the present analysis was to assess outcomes for the subset of patients expected to benefit from combinatorial pharmacogenomic testing because they were taking medications with predicted gene-drug interactions. METHODS: Participants (enrolled from April 14, 2014, to February 10, 2017) had an inadequate response to at least 1 psychotropic medication in the current episode of MDD. Patients were randomized to treatment as usual (TAU) or the guided-care arm, in which clinicians had access to a combinatorial pharmacogenomic test report to inform medication selection. Patients and raters were blinded to study arm through week 8. The following outcomes were assessed using the 17-item Hamilton Depression Rating Scale (HDRS-17): symptom improvement (percent change in HDRS-17 score), response (≥ 50% decrease in HDRS-17 score), and remission (HDRS-17 score ≤ 7). In the GUIDED trial, the primary endpoint of symptom improvement did not reach significance in the intent-to-treat cohort (P = .069). Here, a post hoc analysis of patients who were taking medications subject to gene-drug interactions at baseline as predicted by combinatorial pharmacogenomic testing (N = 912) is presented. RESULTS: Among participants taking medications subject to gene-drug interactions at baseline, outcomes at week 8 were significantly improved for those in the guided-care arm compared to TAU (symptom improvement: 27.1% versus 22.1%, P = .029; response: 27.0% versus 19.0%, P = .008; remission: 18.2% versus 10.7%, P = .003). When patients who switched medications were assessed, all outcomes were significantly improved in the guided-care arm compared to TAU (P = .011 for symptom improvement, P = .011 for response, P = .008 for remission). CONCLUSIONS: By identifying and focusing on the patients with predicted gene-drug interactions, use of a combinatorial pharmacogenomic test significantly improved outcomes among patients with MDD who had at least 1 prior medication failure. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02109939. © Copyright 2019 Physicians Postgraduate Press, Inc.
Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access
“Structured inhibitory activity dynamics in new virtual environments” (2019) eLife
Structured inhibitory activity dynamics in new virtual environments
(2019) eLife, 8, .
Arriaga, M., Han, E.B.
Department of Neuroscience, Washington University School of Medicine, St. Louis, United States
Abstract
Inhibition plays a powerful role in regulating network excitation and plasticity; however, the activity of defined interneuron types during spatial exploration remain poorly understood. Using two-photon calcium imaging, we recorded hippocampal CA1 somatostatin- and parvalbumin-expressing interneurons as mice performed a goal-directed spatial navigation task in new visual virtual reality (VR) contexts. Activity in both interneuron classes was strongly suppressed but recovered as animals learned to adapt the previously learned task to the new spatial context. Surprisingly, although there was a range of activity suppression across the population, individual somatostatin-expressing interneurons showed consistent levels of activity modulation across exposure to multiple novel environments, suggesting context-independent, stable network roles during spatial exploration. This work reveals population-level temporally dynamic interneuron activity in new environments, within which each interneuron shows stable and consistent activity modulation. © 2019, Arriaga and Han.
Author Keywords
calcium imaging; circuits; hippocampus; inhibition; learning; mouse; neuroscience; virtual reality
Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access
“Mitochondria fragments fuel the fire of neuroinflammation” (2019) Science Translational Medicine
Mitochondria fragments fuel the fire of neuroinflammation
(2019) Science Translational Medicine, 11 (512), art. no. eaaz3714, .
Gallardo, G.
Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
Document Type: Note
Publication Stage: Final
Source: Scopus
“Imaging in the repair of peripheral nerve injury” (2019) Nanomedicine (London, England)
Imaging in the repair of peripheral nerve injury
(2019) Nanomedicine (London, England), 14 (20), pp. 2659-2677.
Luzhansky, I.D.a b , Sudlow, L.C.a , Brogan, D.M.c , Wood, M.D.d , Berezin, M.Y.a b
a Department of Radiology, Washington University School of Medicine, St Louis, MO 63110, USA
b The Institute of Materials Science & Engineering, Washington University, St Louis, MO 63130, USA
c Department of Orthopedic Surgery, Washington University School of Medicine, St Louis, MO 63110, USA
d Department of Surgery, Washington University School of Medicine, St Louis, MO 63110, USA
Abstract
Surgical intervention followed by physical therapy remains the major way to repair damaged nerves and restore function. Imaging constitutes promising, yet underutilized, approaches to improve surgical and postoperative techniques. Dedicated methods for imaging nerve regeneration will potentially provide surgical guidance, enable recovery monitoring and postrepair intervention, elucidate failure mechanisms and optimize preclinical procedures. Herein, we present an outline of promising innovations in imaging-based tracking of in vivo peripheral nerve regeneration. We emphasize optical imaging because of its cost, versatility, relatively low toxicity and sensitivity. We discuss the use of targeted probes and contrast agents (small molecules and nanoparticles) to facilitate nerve regeneration imaging and the engineering of grafts that could be used to track nerve repair. We also discuss how new imaging methods might overcome the most significant challenges in nerve injury treatment.
Author Keywords
contrast agents; fluorescence imaging; imageable implants; MRI; nerve regeneration; nerve tissue engineering; nuclear imaging; peripheral nerves; photoacoustics; Raman imaging; ultrasound imaging
Document Type: Article
Publication Stage: Final
Source: Scopus
“Apples to apples? Neural correlates of emotion regulation differences between high- and low-risk adolescents” (2019) Social Cognitive and Affective Neuroscience
Apples to apples? Neural correlates of emotion regulation differences between high- and low-risk adolescents
(2019) Social Cognitive and Affective Neuroscience, 14 (8), pp. 827-836.
Perino, M.T.a , Guassi Moreira, J.F.b , McCormick, E.M.c , Telzer, E.H.c
a Department of Psychiatry, Washington University in St Louis School of Medicine, 4559 Scott Avenue, Suite 1153, St Louis, MO 63110, USA
b Department of Psychology, University of California, Los Angeles, 502 Portola Plaza, A191 Franz Hall, Los Angeles, CA 90095, USA
c Department of Psychology & Neuroscience, University of North Carolina, Room 213D, 235 E Cameron AvenueChapel HillNC 27599, United States
Abstract
Adolescence has been noted as a period of increased risk taking. The literature on normative neurodevelopment implicates aberrant activation of affective and regulatory regions as key to inhibitory failures. However, many of these studies have not included adolescents engaging in high rates of risky behavior, making generalizations to the most at-risk populations potentially problematic. We conducted a comparative study of nondelinquent community (n = 24, mean age = 15.8 years, 12 female) and delinquent adolescents (n = 24, mean age = 16.2 years, 12 female) who completed a cognitive control task during functional magnetic resonance imaging, where behavioral inhibition was assessed in the presence of appetitive and aversive socioaffective cues. Community adolescents showed poorer behavioral regulation to appetitive relative to aversive cues, whereas the delinquent sample showed the opposite pattern. Recruitment of the inferior frontal gyrus, medial prefrontal cortex, and tempoparietal junction differentiated community and high-risk adolescents, as delinquent adolescents showed significantly greater recruitment when inhibiting their responses in the presence of aversive cues, while the community sample showed greater recruitment when inhibiting their responses in the presence of appetitive cues. Accounting for behavioral history may be key in understanding when adolescents will have regulatory difficulties, highlighting a need for comparative research into normative and nonnormative risk-taking trajectories. © The Author(s) 2019. Published by Oxford University Press.
Author Keywords
adolescent delinquency; emotion regulation; fMRI; neurodevelopment; social processing
Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access
“Where Is Cannabis Legalization Leading?” (2019) JAMA Psychiatry
Where Is Cannabis Legalization Leading?
(2019) JAMA Psychiatry, .
Grucza, R.A.a , Plunk, A.D.b
a Department of Psychiatry, Washington University, School of Medicine in St Louis, 660 S Euclid Ave, PO Box 8134, St Louis, MO 63110, United States
b Department of Pediatrics, Eastern Virginia Medical School, Norfolk, VA, United States
Document Type: Editorial
Publication Stage: Article in Press
Source: Scopus
“Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders” (2019) Molecular Psychiatry
Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders
(2019) Molecular Psychiatry, .
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, Middeldorp, C.M.hx km kn , Mihailov, E.ko , Milaneschi, Y.ih , Milani, L.ko , Mondimore, F.M.jm , Montgomery, G.W.hp , Mostafavi, S.kp kq , Mullins, N.iq , Nauck, M.kr ks , Ng, B.kq , Nivard, M.G.hx , Nyholt, D.R.kt , O’Reilly, P.F.iq , Oskarsson, H.ku , Owen, M.J.jw , Painter, J.N.ir , Pedersen, C.B.hz ia ib , Pedersen, M.G.hz ia ib , Peterson, R.E.if kv , Pettersson, E.ik , Peyrot, W.J.ih , Pistis, G.ip , Posthuma, D.kw kx , Quiroz, J.A.ky , Qvist, P.hw ib im , Rice, J.P.kz , Riley, B.P.if , Rivera, M.iq la , Mirza, S.S.iy , Schoevers, R.lb , Schulte, E.C.lc ld , Shen, L.jy , Shi, J.le , Shyn, S.I.lf , Sigurdsson, E.lg , Sinnamon, G.C.B.lh , Smit, J.H.ih , Smith, D.J.li , Stefansson, H.lj , Steinberg, S.lj , Streit, F.jh , Strohmaier, J.jh , Tansey, K.E.lk , Teismann, H.ll , Teumer, A.lm , Thompson, W.ib jq ln lo , Thomson, P.A.lp , Thorgeirsson, T.E.lj , Traylor, M.lq , Treutlein, J.jh , Trubetskoy, V.hs , Uitterlinden, A.G.lr , Umbricht, D.ls , Van der Auwera, S.lt , van Hemert, A.M.lu , Viktorin, A.ik , Visscher, P.M.hp hq , Wang, Y.ib jq lo , Webb, B.T.lv , Weinsheimer, S.M.ib jq , Wellmann, J.ll , Willemsen, G.hx , Witt, S.H.jh , Wu, Y.hp , Xi, H.S.lw , Yang, J.hq lx , Zhang, F.hp , Arolt, V.ly , Baune, B.T.lz ma mb , Berger, K.ll , Boomsma, D.I.hx , Cichon, S.ix jj mc md , Dannlowski, U.ly , de Geus, E.J.C.hx me , DePaulo, J.R.jm , Domenici, E.mf , Domschke, K.mg mh , Esko, T.ht ko , Grabe, H.J.lt , Hamilton, S.P.mi , Hayward, C.mj , Heath, A.C.kz , Kendler, K.S.if , Kloiber, S.jv mk ml , Lewis, G.mm , Li, Q.S.mn , Lucae, S.jv , Madden, P.A.F.kz , Magnusson, P.K.ik , Martin, N.G.ir , McIntosh, A.M.hy iw , Metspalu, A.ko mo , Mors, O.ib mp , Mortensen, P.B.hz ia ib im , Müller-Myhsok, B.id mq mr , Nordentoft, M.ib ms , Nöthen, M.M.ix , O’Donovan, M.C.jw , Paciga, S.A.mt , Pedersen, N.L.ik , Penninx, B.W.J.H.ih , Perlis, R.H.ja mu , Porteous, D.J.lp , Potash, J.B.mv , Preisig, M.ip , Rietschel, M.jh , Schaefer, C.jy , Schulze, T.G.jh ld mw mx my , Smoller, J.W.ja jb jc , Stefansson, K.lj mz , Tiemeier, H.iy na nb , Uher, R.nc , Völzke, H.lm , Weissman, M.M.kk nd , Werge, T.ib jq ne , Lewis, C.M.iq nf , Levinson, D.F.ng , Breen, G.iq nh , Børglum, A.D.hw ib im , Sullivan, P.F.ik ni nj , Rivas, F.c , Mayoral, F.c , Müller-Myhsok, B.a q r , Forstner, A.J.m n s t , Nöthen, M.M.m , Rietschel, M.d , Bipolar Disorder Working Group of the Psychiatric Genomics Consortiumnk , Major Depressive Disorder Working Group of the Psychiatric Genomics Consortiumnk
a Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
b Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
c Department of Mental Health, University Regional Hospital of Málaga, Institute of Biomedicine of Málaga (IBIMA), Málaga, Spain
d Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
e Department of Mental Health, Hospital of Puerto Real, Cádiz, Spain
f Department of Mental Health, University Hospital of Reina Sofia, Córdoba, Spain
g Department of Mental Health, Hospital of Jaén, Jaén, Spain
h Department of Mental Health, Hospital of Jerez de la Frontera, Jerez de la Frontera, Spain
i Department of Mental Health, Hospital Punta de Europa, Algeciras, Spain
j Unidad de Gestión Clínica del Dispositivo de Cuidados Críticos y Urgencias del Distrito Sanitario Málaga—Coin-Guadalhorce, Málaga, Spain
k Department of Personality, Assessment and Psychological Treatment, University of Malaga, Institute of Biomedicine of Málaga (IBIMA), Málaga, Spain
l Department of Neurology, Goethe University Medical School, Frankfurt am Main, Germany
m Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
n Department of Biomedicine, University of Basel, Basel, Switzerland
o Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
p Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
q Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
r Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
s Centre for Human Genetics, University of Marburg, Marburg, Germany
t Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
u Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
v Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
w Medical and Population Genetics, Broad Institute, Cambridge, MA, United States
x MRC Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, GB, United Kingdom
y NIHR BRC for Mental Health, King’s College London, London, GB, United Kingdom
z Human Genomics Research Group, Department of Biomedicine, University of Basel, Basel, CH, Switzerland
aa Department of Psychiatry (UPK), University of Basel, Basel, CH, Switzerland
ab Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, DE, Germany
ac Department of Genomics, Life&Brain Center, University of Bonn, Bonn, DE, Germany
ad Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, CH, Switzerland
ae Division of Psychiatry, University College London, London, GB, United Kingdom
af Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, United States
ag Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin, Berlin, DE, Germany
ah Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States
ai iSEQ, Center for Integrative Sequencing, Aarhus University, Aarhus, Denmark
aj Department of Biomedicine – Human Genetics, Aarhus University, Aarhus, Denmark
ak Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, SE, Sweden
al Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital Würzburg, Würzburg, DE, Germany
am iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Risskov, Denmark
an Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Copenhagen, Denmark
ao Institute of Clinical Medicine, University of Oslo, Oslo, NO, Norway
ap Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
aq deCODE Genetics / Amgen, Reykjavik, IS, Reykjavík, Iceland
ar Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
as Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
at Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, MA, United States
au Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, GB, United Kingdom
av National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
aw Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
ax Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
ay NEUROSCIENCE, Istituto Di Ricerche Farmacologiche Mario Negri, Milano, Italy
az Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
ba Psychiatry, Berkshire Healthcare NHS Foundation Trust, Bracknell, GB, United Kingdom
bb Psychiatry, Rush University Medical Center, Chicago, IL, United States
bc Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
bd Department of Psychiatry, Weill Cornell Medical College, New York, NY, United States
be Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, DE, Germany
bf Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, SE, Sweden
bg Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, NO, Norway
bh Psychiatry, UMC Utrecht Hersencentrum Rudolf Magnus, Utrecht, Netherlands
bi Human Genetics, University of California Los Angeles, Los Angeles, CA, United States
bj Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, DE, Germany
bk Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States
bl Molecular & Behavioral Neuroscience Institute and Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, United States
bm Psychiatry, University of California San Francisco, San Francisco, CA, United States
bn Instituto de Salud Carlos III, Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, ES, Spain
bo Department of Psychiatry, Hospital Universitari Vall d´Hebron, Barcelona, ES, Spain
bp Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, ES, Spain
bq Psychiatric Genetics Unit, Group of Psychiatry Mental Health and Addictions, Vall d´Hebron Research Institut (VHIR), Universitat Autònoma de Barcelona, Barcelona, ES, Spain
br Department of Psychiatry, Mood Disorders Program, McGill University Health Center, Montreal, QC, Canada
bs Division of Psychiatry, University of Edinburgh, Edinburgh, GB, United Kingdom
bt University of Iowa Hospitals and Clinics, Iowa City, IA, United States
bu Translational Genomics, USC, Phoenix, AZ, United States
bv Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, DE, Germany
bw Department of Psychiatry, Laboratory of Psychiatric Genetics, Poznan University of Medical Sciences, Poznan, PL, Poland
bx Department of Neurosciences, University of California San Diego, La Jolla, CA, United States
by Department of Radiology, University of California San Diego, La Jolla, CA, United States
bz Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
ca Department of Cognitive Science, University of California San Diego, La Jolla, CA, United States
cb Applied Molecular Genomics Unit, VIB Department of Molecular Genetics, University of Antwerp, Antwerp, Belgium
cc Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
cd Department of Medical Genetics, Oslo University Hospital Ullevål, Oslo, NO, Norway
ce NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, NO, Norway
cf Department of Neurology, Oslo University Hospital, Oslo, NO, Norway
cg NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, NO, Norway
ch Center for Statistical Genetics and Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States
ci Department of Medical & Molecular Genetics, Indiana University, Indianapolis, IN, United States
cj Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, DE, Germany
ck Center for Neurobehavioral Genetics, University of California Los Angeles, Los Angeles, CA, United States
cl Department of Molecular Medicine and Surgery, Karolinska Institutet and Center for Molecular Medicine, Karolinska University Hospital, Stockholm, SE, Sweden
cm Department of Clinical Neuroscience, Karolinska Institutet and Center for Molecular Medicine, Karolinska University Hospital, Stockholm, SE, Sweden
cn Child and Adolescent Psychiatry Research Center, Stockholm, SE, Sweden
co Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, DE, Germany
cp Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
cq Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
cr Department of Psychological Medicine, University of Worcester, Worcester, GB, United Kingdom
cs School of Biomedical and Healthcare Sciences, Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth, GB, United Kingdom
ct School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
cu Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
cv Biostatistics, University of Minnesota System, Minneapolis, MN, United States
cw Mental Health Department, University Regional Hospital, Biomedicine Institute (IBIMA), Málaga, ES, Spain
cx Department of Psychology, Eberhard Karls Universität Tübingen, Tubingen, DE, Germany
cy Department of Psychiatry and Behavioral Sciences, Howard University Hospital, Washington, DC, United States
cz Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
da Psychiatrie Translationnelle, Inserm, Créteil, U955, France
db Faculté de Médecine, Université Paris Est, Créteil, France
dc Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
dd Neurogenetics Section, Centre for Addiction and Mental Health, Toronto, ON, Canada
de Department of Psychiatry, University of Toronto, Toronto, ON, Canada
df Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
dg Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main, DE, Germany
dh Cell Biology, SUNY Downstate Medical Center College of Medicine, Brooklyn, NY, United States
di Institute for Genomic Health, SUNY Downstate Medical Center College of Medicine, Brooklyn, NY, United States
dj ISGlobal, Barcelona, ES, Spain
dk Psychiatry, Altrecht, Utrecht, Netherlands
dl Psychiatry, GGZ inGeest, Amsterdam, Netherlands
dm Psychiatry, VU medisch centrum, Amsterdam, Netherlands
dn Psychiatry, North East London NHS Foundation Trust, Ilford, GB, United Kingdom
do Clinic for Psychiatry and Psychotherapy, University Hospital Cologne, Cologne, DE, Germany
dp Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, United States
dq HudsonAlpha Institute for Biotechnology, Huntsville, AL, United States
dr Department of Human Genetics, University of Michigan, Ann Arbor, MI, United States
ds Psychiatry, University of Illinois at Chicago College of Medicine, Chicago, IL, United States
dt Max Planck Institute of Psychiatry, Munich, DE, Germany
du Mental Health, NHS 24, Glasgow, GB, United Kingdom
dv Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, GB, United Kingdom
dw Psychiatry, Brigham and Women’s Hospital, Boston, MA, United States
dx Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, DE, Germany
dy Department of Genetics, Harvard Medical School, Boston, MA, United States
dz Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
ea Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, Lyon, France
eb Estonian Genome Center, University of Tartu, Tartu, EE, Estonia
ec Discipline of Biochemistry, Neuroimaging and Cognitive Genomics (NICOG) Centre, National University of Ireland, Galway, Galway, IE, Ireland
ed Neuropsychiatric Genetics Research Group, Dept of Psychiatry and Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, IE, Ireland
ee Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, DE, Germany
ef Research/Psychiatry, Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
eg Department of Clinical Sciences, Psychiatry, Umeå University Medical Faculty, Umeå, SE, Sweden
eh Department of Clinical Psychiatry, Psychiatry Clinic, Clinical Center University of Sarajevo, Sarajevo, BA, Bosnia and Herzegovina
ei Department of Neurobiology, Care sciences, and Society, Karolinska Institutet and Center for Molecular Medicine, Karolinska University Hospital, Stockholm, SE, Sweden
ej Psychiatry, Harvard Medical School, Boston, MA, United States
ek Division of Clinical Research, Massachusetts General Hospital, Boston, MA, United States
el Outpatient Clinic for Bipolar Disorder, Altrecht, Utrecht, Netherlands
em Department of Psychiatry, Washington University in Saint Louis, Saint Louis, MO, United States
en Department of Biochemistry and Molecular Biology II, Institute of Neurosciences, Center for Biomedical Research, University of Granada, Granada, ES, Spain
eo Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
ep Medicine, Psychiatry, Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
eq Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United States
er Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
es Rush University Medical Center, Chicago, IL, United States
et Scripps Translational Science Institute, La Jolla, CA, United States
eu Neuroscience Research Australia, Sydney, NSW, Australia
ev Faculty of Medicine, Department of Psychiatry, School of Health Sciences, University of Iceland, Reykjavik, IS, Iceland
ew Div Mental Health and Addiction, Oslo University Hospital, Oslo, NO, Norway
ex NORMENT, University of Oslo, Oslo, NO, Norway
ey Psychiatry and the Behavioral Sciences, University of Southern California, Los Angeles, CA, United States
ez Mood Disorders, PsyQ, Rotterdam, Netherlands
fa Institute for Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom
fb Research Division, Federal Institute for Drugs and Medical Devices (BfArM), Bonn, DE, Germany
fc Centre for Addiction and Mental Health, Toronto, ON, Canada
fd Neurogenomics, TGen, Los Angeles, AZ, United States
fe Psychiatry, Psychiatrisches Zentrum Nordbaden, Wiesloch, DE, Germany
ff Computational Sciences Center of Emphasis, Pfizer Global Research and Development, Cambridge, MA, United States
fg Department of Biostatistics, Princess Margaret Cancer Centre, Toronto, ON, Canada
fh Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
fi Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, GB, United Kingdom
fj Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, United States
fk Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
fl NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Institute of Clinical Medicine and Diakonhjemmet Hospital, University of Oslo, Oslo, NO, Norway
fm National Institute of Mental Health, Klecany, CZ, Czech Republic
fn Discipline of Psychiatry, University of Adelaide, Adelaide, SA, Australia
fo Department of Psychiatry and Addiction Medicine, Assistance Publique – Hôpitaux de Paris, Paris, France
fp Paris Bipolar and TRD Expert Centres, FondaMental Foundation, Paris, France
fq UMR-S1144 Team 1: Biomarkers of relapse and therapeutic response in addiction and mood disorders, INSERM, Paris, France
fr Psychiatry, Université Paris Diderot, Paris, France
fs Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
ft Department of Psychiatry, University of Münster, Münster, DE, Germany
fu Division of Endocrinology, Children’s Hospital Boston, Boston, MA, United States
fv Centre for Affective Disorders, Institute of Psychiatry, Psychology and Neuroscience, London, GB, United Kingdom
fw Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, United States
fx School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
fy Department of Human Genetics, University of Chicago, Chicago, IL, United States
fz Biometric Psychiatric Genetics Research Unit, Alexandru Obregia Clinical Psychiatric Hospital, Bucharest, RO, Romania
ga Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, SE, Sweden
gb INSERM, Paris, France
gc Department of Medical & Molecular Genetics, King’s College London, London, GB, United Kingdom
gd Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Titusville, NJ, United States
ge Cancer Epidemiology and Prevention, M. Sklodowska-Curie Cancer Center and Institute of Oncology, Warsaw, PL, Poland
gf School of Psychology, The University of Queensland, Brisbane, QLD, Australia
gg Research Institute, Lindner Center of HOPE, Mason, OH, United States
gh Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, GB, United Kingdom
gi Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, MD, United States
gj Division of Mental Health and Addiction, Oslo University Hospital, Oslo, NO, Norway
gk Division of Mental Health and Addiction, University of Oslo, Institute of Clinical Medicine, Oslo, NO, Norway
gl Institute of Molecular and Cell Biology, University of Tartu, Tartu, EE, Estonia
gm Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology – NTNU, Trondheim, NO, Norway
gn Psychiatry, St Olavs University Hospital, Trondheim, NO, Norway
go Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
gp Munich Cluster for Systems Neurology (SyNergy), Munich, DE, Germany
gq University of Liverpool, Liverpool, GB, United Kingdom
gr Psychiatry and Human Genetics, University of Pittsburgh, Pittsburgh, PA, United States
gs Mental Health Services in the Capital Region of Denmark, Mental Health Center Copenhagen, University of Copenhagen, Copenhagen, Denmark
gt Division of Psychiatry, Haukeland Universitetssjukehus, Bergen, NO, Norway
gu Faculty of Medicine and Dentistry, University of Bergen, Bergen, NO, Norway
gv Human Genetics and Computational Biomedicine, Pfizer Global Research and Development, Groton, CT, United States
gw College of Medicine Institute for Genomic Health, SUNY Downstate Medical Center College of Medicine, Brooklyn, NY, United States
gx Department of Clinical Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam, Netherlands
gy Department of Neurology and Neurosurgery, McGill University, Faculty of Medicine, Montreal, QC, Canada
gz Montreal Neurological Institute and Hospital, Montreal, QC, Canada
ha Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy
hb Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
hc Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital, Boston, MA, United States
hd Faculty of Medicine, University of Iceland, Reykjavik, IS, Iceland
he Department of Psychiatry, Hospital Namsos, Namsos, NO, Norway
hf Department of Neuroscience, Norges Teknisk Naturvitenskapelige Universitet Fakultet for naturvitenskap og teknologi, Trondheim, NO, Norway
hg Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
hh Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
hi Department of Psychiatry, McGill University, Montreal, QC, Canada
hj Dept of Psychiatry, Sankt Olavs Hospital Universitetssykehuset i Trondheim, Trondheim, NO, Norway
hk Clinical Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, ES, Spain
hl Institute of Biological Psychiatry, MHC Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
hm Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
hn Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States
ho Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, United States
hp Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
hq Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
hr Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States
hs Department of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, DE, Germany
ht Medical and Population Genetics, Broad Institute, Cambridge, MA, United States
hu Department of Psychiatry, Psychosomatics and Psychotherapy, University of Wurzburg, Wurzburg, DE, Germany
hv Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, SE, Sweden
hw Department of Biomedicine, Aarhus University, Aarhus, Denmark
hx Dept of Biological Psychology & EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
hy Division of Psychiatry, University of Edinburgh, Edinburgh, GB, United Kingdom
hz Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
ia National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
ib iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Risskov, Denmark
ic Discipline of Psychiatry, University of Adelaide, Adelaide, SA, Australia
id Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, DE, Germany
ie Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, DE, Germany
if Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States
ig Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
ih Department of Psychiatry, Vrije Universiteit Medical Center and GGZ inGeest, Amsterdam, Netherlands
ii Virginia Institute for Psychiatric and Behavior Genetics, Richmond, VA, United States
ij Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
ik Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, SE, Sweden
il Department of Clinical Medicine, Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark
im iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark
in Human Genetics, Wellcome Trust Sanger Institute, Cambridge, GB, United Kingdom
io Statistical genomics and systems genetics, European Bioinformatics Institute (EMBL-EBI), Cambridge, GB, United Kingdom
ip Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, CH, Switzerland
iq Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, GB, United Kingdom
ir Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
is Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
it Psychological Medicine, Cardiff University, Cardiff, GB, United Kingdom
iu Center for Genomic and Computational Biology, Duke University, Durham, NC, United States
iv Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, NC, United States
iw Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, GB, United Kingdom
ix Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, DE, Germany
iy Epidemiology, Erasmus MC, Rotterdam, Zuid-Holland, Netherlands
iz Psychiatry, Dokuz Eylul University School Of Medicine, Izmir, TR, Turkey
ja Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
jb Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital, Boston, MA, United States
jc Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, United States
jd Neuroscience and Mental Health, Cardiff University, Cardiff, GB, United Kingdom
je Bioinformatics, University of British Columbia, Vancouver, BC, Canada
jf Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States
jg Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, United States
jh Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Baden-Württemberg, DE, Germany
ji Department of Psychiatry (UPK), University of Basel, Basel, CH, Switzerland
jj Department of Biomedicine, University of Basel, Basel, CH, Switzerland
jk Centre for Human Genetics, University of Marburg, Marburg, DE, Germany
jl Department of Psychiatry, Trinity College Dublin, Dublin, IE, Ireland
jm Psychiatry & Behavioral Sciences, Johns Hopkins University, Baltimore, MD, United States
jn Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
jo Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, GB, United Kingdom
jp Danish Headache Centre, Department of Neurology, Rigshospitalet, Glostrup, Denmark
jq Institute of Biological Psychiatry, Mental Health Center Sct, Hans, Mental Health Services Capital Region of Denmark, Copenhagen, Denmark
jr iPSYCH, The Lundbeck Foundation Initiative for Psychiatric Research, Copenhagen, Denmark
js Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
jt Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine and Ernst Moritz Arndt University Greifswald, Greifswald, Mecklenburg-Vorpommern, DE, Germany
ju Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, CH, Switzerland
jv Max Planck Institute of Psychiatry, Munich, DE, Germany
jw MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, GB, United Kingdom
jx Department of Psychological Medicine, University of Worcester, Worcester, GB, United Kingdom
jy Division of Research, Kaiser Permanente Northern California, Oakland, CA, United States
jz Psychiatry & The Behavioral Sciences, University of Southern California, Los Angeles, CA, United States
ka Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
kb Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States
kc Informatics Program, Boston Children’s Hospital, Boston, MA, United States
kd Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, GB, United Kingdom
ke Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital and University of Lausanne, Lausanne, VD, CH, Switzerland
kf Swiss Institute of Bioinformatics, Lausanne, VD, CH, Switzerland
kg Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, GB, United Kingdom
kh Mental Health, NHS 24, Glasgow, GB, United Kingdom
ki Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, DE, Germany
kj Statistics, University of Oxford, Oxford, GB, United Kingdom
kk Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY, United States
kl School of Psychology and Counseling, Queensland University of Technology, Brisbane, QLD, Australia
km Child and Youth Mental Health Service, Children’s Health Queensland Hospital and Health Service, South Brisbane, QLD, Australia
kn Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
ko Estonian Genome Center, University of Tartu, Tartu, EE, Estonia
kp Medical Genetics, University of British Columbia, Vancouver, BC, Canada
kq Statistics, University of British Columbia, Vancouver, BC, Canada
kr DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, University Medicine Greifswald, Greifswald, Mecklenburg-Vorpommern, DE, Germany
ks Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Mecklenburg-Vorpommern, DE, Germany
kt Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
ku Humus, Reykjavik, IS, Iceland
kv Virginia Institute for Psychiatric & Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
kw Clinical Genetics, Vrije Universiteit Medical Center, Amsterdam, Netherlands
kx Complex Trait Genetics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
ky Solid Biosciences, Boston, MA, United States
kz Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, United States
la Department of Biochemistry and Molecular Biology II, Institute of Neurosciences, Biomedical Research Center (CIBM), University of Granada, Granada, ES, Spain
lb Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
lc Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University Munich, Munich, DE, Germany
ld Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, Ludwig Maximilian University Munich, Munich, DE, Germany
le Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States
lf Behavioral Health Services, Kaiser Permanente Washington, Seattle, WA, United States
lg Faculty of Medicine, Department of Psychiatry, University of Iceland, Reykjavik, IS, Iceland
lh School of Medicine and Dentistry, James Cook University, Townsville, QLD, Australia
li Institute of Health and Wellbeing, University of Glasgow, Glasgow, GB, United Kingdom
lj deCODE Genetics / Amgen, Reykjavik, IS, Iceland
lk College of Biomedical and Life Sciences, Cardiff University, Cardiff, GB, United Kingdom
ll Institute of Epidemiology and Social Medicine, University of Münster, Münster, Nordrhein-Westfalen, DE, Germany
lm Institute for Community Medicine, University Medicine Greifswald, Greifswald, Mecklenburg-Vorpommern, DE, Germany
ln Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
lo KG Jebsen Centre for Psychosis Research, Norway Division of Mental Health and Addiction, Oslo University Hospital, Oslo, NO, Norway
lp Medical Genetics Section, CGEM, IGMM, University of Edinburgh, Edinburgh, GB, United Kingdom
lq Clinical Neurosciences, University of Cambridge, Cambridge, GB, United Kingdom
lr Internal Medicine, Erasmus MC, Rotterdam, Zuid-Holland, Netherlands
ls Roche Pharmaceutical Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases Discovery & Translational Medicine Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, CH, Switzerland
lt Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Mecklenburg-Vorpommern, DE, Germany
lu Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands
lv Virginia Institute for Psychiatric & Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
lw Computational Sciences Center of Emphasis, Pfizer Global Research and Development, Cambridge, MA, United States
lx Institute for Molecular Bioscience; Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
ly Department of Psychiatry, University of Münster, Münster, Nordrhein-Westfalen, DE, Germany
lz Department of Psychiatry, University of Münster, Münster, DE, Germany
ma Department of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, Australia
mb Florey Institute for Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
mc Institute of Medical Genetics and Pathology, University Hospital Basel, University of Basel, Basel, CH, Switzerland
md Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, DE, Germany
me Amsterdam Public Health Institute, Vrije Universiteit Medical Center, Amsterdam, Netherlands
mf Centre for Integrative Biology, Università degli Studi di Trento, Trento, Trentino-Alto Adige, Italy
mg Department of Psychiatry and Psychotherapy, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, DE, Germany
mh Center for NeuroModulation, Faculty of Medicine, University of Freiburg, Freiburg, DE, Germany
mi Psychiatry, Kaiser Permanente Northern California, San Francisco, CA, United States
mj Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, GB, United Kingdom
mk Department of Psychiatry, University of Toronto, Toronto, ON, Canada
ml Centre for Addiction and Mental Health, Toronto, ON, Canada
mm Division of Psychiatry, University College London, London, GB, United Kingdom
mn Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Titusville, NJ, United States
mo Institute of Molecular and Cell Biology, University of Tartu, Tartu, EE, Estonia
mp Psychosis Research Unit, Aarhus University Hospital, Risskov, Aarhus, Denmark
mq M5 (SyNergy), Munich, DE, Germany
mr University of Liverpool, Liverpool, GB, United Kingdom
ms Mental Health Center Copenhagen, Copenhagen Universtity Hospital, Copenhagen, Denmark
mt Human Genetics and Computational Biomedicine, Pfizer Global Research and Development, Groton, CT, United States
mu Psychiatry, Harvard Medical School, Boston, MA, United States
mv Psychiatry, University of Iowa, Iowa City, IA, United States
mw Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, United States
mx Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Goettingen, Niedersachsen, DE, Germany
my Human Genetics Branch, NIMH Division of Intramural Research Programs, Bethesda, MD, United States
mz Faculty of Medicine, University of Iceland, Reykjavik, IS, Iceland
na Child and Adolescent Psychiatry, Erasmus MC, Rotterdam, Zuid-Holland, Netherlands
nb Psychiatry, Erasmus MC, Rotterdam, Zuid-Holland, Netherlands
nc Psychiatry, Dalhousie University, Halifax, NS, Canada
nd Division of Epidemiology, New York State Psychiatric Institute, New York, NY, United States
ne Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
nf Department of Medical & Molecular Genetics, King’s College London, London, GB, United Kingdom
ng Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, United States
nh NIHR Maudsley Biomedical Research Centre, King’s College London, London, GB, United Kingdom
ni Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
nj Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
Abstract
Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development. © 2019, The Author(s).
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Comorbid Diabetes and Severe Mental Illness: Outcomes in an Integrated Health Care Delivery System” (2019) Journal of General Internal Medicine
Comorbid Diabetes and Severe Mental Illness: Outcomes in an Integrated Health Care Delivery System
(2019) Journal of General Internal Medicine, .
Mangurian, C.a b , Schillinger, D.b c , Newcomer, J.W.d , Vittinghoff, E.e , Essock, S.f , Zhu, Z.g , Dyer, W.g , Young-Wolff, K.C.a g g , Schmittdiel, J.g
a Department of Psychiatry, Weill Institute of Neurosciences, University of California, San Francisco, San Francisco, CA, United States
b UCSF Center for Vulnerable Populations at Zuckerberg San Francisco General Hospital, San Francisco, CA, United States
c UCSF Division of General Internal Medicine at Zuckerberg San Francisco General Hospital, San Francisco, CA, United States
d Thriving Mind South Florida and Washington University School of Medicine, St Louis, CA, United States
e Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
f Department of Psychiatry, Columbia University, New York City, NY, United States
g Kaiser Permanente Northern California Division of Research, Oakland, CA, United States
Abstract
Background: Diabetes prevalence is twice as high among people with severe mental illness (SMI) when compared to the general population. Despite high prevalence, care outcomes are not well understood. Objective: To compare diabetes health outcomes received by people with and without comorbid SMI, and to understand demographic factors associated with poor diabetes control among those with SMI. Design: Retrospective cohort study Participants: 269,243 adults with diabetes Main Measures: Primary outcomes included optimal glycemic control (A1c < 7) or poor diabetes control (A1c > 9) in 2014. Secondary outcomes included control of other cardiometabolic risk factors (hypertension, dyslipidemia, smoking) and recommended diabetes monitoring. Key Results: Among this cohort, people with SMI (N = 4,399), compared to those without SMI (N = 264,844), were more likely to have optimal glycemic control, adjusting for various covariates (adjusted relative risk (aRR) 1.25, 95% CI 1.21–1.28, p <.001) and less likely to have poor control (aRR 0.92, 95% CI 0.87–0.98, p = 0.012). Better blood pressure and lipid control was more prevalent among people with SMI when compared to those without SMI (aRR 1.03; 95% CI 1.02–1.05, p <.001; aRR 1.02; 95% CI 1.00–1.05, p = 0.044, respectively). No differences were observed in recommended A1c or LDL testing, but people with SMI were more likely to have blood pressure checked (aRR 1.02, 95% CI 1.02–1.03, p <.001) and less likely to receive retinopathy screening (aRR 0.80, 95% CI 0.71–0.91, p <.001) than those without SMI. Among people with diabetes and comorbid SMI, younger adults and Hispanics were more likely to have poor diabetes control. Conclusions: Adults with diabetes and comorbid SMI had better cardiometabolic control than people with diabetes who did not have SMI, despite lower rates of retinopathy screening. Among those with comorbid SMI, younger adults and Hispanics were more vulnerable to poor A1c control. © 2019, Society of General Internal Medicine.
Author Keywords
diabetes; health outcomes; healthcare delivery system; severe mental illness
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation” (2019) PLoS ONE
Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation
(2019) PLoS ONE, 14 (11), art. no. e0225093, .
Wang, Q.a , Guzmán Pérez-Carrillo, G.J.b , Ponisio, M.R.a , LaMontagne, P.a , Dahiya, S.c , Marcus, D.S.a , Milchenko, M.a , Shimony, J.a , Liu, J.d , Chen, G.a , Salter, A.e , Massoumzadeh, P.a , Miller-Thomas, M.M.a , Rich, K.M.f , McConathy, J.g , Benzinger, T.L.S.a , Wang, Y.a h
a Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States
b Department of Medical Imaging, Neuroradiology Section, University of Arizona, Tucson, AZ, United States
c Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, United States
d Department of Surgery, Washington University in St. Louis, St. Louis, MO, United States
e Department of Biostatistics, Washington University in St. Louis, St. Louis, MO, United States
f Department of Neurosurgery, Washington University in St. Louis, St. Louis, MO, United States
g Department of Radiology, Division of Molecular Imaging and Therapeutics, University of Alabama at Birmingham, Birmingham, AL, United States
h Department of Obstetrics and Gynecology, Washington University in St. Louis, St. Louis, MO, United States
Abstract
Objectives Primary brain tumors are composed of tumor cells, neural/glial tissues, edema, and vasculature tissue. Conventional MRI has a limited ability to evaluate heterogeneous tumor pathologies. We developed a novel diffusion MRI-based method—Heterogeneity Diffusion Imaging (HDI)—to simultaneously detect and characterize multiple tumor pathologies and capillary blood perfusion using a single diffusion MRI scan. Methods Seven adult patients with primary brain tumors underwent standard-of-care MRI protocols and HDI protocol before planned surgical resection and/or stereotactic biopsy. Twelve tumor sampling sites were identified using a neuronavigational system and recorded for imaging data quantification. Metrics from both protocols were compared between World Health Organization (WHO) II and III tumor groups. Cerebral blood volume (CBV) derived from dynamic susceptibility contrast (DSC) perfusion imaging was also compared with the HDI-derived perfusion fraction. Results The conventional apparent diffusion coefficient did not identify differences between WHO II and III tumor groups. HDI-derived slow hindered diffusion fraction was significantly elevated in the WHO III group as compared with the WHO II group. There was a non-significantly increasing trend of HDI-derived tumor cellularity fraction in the WHO III group, and both HDI-derived perfusion fraction and DSC-derived CBV were found to be significantly higher in the WHO III group. Both HDI-derived perfusion fraction and slow hindered diffusion fraction strongly correlated with DSC-derived CBV. Neither HDI-derived cellularity fraction nor HDI-derived fast hindered diffusion fraction correlated with DSC-derived CBV. Conclusions Conventional apparent diffusion coefficient, which measures averaged pathology properties of brain tumors, has compromised accuracy and specificity. HDI holds great promise to accurately separate and quantify the tumor cell fraction, the tumor cell packing density, edema, and capillary blood perfusion, thereby leading to an improved microenvironment characterization of primary brain tumors. Larger studies will further establish HDI’s clinical value and use for facilitating biopsy planning, treatment evaluation, and noninvasive tumor grading. © 2019 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Document Type: Article
Publication Stage: Final
Source: Scopus
“Driving in the elderly in health and disease” (2019) Handbook of Clinical Neurology
Driving in the elderly in health and disease
(2019) Handbook of Clinical Neurology, 167, pp. 563-573.
Carr, D.B.a , Stowe, J.D.b , Morris, J.C.c
a Departments of Medicine and Neurology, Washington University School of Medicine, St Louis, MO, United States
b Aging and Adult Services, Mid-America Regional Council, Kansas City, MO, United States
c Department of Neurology and Director, Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO, United States
Abstract
Driving is a complex, multifaceted instrumental activity of daily living that has an independent influence on multiple health and well-being outcomes among older adults. Therefore, the benefits of driving to the individual must be balanced, through careful assessment and diagnosis, with the potential risk to self and others posed by a medically impaired driver. The influence of dementia changes substantially during the disease progression from very mild to mild, and driving is not advised for those who have progressed to the moderate stage of Alzheimer disease. Fortunately, validated high-quality screening instruments, including modern simulators and other technology aids, can help clinicians trichotomize risk (i.e., high, moderate, or low) and determine which patients need further evaluation by a driving specialist (e.g., those in the moderate range). Moreover, a body of evidence is building regarding the efficacy of certain intervention pathways to maintain current levels of driving performance among individuals with dementia, or at least slow its decline. Even with the progression of advanced driving technologies, understanding driving ability of patients with dementia will remain a critical challenge to clinicians for the foreseeable future. © 2019 Elsevier B.V.
Author Keywords
Alzheimer disease; Dementia; Driving; Driving simulator; Mild cognitive impairment; Motor vehicle crash
Document Type: Book Chapter
Publication Stage: Final
Source: Scopus
“Assessment and treatment of major depression in older adults” (2019) Handbook of Clinical Neurology
Assessment and treatment of major depression in older adults
(2019) Handbook of Clinical Neurology, 167, pp. 429-435.
Reynolds, C.F., IIIa , Lenze, E.b , Mulsant, B.H.c
a University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
b Department of Psychiatry, Washington University School of Medicine, St Louis, MO, United States
c Department of Psychiatry, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada
Abstract
Late life depression is a significant public health problem as well as a burden on patients, their families, and caregivers. There are significant associations of late life depression with medical disorders and cognitive impairment, the latter due to effects of the depression itself or association with dementia. Diagnostic criteria and screening tests have continued to evolve and provide structure and guidelines for assessment. Accurate diagnosis and treatment are of utmost importance to improve quality of life, alleviate suffering, and prevent suicide. A number of effective antidepressant medications are available; combination therapy with these medications and cognitive behavioral therapy appear most efficacious, and maintenance therapy can decrease the chances of remission. A sequence for treatment of late life depression is provided, with strategies for treatment-resistant depression. The relationship of dementia to depression and the interaction of depression with mechanisms of aging are major foci of research. © 2019 Elsevier B.V.
Author Keywords
Antidepressant; Depression; Diagnosis; Medical and neurologic comorbidity; Older adults; Prevention of dementia; Treatment
Document Type: Book Chapter
Publication Stage: Final
Source: Scopus
“The neurogenetics of sexually dimorphic behaviors from a postdevelopmental perspective” (2019) Genes, Brain and Behavior
The neurogenetics of sexually dimorphic behaviors from a postdevelopmental perspective
(2019) Genes, Brain and Behavior, art. no. e12623, .
Leitner, N., Ben-Shahar, Y.
Department of Biology, Washington University in St. Louis, St. Louis, MO, United States
Abstract
Most sexually reproducing animal species are characterized by two morphologically and behaviorally distinct sexes. The genetic, molecular and cellular processes that produce sexual dimorphisms are phylogenetically diverse, though in most cases they are thought to occur early in development. In some species, however, sexual dimorphisms are manifested after development is complete, suggesting the intriguing hypothesis that sex, more generally, might be considered a continuous trait that is influenced by both developmental and postdevelopmental processes. Here, we explore how biological sex is defined at the genetic, neuronal and behavioral levels, its effects on neuronal development and function, and how it might lead to sexually dimorphic behavioral traits in health and disease. We also propose a unifying framework for understanding neuronal and behavioral sexual dimorphisms in the context of both developmental and postdevelopmental, physiological timescales. Together, these two temporally separate processes might drive sex-specific neuronal functions in sexually mature adults, particularly as it pertains to behavior in health and disease. © 2019 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society
Author Keywords
biological sex; Drosophila melanogaster; Mus musculus; sex determination; sexual dimorphism; sexual reproduction
Document Type: Review
Publication Stage: Article in Press
Source: Scopus
Access Type: Open Access
“Author Correction: V2a interneuron differentiation from mouse and human pluripotent stem cells (Nature Protocols, (2019), 14, 11, (3033-3058), 10.1038/s41596-019-0203-1)” (2019) Nature Protocols
Author Correction: V2a interneuron differentiation from mouse and human pluripotent stem cells (Nature Protocols, (2019), 14, 11, (3033-3058), 10.1038/s41596-019-0203-1)
(2019) Nature Protocols, .
Butts, J.C.a b , Iyer, N.c , White, N.d , Thompson, R.e , Sakiyama-Elbert, S.d , McDevitt, T.C.a f
a Gladstone Institutes, San Francisco, CA, United States
b Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, CA, United States
c Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, United States
d Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, United States
e Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States
f Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States
Abstract
In the version of this article initially published, co-corresponding author Shelly Sakiyama-Elbert was not designated as a corresponding author and her e-mail address was not listed. The errors have been corrected in the HTML and PDF versions of the article. © 2019, Springer Nature Limited.
Document Type: Erratum
Publication Stage: Article in Press
Source: Scopus
“GABA-A receptor and mitochondrial TSPO signaling act in parallel to regulate melanocyte stem cell quiescence in larval zebrafish” (2019) Pigment Cell and Melanoma Research
GABA-A receptor and mitochondrial TSPO signaling act in parallel to regulate melanocyte stem cell quiescence in larval zebrafish
(2019) Pigment Cell and Melanoma Research, .
Allen, J.R., Skeath, J.B., Johnson, S.L.
Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Tissue regeneration and homeostasis often require recruitment of undifferentiated precursors (adult stem cells; ASCs). While many ASCs continuously proliferate throughout the lifetime of an organism, others are recruited from a quiescent state to replenish their target tissue. A long-standing question in stem cell biology concerns how long-lived, non-dividing ASCs regulate the transition between quiescence and proliferation. We study the melanocyte stem cell (MSC) to investigate the molecular pathways that regulate ASC quiescence. Our prior work indicated that GABA-A receptor activation promotes MSC quiescence in larval zebrafish. Here, through pharmacological and genetic approaches we show that GABA-A acts through calcium signaling to maintain MSC quiescence. Unexpectedly, we identified translocator protein (TSPO), a mitochondrial membrane-associated protein that regulates mitochondrial function and metabolic homeostasis, as a parallel regulator of MSC quiescence. We found that both TSPO-specific ligands and induction of gluconeogenesis likely act in the same pathway to promote MSC activation and melanocyte production in larval zebrafish. In contrast, TSPO and gluconeogenesis appear to act in parallel to GABA-A receptor signaling to regulate MSC quiescence and vertebrate pigment patterning. © 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
Author Keywords
GABA-A; melanocyte; stem cell; translocator protein; zebrafish
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Personality traits predict dietary habits in middle-to-older adults” (2019) Psychology, Health and Medicine
Personality traits predict dietary habits in middle-to-older adults
(2019) Psychology, Health and Medicine, .
Weston, S.J.a , Edmonds, G.W.b , Hill, P.L.c
a Department of Psychology, University of Oregon, Eugene, OR, United States
b Oregon Research Institute, Eugene, OR, United States
c Department of Psychological and Brain Sciences, Washington University, St. Louis, MO, United States
Abstract
Personality traits are consistently associated with health behaviors, but little research has examined the role of personality on eating habits among middle-to-older adults. The current study (n = 665) examined the associations between traits and dietary habits and whether healthy eating predicted health at age 60, with the Hawaii Personality and Health Cohort. Eating healthy foods was associated with higher agreeableness, conscientiousness, emotional stability, and openness, and predicted better self-rated health and lower BMI. Eating unhealthy foods was associated with lower agreeableness, conscientiousness, emotional stability, and openness, and predicted lower self-rated health. Results were not moderated by SES. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
Author Keywords
adulthood; BMI; diet; health; Personality; socioeconomic status
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Ludwig Heinrich Bojanus (1776–1827) on Gall’s craniognomic system, zoology, and comparative anatomy” (2019) Journal of the History of the Neurosciences
Ludwig Heinrich Bojanus (1776–1827) on Gall’s craniognomic system, zoology, and comparative anatomy
(2019) Journal of the History of the Neurosciences, .
Sakalauskaitė-Juodeikienė, E.a , Eling, P.b , Finger, S.c
a Department of Neurology and Neurosurgery, Institute of Clinical Medicine; Centre for Medical Ethics, Law and History, Institute of Health Sciences, Vilnius University, Faculty of Medicine, Vilnius, Lithuania
b Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, Netherlands
c Department of Psychological and Brain Sciences, and Program in History of Medicine, Washington University, St. Louis, MO, United States
Abstract
Most of what was known about Franz Joseph Gall’s (1758–1828) organology or Schädellehre prior to the 1820s came from secondary sources, including letters from correspondents, promotional materials, brief newspaper articles about his lecture-demonstrations, and editions and translations of some lengthier works of varying quality in German. Physician Ludwig Heinrich Bojanus (1776–1827) practiced in Vienna’s General Hospital in 1797–1798; attended some of Gall’s public lectures; and, in 1801–1802, became one of the first physicians to provide detailed reports on Gall’s emerging organology in French and English, respectively. Although Bojanus considered the human mind to be indivisible and did not entirely agree with Gall’s assumption that the brain consists of a number of independent organs responsible for various faculties, he provided valuable information and thoughtful commentary on Gall’s views. Furthermore, he defended Gall against the charge that his sort of thinking would lead to materialism and cautiously predicted that the new system would be fruitful for developing and stimulating important new research about the brain and mind. Bojanus became a professor of zoology in 1806 and a professor of comparative anatomy in 1814 at Vilnius University, where, among other accomplishments, he established himself as a founder of modern veterinary medicine and a pioneer of pre-Darwinian and pre-Lamarckian evolutionism. © 2019, © 2019 Taylor & Francis.
Author Keywords
comparative anatomy; craniognomic system; Franz Joseph Gall; Ludwig Heinrich Bojanus; organology; Vilnius University; zoology
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Gst-4-dependent suppression of neurodegeneration in c. Elegans models of parkinson’s and machado-joseph disease by rapeseed pomace extract supplementation” (2019) Frontiers in Neuroscience
Gst-4-dependent suppression of neurodegeneration in c. Elegans models of parkinson’s and machado-joseph disease by rapeseed pomace extract supplementation
(2019) Frontiers in Neuroscience, 13 (OCT), art. no. 1091, .
Pohl, F.a e , Teixeira-Castro, A.b c , Costa, M.D.b c , Lindsay, V.a f , Fiúza-Fernandes, J.b c , Goua, M.a , Bermano, G.a , Russell, W.d , Maciel, P.b c , Lin, P.K.T.a
a School of Pharmacy and Life Sciences, Robert Gordon University, Aberdeen, United Kingdom
b Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
c ICVS/3B’s – PT Government Associate Laboratory, Braga, Portugal
d Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, United Kingdom
e Division of Oncology, Department of Medicine, Washington University, St. Louis, MO, United States
f Department of Clinical Sciences and Services, Royal Veterinary College, University of London, Hatfield, United Kingdom
Abstract
Genetic mutations and aging-associated oxidative damage underlie the onset and progression of neurodegenerative diseases, like Parkinson’s disease (PD) and Machado-Joseph disease (MJD). Natural products derived from plants have been regarded as important sources of novel bioactive compounds to counteract neurodegeneration. Here, we tested the neuroprotective effect of an ethanolic extract of rapeseed pomace (RSP), a rapeseed (canola) oil production by-product, in C. elegans models of MJD and PD. The extract, containing sinapine and other phenolics, restored motor function of mutant ataxin-3 (ATXN3) animals (MJD) and prevented degeneration of dopaminergic neurons in one toxin-induced and two genetic models of PD. Wholeorganism sensors of antioxidant and xenobiotic response activation revealed the induction of phase II detoxification enzymes, including glutathione S- transferase (GST-4) upon RSP extract supplementation. Furthermore in vivo pharmacogenetic studies confirmed gst-4 is required for the therapeutic effect of RSP extract in the two disease models. The results suggest that GST-4-mediated antioxidant pathways may constitute promising therapeutic co-targets for neurodegenerative diseases and confirm the utility of searching for bioactive compounds in novel sources, including food and agricultural waste/by-products, such as RSP. © 2019 2019 Pohl, Teixeira-Castro, Costa, Lindsay, Fiúza-Fernandes, Goua, Bermano, Russell, Maciel and Kong Thoo Lin.
Author Keywords
Antioxidant; C. Elegans; Gst-4; Machado-Joseph disease; Parkinson’s disease; Rapeseed (canola) pomace; Sod-3; Spinocerebellar ataxia 3
Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access
“The psychobiology of the path to a joyful life: implications for future research and practice” (2019) Journal of Positive Psychology
The psychobiology of the path to a joyful life: implications for future research and practice
(2019) Journal of Positive Psychology, .
Cloninger, K.M.a , Cloninger, C.R.a b c d
a Anthropedia Foundation, St. Louis, MO, United States
b Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
c Department of Psychological and Brain Sciences, School of Arts and Sciences, Washington University, St. Louis, MO, United States
d Department of Genetics, School of Medicine, St. Louis, MO, United States
Abstract
Recent psychobiological and developmental research shows that the path to a good and joyful life depends on the integration of three distinct systems of learning and memory that regulate (1) associative conditioning, (2) intentional self-control, and (3) self-awareness. The integration of these learning networks depends on complex molecular pathways involving 972 genes that regulate human temperament and character, which we recently identified and replicated in independent samples despite variable environments and cultures. Awareness of these processes of human thought facilitates self-regulation of how these genes are expressed and how learning processes are integrated to adapt to ever-changing conditions. Such awareness leads to a self-transcendent outlook that activates psychobiological mechanisms that promote healthy longevity, positive emotionality, and prosocial behavior. Our empirical findings show that the path to a good life requires the integration of physical, mental, and spiritual aspects of the person, rather than only one or two of these aspects. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
Author Keywords
character; complex adaptive systems; joy; learning networks; plasticity; self-regulation; virtue; Well-being
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Erratum to: Terminology for bladder health research in women and girls: Prevention of Lower Urinary Tract Symptoms transdisciplinary consortium definitions (Neurourology and Urodynamics, (2019), 38, 5, (1339-1352), 10.1002/nau.23985)” (2019) Neurourology and Urodynamics
Erratum to: Terminology for bladder health research in women and girls: Prevention of Lower Urinary Tract Symptoms transdisciplinary consortium definitions (Neurourology and Urodynamics, (2019), 38, 5, (1339-1352), 10.1002/nau.23985)
(2019) Neurourology and Urodynamics, .
Lowder, J.L.a , Bavendam, T.G.b , Berry, A.c , Brady, S.S.d , Fitzgerald, C.M.e f , Fok, C.S.g , Goode, P.S.h i , Lewis, C.E.j , Mueller, E.R.e , Newman, D.K.k , Palmer, M.H.l , Rickey, L.m , Stapleton, A.n , Lukacz, E.S.o , Prevention of Lower Urinary Tract Symptoms (PLUS) Research Consortiump
a Division of Female Pelvic Medicine and Reconstructive Surgery, Department of Obstetrics and Gynecology, School of Medicine, Washington University in St. Louis, St. Louis, MO, United States
b Division of Kidney, Urologic and Hematologic Disease, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
c Division of Urology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
d Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN, United States
e Division of Female Pelvic Medicine and Reconstructive Surgery, Department of Obstetrics and Gynecology, Loyola University Stritch School of Medicine, Chicago, IL, United States
f Department of Physical Medicine and Rehabilitation, Loyola University Stritch School of Medicine, Chicago, IL, United States
g Department of Urology, University of Minnesota, Minneapolis, MN, United States
h Division of Gerontology, Geriatrics, and Palliative Care, University of Alabama at Birmingham, Birmingham, AL, United States
i Birmingham/Atlanta Veterans Affairs Geriatric Research, Education, and Clinical Center, Birmingham, AL, United States
j Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States
k Department of Urology, Division of Urology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
l School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
m Division of Female Pelvic Medicine and Reconstructive Surgery, Department of Urology and Obstetrics & Gynecology, Yale University, New Haven, CT, United States
n Department of Medicine, Division of Allergy and Infectious Diseases, University of Washington School of Medicine, Seattle, WA, United States
o Division of Female Pelvic Medicine & Reconstructive Surgery, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Diego, San Diego, CA, United States
Abstract
The article entitled “Terminology for Bladder Health Research in Women and Girls–PLUS Transdisciplinary Consortium Definitions” published in (Volume 38, Issue 5, pages 1339-1352, April 2019) had missing text in author byline which is “Prevention of Lower Urinary Tract Symptoms (PLUS) Research Consortium”. © 2019 Wiley Periodicals, Inc.
Document Type: Erratum
Publication Stage: Article in Press
Source: Scopus
Access Type: Open Access
“Cryptogenic small-fiber neuropathies: Serum autoantibody binding to trisulfated heparan disaccharide and fibroblast growth factor receptor-3” (2019) Muscle and Nerve
Cryptogenic small-fiber neuropathies: Serum autoantibody binding to trisulfated heparan disaccharide and fibroblast growth factor receptor-3
(2019) Muscle and Nerve, .
Levine, T.D.a , Kafaie, J.b , Zeidman, L.A.c , Saperstein, D.S.a , Massaquoi, R.b , Bland, R.J.a , Pestronk, A.d
a Phoenix Neurological Associates, Phoenix, AZ, United States
b Saint Louis University, St Louis, MO, United States
c University of Illinois-Chicago, Chicago, IL, United States
d Washington University, St Louis, MO, United States
Abstract
Introduction: Causes of small-fiber peripheral neuropathies (SFN) are often undefined. In this study we investigated associations of serum autoantibodies, immunoglobulin G (IgG) vs fibroblast growth factor receptor-3 (FGFR-3), and immunoglobulin M (IgM) vs trisulfated heparan disaccharide (TS-HDS) in cryptogenic SFN. Methods: One hundred fifty-five patients with biopsy-proven SFN and no identified cause for their neuropathy were blindly tested for serum IgM vs TS-HDS and IgG vs FGFR-3. Results: Forty-eight percent of SFN patients had serum antibodies, 37% with IgM vs TS-HDS and 15% with IgG vs FGFR-3. TS-HDS antibodies were more frequent in SFN patients than in controls (P =.0012). Both antibodies were more common in females, and with non–length-dependent nerve pathology. Nintey-two percent of patients with acute-onset SFN had serum IgM vs TS-HDS. Discussion: Autoantibodies directed against TS-HDS and FGFR-3 suggest an immune disorder in otherwise idiopathic SFN. Serum IgM vs TS-HDS may be a marker for SFN with an acute onset. © 2019 Wiley Periodicals, Inc.
Author Keywords
autoantibodies; FGFR-3; pathogenesis; small-fiber neuropathy; TS-HDS
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Reactions to Multiple Ascending Doses of the Microtubule Stabilizer TPI-287 in Patients with Alzheimer Disease, Progressive Supranuclear Palsy, and Corticobasal Syndrome: A Randomized Clinical Trial” (2019) JAMA Neurology
Reactions to Multiple Ascending Doses of the Microtubule Stabilizer TPI-287 in Patients with Alzheimer Disease, Progressive Supranuclear Palsy, and Corticobasal Syndrome: A Randomized Clinical Trial
(2019) JAMA Neurology, .
Tsai, R.M.a , Miller, Z.a , Koestler, M.a , Rojas, J.C.a , Ljubenkov, P.A.a , Rosen, H.J.a , Rabinovici, G.D.a b , Fagan, A.M.c , Cobigo, Y.a , Brown, J.A.a , Jung, J.I.a , Hare, E.a , Geldmacher, D.S.d , Natelson-Love, M.d , McKinley, E.C.d , Luong, P.N.a , Chuu, E.L.a , Powers, R.a , Mumford, P.a , Wolf, A.a , Wang, P.a , Shamloo, M.e , Miller, B.L.a , Roberson, E.D.d , Boxer, A.L.a
a Memory and Aging Center, Department of Neurology, Sandler Neurosciences Center, University of California, San Francisco, 675 Nelson Rising Ln, San Francisco, CA 94158, United States
b Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
c Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO, United States
d Alzheimer’s Disease Center, Department of Neurology, University of Alabama, Birmingham, United States
e Wu Tsai Neurosciences Institute, Stanford University, Palo Alto, CA, United States
Abstract
Importance: Basket-design clinical trials that allow investigation of treatment effects on different clinical syndromes that share the same molecular pathophysiology have not previously been attempted in neurodegenerative disease. Objective: To assess the safety, tolerability, and pharmacodynamics of the microtubule stabilizer TPI-287 (abeotaxane) in Alzheimer disease (AD) or the 4-repeat tauopathies (4RT) progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS). Design, Setting, and Participants: Two parallel-design, double-blind, placebo-controlled phase 1 randomized clinical trials in AD and 4RT were conducted from December 20, 2013, through May 4, 2017, at the University of California, San Francisco, and University of Alabama at Birmingham. A total of 94 patients with clinically diagnosed AD (n = 39) and 4RT (n = 55) were screened; of these, 3 refused to participate, and 10 with AD and 11 with 4RT did not meet inclusion criteria. A total of 29 patients with AD, 14 with PSP, and 30 with β-amyloid-negative CBS (determined on positron emission tomography findings) were enrolled. Data were analyzed from December 20, 2013, through May 4, 2017, based on modified intention to treat. Interventions: Randomization was 8:3 drug to placebo in 3 sequential dose cohorts receiving 2.0, 6.3, or 20.0 mg/m2 of intravenous TPI-287 once every 3 weeks for 9 weeks, with an optional 6-week open-label extension. Main Outcomes and Measures: Primary end points were safety and tolerability (maximal tolerated dose) of TPI-287. Secondary and exploratory end points included TPI-287 levels in cerebrospinal fluid (CSF) and changes on biomarker, clinical, and neuropsychology measures. Results: A total of 68 participants (38 men [56%]; median age, 65 [range, 50-85] years) were included in the modified intention-to-treat analysis, of whom 26 had AD (14 women [54%]; median age, 63 [range, 50-76] years), and 42 had 4RT (16 women [38%]; median age, 69 [range, 54-83] years). Three severe anaphylactoid reactions occurred in TPI-287-treated patients with AD, whereas none were seen in patients with 4RT, leading to a maximal tolerated dose of 6.3 mg/m2 for AD and 20.0 mg/m2 for 4RT. More falls (3 in the placebo group vs 11 in the TPI-287 group) and a dose-related worsening of dementia symptoms (mean [SD] in the CDR plus NACC FTLD-SB [Clinical Dementia Rating scale sum of boxes with frontotemporal dementia measures], 0.5 [1.8] in the placebo group vs 0.7 [1.6] in the TPI-287 group; median difference, 1.5 [95% CI, 0-2.5]; P =.03) were seen in patients with 4RT. Despite undetectable TPI-287 levels in CSF, CSF biomarkers demonstrated decreased chitinase-3-like protein-1 (YKL-40) levels in the 4RT treatment arm (mean [SD], -8.4 [26.0] ng/mL) compared with placebo (mean [SD], 10.4 [42.3] ng/mL; median difference, -14.6 [95% CI, -30.0 to 0.2] ng/mL; P =.048, Mann-Whitney test). Conclusions and Relevance: In this randomized clinical trial, TPI-287 was less tolerated in patients with AD than in those with 4RT owing to the presence of anaphylactoid reactions. The ability to reveal different tau therapeutic effects in various tauopathy syndromes suggests that basket trials are a valuable approach to tau therapeutic early clinical development. Trial Registration: ClinicalTrials.gov identifiers: NCT019666666 and NCT02133846. © 2019 American Medical Association. All rights reserved.
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Training Models for Implementing Evidence-Based Psychological Treatment: A Cluster-Randomized Trial in College Counseling Centers” (2019) JAMA Psychiatry
Training Models for Implementing Evidence-Based Psychological Treatment: A Cluster-Randomized Trial in College Counseling Centers
(2019) JAMA Psychiatry, .
Wilfley, D.E.a , Agras, W.S.b , Fitzsimmons-Craft, E.E.a , Bohon, C.b , Eichen, D.M.c , Welch, R.R.a , Jo, B.b , Raghavan, R.d , Proctor, E.K.e , Wilson, G.T.f
a Department of Psychiatry, Washington University School of Medicine, Mailstop 8134-29-2100, 660 S Euclid Ave, St Louis, MO 63110, United States
b Stanford University School of Medicine, Department of Psychiatry and Behavioral Sciences, Stanford, CA, United States
c Department of Pediatrics, University of California, San Diego, United States
d School of Social Work, Rutgers, State University of New Jersey, New Brunswick, United States
e George Warren Brown School of Social Work, Washington University in St Louis, St Louis, MO, United States
f Graduate School of Applied and Professional Psychology, Rutgers, State University of New Jersey, Piscataway, United States
Abstract
Importance: Progress has been made in establishing evidence-based treatments for psychiatric disorders, but these are not often delivered in routine settings. A scalable solution for training clinicians in evidence-based treatments is needed. Objective: To compare 2 methods of training college (university) counseling center therapists to treat psychiatric disorders using interpersonal psychotherapy. The hypothesis was that the train-the-trainer condition would demonstrate superior implementation outcomes vs the expert condition. Moderating factors were also explored. Design, Setting, and Participants: This cluster-randomized trial was conducted from October 2012 to December 2017 in 24 college counseling centers across the United States. Therapist participants were recruited from enrolled centers, and student patients with symptoms of depression and eating disorders were recruited by therapists. Data were analyzed from 184 enrolled therapists. Interventions: Counseling centers were randomized to the expert condition, which involved a workshop and 12 months of follow-up consultation, or the train-the-trainer condition, in which a staff member from the counseling center was coached to train other staff members. Main Outcomes and Measures: The main outcome was therapist fidelity (adherence and competence) to interpersonal psychotherapy, as assessed via audio recordings of therapy sessions. Therapist knowledge of interpersonal psychotherapy was a secondary outcome. Result: A total of 184 therapists (mean [SD] age, 41.9 [10.6] years; 140 female [76.1%]; 142 white [77.2%]) were included. Both the train-the-trainer-condition and expert-condition groups showed significant within-group improvement for adherence to interpersonal psychotherapy (change: 0.233 [95% CI, 0.192-0.274] and 0.190 [0.145-0.235], respectively; both P <.001), with large effect sizes (1.64 [95% CI, 1.35-1.93] and 1.34 [95% CI, 1.02-1.66], respectively) and no significant difference between conditions. Both groups also showed significant within-group improvement in interpersonal therapy competence (change: 0.179 [95% CI, 0.132-0.226] and 0.106 [0.059-0.153], respectively; both P <.001), with a large effect size for the train-the-trainer condition (1.16 [95% CI, 0.85-1.46]; P <.001) and a significant difference between groups favoring the train-the-trainer condition (effect size, 0.47 [95% CI, 0.05-0.89]; P =.03). Knowledge of interpersonal psychotherapy improved significantly within both groups (effect sizes: Train-the-trainer, 0.64 [95% CI, 0.28-0.99]; P =.005; expert, 0.69 [95% CI, 0.38-1.01]; P <.001), with no significant difference between groups. The significant moderating factors were job satisfaction for adherence (b, 0.120 [95% CI, 0.001-0.24]; P =.048) and competence (b, 0.133 [95% CI, 0.001-0.27]; P =.048), and frequency of clinical supervision for competence (b, 0.05 [95% CI, 0.004-0.09]; P =.03). Conclusions and Relevance: Results demonstrate that the train-the-trainer model produced training outcomes comparable with the expert model for adherence and was superior on competence. Given its potential capability to train more therapists over time, it has the potential to facilitate widespread dissemination of evidence-based treatments. Trial Registration: ClinicalTrials.gov Identifier: NCT02079142. © 2019 © 2019 S. Karger AG, Basel. Copyright: All rights reserved.
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Simultaneous PET-MRI imaging of cerebral blood flow and glucose metabolism in the symptomatic unilateral internal carotid artery/middle cerebral artery steno-occlusive disease” (2019) European Journal of Nuclear Medicine and Molecular Imaging
Simultaneous PET-MRI imaging of cerebral blood flow and glucose metabolism in the symptomatic unilateral internal carotid artery/middle cerebral artery steno-occlusive disease
(2019) European Journal of Nuclear Medicine and Molecular Imaging, .
Cui, B.a , Zhang, T.b c , Ma, Y.d , Chen, Z.e , Ma, J.a , Ma, L.a , Jiao, L.d , Zhou, Y.f , Shan, B.b c g , Lu, J.a h
a Department of Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China
b Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
c School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
d Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China
e GE Healthcare, Beijing, China
f Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
g CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China
h Department of Radiology, Xuanwu Hospital Capital Medical University, Beijing, China
Abstract
Purpose: Cerebral blood flow (CBF) and glucose metabolism are important and significant factors in ischaemic cerebrovascular disease. The objective of this study was to use quantitative hybrid PET/MR to evaluate the effects of surgery treatment on the symptomatic unilateral internal carotid artery/middle cerebral artery steno-occlusive disease. Methods: Fifteen patients diagnosed with ischaemic cerebrovascular disease were evaluated using a hybrid TOF PET/MR system (Signa, GE Healthcare). The CBF value measured by arterial spin labelling (ASL) and the standardized uptake value ratio (SUVR) measured by 18F-FDG PET were obtained, except for the infarct area and its contralateral side, before and after bypass surgery. The asymmetry index (AI) was calculated from the CBF and SUVR of the ipsilateral and contralateral cerebral hemispheres, respectively. The ΔCBF and ΔSUVR were calculated as the percent changes of CBF and SUVR between before and after surgery, and paired t tests were used to determine whether a significant change occurred. Spearman’s rank correlation was also used to compare CBF with glucose metabolism in the same region. Results: The analysis primarily revealed that after bypass surgery, a statistically significant increase occurred in the CBF on the affected side (P < 0.01). The postprocedural SUVR was not significantly higher than the preprocedural SUVR (P > 0.05). However, the postprocedural AI values for CBF and SUVR were significantly lower after surgery than before surgery (P < 0.01). A significant correlation was found between the AI values for preoperative CBF and SUVR on the ipsilateral hemisphere (P < 0.01). Conclusions: The present study demonstrates that a combination of ASL and 18F-FDG PET could be used to simultaneously analyse changes in patients’ cerebral haemodynamic patterns and metabolism between before and after superficial temporal artery-middle cerebral artery (STA-MCA) bypass surgery. This therefore represents an essential tool for the evaluation of critical haemodynamic and metabolic status in patients with symptomatic unilateral ischaemic cerebrovascular disease. © 2019, The Author(s).
Author Keywords
Cerebral blood flow; Glucose metabolism; Ischaemic cerebrovascular disease; PET/MR; Superficial temporal artery-middle cerebral artery bypass
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Access Type: Open Access
“Diroximel fumarate (DRF) in patients with relapsing–remitting multiple sclerosis: Interim safety and efficacy results from the phase 3 EVOLVE-MS-1 study” (2019) Multiple Sclerosis Journal
Diroximel fumarate (DRF) in patients with relapsing–remitting multiple sclerosis: Interim safety and efficacy results from the phase 3 EVOLVE-MS-1 study
(2019) Multiple Sclerosis Journal, .
Naismith, R.T.a , Wolinsky, J.S.b , Wundes, A.c , LaGanke, C.d , Arnold, D.L.e m , Obradovic, D.f , Freedman, M.S.g , Gudesblatt, M.h , Ziemssen, T.i , Kandinov, B.j , Bidollari, I.j , Lopez-Bresnahan, M.j , Nangia, N.j , Rezendes, D.j , Yang, L.k , Chen, H.k , Liu, S.k , Hanna, J.l , Miller, C.k , Leigh-Pemberton, R.j
a Washington University School of Medicine, St. Louis, MO, United States
b Department of Neurology, McGovern Medical School, The University of Texas Health Science Center at Houston (UTHealth), Houston, TX, United States
c Department of Neurology, University of Washington Medical Center, Seattle, WA, United States
d North Central Neurology Associates, Cullman, AL, United States
e Montreal Neurological Institute, McGill University, Montreal, QC, Canada
f Department of Neurology, Military Medical Academy, Belgrade, Serbia
g University of Ottawa, Ottawa Hospital Research Institute, Ottawa, ON, Canada
h South Shore Neurologic Associates, Patchogue, NY, United States
i Center of Clinical Neuroscience, Carl Gustav Carus University Hospital, Dresden, Germany
j Alkermes Inc, Waltham, MA, United States
k Biogen, Cambridge, MA, United States
l Biogen, Maidenhead, United Kingdom
m NeuroRx Research Inc., Montreal, QC, Canada
Abstract
Background: Diroximel fumarate (DRF) is a novel oral fumarate for patients with relapsing–remitting multiple sclerosis (RRMS). DRF and the approved drug dimethyl fumarate yield bioequivalent exposure to the active metabolite monomethyl fumarate; thus, efficacy/safety profiles are expected to be similar. However, DRF’s distinct chemical structure may result in a differentiated gastrointestinal (GI) tolerability profile. Objective: To report interim safety/efficacy findings from patients in the ongoing EVOLVE-MS-1 study. Methods: EVOLVE-MS-1 is an ongoing, open-label, 96-week, phase 3 study assessing DRF safety, tolerability, and efficacy in RRMS patients. Primary endpoint is safety and tolerability; efficacy endpoints are exploratory. Results: As of March 2018, 696 patients were enrolled; median exposure was 59.9 (range: 0.1–98.9) weeks. Adverse events (AEs) occurred in 84.6% (589/696) of patients; the majority were mild (31.2%; 217/696) or moderate (46.8%; 326/696) in severity. Overall treatment discontinuation was 14.9%; 6.3% due to AEs and <1% due to GI AEs. At Week 48, mean number of gadolinium-enhancing lesions was significantly reduced from baseline (77%; p < 0.0001) and adjusted annualized relapse rate was low (0.16; 95% confidence interval: 0.13–0.20). Conclusion: Interim data from EVOLVE-MS-1 suggest DRF is a well-tolerated treatment with a favorable safety/efficacy profile for patients with RRMS. © The Author(s), 2019.
Author Keywords
clinical trial; diroximel fumarate; disease-modifying therapy; efficacy; monomethyl fumarate; multiple sclerosis; Relapsing–remitting multiple sclerosis; safety
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Children’s awareness of the context-appropriate nature of emotion regulation strategies across emotions” (2019) Cognition and Emotion
Children’s awareness of the context-appropriate nature of emotion regulation strategies across emotions
(2019) Cognition and Emotion, .
Quiñones-Camacho, L.E.a b , Davis, E.L.a
a Department of Psychology, University of California Riverside, Riverside, CA, United States
b Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, United States
Abstract
Emotion regulation (ER) substantially develops during the childhood years. This growth includes an increasing awareness that certain ER strategies are more appropriate in some contexts than others, but few studies have explored how children tailor ER strategies across contexts (i.e. context sensitivity). Understanding this could help clarify why some children have difficulties effectively regulating their emotions even when they have a broad strategy repertoire. The current study explored differences in Hispanic children’s ER strategy context sensitivity across three emotions and explored attentional control as a possible moderator of this sensitivity. Children (N = 78; M = 9.91; SD = 1.14; 50% girls; household income M = 31–40k) completed an attentional control task and were interviewed about their ER strategy preferences for sadness, fear, and anger. Context sensitivity was measured as the proportion of endorsed ER strategies that theoretically “fit” the given emotion. Children showed more sensitivity for anger and fear compared to sadness. Attentional control predicted context sensitivity for sadness only, but this was qualified by age. Older children showed more context sensitivity with increasing attentional control. Findings provide insight into emotional development in late childhood by highlighting children’s awareness of the context-appropriate nature of ER strategies across emotions. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
Author Keywords
attentional control; childhood; context sensitivity; discrete emotions; Emotion regulation
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Adolescents and young adults engaged with pro-eating disorder social media: eating disorder and comorbid psychopathology, health care utilization, treatment barriers, and opinions on harnessing technology for treatment” (2019) Eating and Weight Disorders
Adolescents and young adults engaged with pro-eating disorder social media: eating disorder and comorbid psychopathology, health care utilization, treatment barriers, and opinions on harnessing technology for treatment
(2019) Eating and Weight Disorders, .
Fitzsimmons-Craft, E.E., Krauss, M.J., Costello, S.J., Floyd, G.M., Wilfley, D.E., Cavazos-Rehg, P.A.
Department of Psychiatry, Washington University School of Medicine, 660 South Euclid Avenue, 8134, St. Louis, MO 63110, United States
Abstract
Purpose: The purpose of this study was to examine exposure (i.e., seeing, following, posting) to body image content emphasizing a thin ideal on various social media platforms and probable eating disorder (ED) diagnoses, ED-related quality of life, and psychiatric comorbidities (i.e., depression, anxiety) among adolescents and young adult females recruited via social media who endorsed viewing and/or posting pro-ED online content. We also investigated health care utilization, treatment barriers, and opinions on harnessing technology for treatment. Methods: Participants were 405 adolescent and young adult females engaged with pro-ED social media. We reported on study constructs for the sample as a whole, as well as on differences between age groups. Results: Eighty-four percent of participants’ self-reported symptoms were consistent with a clinical/subclinical ED, and this was slightly more common among young adults. Participants endorsed reduced ED-related quality of life, as well as comorbid depression and anxiety. Among those with clinical/subclinical EDs, only 14% had received treatment. The most common treatment barriers were believing the problem was not serious enough and believing one should help themselves. The majority of participants approved of harnessing technology for treatment. Conclusions: Results provide support for engagement with pro-ED online content serving as a potential indicator of ED symptoms and suggest promise for facilitating linkage from social media to technology-enhanced interventions. Level of evidence: V, cross-sectional descriptive study. © 2019, Springer Nature Switzerland AG.
Author Keywords
Adolescent; Cross-sectional studies; Feeding and eating disorders; Social media; Young adult
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“DLK Activation Synergizes with Mitochondrial Dysfunction to Downregulate Axon Survival Factors and Promote SARM1-Dependent Axon Degeneration” (2019) Molecular Neurobiology
DLK Activation Synergizes with Mitochondrial Dysfunction to Downregulate Axon Survival Factors and Promote SARM1-Dependent Axon Degeneration
(2019) Molecular Neurobiology, .
Summers, D.W.a b c , Frey, E.c , Walker, L.J.c , Milbrandt, J.d e , DiAntonio, A.c e
a Department of Biology, University of Iowa, Iowa City, IA 52242, United States
b Iowa Neuroscience Institute, University of Iowa, Iowa City, IA 52242, United States
c Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO 63110, United States
d Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, United States
e Needleman Center for Neurometabolism and Axonal Therapeutics, Washington University School of Medicine, St. Louis, MO 63110, United States
Abstract
Axon degeneration is a prominent component of many neurological disorders. Identifying cellular pathways that contribute to axon vulnerability may identify new therapeutic strategies for maintenance of neural circuits. Dual leucine zipper kinase (DLK) is an axonal stress response MAP3K that is chronically activated in several neurodegenerative diseases. Activated DLK transmits an axon injury signal to the neuronal cell body to provoke transcriptional adaptations. However, the consequence of enhanced DLK signaling to axon vulnerability is unknown. We find that stimulating DLK activity predisposes axons to SARM1-dependent degeneration. Activating DLK reduces levels of the axon survival factors NMNAT2 and SCG10, accelerating their loss from severed axons. Moreover, mitochondrial dysfunction independently decreases the levels of NMNAT2 and SCG10 in axons, and in conjunction with DLK activation, leads to a dramatic loss of axonal NMNAT2 and SCG10 and evokes spontaneous axon degeneration. Hence, enhanced DLK activity reduces axon survival factor abundance and renders axons more susceptible to trauma and metabolic insult. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
Author Keywords
Axon; DLK; Mitochondria; NMNAT2; SARM1; STMN2
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Confidential genetic testing and electronic health records: A survey of current practices among Huntington disease testing centers” (2019) Molecular Genetics and Genomic Medicine
Confidential genetic testing and electronic health records: A survey of current practices among Huntington disease testing centers
(2019) Molecular Genetics and Genomic Medicine, art. no. e1026, .
Eno, C.C.a , Barton, S.K.b , Dorrani, N.a , Cederbaum, S.D.a , Deignan, J.L.a , Grody, W.W.a
a University of California, Los Angeles Los Angeles, CA, United States
b Washington University, St. Louis, MO, United States
Abstract
Background: Clinical care teams providing presymptomatic genetic testing often employ advanced confidentiality practices for documentation and result storage. However, patient requests for increased confidentiality may be in conflict with the legal obligations of medical providers to document patient care activities in the electronic health record (EHR). Huntington disease presents a representative case study for investigating the ways centers currently balance the requirements of EHRs with the privacy demands of patients seeking presymptomatic genetic testing. Methods: We surveyed 23 HD centers (53% response rate) regarding their use of the EHR for presymptomatic HD testing. Results: Our survey revealed that clinical care teams and laboratories have each developed their own practices, which are cumbersome and often include EHR avoidance. We found that a majority of HD care teams record appointments in the EHR (91%), often using vague notes. Approximately half of the care teams (52%) keep presymptomatic results of out of the EHR. Conclusion: As genetic knowledge grows, linking more genes to late-onset conditions, institutions will benefit from having professional recommendations to guide development of policies for EHR documentation of presymptomatic genetic results. Policies must be sensitive to the ethical differences and patient demands for presymptomatic genetic testing compared to those undergoing confirmatory genetic testing. © 2019 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.
Author Keywords
confidentiality; electronic health record; Huntington disease; presymptomatic testing; privacy
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Access Type: Open Access
“Differences in Driving Outcomes Among Cognitively Normal African American and Caucasian Older Adults” (2019) Journal of Racial and Ethnic Health Disparities
Differences in Driving Outcomes Among Cognitively Normal African American and Caucasian Older Adults
(2019) Journal of Racial and Ethnic Health Disparities, .
Babulal, G.M.a b , Stout, S.H.a b , Williams, M.M.c , Rajasekar, G.a b , Harmon, A.d , Vivoda, J.e , Zuelsdorff, M.f , Benzinger, T.L.S.a g h , Morris, J.C.a b g i j k l , Ances, B.a b i , Roe, C.M.a b
a Charles F. and Joanne Knight Alzheimer’s Disease Research Center, 660 S. Euclid Ave., Campus Box, St. Louis, MO 8111, United States
b Department of Neurology, Washington University, St. Louis, MO, United States
c BJC Medical Group, St. Louis, MO, United States
d Department of Medicine, Washington University, St. Louis, MO, United States
e Miami University, Oxford, OH, United States
f University of Wisconsin, Madison, WI, United States
g Department of Radiology, Washington University, St. Louis, MO, United States
h Department of Neurosurgery, Washington University, St. Louis, MO, United States
i Hope Center for Neurological Disorders, Washington University, St. Louis, MO, United States
j Department of Pathology and Immunology, Washington University, St. Louis, MO, United States
k Department of Physical Therapy, Washington University, St. Louis, MO, United States
l Department of Occupational Therapy, Washington University, St. Louis, MO, United States
Abstract
Objective: To examine the effect of race in driving performance and behavior prospectively among cognitively normal older adults. Methods: Cognitively normal participants (Clinical Dementia Rating 0), ≥ 65 years of age (n = 177) were selected from prospective, longitudinal studies at the Knight Alzheimer Disease Research Center at Washington University. Self-reported driving behavior (Driving Habits Questionnaire) and driving performance (road test) were annually assessed. Daily driving behavior data were collected using the Driving Real World In-Vehicle Evaluation System (DRIVES). Baseline differences between African Americans and Caucasians were tested using t tests and general linear models. Amyloid imaging and cerebrospinal fluid Alzheimer disease (AD) biomarkers were compared across groups. Linear mixed models examined change in daily driving behavior over time. Survival analyses tested time to a marginal or fail rating on the road test. Results: There were no differences between African Americans (n = 34) and Caucasians (n = 143) in age, sex, education, or vascular risk factors. Baseline self-reported driving behavior and road test performance were largely similar for both races. Longitudinal analyses using the DRIVES data aggregated monthly showed that African Americans had a greater reduction in number of trips made per month, miles driven per month, and trips with aggressive behavior compared to Caucasians. These effects remained after controlling for AD biomarkers, age, education, and sex. Conclusions: In this sample of cognitively normal older adults, African Americans had a greater reduction of daily driving behavior compared to Caucasians. Observed racial differences may reflect differences in environmental/social factors, changes in cognition, and/or physical functioning. © 2019, W. Montague Cobb-NMA Health Institute.
Author Keywords
African Americans; Alzheimer’s disease; Driving; Older adults; Race
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Health-Related Quality of Life and Cognitive Functioning in Pediatric Liver Transplant Recipients” (2019) Liver Transplantation
Health-Related Quality of Life and Cognitive Functioning in Pediatric Liver Transplant Recipients
(2019) Liver Transplantation, .
Ohnemus, D.a , Neighbors, K.b , Rychlik, K.c , Venick, R.S.d , Bucuvalas, J.C.e , Sundaram, S.S.f , Ng, V.L.g , Andrews, W.S.h , Turmelle, Y.i , Mazariegos, G.V.j , Sorensen, L.G.k , Alonso, E.M.b , for Studies of Pediatric Liver Transplantation (SPLIT)l
a Northwestern University Feinberg School of Medicine, Chicago, IL, United States
b Division of Gastroenterology, Hepatology and Nutrition, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, United States
c Stanley Manne Children’s Research Institute, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, United States
d Department of Pediatrics, Division of Gastroenterology, David Geffen School of Medicine, University of California, Los Angeles, CA, United States
e Jack and Lucy Clark Department of Pediatrics, Mount Sinai Kravis Children’s Hospital Recanati/Miller Transplantation Institute, New York, NY, United States
f Section of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics and the Digestive Health Institute, Children’s Hospital of Colorado and University of Colorado School of Medicine, Aurora, CO, United States
g Division of Pediatric Gastroenterology, Hepatology and Nutrition, Transplant and Regenerative Medicine Center, Toronto, ON, Canada
h Department of Pediatric Surgery, Children’s Mercy Hospital, Kansas City, MO, United States
i Section of Hepatology, Department of Pediatrics, Washington University, St. Louis, MO, United States
j Hillman Center for Pediatric Transplantation, Children’s Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, PA, United States
k Department of Child and Adolescent Psychiatry, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, United States
Abstract
The goal of this work was to examine the change in health-related quality of life (HRQOL) and cognitive functioning from early childhood to adolescence in pediatric liver transplantation (LT) recipients. Patients were recruited from 8 North American centers through the Studies of Pediatric Liver Transplantation consortium. A total of 79 participants, ages 11-18 years, previously tested at age 5-6 years in the Functional Outcomes Group study were identified as surviving most recent LT by 2 years and in stable medical follow-up. The Pediatric Quality of Life 4.0 Generic Core Scale, Pediatric Quality of Life Cognitive Function Scale, and PROMIS Pediatric Cognitive Function tool were distributed to families electronically. Data were analyzed using repeated measures and paired t tests. Predictive variables were analyzed using univariate regression analysis. Of the 69 families contacted, 65 (94.2%) parents and 61 (88.4%) children completed surveys. Median age of participants was 16.1 years (range, 12.9-18.0 years), 55.4% were female, 33.8% were nonwhite, and 84.0% of primary caregivers had received at least some college education. Median age at LT was 1.1 years (range, 0.1-4.8 years). The majority of participants (86.2%) were not hospitalized in the last year. According to parents, adolescents had worse HRQOL and cognitive functioning compared with healthy children in all domains. Adolescents reported HRQOL similar to healthy children in all domains except psychosocial, school, and cognitive functioning (P = 0.02; P < 0.001; P = 0.04). Participants showed no improvement in HRQOL or cognitive functioning over time. For cognitive and school functioning, 60.0% and 50.8% of parents reported “poor” functioning, respectively (>1 standard deviation below the healthy mean). Deficits in HRQOL seem to persist in adolescence. Over half of adolescent LT recipients appear to be at risk for poor school and cognitive functioning, likely reflecting attention and executive function deficits. Copyright © 2019 by the American Association for the Study of Liver Diseases
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“The interactions of dopamine and oxidative damage in the striatum of patients with neurodegenerative diseases” (2019) Journal of Neurochemistry
The interactions of dopamine and oxidative damage in the striatum of patients with neurodegenerative diseases
(2019) Journal of Neurochemistry, .
Li, H.a , Yang, P.a , Knight, W.a , Guo, Y.a , Perlmutter, J.S.a b c d e , Benzinger, T.L.S.a , Morris, J.C.b , Xu, J.a
a Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
b Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
c Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
d Department of Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States
e Department of Occupational Therapy, Washington University School of Medicine, St. Louis, MO, United States
Abstract
The striatum with a number of dopamine containing neurons, receiving projections from the substantia nigra and ventral tegmental area; plays a critical role in neurodegenerative diseases of motor and memory function. Additionally, oxidative damage to nucleic acid may be vital in the development of age-associated neurodegeneration. The metabolism of dopamine is recognized as one of the sources of reactive oxygen species through the Fenton mechanism. The proposed interactions of oxidative insults and dopamine in the striatum during the progression of diseases are the hypotheses of most interest to our study. This study investigated the possibility of significant interactions between these molecules that are involved in the late-stage of Alzheimer’s disease (AD), Parkinson disease (PD), Parkinson disease dementia, dementia with Lewy bodies, and controls using ELISA assays, autoradiography, and mRNA in situ hybridization assay. Interestingly, lower DNA/RNA oxidative adducts levels in the caudate and putamen of diseased brains were observed with the exception of an increased DNA oxidative product in the caudate of AD brains. Similar changes were found for dopamine concentration and vesicular monoamine transporter 2 densities. We also found that downstream pre-synaptic dopamine D1 Receptor binding correlated with dopamine loss in Lewy body disease groups, and RNA damage and β-site APP cleaving enzyme 1 in the caudate of AD. This is the first demonstration of region-specific alterations of DNA/RNA oxidative damage which cannot be viewed in isolation, but rather in connection with the interrelationship between different neuronal events; chiefly DNA oxidative adducts and density of vesicular monoamine transporter 2 densities in AD and PD patients. (Figure presented.). © 2019 The Authors. Journal of Neurochemistry published by John Wiley & Sons Ltd on behalf of International Society for Neurochemistry
Author Keywords
Alzheimer’s disease; dopamine; Lewy body diseases; oxidative damage; striatum
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Access Type: Open Access
“Performance on the Verbal Naming Test among healthy, community-dwelling older adults” (2019) Clinical Neuropsychologist
Performance on the Verbal Naming Test among healthy, community-dwelling older adults
(2019) Clinical Neuropsychologist, .
Wynn, M.J.a , Sha, A.Z.a , Lamb, K.a , Carpenter, B.D.a , Yochim, B.P.b
a Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States
b VA St. Louis Health Care System, St. Louis, MO, United States
Abstract
Objective: The Verbal Naming Test (VNT) is a nonvisual measure of word finding with stimuli chosen based on rare frequency of usage in spoken English. The purpose of the current study was to evaluate the psychometric properties of the VNT and test the feasibility of telephone administration. In addition, regression-based normative data were obtained for the VNT as well as other measures. Method: Eighty-one community-dwelling older adults 61–92 years old (mean = 74.19 years) completed the VNT, the Naming subtests of the Neuropsychological Assessment Battery (NAB), the WIAT-III Sentence Repetition subtest, and the Montreal Cognitive Assessment (MoCA). Results: As evidence of construct validity, the VNT had large correlations with the NAB Naming test and medium correlations with the MoCA and WIAT-III Sentence Repetition test. Cronbach’s alpha in this sample was 0.621. Age, education, and gender were entered into linear regression equations and regression-based normative equations are presented. Lastly, administration of the VNT over the telephone was found to be feasible. Conclusions: The VNT is a valid measure of naming among community-dwelling older adults. Regression-based normative data for the measure will enable its use in the neuropsychological assessment of naming with a wide range of older adults. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
Author Keywords
Anomia; cognitive disorders; neuropsychology; normative data; psychometrics
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Comorbid anxiety in late-life depression: Relationship with remission and suicidal ideation on venlafaxine treatment” (2019) Depression and Anxiety,
Comorbid anxiety in late-life depression: Relationship with remission and suicidal ideation on venlafaxine treatment
(2019) Depression and Anxiety, .
Saade, Y.M.a , Nicol, G.a , Lenze, E.J.a , Miller, J.P.b , Yingling, M.a , Wetherell, J.L.c , Reynolds, C.F., IIId , Mulsant, B.H.e
a Department of Psychiatry, Washington University, St. Louis, MO, United States
b Division of Biostatistics, Washington University in St. Louis, St. Louis, MO, United States
c Department of Psychiatry, VA San Diego Healthcare System, University of California, San Diego, CA, United States
d Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
e Department of Psychiatry, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada
Abstract
Objective: The purpose of this study was to examine the influence of comorbid anxiety symptoms on antidepressant treatment remission in older adults with major depressive disorder (MDD). Method: In this multisite clinical trial, 468 older adults aged 60 years or older with MDD received open-label protocolized treatment with venlafaxine extended release (ER) titrated to a maximum of 300 mg daily. At baseline, anxiety was assessed with the Anxiety Sensitivity Index, the Brief Symptom Inventory (BSI) anxiety subscale, and the Penn State Worry Questionnaire. To measure treatment response, depressive symptoms and suicidality were assessed every 1–2 weeks with the Montgomery–Asberg Depression Rating Scale and the 19-item Scale for Suicide Ideation; anxiety was assessed with the BSI. Logistic regression and survival analysis were used to evaluate whether anxiety symptoms predicted depression remission. We also examined the relationships between anxiety scores and suicidality at baseline. Results: Baseline anxiety symptoms did not predict remission or time to remission of depressive symptoms. Depressive, worry, and panic symptoms decreased in parallel in patients with high anxiety. Anxiety symptoms were associated with the severity of depression and with suicidality. Conclusion: In older adults with MDD, comorbid anxiety symptoms are associated with symptom severity but do not affect antidepressant remission or time to remission. © 2019 Wiley Periodicals, Inc.
Author Keywords
antidepressants; anxiety/anxiety disorders; depression; geriatric/aging/elderly; suicide/self-harm
Document Type: Article
Publication Stage: Article in Press
Source: Scopus