Evidence and sources of placebo effects in transcranial direct current stimulation during a single session of visuospatial working memory practice
(2024) Scientific Reports, 14 (1), art. no. 9094, .
Hooyman, A.a , Haikalis, N.K.a , Wang, P.a , Schambra, H.M.b , Lohse, K.R.c , Schaefer, S.Y.a
a School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, MC 9709, Tempe, AZ 85287, United States
b Department of Neurology and Department of Physical Medicine and Rehabilitation, Grossman School of Medicine, New York University, New York, NY, United States
c Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Transcranial direct current stimulation (tDCS) can be used to non-invasively augment cognitive training. However, the benefits of tDCS may be due in part to placebo effects, which have not been well-characterized. The purpose of this study was to determine whether tDCS can have a measurable placebo effect on cognitive training and to identify potential sources of this effect. Eighty-three right-handed adults were randomly assigned to one of three groups: control (no exposure to tDCS), sham tDCS, or active tDCS. The sham and active tDCS groups were double-blinded. Each group performed 20 min of an adapted Corsi Block Tapping Task (CBTT), a visuospatial working memory task. Anodal or sham tDCS was applied during CBTT training in a right parietal-left supraorbital montage. After training, active and sham tDCS groups were surveyed on expectations about tDCS efficacy. Linear mixed effects models showed that the tDCS groups (active and sham combined) improved more on the CBTT with training than the control group, suggesting a placebo effect of tDCS. Participants’ tDCS expectations were significantly related to the placebo effect, as was the belief of receiving active stimulation. This placebo effect shows that the benefits of tDCS on cognitive training can occur even in absence of active stimulation. Future tDCS studies should consider how treatment expectations may be a source of the placebo effect in tDCS research, and identify ways to potentially leverage them to maximize treatment benefit. © The Author(s) 2024.
Document Type: Article
Publication Stage: Final
Source: Scopus
TOPMed imputed genomics enhances genomic atlas of the human proteome in brain, cerebrospinal fluid, and plasma
(2024) Scientific Data, 11 (1), art. no. 387, .
Yi, H.a b , Yang, Q.b , Repaci, C.b c , Lee, C.M.b d , Heo, G.a b , Timsina, J.a b , Gorijala, P.a b , Yang, C.a b , Budde, J.a b , Wang, L.a b , Cruchaga, C.a b e , Sung, Y.J.a b c
a Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
b NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, United States
c Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
d Institute for Informatics, Washington University School of Medicine, St. Louis, MO, United States
e Hope Center for Neurologic Diseases, Washington University, St. Louis, MO, United States
Abstract
Comprehensive expression quantitative trait loci studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein quantitative trait loci in brain, cerebrospinal fluid, and plasma. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in cerebrospinal fluid, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 loci in brain, 30 loci in cerebrospinal fluid, and 22 loci in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These resources are accessible through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer for use by the scientific community. © The Author(s) 2024.
Document Type: Article
Publication Stage: Final
Source: Scopus
Characterization of early markers of disease in the mouse model of mucopolysaccharidosis IIIB
(2024) Journal of Neurodevelopmental Disorders, 16 (1), art. no. 16, .
McCullough, K.B.a b , Titus, A.a , Reardon, K.a , Conyers, S.a , Dougherty, J.D.a b c , Ge, X.d , Garbow, J.R.c d , Dickson, P.c e , Yuede, C.M.a c f g , Maloney, S.E.a b c
a Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
b Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, United States
c Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, MO 63110, United States
d Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
e Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
f Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
g Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States
Abstract
Background: Mucopolysaccharidosis (MPS) IIIB, also known as Sanfilippo Syndrome B, is a devastating childhood disease. Unfortunately, there are currently no available treatments for MPS IIIB patients. Yet, animal models of lysosomal storage diseases have been valuable tools in identifying promising avenues of treatment. Enzyme replacement therapy, gene therapy, and bone marrow transplant have all shown efficacy in the MPS IIIB model systems. A ubiquitous finding across rodent models of lysosomal storage diseases is that the best treatment outcomes resulted from intervention prior to symptom onset. Therefore, the aim of the current study was to identify early markers of disease in the MPS IIIB mouse model as well as examine clinically-relevant behavioral domains not yet explored in this model. Methods: Using the MPS IIIB mouse model, we explored early developmental trajectories of communication and gait, and later social behavior, fear-related startle and conditioning, and visual capabilities. In addition, we examined brain structure and function via magnetic resonance imaging and diffusion tensor imaging. Results: We observed reduced maternal isolation-induced ultrasonic vocalizations in MPS IIIB mice relative to controls, as well as disruption in a number of the spectrotemporal features. MPS IIIB also exhibited disrupted thermoregulation during the first two postnatal weeks without any differences in body weight. The developmental trajectories of gait were largely normal. In early adulthood, we observed intact visual acuity and sociability yet a more submissive phenotype, increased aggressive behavior, and decreased social sniffing relative to controls. MPS IIIB mice showed greater inhibition of startle in response to a pretone with a decrease in overall startle response and reduced cued fear memory. MPS IIIB also weighed significantly more than controls throughout adulthood and showed larger whole brain volumes and normalized regional volumes with intact tissue integrity as measured with magnetic resonance and diffusion tensor imaging, respectively. Conclusions: Together, these results indicate disease markers are present as early as the first two weeks postnatal in this model. Further, this model recapitulates social, sensory and fear-related clinical features. Our study using a mouse model of MPS IIIB provides essential baseline information that will be useful in future evaluations of potential treatments. © The Author(s) 2024.
Author Keywords
Aggression; Dominance; Fear conditioning; Gait; Lysosomal storage disorder; MRI/DTI; Mucopolysaccharidosis IIIB; Sanfilippo B; Startle response; Ultrasonic vocalization
Document Type: Article
Publication Stage: Final
Source: Scopus
The Brain Gene Registry: a data snapshot
(2024) Journal of Neurodevelopmental Disorders, 16 (1), art. no. 17, .
Baldridge, D.a , Kaster, L.b , Sancimino, C.c , Srivastava, S.d e , Molholm, S.f , Gupta, A.b , Oh, I.b , Lanzotti, V.g , Grewal, D.b , Riggs, E.R.h , Savatt, J.M.i , Hauck, R.b , Sveden, A.e , Constantino, J.N.j , Piven, J.k , Gurnett, C.A.l , Chopra, M.d e , Hazlett, H.k , Payne, P.R.O.b
a Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
b Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
c Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, United States
d Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
e Rosamund Stone Zander Translational Neuroscience Center, Boston Children’s Hospital, Boston, MA, United States
f Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine, Bronx, NY, United States
g Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
h Autism and Developmental Medicine Institute, Geisinger, Danville, PA, United States
i Department of Genomic Health, Geisinger, Danville, PA, United States
j Division of Behavioral and Mental Health, Departments of Psychiatry and Pediatrics, Children’s Healthcare of Atlanta, Emory University, Atlanta, GA, United States
k The Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, United States
l Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
Abstract
Monogenic disorders account for a large proportion of population-attributable risk for neurodevelopmental disabilities. However, the data necessary to infer a causal relationship between a given genetic variant and a particular neurodevelopmental disorder is often lacking. Recognizing this scientific roadblock, 13 Intellectual and Developmental Disabilities Research Centers (IDDRCs) formed a consortium to create the Brain Gene Registry (BGR), a repository pairing clinical genetic data with phenotypic data from participants with variants in putative brain genes. Phenotypic profiles are assembled from the electronic health record (EHR) and a battery of remotely administered standardized assessments collectively referred to as the Rapid Neurobehavioral Assessment Protocol (RNAP), which include cognitive, neurologic, and neuropsychiatric assessments, as well as assessments for attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Co-enrollment of BGR participants in the Clinical Genome Resource’s (ClinGen’s) GenomeConnect enables display of variant information in ClinVar. The BGR currently contains data on 479 participants who are 55% male, 6% Asian, 6% Black or African American, 76% white, and 12% Hispanic/Latine. Over 200 genes are represented in the BGR, with 12 or more participants harboring variants in each of these genes: CACNA1A, DNMT3A, SLC6A1, SETD5, and MYT1L. More than 30% of variants are de novo and 43% are classified as variants of uncertain significance (VUSs). Mean standard scores on cognitive or developmental screens are below average for the BGR cohort. EHR data reveal developmental delay as the earliest and most common diagnosis in this sample, followed by speech and language disorders, ASD, and ADHD. BGR data has already been used to accelerate gene-disease validity curation of 36 genes evaluated by ClinGen’s BGR Intellectual Disability (ID)-Autism (ASD) Gene Curation Expert Panel. In summary, the BGR is a resource for use by stakeholders interested in advancing translational research for brain genes and continues to recruit participants with clinically reported variants to establish a rich and well-characterized national resource to promote research on neurodevelopmental disorders. © The Author(s) 2024.
Author Keywords
Brain gene registry; Electronic health records; Neurodevelopmental disorders
Funding details
Boston Children’s HospitalBCH
School of Medicine, Washington University in St. LouisWUSM
Albert Einstein College of Medicine, Yeshiva UniversityAECOM
Alvin J. Siteman Cancer CenterSCC
Children’s National Hospital
National Institutes of HealthNIH
University of North Carolina WilmingtonUNCW
Baylor College of Medicine
National Center for Advancing Translational SciencesNCATS
U24HG006834
National Cancer InstituteNCIP30CA091842
P50HD103573
National Human Genome Research InstituteNHGRIUL1TR002345
Intellectual and Developmental Disabilities Research Center, School of Medicine, Washington University in St. LouisIDDRCP50HD105351
P50HD103525
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHDP50HD105352
Document Type: Article
Publication Stage: Final
Source: Scopus
Characteristics of women concordant and discordant for urine drug screens for cannabis exposure and self-reported cannabis use during pregnancy
(2024) Neurotoxicology and Teratology, 103, art. no. 107351, .
Bogdan, R.a , Leverett, S.D.b c , Constantino-Petit, A.M.c , Lashley-Simms, N.c , Liss, D.B.d , Johnson, E.C.c , Lenze, S.N.c , Lean, R.E.c , Smyser, T.A.c , Carter, E.B.e , Smyser, C.D.f , Rogers, C.E.c , Agrawal, A.c
a Psychological & Brain Sciences, Washington University in Saint Louis, United States
b Division of Biology & Biomedical Sciences, Neurosciences Program, Washington University in Saint Louis, United States
c Department of Psychiatry, Washington University in Saint Louis, United States
d Department of Emergency Medicine, Washington University in Saint Louis, United States
e Department of Obstetrics & Gynecology, Washington University in Saint Louis, United States
f Department of Neurology, Washington University in Saint Louis, United States
Abstract
Background: Increasing cannabis use among pregnant people and equivocal evidence linking prenatal cannabis exposure to adverse outcomes in offspring highlights the need to understand its potential impact on pregnancy and child outcomes. Assessing cannabis use during pregnancy remains a major challenge with potential influences of stigma on self-report as well as detection limitations of easily collected biological matrices. Objective: This descriptive study examined the concordance between self-reported (SR) cannabis use and urine drug screen (UDS) detection of cannabis exposure during the first trimester of pregnancy and characterized concordant and discordant groups for sociodemographic factors, modes of use, secondhand exposure to cannabis and tobacco, and alcohol use and cotinine positivity. Study design: The Cannabis Use During Development and Early Life (CUDDEL) Study is an ongoing longitudinal study that recruits pregnant individuals presenting for obstetric care, who report lifetime cannabis use as well as using (n = 289) or not using cannabis (n = 169) during pregnancy. During the first trimester pregnancy visit, SR of cannabis use and a UDS for cannabis, other illicit drugs and nicotine are acquired from eligible participants, of whom 333 as of 05/01/2023 had both. Results: Using available CUDDEL Study data on both SR and UDS (n = 333; age 26.6 ± 4.7; 88.6% Black; 45.4% below federal poverty threshold; 56.5% with paid employment; 89% with high school education; 22% first pregnancy; 12.3 ± 3.6 weeks gestation), we classified pregnant individuals with SR and UDS data into 4 groups based on concordance (k = 0.49 [95% C.I. 0.40–0.58]) between SR cannabis use and UDS cannabis detection during the first trimester: 1) SR+/UDS+ (n = 107); 2) SR-/UDS- (n = 142); 3) SR+/UDS- (n = 44); 4) SR-/UDS+ (n = 40). Those who were SR+/UDS- reported less frequent cannabis use and fewer hours under the influence of cannabis during their pregnancy. Those who were SR-/UDS+ were more likely to have joined the study at a lower gestational age with 62.5% reporting cannabis use during their pregnancy prior to being aware that they were pregnant. Of the 40 SR-/UDS+ women, 14 (i.e., 35%) reported past month secondhand exposure, or blunt usage. In the subset of individuals with SR and UDS available at trimester 2 (N = 160) and 3 (N = 140), concordant groups were mostly stable and > 50% of those in the discordant groups became concordant by the second trimester. Classifying individuals as exposed or not exposed who were SR+ and/or UDS+ resulted in minor changes in group status based on self-report at screening. Conclusion: Overall, there was moderate concordance between SR and UDS for cannabis use/exposure during pregnancy. Instances of SR+/UDS- discordancy may partially be attributable to lower levels of use that are not detected on UDS. SR-/UDS+ discordancy may arise from recent use prior to knowledge of pregnancy, extreme secondhand exposure, deception, and challenges with completing questionnaires. Acquiring both self-report and biological detection of cannabis use/exposure allows for the examination of convergent evidence. Classifying those who are SR+ and/or UDS+ as individuals who used cannabis during their first trimester after being aware of their pregnancy resulted in only a minor change in exposure status; thus, relying on self-report screening, at least in this population and within this sociocultural context likely provides an adequate approximation of cannabis use during pregnancy. © 2024 Elsevier Inc.
Author Keywords
cannabis; Pregnancy; Prenatal; Urine
Funding details
National Institutes of HealthNIHR01MH113570, 5T32NS121881, U01 DA055367, R21 AA027827, U01NS107486, R01 DA054750, K01MH122735, R01 AG061162
Document Type: Article
Publication Stage: Final
Source: Scopus
Encoding of Visual Objects in the Human Medial Temporal Lobe
(2024) Journal of Neuroscience, 44 (16), art. no. e2135232024, .
Wang, Y., Cao, R., Wang, S.
Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
Abstract
The human medial temporal lobe (MTL) plays a crucial role in recognizing visual objects, a key cognitive function that relies on the formation of semantic representations. Nonetheless, it remains unknown how visual information of general objects is translated into semantic representations in the MTL. Furthermore, the debate about whether the human MTL is involved in perception has endured for a long time. To address these questions, we investigated three distinct models of neural object coding-semantic coding, axisbased feature coding, and region-based feature coding-in each subregion of the human MTL, using high-resolution fMRI in two male and six female participants. Our findings revealed the presence of semantic coding throughout the MTL, with a higher prevalence observed in the parahippocampal cortex (PHC) and perirhinal cortex (PRC), while axis coding and region coding were primarily observed in the earlier regions of the MTL. Moreover, we demonstrated that voxels exhibiting axis coding supported the transition to region coding and contained information relevant to semantic coding. Together, by providing a detailed characterization of neural object coding schemes and offering a comprehensive summary of visual coding information for each MTL subregion, our results not only emphasize a clear role of the MTL in perceptual processing but also shed light on the translation of perceptiondriven representations of visual features into memory-driven representations of semantics along the MTL processing pathway. © 2024 the authors.
Author Keywords
amygdala; entorhinal cortex; hippocampus; medial temporal lobe; neural object coding; parahippocampal cortex; perirhinal cortex
Document Type: Article
Publication Stage: Final
Source: Scopus
Pharmacogenetic Influence on Stereoselective Steady-State Disposition of Bupropion
(2024) Drug Metabolism and Disposition: The Biological Fate of Chemicals, 52 (5), pp. 455-466.
Kharasch, E.D., Lenze, E.J.
Department of Anesthesiology, Duke University, Durham, North Carolina (E.D.K.); Bermaride, LLC (E.D.K.); and Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri (E.J.L.)
Abstract
Bupropion is used for treating depression, obesity, and seasonal affective disorder, and for smoking cessation. Bupropion is commonly prescribed, but has complex pharmacokinetics and interindividual variability in metabolism and bioactivation may influence therapeutic response, tolerability, and safety. Bupropion is extensively and stereoselectively metabolized, the metabolites are pharmacologically active, and allelic variation in cytochrome P450 (CYP) 2B6 affects clinical hydroxylation of single-dose bupropion. Genetic effects on stereoselective disposition of steady-state bupropion are not known. In this preplanned secondary analysis of a prospective, randomized, double-blinded, crossover study which compared brand and generic bupropion XL 300 mg drug products, we measured steady-state enantiomeric plasma and urine parent bupropion and primary and secondary metabolite concentrations. This investigation evaluated the influence of genetic polymorphisms in CYP2B6, CYP2C19, and P450 oxidoreductase on the disposition of Valeant Pharmaceuticals Wellbutrin brand bupropion in 67 participants with major depressive disorder. We found that hydroxylation of both bupropion enantiomers was lower in carriers of the CYP2B6*6 allele and in carriers of the CYP2B6 516G>T variant, with correspondingly greater bupropion and lesser hydroxybupropion plasma concentrations. Hydroxylation was 25-50% lower in CYP2B6*6 carriers and one-third to one-half less in 516T carriers. Hydroxylation of the bupropion enantiomers was comparably affected by CYP2B6 variants. CYP2C19 polymorphisms did not influence bupropion plasma concentrations or hydroxybupropion formation but did influence the minor pathway of 4′-hydroxylation of bupropion and primary metabolites. P450 oxidoreductase variants did not influence bupropion disposition. Results show that CYP2B6 genetic variants affect steady-state metabolism and bioactivation of Valeant brand bupropion, which may influence therapeutic outcomes. SIGNIFICANCE STATEMENT: Bupropion, used for depression, obesity, and smoking cessation, undergoes metabolic bioactivation, with incompletely elucidated interindividual variability. We evaluated cytochrome P450 (CYP) 2B6, CYP2C19 and P450 oxidoreductase genetic variants and steady-state bupropion and metabolite enantiomers disposition. Both enantiomers hydroxylation was lower in CYP2B6*6 and CYP2B6 516G>T carriers, with greater bupropion and lesser hydroxybupropion plasma concentrations. CYP2C19 polymorphisms did not affect bupropion or hydroxybupropion but did influence minor 4′-hydroxylation of bupropion and primary metabolites. CYP2B6 variants affect steady-state bupropion bioactivation, which may influence therapeutic outcomes. Copyright © 2024 by The American Society for Pharmacology and Experimental Therapeutics.
Document Type: Article
Publication Stage: Final
Source: Scopus
F-box protein FBXB-65 regulates anterograde transport of the kinesin-3 motor UNC-104 through a PTM near its cargo-binding PH domain
(2024) Journal of Cell Science, 137 (7), .
Sabharwal, V.a , Boyanapalli, S.P.P.a , Shee, A.b c d , Nonet, M.L.e , Nandi, A.f , Chaudhuri, D.b c , Koushika, S.P.a
a Department of Biological Sciences, Tata Institute of Fundamental Research, Mumbai, 400005, India
b Institute of Physics, Sachivalaya Marg, Bhubaneswar, 751005, India
c Homi Bhabha National Institute, Anushaktinagar, Mumbai, 400094, India
d Northwestern Institute on Complex Systems and ESAM, Northwestern University, Evanston, IL 60208, United States
e Department of Neuroscience, Washington University School of Medicine, St Louis, MO 63110, United States
f Department of Physics, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India
Abstract
Axonal transport in neurons is essential for cargo movement between the cell body and synapses. Caenorhabditis elegans UNC-104 and its homolog KIF1A are kinesin-3 motors that anterogradely transport precursors of synaptic vesicles (pre-SVs) and are degraded at synapses. However, in C. elegans, touch neuron-specific knockdown of the E1 ubiquitin-activating enzyme, uba-1, leads to UNC-104 accumulation at neuronal ends and synapses. Here, we performed an RNAi screen and identified that depletion of fbxb-65, which encodes an F-box protein, leads to UNC-104 accumulation at neuronal distal ends, and alters UNC-104 net anterograde movement and levels of UNC-104 on cargo without changing synaptic UNC-104 levels. Split fluorescence reconstitution showed that UNC-104 and FBXB-65 interact throughout the neuron. Our theoretical model suggests that UNC-104 might exhibit cooperative cargo binding that is regulated by FBXB-65. FBXB-65 regulates an unidentified post-translational modification (PTM) of UNC-104 in a region beside the cargo-binding PH domain. Both fbxb-65 and UNC-104, independently of FBXB-65, regulate axonal pre-SV distribution, transport of pre-SVs at branch points and organismal lifespan. FBXB-65 regulates a PTM of UNC-104 and the number of motors on the cargo surface, which can fine-tune cargo transport to the synapse. © 2024. Published by The Company of Biologists Ltd.
Author Keywords
Axonal transport; E3 ligase; KIF1A; Kinesin-3; Motor-cargo interaction; Synaptic vesicles; UNC-104
Document Type: Article
Publication Stage: Final
Source: Scopus
Cognitive and functional performance and plasma biomarkers of early Alzheimer’s disease in Down syndrome
(2024) Alzheimer’s and Dementia: Diagnosis, Assessment and Disease Monitoring, 16 (2), art. no. e12582, .
Schworer, E.K.a , Handen, B.L.b , Petersen, M.c , O’Bryant, S.c , Peven, J.C.b , Tudorascu, D.L.b , Lee, L.b , Krinsky-McHale, S.J.d , Hom, C.L.e , Clare, I.C.H.f , Christian, B.T.a , Schupf, N.g , Lee, J.H.g , Head, E.h , Mapstone, M.i , Lott, I.i , Ances, B.M.j , Zaman, S.f , Brickman, A.M.g , Lai, F.k , Rosas, H.D.k l , Hartley, S.L.a m
a Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
b Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
c Department of Family Medicine and Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, United States
d New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY, United States
e Department of Psychiatry and Human Behavior, University of California, Irvine, CA, United States
f Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
g Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Sergievsky Center, and Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, United States
h Department of Pathology & Laboratory Medicine, University of California, Irvine School of Medicine, Irvine, CA, United States
i Department of Neurology, University of California, Irvine School of Medicine, Irvine, CA, United States
j Department of Neurology, Washington University at St. Louis, St. Louis, MO, United States
k Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
l Center for Neuro-imaging of Aging and Neurodegenerative Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
m School of Human Ecology, University of Wisconsin-Madison, Madison, WI, United States
Abstract
INTRODUCTION: People with Down syndrome (DS) have a 75% to 90% lifetime risk of Alzheimer’s disease (AD). AD pathology begins a decade or more prior to onset of clinical AD dementia in people with DS. It is not clear if plasma biomarkers of AD pathology are correlated with early cognitive and functional impairments in DS, and if these biomarkers could be used to track the early stages of AD in DS or to inform inclusion criteria for clinical AD treatment trials. METHODS: This large cross-sectional cohort study investigated the associations between plasma biomarkers of amyloid beta (Aβ)42/40, total tau, and neurofilament light chain (NfL) and cognitive (episodic memory, visual–motor integration, and visuospatial abilities) and functional (adaptive behavior) impairments in 260 adults with DS without dementia (aged 25–81 years). RESULTS: In general linear models lower plasma Aβ42/40 was related to lower visuospatial ability, higher total tau was related to lower episodic memory, and higher NfL was related to lower visuospatial ability and lower episodic memory. DISCUSSION: Plasma biomarkers may have utility in tracking AD pathology associated with early stages of cognitive decline in adults with DS, although associations were modest. Highlights: Plasma Alzheimer’s disease (AD) biomarkers correlate with cognition prior to dementia in Down syndrome. Lower plasma amyloid beta 42/40 was related to lower visuospatial abilities. Higher plasma total tau and neurofilament light chain were associated with lower cognitive performance. Plasma biomarkers show potential for tracking early stages of AD symptomology. © 2024 The Authors. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.
Author Keywords
adaptive behavior; adults; cognitive performance; functional abilities; neurofilament light chain; plasma amyloid beta; plasma total tau; trisomy 21
Document Type: Article
Publication Stage: Final
Source: Scopus
Between-Task Transfer of Item-Specific Control Is Replicable and Extends to Novel Conditions
(2024) Journal of Experimental Psychology: Human Perception and Performance, .
Ileri-Tayar, M., Colvett, J.S., Bugg, J.M.
Department of Psychological and Brain Sciences, Washington University in St. Louis, United States
Abstract
Learning-guided control refers to adjustments of cognitive control settings based on learned associations between predictive cues and the likelihood of conflict. In three preregistered experiments, we examined transfer of item-specific control settings beyond conditions under which they were learned. In Experiment 1, an item-specific proportion congruence (ISPC) manipulation was applied in a training phase in which target color in a Flanker task was biased (mostly congruent or mostly incongruent). In a subsequent transfer phase, participants performed a color-word Stroop task in which the same target colors were unbiased (50% congruent). The same design was implemented in Experiment 2, but training and transfer tasks were intermixed within blocks. Between-task transfer was evidenced in both experiments, suggesting learned control settings associated with the predictive cues were retrieved when encountering unbiased transfer items. In Experiment 3, we investigated a farther version of between-task transfer by using training (color-word Stroop) and transfer (picture-word Stroop) tasks that did not share the relevant (to-be-named) dimension or response sets. Despite the stronger, between-task boundary, we observed an ISPC effect for the transfer items, but it did not emerge until the second half of the experiment. The results provided converging evidence for the flexibility and automaticity of item-specific control. © 2024 American Psychological Association
Author Keywords
cognitive control; episodic retrieval; item-specific proportion congruence; learning-guided control; transfer
Funding details
Office of Naval ResearchONR
U.S. Department of DefenseDODN00014-23-1-2792
U.S. Department of DefenseDOD
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Muscle Synergy Plasticity in Motor Function Recovery after Stroke
(2024) IEEE Transactions on Neural Systems and Rehabilitation Engineering, pp. 1-1.
Sheng, Y.a , Wang, J.b , Tan, G.c , Chang, H.a , Xie, Q.b , Liu, H.d
a State Key Laboratory of Robotics and System, Harbin Institute of Technology, Shenzhen, China
b Depart of Rehabilitation medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
c Department of Biomedical Engineering, Washington University in St.Louis, USA
d State Key Laboratory of Robotics and System, Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics, School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China
Abstract
In certain neurological disorders such as stroke, the impairment of upper limb function significantly impacts daily life quality and necessitates enhanced neurological control. This poses a formidable challenge in the realm of rehabilitation due to its intricate nature. Moreover, the plasticity of muscle synergy proves advantageous in assessing the enhancement of motor function among stroke patients pre and post rehabilitation training intervention, owing to the modular control strategy of central nervous system. It also facilitates the investigation of long-term alterations in remodeling of muscle functional performance among patients undergoing clinical rehabilitation, aiming to establish correlations between changes in muscle synergies and stroke characteristics such as type, stage, and sites. In this study, a three-week rehabilitation monitoring experiment was conducted to assess the motor function of stroke patients at different stages of rehabilitation based on muscle synergy performance. Additionally, we aimed to investigate the correlation between clinical scale scores, rehabilitation stages, and synergy performance in order to provide a more comprehensive understanding of stroke patient recovery. The results of 7 healthy controls and 16 stroke patients showed that high-functioning patients were superior to low-functioning patients in terms of motor function plasticity towards healthy individuals. Moreover, there was a high positive correlation between muscle synergies and clinical scale scores in high-functioning patients, and the significance gradually emerged with treatment, highlighting the potential of muscle synergy plasticity as a valuable tool for monitoring rehabilitation progress. The potential of this study was also demonstrated for elucidating the physiological mechanisms underlying motor function reconstruction within the central nervous system, which is expected to promote the further application of muscle synergy in clinical assessment. Authors
Author Keywords
Biomedical monitoring; electromyography; Hospitals; motor function; Motors; muscle synergy; Muscles; neural remodeling; Robots; Stroke (medical condition); stroke rehabilitation; Training
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes
(2024) Nature Human Behaviour, .
Toikumo, S.a b , Jennings, M.V.c , Pham, B.K.c , Lee, H.d , Mallard, T.T.e f g h , Bianchi, S.B.c , Meredith, J.J.c , Vilar-Ribó, L.i , Xu, H.c , Hatoum, A.S.j , Johnson, E.C.j , Pazdernik, V.K.k , Jinwala, Z.b , Pakala, S.R.c , Leger, B.S.c l , Niarchou, M.m , Ehinmowo, M.n , Jenkins, G.D.k , Batzler, A.k , Pendegraft, R.k , Palmer, A.A.c o , Zhou, H.p q , Biernacka, J.M.k r , Coombes, B.J.k , Gelernter, J.p q , Xu, K.p q , Hancock, D.B.s , Cox, N.J.t , Smoller, J.W.e f g h , Davis, L.K.d m t , Justice, A.C.q u v , Kranzler, H.R.a b , Kember, R.L.a b , Sanchez-Roige, S.c m o
a Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, United States
b Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
c Department of Psychiatry, University of California San Diego, La JollaCA, United States
d Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
e Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States
f Department of Psychiatry, Harvard Medical School, Boston, MA, United States
g Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
h Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, United States
i Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
j Psychological & amp; Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States
k Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
l Program in Biomedical Sciences, University of California San Diego, La JollaCA, United States
m Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, United States
n Department of Psychology, University of Ibadan, Ibadan, Nigeria
o Institute for Genomic Medicine, University of California San Diego, La JollaCA, United States
p Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
q Veterans Affairs Connecticut Healthcare System, West Haven, CT, United States
r Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
s RTI International, Research Triangle Park, NC, United States
t Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
u Yale University School of Public Health, New Haven, CT, United States
v Yale University School of Medicine, New Haven, CT, United States
Abstract
Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD. © The Author(s), under exclusive licence to Springer Nature Limited 2024.
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Structural insights into vesicular monoamine storage and drug interactions
(2024) Nature, .
Ye, J.a , Chen, H.b , Wang, K.c , Wang, Y.a , Ammerman, A.a , Awasthi, S.a , Xu, J.b , Liu, B.d , Li, W.a
a Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St Louis, MO, United States
b Department of Radiology, Washington University School of Medicine, St Louis, MO, United States
c Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
d The Hormel Institute, University of Minnesota, Austin, MN, United States
Abstract
Biogenic monoamines—vital transmitters orchestrating neurological, endocrinal and immunological functions1–5—are stored in secretory vesicles by vesicular monoamine transporters (VMATs) for controlled quantal release6,7. Harnessing proton antiport, VMATs enrich monoamines around 10,000-fold and sequester neurotoxicants to protect neurons8–10. VMATs are targeted by an arsenal of therapeutic drugs and imaging agents to treat and monitor neurodegenerative disorders, hypertension and drug addiction1,8,11–16. However, the structural mechanisms underlying these actions remain unclear. Here we report eight cryo-electron microscopy structures of human VMAT1 in unbound form and in complex with four monoamines (dopamine, noradrenaline, serotonin and histamine), the Parkinsonism-inducing MPP+, the psychostimulant amphetamine and the antihypertensive drug reserpine. Reserpine binding captures a cytoplasmic-open conformation, whereas the other structures show a lumenal-open conformation stabilized by extensive gating interactions. The favoured transition to this lumenal-open state contributes to monoamine accumulation, while protonation facilitates the cytoplasmic-open transition and concurrently prevents monoamine binding to avoid unintended depletion. Monoamines and neurotoxicants share a binding pocket that possesses polar sites for specificity and a wrist-and-fist shape for versatility. Variations in this pocket explain substrate preferences across the SLC18 family. Overall, these structural insights and supporting functional studies elucidate the mechanism of vesicular monoamine transport and provide the basis to develop therapeutics for neurodegenerative diseases and substance abuse. © The Author(s), under exclusive licence to Springer Nature Limited 2024.
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder
(2024) Nature Genetics, . Cited 1 time.
Nievergelt, C.M.a b c , Maihofer, A.X.a b c , Atkinson, E.G.d , Chen, C.-Y.e , Choi, K.W.f g , Coleman, J.R.I.h i , Daskalakis, N.P.j k l , Duncan, L.E.m , Polimanti, R.n o , Aaronson, C.p , Amstadter, A.B.q , Andersen, S.B.r , Andreassen, O.A.s t , Arbisi, P.A.u v , Ashley-Koch, A.E.w , Austin, S.B.x y z , Avdibegoviç, E.aa , Babić, D.ab , Bacanu, S.-A.ac , Baker, D.G.a b ad , Batzler, A.ae , Beckham, J.C.af ag ah , Belangero, S.ai aj , Benjet, C.ak , Bergner, C.al , Bierer, L.M.am , Biernacka, J.M.ae an , Bierut, L.J.ao , Bisson, J.I.ap , Boks, M.P.aq , Bolger, E.A.k ar , Brandolino, A.as , Breen, G.i at , Bressan, R.A.aj au , Bryant, R.A.av , Bustamante, A.C.aw , Bybjerg-Grauholm, J.ax ay , Bækvad-Hansen, M.ax ay , Børglum, A.D.ay az ba , Børte, S.bb bc , Cahn, L.p , Calabrese, J.R.bd be , Caldas-de-Almeida, J.M.bf , Chatzinakos, C.j k bg , Cheema, S.bh , Clouston, S.A.P.bi bj , Colodro-Conde, L.bk , Coombes, B.J.ae , Cruz-Fuentes, C.S.bl , Dale, A.M.bm , Dalvie, S.bn , Davis, L.K.bo , Deckert, J.bp , Delahanty, D.L.bq , Dennis, M.F.af ag ah , Desarnaud, F.p , DiPietro, C.P.j bg , Disner, S.G.br bs , Docherty, A.R.bt bu , Domschke, K.bv bw , Dyb, G.t bx , Kulenović, A.D.by , Edenberg, H.J.bz ca , Evans, A.ap , Fabbri, C.i cb , Fani, N.cc , Farrer, L.A.cd ce cf cg ch , Feder, A.p , Feeny, N.C.ci , Flory, J.D.p , Forbes, D.cj , Franz, C.E.a , Galea, S.ck , Garrett, M.E.w , Gelaye, B.f , Gelernter, J.cl cm , Geuze, E.cn co , Gillespie, C.F.cc , Goleva, S.B.bo cp , Gordon, S.D.bk , Goçi, A.cq , Grasser, L.R.cr , Guindalini, C.cs , Haas, M.ct , Hagenaars, S.h i , Hauser, M.A.af , Heath, A.C.cu , Hemmings, S.M.J.cv cw , Hesselbrock, V.cx , Hickie, I.B.cy , Hogan, K.a b c , Hougaard, D.M.ax ay , Huang, H.j cz , Huckins, L.M.da , Hveem, K.bb , Jakovljević, M.db , Javanbakht, A.cr , Jenkins, G.D.ae , Johnson, J.dc , Jones, I.dd , Jovanovic, T.cc , Karstoft, K.-I.r de , Kaufman, M.L.k ar , Kennedy, J.L.df dg dh di , Kessler, R.C.dj , Khan, A.k ar , Kimbrel, N.A.af ah dk , King, A.P.dl , Koen, N.dm , Kotov, R.dn , Kranzler, H.R.do dp , Krebs, K.dq , Kremen, W.S.a , Kuan, P.-F.dr , Lawford, B.R.ds , Lebois, L.A.M.k l , Lehto, K.dq , Levey, D.F.n o , Lewis, C.ap , Liberzon, I.dt , Linnstaedt, S.D.du , Logue, M.W.cg dv dw , Lori, A.cc , Lu, Y.dx , Luft, B.J.dy , Lupton, M.K.bk , Luykx, J.J.co dz , Makotkine, I.p , Maples-Keller, J.L.cc , Marchese, S.ea , Marmar, C.eb , Martin, N.G.ec , Martínez-Levy, G.A.bl , McAloney, K.bk , McFarlane, A.ed , McLaughlin, K.A.ee , McLean, S.A.du ef , Medland, S.E.bk , Mehta, D.ds eg , Meyers, J.eh , Michopoulos, V.cc , Mikita, E.A.a b c , Milani, L.dq , Milberg, W.ei , Miller, M.W.dv dw , Morey, R.A.ej , Morris, C.P.ds , Mors, O.ay ek , Mortensen, P.B.ay az el em , Mufford, M.S.bn , Nelson, E.C.ao , Nordentoft, M.ay en , Norman, S.B.a b eo , Nugent, N.R.ep eq er , O’Donnell, M.es , Orcutt, H.K.et , Pan, P.M.eu , Panizzon, M.S.a , Pathak, G.A.n o , Peters, E.S.ev , Peterson, A.L.ew ex , Peverill, M.ey , Pietrzak, R.H.o ez , Polusny, M.A.u bs fa , Porjesz, B.eh , Powers, A.cc , Qin, X.-J.w , Ratanatharathorn, A.f fb , Risbrough, V.B.a b c , Roberts, A.L.fc , Rothbaum, A.O.fd fe , Rothbaum, B.O.cc , Roy-Byrne, P.ff , Ruggiero, K.J.fg , Rung, A.fh , Runz, H.fi , Rutten, B.P.F.fj , de Viteri, S.S.fk , Salum, G.A.fl fm , Sampson, L.f ch , Sanchez, S.E.fn , Santoro, M.fo , Seah, C.ea , Seedat, S.cv fp , Seng, J.S.fq fr fs ft , Shabalin, A.bu , Sheerin, C.M.q , Silove, D.fu , Smith, A.K.cc fv , Smoller, J.W.g j fw , Sponheim, S.R.u fx , Stein, D.J.dm , Stensland, S.bc bx , Stevens, J.S.cc , Sumner, J.A.fy , Teicher, M.H.k fz , Thompson, W.K.ga gb , Tiwari, A.K.df dg dh , Trapido, E.fh , Uddin, M.gc , Ursano, R.J.gd , Valdimarsdóttir, U.ge gf , Van Hooff, M.gg , Vermetten, E.gh gi gj , Vinkers, C.H.gk gl gm , Voisey, J.ds eg , Wang, Y.gn , Wang, Z.go gp , Waszczuk, M.gq , Weber, H.bp , Wendt, F.R.gr , Werge, T.ay gs gt gu , Williams, M.A.f , Williamson, D.E.af ag , Winsvold, B.S.bb bc gv , Winternitz, S.k ar , Wolf, C.bp , Wolf, E.J.dw gw , Xia, Y.j cz , Xiong, Y.dx , Yehuda, R.p gx , Young, K.A.gy gz , Young, R.M.ha hb , Zai, C.C.j df dg dh di hc , Zai, G.C.df dg dh di hd , Zervas, M.ct , Zhao, H.he , Zoellner, L.A.ey , Zwart, J.-A.t bb bc , deRoon-Cassini, T.as , van Rooij, S.J.H.cc , van den Heuvel, L.L.cv cw , Stein, M.B.a ad hf , Ressler, K.J.k ar cc , Koenen, K.C.f j fw
a Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
b Veterans Affairs San Diego Healthcare System, Center of Excellence for Stress and Mental Health, San Diego, CA, United States
c Veterans Affairs San Diego Healthcare System, Research Service, San Diego, CA, United States
d Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
e Biogen Inc.,Translational Sciences, Cambridge, MA, United States
f Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States
g Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
h King’s College London, National Institute for Health and Care Research Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, United Kingdom
i King’s College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom
j Broad Institute of MIT and Harvard, Stanley Center for Psychiatric Research, Cambridge, MA, United States
k Department of Psychiatry, Harvard Medical School, Boston, MA, United States
l McLean Hospital, Center of Excellence in Depression and Anxiety Disorders, Belmont, MA, United States
m Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States
n VA Connecticut Healthcare Center, West Haven, CT, United States
o Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
p Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
q Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, United States
r The Danish Veteran Centre, Research and Knowledge Centre, Ringsted, Denmark
s Oslo University Hospital, Division of Mental Health and Addiction, Oslo, Norway
t University of Oslo, Institute of Clinical Medicine, Oslo, Norway
u Minneapolis VA Health Care System, Mental Health Service Line, Minneapolis, MN, United States
v Department of Psychiatry, University of Minnesota, Minneapolis, MN, United States
w Duke University, Duke Molecular Physiology Institute, Durham, NC, United States
x Boston Children’s Hospital, Division of Adolescent and Young Adult Medicine, Boston, MA, United States
y Department of Pediatrics, Harvard Medical School, Boston, MA, United States
z Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States
aa Department of Psychiatry, University Clinical Center of Tuzla, Tuzla, Bosnia and Herzegovina
ab Department of Psychiatry, University Clinical Center of Mostar, Mostar, Bosnia and Herzegovina
ac Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States
ad Veterans Affairs San Diego Healthcare System, Psychiatry Service, San Diego, CA, United States
ae Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
af Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
ag Research, Durham VA Health Care System, Durham, NC, United States
ah VA Mid-Atlantic Mental Illness Research, Education, and Clinical Center (MIRECC), Genetics Research Laboratory, Durham, NC, United States
ai Department of Morphology and Genetics, Universidade Federal de São Paulo, São Paulo, Brazil
aj Department of Psychiatry, Universidade Federal de São Paulo, Laboratory of Integrative Neuroscience, São Paulo, Brazil
ak Instituto Nacional de Psiquiatraía Ramón de la Fuente Muñiz, Center for Global Mental Health, Mexico City, Mexico
al Medical College of Wisconsin, Comprehensive Injury Center, Milwaukee, WI, United States
am Department of Psychiatry, James J. Peters VA Medical Center, Bronx, NY, United States
an Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
ao Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, United States
ap Cardiff University, National Centre for Mental Health, MRC Centre for Psychiatric Genetics and Genomics, Cardiff, United Kingdom
aq Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht, Netherlands
ar McLean Hospital, Belmont, MA, United States
as Department of Surgery, Division of Trauma & amp; Acute Care Surgery, Medical College of Wisconsin, Milwaukee, WI, United States
at King’s College London, NIHR Maudsley BRC, London, United Kingdom
au Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil
av University of New South Wales, School of Psychology, Sydney, NSW, Australia
aw Department of Internal Medicine, University of Michigan Medical School, Division of Pulmonary and Critical Care Medicine, Ann Arbor, MI, United States
ax Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
ay The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
az Aarhus University, Centre for Integrative Sequencing, iSEQ, Aarhus, Denmark
ba Department of Biomedicine—Human Genetics, Aarhus University, Aarhus, Denmark
bb Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, K. G. Jebsen Center for Genetic Epidemiology, Trondheim, Norway
bc Oslo University Hospital, Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo, Norway
bd Case Western Reserve University, School of Medicine, Cleveland, OH, United States
be Department of Psychiatry, University Hospitals, Cleveland, OH, United States
bf Chronic Diseases Research Centre (CEDOC), Lisbon Institute of Global Mental Health, Lisbon, Portugal
bg McLean Hospital, Division of Depression and Anxiety Disorders, Belmont, MA, United States
bh University of Toronto, CanPath National Coordinating Center, Toronto, ON, Canada
bi Stony Brook University, Family, Population, and Preventive Medicine, Stony Brook, NY, United States
bj Stony Brook University, Public Health, Stony Brook, NY, United States
bk QIMR Berghofer Medical Research Institute, Mental Health & amp; Neuroscience Program, Brisbane, QLD, Australia
bl Department of Genetics, Instituto Nacional de Psiquiatraía Ramón de la Fuente Muñiz, Mexico City, Mexico
bm Department of Radiology, Department of Neurosciences, University of California San Diego, La Jolla, CA, United States
bn Department of Pathology, University of Cape Town, Division of Human Genetics, Cape Town, South Africa
bo Vanderbilt University Medical Center, Vanderbilt Genetics Institute, Nashville, TN, United States
bp University Hospital of Würzburg, Center of Mental Health, Psychiatry, Psychosomatics and Psychotherapy, Würzburg, Denmark
bq Department of Psychological Sciences, Kent State University, Kent, OH, United States
br Minneapolis VA Health Care System, Research Service Line, Minneapolis, MN, United States
bs Department of Psychiatry & amp; Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, United States
bt Huntsman Mental Health Institute, Salt Lake City, UT, United States
bu Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, United States
bv University of Freiburg, Faculty of Medicine, Centre for Basics in Neuromodulation, Freiburg, Denmark
bw Department of Psychiatry and Psychotherapy, University of Freiburg, Faculty of Medicine, Freiburg, Denmark
bx Norwegian Centre for Violence and Traumatic Stress Studies, Oslo, Norway
by Department of Psychiatry, University Clinical Center of Sarajevo, Sarajevo, Bosnia and Herzegovina
bz Indiana University School of Medicine, Biochemistry and Molecular Biology, Indianapolis, IN, United States
ca Indiana University School of Medicine, Medical and Molecular Genetics, Indianapolis, IN, United States
cb Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
cc Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
cd Department of Medicine (Biomedical Genetics), Boston University Chobanian & amp; Avedisian School of Medicine, Boston, MA, United States
ce Department of Neurology, Boston University Chobanian & amp; Avedisian School of Medicine, Boston, MA, United States
cf Department of Ophthalmology, Boston University Chobanian & amp; Avedisian School of Medicine, Boston, MA, United States
cg Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
ch Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
ci Department of Psychological Sciences, Case Western Reserve University, Cleveland, OH, United States
cj Department of Psychiatry, University of Melbourne, Melbourne, VIC, Australia
ck Boston University School of Public Health, Boston, MA, United States
cl VA Connecticut Healthcare Center, Psychiatry Service, West Haven, CT, United States
cm Department of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, United States
cn Netherlands Ministry of Defence, Brain Research and Innovation Centre, Utrecht, Netherlands
co Department of Psychiatry, UMC Utrecht Brain Center Rudolf Magnus, Utrecht, Netherlands
cp National Institutes of Health, National Human Genome Research Institute, Bethesda, MD, United States
cq Department of Psychiatry, University Clinical Centre of Kosovo, Prishtina
cr Wayne State University School of Medicine, Psychiatry and Behavioral Neurosciencess, Detroit, MI, United States
cs Gallipoli Medical Research Foundation, Greenslopes Private Hospital, Greenslopes, QLD, Australia
ct Cohen Veterans Bioscience, New York City, NY, United States
cu Department of Genetics, Washington University in Saint Louis School of Medicine, Saint Louis, MO, United States
cv Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
cw SAMRC Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
cx University of Connecticut School of Medicine, Psychiatry, Farmington, CT, United States
cy University of Sydney, Brain and Mind Centre, Sydney, NSW, Australia
cz Department of Medicine, Massachusetts General Hospital, Analytic and Translational Genetics Unit, Boston, MA, United States
da Department of Psychiatry, Yale University, New Haven, CT, United States
db Department of Psychiatry, University Hospital Center of Zagreb, Zagreb, Croatia
dc Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
dd Cardiff University, National Centre for Mental Health, Cardiff University Centre for Psychiatric Genetics and Genomics, Cardiff, United Kingdom
de Department of Psychology, University of Copenhagen, Copenhagen, Denmark
df Centre for Addiction and Mental Health, Neurogenetics Section, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
dg Centre for Addiction and Mental Health, Tanenbaum Centre for Pharmacogenetics, Toronto, ON, Canada
dh Department of Psychiatry, University of Toronto, Toronto, ON, Canada
di Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
dj Department of Health Care Policy, Harvard Medical School, Boston, MA, United States
dk Durham VA Health Care System, Mental Health Service Line, Durham, NC, United States
dl The Ohio State University, College of Medicine, Institute for Behavioral Medicine Research, Columbus, OH, United States
dm University of Cape Town, Department of Psychiatry & amp; Neuroscience Institute, SA MRC Unit on Risk & amp; Resilience in Mental Disorders, Cape Town, South Africa
dn Department of Psychiatry, Stony Brook University, Stony Brook, NY, United States
do Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, United States
dp Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
dq University of Tartu, Institute of Genomics, Estonian Genome Center, Tartu, Estonia
dr Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
ds Queensland University of Technology, School of Biomedical Sciences, Kelvin Grove, QLD, Australia
dt Department of Psychiatry and Behavioral Sciences, Texas A & amp;M University College of Medicine, Bryan, TX, United States
du Department of Anesthesiology, UNC Institute for Trauma Recovery, Chapel Hill, NC, United States
dv Boston University School of Medicine, Psychiatry, Biomedical Genetics, Boston, MA, United States
dw VA Boston Healthcare System, National Center for PTSD, Boston, MA, United States
dx Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
dy Department of Medicine, Stony Brook University, Stony Brook, NY, United States
dz Department of Translational Neuroscience, UMC Utrecht Brain Center Rudolf Magnus, Utrecht, Netherlands
ea Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
eb New York University, Grossman School of Medicine, New York City, NY, United States
ec QIMR Berghofer Medical Research Institute, Genetics, Brisbane, QLD, Australia
ed University of Adelaide, Discipline of Psychiatry, Adelaide, SA, Australia
ee Department of Psychology, Harvard University, Boston, MA, United States
ef Department of Emergency Medicine, UNC Institute for Trauma Recovery, Chapel Hill, NC, United States
eg Queensland University of Technology, Centre for Genomics and Personalised Health, Kelvin Grove, QLD, Australia
eh Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, United States
ei VA Boston Healthcare System, GRECC/TRACTS, Boston, MA, United States
ej Duke University School of Medicine, Duke Brain Imaging and Analysis Center, Durham, NC, United States
ek Aarhus University Hospital—Psychiatry, Psychosis Research Unit, Aarhus, Denmark
el Aarhus University, Centre for Integrated Register-Based Research, Aarhus, Denmark
em Aarhus University, National Centre for Register-Based Research, Aarhus, Denmark
en University of Copenhagen, Mental Health Services in the Capital Region of Denmark, Copenhagen, Denmark
eo National Center for Post Traumatic Stress Disorder, Executive Division, White River Junction, VT, United States
ep Department of Emergency Medicine, Alpert Brown Medical School, Providence, RI, United States
eq Department of Pediatrics, Alpert Brown Medical School, Providence, RI, United States
er Department of Psychiatry and Human Behavior, Alpert Brown Medical School, Providence, RI, United States
es Department of Psychiatry, University of Melbourne, Phoenix Australia, Melbourne, VIC, Australia
et Department of Psychology, Northern Illinois University, DeKalb, IL, United States
eu Universidade Federal de São Paulo, Psychiatry, São Paulo, Brazil
ev University of Nebraska Medical Center, College of Public Health, Omaha, NE, United States
ew South Texas Veterans Health Care System, Research and Development Service, San Antonio, TX, United States
ex Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
ey Department of Psychology, University of Washington, Seattle, WA, United States
ez U.S. Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, West Haven, CT, United States
fa Center for Care Delivery and Outcomes Research (CCDOR), Minneapolis, MN, United States
fb Department of Epidemiology, Columbia University Mailmain School of Public Health, New York City, NY, United States
fc Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States
fd Department of Psychological Sciences, Emory University, Atlanta, GA, United States
fe Department of Research and Outcomes, Skyland Trail, Atlanta, GA, United States
ff Department of Psychiatry, University of Washington, Seattle, WA, United States
fg Department of Nursing, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, United States
fh Department of Epidemiology, Louisiana State University Health Sciences Center, School of Public Health, New Orleans, LA, United States
fi Biogen Inc., Research & amp; Development, Cambridge, MA, United States
fj Department of Psychiatry and Neuropsychology, Maastricht Universitair Medisch Centrum, School for Mental Health and Neuroscience, Maastricht, Netherlands
fk SUNY Downstate Health Sciences University, School of Public Health, Brooklyn, NY, United States
fl Child Mind Institute, New York City, NY, United States
fm Instituto Nacional de Psiquiatria de Desenvolvimento, São Paulo, Brazil
fn Department of Medicine, Universidad Peruana de Ciencias Aplicadas, Lima, Peru
fo Universidade Federal de São Paulo, Departamento de Bioquímica—Disciplina de Biologia Molecular, São Paulo, Brazil
fp Stellenbosch University, SAMRC Extramural Genomics of Brain Disorders Research Unit, Cape Town, South Africa
fq Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, United States
fr Department of Women’s and Gender Studies, University of Michigan, Ann Arbor, MI, United States
fs University of Michigan, Institute for Research on Women and Gender, Ann Arbor, MI, United States
ft University of Michigan, School of Nursing, Ann Arbor, MI, United States
fu Department of Psychiatry, University of New South Wales, Sydney, NSW, Australia
fv Department of Gynecology and Obstetrics, Department of Psychiatry and Behavioral Sciences, Department of Human Genetics, Emory University, Atlanta, GA, United States
fw Massachusetts General Hospital, Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Boston, MA, United States
fx Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, United States
fy Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
fz McLean Hospital, Developmental Biopsychiatry Research Program, Belmont, MA, United States
ga Mental Health Centre Sct. Hans, Institute of Biological Psychiatry, Roskilde, Denmark
gb University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science, La Jolla, CA, United States
gc University of South Florida College of Public Health, Genomics Program, Tampa, FL, United States
gd Department of Psychiatry, Uniformed Services University, Bethesda, MD, United States
ge Karolinska Institutet, Unit of Integrative Epidemiology, Institute of Environmental Medicine, Stockholm, Sweden
gf University of Iceland, Faculty of Medicine, Center of Public Health Sciences, School of Health Sciences, Reykjavik, Iceland
gg University of Adelaide, Adelaide Medical School, Adelaide, SA, Australia
gh ARQ Nationaal Psychotrauma Centrum, Psychotrauma Research Expert Group, Diemen, Netherlands
gi Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands
gj Department of Psychiatry, New York University School of Medicine, New York City, NY, United States
gk Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & amp; Stress Program, Amsterdam, Netherlands
gl Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, Netherlands
gm Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, Netherlands
gn Department of Psychology, University of Oslo, Lifespan Changes in Brain and Cognition (LCBC), Oslo, Norway
go Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, United States
gp Department of Mental Health, Ralph H Johnson VA Medical Center, Charleston, SC, United States
gq Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States
gr Department of Anthropology, University of Toronto, Dalla Lana School of Public Health, Toronto, ON, Canada
gs Copenhagen University Hospital, Institute of Biological Psychiatry, Mental Health Services, Copenhagen, Denmark
gt Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
gu University of Copenhagen, The Globe Institute, Lundbeck Foundation Center for Geogenetics, Copenhagen, Denmark
gv Department of Neurology, Oslo University Hospital, Oslo, Norway
gw Department of Psychiatry, Boston University Chobanian & amp; Avedisian School of Medicine, Boston, MA, United States
gx Department of Mental Health, James J. Peters VA Medical Center, Bronx, NY, United States
gy Central Texas Veterans Health Care System, Research Service, Temple, TX, United States
gz Department of Psychiatry and Behavioral Sciences, Texas A & amp;M University School of Medicine, Bryan, TX, United States
ha Queensland University of Technology, School of Clinical Sciences, Kelvin Grove, QLD, Australia
hb University of the Sunshine Coast, The Chancellory, Sippy Downs, QLD, Australia
hc Department of Laboratory Medicine and Pathology, University of Toronto, Toronto, ON, Canada
hd Centre for Addiction and Mental Health, General Adult Psychiatry and Health Systems Division, Toronto, ON, Canada
he Department of Biostatistics, Yale University, New Haven, CT, United States
hf University of California San Diego, School of Public Health, La Jolla, CA, United States
Abstract
Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation. © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024.
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Trends in ototoxicity monitoring among cisplatin-treated patients with cancer
(2024) Journal of Cancer Survivorship, .
Lee, D.S.a , Travis, E.Y.b , Wong, S.K.b , Munyemana, M.-A.a , Mueller, L.a , Rowling, C.C.b , Rich, J.T.a , Pipkorn, P.a , Puram, S.V.a c , Jackson, R.S.a , Adkins, D.R.d , Oppelt, P.d , Thorstad, W.L.e , Wick, C.C.a , Zevallos, J.P.f , McClannahan, K.b , Mazul, A.L.f
a Department of Otolaryngology – Head and Neck Surgery, Washington University School of Medicine, 660 South Euclid Avenue, Campus, St. Louis, MO 63110, United States
b Division of Adult Audiology, Department of Otolaryngology – Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO, United States
c Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
d Department of Medical Oncology, Washington University School of Medicine, St. Louis, MO, United States
e Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, United States
f Department of Otolaryngology – Head and Neck Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
Abstract
Purpose: This study aims to characterize patterns in ototoxicity monitoring and identify potential barriers to audiologic follow-up. Methods: We performed a single-institution retrospective cohort study on adult (≥ 18 years old) cancer patients treated with cisplatin from January 2014 to September 2021. Our primary outcomes were rates of baseline and post-treatment audiograms at the following time points: 3, 6, 12, and greater than 12 months. Time-to-event analyses were performed to describe additional insights to ototoxicity monitoring patterns. Results: Nine hundred fifty-five patients with cancer were included for analysis. The most common primary cancer sites were head and neck (64%), followed by cervical (24%). Three hundred seventy-three patients (39%) underwent baseline audiometric assessment, 38 patients (4%) received audiologic evaluation during chemotherapy, and 346 patients (36%) obtained at least one post-treatment audiogram. Audiologic follow-up was greatest within 3 months of completing chemotherapy (26%), but this tapered dramatically to less than 10% at every other post-treatment time point. Patients with head and neck cancer achieved higher rates of audiologic follow-up at every time point than patients with non–head and neck cancer except for during treatment. Conclusions: Ototoxicity monitoring is an inconsistent practice, particularly during chemotherapy and for long-term surveillance of hearing loss. Patients with non–head and neck cancer may be at increased risk for loss of audiologic follow-up. Implications for Cancer Survivors: Cisplatin ototoxicity is a common occurrence that can be effectively managed with auditory rehabilitation. Therefore, referrals to audiology and counseling on treatment-related ototoxicity are recommended throughout chemotherapy and cancer survivorship. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Author Keywords
Cancer; Cisplatin; Head and neck cancer; Ototoxicity; Ototoxicity monitoring
Document Type: Article
Publication Stage: Article in Press
Source: Scopus