WashU weekly Neuroscience publications

Single cell transcriptomics reveals opioid usage evokes widespread suppression of antiviral gene program
(2020) Nature Communications, 11 (1), art. no. 2611, . 

Karagiannis, T.T.^{a b} , Cleary, J.P., Jr.^{b c} , Gok, B.^{b d} , Henderson, A.J.^e , Martin, N.G.^f , Yajima, M.^g , Nelson, E.C.^h , Cheng, C.S.^{a b c d}

^a Program in Bioinformatics, Boston University, 24 Cummington Mall, Boston, MA 02215, United States
^b Department of Biology, Boston University, 5 Cummington Mall, Boston, MA 02215, United States
^c Program in Molecular Biology, Cell Biology and Biochemistry, Boston University, 24 Cummington Mall, Boston, MA 02215, United States
^d Program in Cell and Molecular Biology, Boston University, 24 Cummington Mall, Boston, MA 02215, United States
^e Department of Medicine and Microbiology, Boston University School of Medicine, 650 Albany St, Boston, MA 02215, United States
^f QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
^g Department of Mathematics and Statistics, Boston University, 111 Cummington Mall, Boston, MA 02215, United States
^h Department of Psychiatry, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO 63110, United States

Abstract
Chronic opioid usage not only causes addiction behavior through the central nervous system, but also modulates the peripheral immune system. However, how opioid impacts the immune system is still barely characterized systematically. In order to understand the immune modulatory effect of opioids in an unbiased way, here we perform single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells from opioid-dependent individuals and controls to show that chronic opioid usage evokes widespread suppression of antiviral gene program in naive monocytes, as well as in multiple immune cell types upon stimulation with the pathogen component lipopolysaccharide. Furthermore, scRNA-seq reveals the same phenomenon after a short in vitro morphine treatment. These findings indicate that both acute and chronic opioid exposure may be harmful to our immune system by suppressing the antiviral gene program. Our results suggest that further characterization of the immune modulatory effects of opioid is critical to ensure the safety of clinical opioids. © 2020, The Author(s).

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Real-time Inference and Detection of Disruptive EEG Networks for Epileptic Seizures
(2020) Scientific Reports, 10 (1), art. no. 8653, . 

Bomela, W.^a , Wang, S.^b , Chou, C.-A.^c , Li, J.-S.^a

^a Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
^b Department of Mechanical & Aerospace Engineering, University of Texas at Arlington, Arlington, TX 76010, United States
^c Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, United States

Abstract
Recent studies in brain science and neurological medicine paid a particular attention to develop machine learning-based techniques for the detection and prediction of epileptic seizures with electroencephalogram (EEG). As a noninvasive monitoring method to record brain electrical activities, EEG has been widely used for capturing the underlying dynamics of disruptive neuronal responses across the brain in real-time to provide clinical guidance in support of epileptic seizure treatments in practice. In this study, we introduce a novel dynamic learning method that first infers a time-varying network constituted by multivariate EEG signals, which represents the overall dynamics of the brain network, and subsequently quantifies its topological property using graph theory. We demonstrate the efficacy of our learning method to detect relatively strong synchronization (characterized by the algebraic connectivity metric) caused by abnormal neuronal firing during a seizure onset. The computational results for a realistic scalp EEG database show a detection rate of 93.6% and a false positive rate of 0.16 per hour (FP/h); furthermore, our method observes potential pre-seizure phenomena in some cases. © 2020, The Author(s).

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Parental consent: A potential barrier for underage teens’ participation in an mHealth mental health intervention
(2020) Internet Interventions, 21, art. no. 100328, . 

Cavazos-Rehg, P., Min, C., Fitzsimmons-Craft, E.E., Savoy, B., Kaiser, N., Riordan, R., Krauss, M., Costello, S., Wilfley, D.

Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Purpose: We sought to examine whether underage adolescents displaying symptoms for a mental illness (i.e., an eating disorder) would be willing to obtain parental consent to participate in a study to test the efficacy of an evidence-based mobile mental health intervention targeting teens with eating disorders. Methods: The participants (n = 366) were 15 to 17 year-old English-speakers who post or follow social media accounts on Instagram that emphasize being thin as important or attractive. The participants were administered a survey through Qualtrics to assess eating disorder pathology, interest in trying an evidence-based mobile mental-health intervention, and comfort level with obtaining parental consent to partake in a research study about such an intervention. Results: About 85% of participants met clinical or subclinical criteria for an eating disorder; however, only 12% had received a treatment within the past six months. While 83% of participants were interested in trying a mobile health interventions app, only 35% indicated willingness to obtain parental consent to participate in a research study. The primary reasons presented for unwillingness to obtain consent included importance of retaining privacy and feeling that parents lack awareness or understanding about mental health issues. Conclusions: While barriers exist to obtaining treatment for eating disorders, a mobile intervention app may close some of these gaps. Many underage participants indicated interest in obtaining such treatment, yet only a third were willing to obtain parental consent. Future studies should investigate how to reduce these barriers to obtaining parental consent to facilitate teen access to research and mobile mental health treatment. © 2020 The Authors

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

The CCL2/CCR2 axis is critical to recruiting macrophages into acellular nerve allograft bridging a nerve gap to promote angiogenesis and regeneration
(2020) Experimental Neurology, 331, art. no. 113363, . 

Pan, D., Acevedo-Cintrón, J.A., Sayanagi, J., Snyder-Warwick, A.K., Mackinnon, S.E., Wood, M.D.

Division of Plastic and Reconstructive Surgery, Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110, United States

Abstract
Acellular nerve allografts (ANAs) are increasingly used to repair nerve gaps following injuries. However, these nerve scaffolds have yet to surpass the regenerative capabilities of cellular nerve autografts; improved understanding of their regenerative mechanisms could improve design. Due to their acellular nature, both angiogenesis and diverse cell recruitment is necessary to repopulate these scaffolds to promote functional regeneration. We determined the contribution of angiogenesis to initial cellular repopulation of ANAs used to repair nerve gaps, as well as the signaling that drives a significant portion of this angiogenesis. Wild-type (WT) mice with nerve gaps repaired using ANAs that were treated with an inhibitor of VEGF receptor signaling severely impaired angiogenesis within ANAs, as well as hampered cell repopulation and axon extension into ANAs. Similarly, systemic depletion of hematogenous-derived macrophages, but not neutrophils, in these mice models severely impeded angiogenesis and subsequent nerve regeneration across ANAs suggesting hematogenous-derived macrophages were major contributors to angiogenesis within ANAs. This finding was reinforced using CCR2 knockout (KO) models. As macrophages represented the majority of CCR2 expressing cells, a CCR2 deficiency impaired angiogenesis and subsequent nerve regeneration across ANAs. Furthermore, an essential role for CCL2 during nerve regeneration across ANAs was identified, as nerves repaired using ANAs had reduced angiogenesis and subsequent nerve regeneration in CCL2 KO vs WT mice. Our data demonstrate the CCL2/CCR2 axis is important for macrophage recruitment, which promotes angiogenesis, cell repopulation, and subsequent nerve regeneration and recovery across ANAs used to repair nerve gaps. © 2020 Elsevier Inc.

Author Keywords
Acellular nerve allograft;  Angiogenesis;  Macrophage;  Peripheral nerve;  Regeneration

Document Type: Article
Publication Stage: Final
Source: Scopus

Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity
(2020) NeuroImage, 217, art. no. 116866, . 

Gratton, C.^{a b} , Dworetsky, A.^d , Coalson, R.S.^{c d} , Adeyemo, B.^c , Laumann, T.O.^j , Wig, G.S.^{e f} , Kong, T.S.^{g h} , Gratton, G.^{g h} , Fabiani, M.^{g h} , Barch, D.M.^{d i j} , Tranel, D.^{k l} , Miranda-Dominguez, O.^m , Fair, D.A.^{m n} , Dosenbach, N.U.F.^{c d o p} , Snyder, A.Z.^{c d} , Perlmutter, J.S.^{c d q} , Petersen, S.E.^{c d i j q} , Campbell, M.C.^{c d}

^a Department of Psychology, Northwestern University, Evanston, IL, United States
^b Department of Neurology, Northwestern University, Evanston, IL, United States
^c Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
^d Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States
^e Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, United States
^f Department of Psychiatry, University of Texas Southwestern Medical Center, United States
^g Department of Psychology, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, United States
^h Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, United States
ⁱ Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States
^j Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, United States
^k Department of Neurology, University of Iowa, Iowa City, IA, United States
^l Psychological and Brain Sciences, University of Iowa, Iowa City, IA, United States
^m Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, United States
ⁿ Department of Psychiatry, Oregon Health & Science University, Portland, OR, United States
^o Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, United States
^p Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States
^q Department of Neuroscience, Washington University in St. Louis, St. Louis, MO, United States

Abstract
Denoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., ‘motion’ parameters). However, it is increasingly recognized that respiration introduces factitious head motion via perturbations of the main (B0) field. This effect appears as higher-frequency fluctuations in the motion parameters (>0.1 ​Hz, here referred to as ‘HF-motion’), primarily in the phase-encoding direction. This periodicity can sometimes be obscured in standard single-band fMRI (TR 2.0–2.5 ​s) due to aliasing. Here we examined (1) how prevalent HF-motion effects are in seven single-band datasets with TR from 2.0 to 2.5 ​s and (2) how HF-motion affects functional connectivity. We demonstrate that HF-motion is more common in older adults, those with higher body mass index, and those with lower cardiorespiratory fitness. We propose a low-pass filtering approach to remove the contamination of high frequency effects from motion summary measures, such as framewise displacement (FD). We demonstrate that in most datasets this filtering approach saves a substantial amount of data from FD-based frame censoring, while at the same time reducing motion biases in functional connectivity measures. These findings suggest that filtering motion parameters is an effective way to improve the fidelity of head motion estimates, even in single band datasets. Particularly large data savings may accrue in datasets acquired in older and less fit participants. © 2020 The Authors

Author Keywords
Aging;  Artifacts;  fMRI;  Functional connectivity;  Motion

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Combinatorial Pharmacogenomic Algorithm is Predictive of Citalopram and Escitalopram Metabolism in Patients with Major Depressive Disorder
(2020) Psychiatry Research, 290, art. no. 113017, . 

Shelton, R.C.^a , Parikh, S.V.^b , Law, R.A.^c , Rothschild, A.J.^d , Thase, M.E.^e , Dunlop, B.W.^f , DeBattista, C.^g , Conway, C.R.^h , Forester, B.P.ⁱ , Macaluso, M.^j , Hain, D.T.^c , Aguilar, A.L.^c , Brown, K.^k , Lewis, D.J.^c , Jablonski, M.R.^c , Greden, J.F.^b

^a Department of Psychiatry and School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, United States
^b University of Michigan, Comprehensive Depression Center and Department of Psychiatry, and National Network of Depression Centers, Ann Arbor, MI, United States
^c Myriad Neuroscience, Mason, OH, United States
^d University of Massachusetts, Medical School and UMass Memorial Healthcare, Worcester, MA, United States
^e Perelman School of Medicine of the University of Pennsylvania and the Corporal Michael Crescenz VAMC, Philadelphia, PA, United States
^f Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
^g Stanford University School of Medicine, Department of Psychiatry and Behavioral Sciences, Stanford, CA, United States
^h Department of Psychiatry, Washington University School of Medicine, and the John Cochran Veteran’s Administration Hospital, St. Louis, MO, United States
ⁱ McLean Hospital, Division of Geriatric Psychiatry, Harvard Medical School, Belmont, MA, United States
^j Department of Psychiatry and Behavioral Sciences, University of Kansas School of Medicine-Wichita, Wichita, KS, United States
^k Myriad Genetics, Inc., Salt Lake City, UT, United States

Abstract
Pharmacogenomic tests used to guide clinical treatment for major depressive disorder (MDD) must be thoroughly validated. One important assessment of validity is the ability to predict medication blood levels, which reflect altered metabolism. Historically, the metabolic impact of individual genes has been evaluated; however, we now know that multiple genes are often involved in medication metabolism. Here, we evaluated the ability of individual pharmacokinetic genes (CYP2C19, CYP2D6, CYP3A4) and a combinatorial pharmacogenomic test (GeneSight Psychotropic®; weighted assessment of all three genes) to predict citalopram/escitalopram blood levels in patients with MDD. Patients from the Genomics Used to Improve DEpression Decisions (GUIDED) trial who were taking citalopram/escitalopram at screening and had available blood level data were included (N=191). In multivariate analysis of the individual genes and combinatorial pharmacogenomic test separately (adjusted for age, smoking status), the F statistic for the combinatorial pharmacogenomic test was 1.7 to 2.9-times higher than the individual genes, showing that it explained more variance in citalopram/escitalopram blood levels. In multivariate analysis of the individual genes and combinatorial pharmacogenomic test together, only the combinatorial pharmacogenomic test remained significant. Overall, this demonstrates that the combinatorial pharmacogenomic test was a superior predictor of citalopram/escitalopram blood levels compared to individual genes. © 2020 The Authors

Author Keywords
Citalopram;  Depression;  Escitalopram;  GeneSight;  Medication Blood Levels;  Pharmacokinetics

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

The personality profile of chronic alcohol dependent patients with comorbid gambling disorder symptoms
(2020) Comprehensive Psychiatry, 101, art. no. 152183, . 

Kovács, I.^a , Pribék, I.K.^a , Demeter, I.^a , Rózsa, S.^c , Janka, Z.^a , Demetrovics, Z.^b , Andó, B.^a

^a Department of Psychiatry, Faculty of Medicine, University of Szeged, Kálvária Ave. 57, Szeged, H-6725, Hungary
^b Institute of Psychology, Eötvös Loránd University, Izabella Street 46, Budapest, H-1064, Hungary
^c Department of Psychiatry, Washington University School of Medicine, St. Louis, United States

Abstract
Background and aims: The importance of personality characteristics in the diagnosis and treatment of gambling disorder (GD) and alcohol use disorder (AUD) is often highlighted in scientific literature. This study aimed to test predictions about the associations of temperament and character in chronic AUD patients with comorbid GD symptoms and without them. Methods: Chronic AUD patients enrolled from an inpatient clinic were divided in two groups based on cluster analysis, AUD patients with (AUD + GD group: n = 30) and without (AUD group: n = 68) GD symptoms. Severity of GD symptoms and personality dimensions (Cloninger’s Temperament and Character Inventory Revised, TCI-R) were assessed. Associations of tested variables were analysed with analysis of covariance, one-sample and independent sample t-tests. Results: GD symptoms proved to be a clustering factor in terms of personality, where AUD + GD group expressed a more maladaptive personality profile. Compared to Hungarian normative TCI-R scores, both patient groups showed elevated levels of Harm Avoidance and Novelty Seeking with lower scores of Self-directedness, while the AUD + GD group scored lower on Persistence and Cooperation as well. The AUD + GD group reported significantly higher levels of Harm Avoidance, with lower scores of Reward Dependence compared to the AUD group. Discussion: Comorbid GD symptom severity is an important factor in chronic AUD, where AUD patients with comorbid GD symptoms exhibited a more maladaptive personality constellation than singular AUD patients. These emphasize the need of special attention for comorbid GD symptoms in AUD, since treatment recommendations and prognosis for them may also differ. © 2020 The Authors

Author Keywords
Alcohol use disorder;  Gambling disorder;  Personality;  Symptom severity;  Temperament and character

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Early neurobehavior at 30 weeks postmenstrual age is related to outcome at term equivalent age
(2020) Early Human Development, 146, art. no. 105057, . 

Pineda, R.^{a b c} , Liszka, L.^{c d} , Inder, T.^{e f}

^a University of Southern California, Chan Division of Occupational Science and Occupational Therapy, Los Angeles, CA, United States
^b Keck School of Medicine, Department of Pediatrics, Los Angeles, CA, United States
^c Washington University School of Medicine, Program in Occupational Therapy, St. Louis, MO, United States
^d Seattle Children’s Hospital, Seattle, WA, United States
^e Brigham and Women’s Hospital, Department of Pediatric Newborn Medicine, Boston, MA, United States
^f Harvard University, Harvard Medical School, Boston, MA, United States

Abstract
Aims: To determine 1) the relationship between infant medical factors and early neurobehavior, and 2) the relationship between early neurobehavior at 30 weeks postmenstrual age (PMA) and neurobehavior at term equivalent age. Study design: In this prospective longitudinal study, 88 very preterm infants born ≤30 weeks estimated gestational age (EGA) had neurobehavioral assessments at 30 weeks PMA using the Premie-Neuro and at term equivalent age using the NICU Network Neurobehavioral Scale (NNNS) and Hammersmith Neonatal Neurological Evaluation (HNNE). Results: Lower Premie-Neuro scores at 30 weeks PMA were related to being more immature at birth (p = 0.01; β = 3.87); the presence of patent ductus arteriosus (PDA; p < 0.01; β = −16.50) and cerebral injury (p < 0.01; β = −20.46); and prolonged exposure to oxygen therapy (p < 0.01; β = −0.01), endotracheal intubation (p < 0.01; β = −0.23), and total parenteral nutrition (p < 0.01; β = −0.35). After controlling for EGA, PDA, and number of days of endotracheal intubation, lower Premie-Neuro scores at 30 weeks PMA were independently related to lower total HNNE scores at term (p < 0.01; β = 0.12) and worse outcome on the NNNS with poorer quality of movement (p < 0.01; β = 0.02) and more stress (p < 0.01; ß = −0.004), asymmetry (p = 0.01; β = −0.04), excitability (p < 0.01; β = −0.05) and suboptimal reflexes (p < 0.01; ß = −0.06). Conclusion: Medical factors were associated with early neurobehavioral performance at 30 weeks PMA. Early neurobehavior at 30 weeks PMA was a good marker of adverse neurobehavior at NICU discharge. © 2020 Elsevier B.V.

Author Keywords
Neonatal intensive care unit, outcome, development;  Neurobehavior;  Preterm

Document Type: Article
Publication Stage: Final
Source: Scopus

The Effect of Surgical Video on Resident Performance of Carpal Tunnel Release: A Cadaveric Simulation-Based, Prospective, Randomized, Blinded Pilot Study
(2020) Plastic and Reconstructive Surgery, 145 (6), pp. 1455-1463. 

Yee, A., Padovano, W.M., Rowe, A.G., Hill, E.J.R., Fox, I.K., Moore, A.M., Coert, J.H., Mackinnon, S.E.

St. Louis, Mo.; and Utrecht, The Netherlands From the Division of Plastic and Reconstructive Surgery, Department of Surgery, Washington University School of Medicine; and the Department of Plastic, Reconstructive and Hand Surgery, Utrecht University Medical Center

Abstract
BACKGROUND: Surgical videos are increasingly common, although their role in residency curricula remains unclear. The aim of this study was to evaluate the impact of an educational surgical video on resident performance of an open carpal tunnel release through an Objective Structured Assessment of Technical Skills and serial questionnaires. METHODS: Twenty-two residents representing six postgraduate years were randomized to receive text-based materials with or without a surgical video before performing a carpal tunnel release on human cadavers. Procedures were video recorded, anonymized, and independently evaluated by three hand surgeons using the Objective Structured Assessment of Technical Skills global rating scale, a procedure-specific technical rating scale, a record of operative errors, and pass/fail designation. Residents completed questionnaires before and after the procedure to track confidence in their technical skills. RESULTS: Residents in their first and second postgraduate years (n = 10) who watched the surgical video committed fewer operative errors (median, 4 versus 1.3; p = 0.043) and were more confident in their abilities following the procedure (median, 75 versus 32; p = 0.043) than those receiving text resources alone. There were no significant differences in Objective Structured Assessment of Technical Skills performance or questionnaire responses among more senior residents (n = 12). The technical rating scale was internally consistent (Cronbach α = 0.95; 95 percent CI, 0.91 to 0.98), reliable (intraclass correlation coefficient, 0.73; 95 percent CI, 0.40 to 0.88), and correlated with surgical experience (Spearman ρ = 0.57; p = 0.006). CONCLUSION: Watching an educational surgical video to prepare for a cadaveric procedure significantly reduced operative errors and improved confidence among junior trainees performing a carpal tunnel release.

Document Type: Article
Publication Stage: Final
Source: Scopus

Discussion: Functional Outcome after Reconstruction of a Long Nerve Gap in Rabbits Using Optimized Decellularized Nerve Allografts
(2020) Plastic and Reconstructive Surgery, 145 (6), pp. 1451-1453. 

Mackinnon, S.E., Pan, D., Wood, M.D.

Mo. From the Division of Plastic Surgery, Department of Surgery, Washington University School of Medicine, St. Louis, United States

Document Type: Article
Publication Stage: Final
Source: Scopus

Intraventricular Hemorrhage Clearance in Human Neonatal Cerebrospinal Fluid: Associations With Hydrocephalus
(2020) Stroke, 51 (6), pp. 1712-1719. 

Mahaney, K.B.^a , Buddhala, C.^b , Paturu, M.^b , Morales, D.^b , Limbrick, D.D., Jr^b , Strahle, J.M.^b

^a Department of Neurosurgery, Stanford University, Stanford, United States
^b From the Department of Neurological Surgery, Washington University in St Louis, D.M.

Abstract
Background and Purpose- Preterm neonates with intraventricular hemorrhage (IVH) are at risk for posthemorrhagic hydrocephalus and poor neurological outcomes. Iron has been implicated in ventriculomegaly, hippocampal injury, and poor outcomes following IVH. We hypothesized that levels of cerebrospinal fluid blood breakdown products and endogenous iron clearance proteins in neonates with IVH differ from those of neonates with IVH who subsequently develop posthemorrhagic hydrocephalus. Methods- Premature neonates with an estimated gestational age at birth <30 weeks who underwent lumbar puncture for clinical evaluation an average of 2 weeks after birth were evaluated. Groups consisted of controls (n=16), low-grade IVH (grades I-II; n=4), high-grade IVH (grades III-IV; n=6), and posthemorrhagic hydrocephalus (n=9). Control subjects were preterm neonates born at <30 weeks’ gestation without brain abnormality or hemorrhage on cranial ultrasound, who underwent lumbar puncture for clinical purposes. Cerebrospinal fluid hemoglobin, total bilirubin, total iron, ferritin, ceruloplasmin, transferrin, haptoglobin, and hemopexin were quantified. Results- Cerebrospinal fluid hemoglobin levels were increased in posthemorrhagic hydrocephalus compared with high-grade IVH (9.45 versus 6.06 µg/mL, P<0.05) and cerebrospinal fluid ferritin levels were increased in posthemorrhagic hydrocephalus compared with controls (511.33 versus 67.08, P<0.01). No significant group differences existed for the other cerebrospinal fluid blood breakdown and iron-handling proteins tested. We observed positive correlations between ventricular enlargement (frontal occipital horn ratio) and ferritin (Pearson r=0.67), hemoglobin (Pearson r=0.68), and total bilirubin (Pearson r=0.69). Conclusions- Neonates with posthemorrhagic hydrocephalus had significantly higher levels of hemoglobin than those with high-grade IVH. Levels of blood breakdown products, hemoglobin, ferritin, and bilirubin correlated with ventricular size. There was no elevation of several iron-scavenging proteins in cerebrospinal fluid in neonates with posthemorrhagic hydrocpehalus, indicative of posthemorrhagic hydrocephalus as a disease state occurring when endogenous iron clearance mechanisms are overwhelmed.

Author Keywords
biomarkers;  cerebrospinal fluid;  hemorrhage;  hydrocephalus;  iron

Document Type: Article
Publication Stage: Final
Source: Scopus

Plasma neurofilament light chain in the presenilin 1 E280A autosomal dominant Alzheimer’s disease kindred: a cross-sectional and longitudinal cohort study
(2020) The Lancet Neurology, 19 (6), pp. 513-521. Cited 1 time.

Quiroz, Y.T.^{a b} , Zetterberg, H.^{c d} , Reiman, E.M.^{e f g h} , Chen, Y.^e , Su, Y.^e , Fox-Fuller, J.T.^{a i} , Garcia, G.^b , Villegas, A.^b , Sepulveda-Falla, D.^{b j} , Villada, M.^b , Arboleda-Velasquez, J.F.^k , Guzmán-Vélez, E.^a , Vila-Castelar, C.^a , Gordon, B.A.^l , Schultz, S.A.^l , Protas, H.D.^e , Ghisays, V.^e , Giraldo, M.^b , Tirado, V.^b , Baena, A.^b , Munoz, C.^b , Rios-Romenets, S.^b , Tariot, P.N.^{e f} , Blennow, K.^c , Lopera, F.^b

^a Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
^b Grupo de Neurociencias de Antioquia of Universidad de Antioquia, Medellín, Colombia
^c Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
^d Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
^e Banner Alzheimer’s Institute, Phoenix, AZ, United States
^f University of Arizona College of Medicine, Phoenix, AZ, United States
^g Arizona State University, Tempe, AZ, United States
^h Translational Genomics Research Institute, Phoenix, AZ, United States
ⁱ Department of Psychological and Brain Sciences, Boston University, Boston, MA, United States
^j Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
^k Schepens Eye Research Institute of Mass, Eye and Ear, Harvard Medical School, Boston, MA, United States
^l Knight Alzheimer’s Disease Research Center, Washington University in St Louis, St Louis, MO, United States

Abstract
Background: Neurofilament light chain (NfL) is a promising biomarker of active axonal injury and neuronal degeneration. We aimed to characterise cross-sectional and longitudinal plasma NfL measurements and determine the age at which NfL concentrations begin to differentiate between carriers of the presenilin 1 (PSEN1) E280A (Glu280Ala) mutation and age-matched non-carriers from the Colombian autosomal dominant Alzheimer’s disease kindred. Methods: In this cross-sectional and longitudinal cohort study, members of the familial Alzheimer’s disease Colombian kindred aged 8–75 years with no other neurological or health conditions were recruited from the Alzheimer’s Prevention Initiative Registry at the University of Antioquia (Medellín, Colombia) between Aug 1, 1995, and Dec 15, 2018. We used a single molecule array immunoassay and log-transformed data to examine the relationship between plasma NfL concentrations and age, and establish the earliest age at which NfL concentrations begin to diverge between mutation carriers and non-carriers. Findings: We enrolled a cohort of 1070 PSEN1 E280A mutation carriers and 1074 non-carriers with baseline assessments; of these participants, longitudinal measures (with a mean follow-up of 6 years) were available for 242 mutation carriers and 262 non-carriers. Plasma NfL measurements increased with age in both groups (p<0·0001), and began to differentiate carriers from non-carriers when aged 22 years (22 years before the estimated median age at mild cognitive impairment onset of 44 years), although the ability of plasma NfL to discriminate between carriers and non-carriers only reached high sensitivity close to the age of clinical onset. Interpretation: Our findings further support the promise of plasma NfL as a biomarker of active neurodegeneration in the detection and tracking of Alzheimer’s disease and the evaluation of disease-modifying therapies. Funding: National Institute on Aging, National Institute of Neurological Disorders and Stroke, Banner Alzheimer’s Foundation, COLCIENCIAS, the Torsten Söderberg Foundation, the Swedish Research Council, the Swedish Alzheimer Foundation, the Swedish Brain Foundation, and the Swedish state under the ALF-agreement. © 2020 Elsevier Ltd

Document Type: Article
Publication Stage: Final
Source: Scopus

Organ Culture and Grafting of Choroid Plexus into the Ventricular CSF of Normal and Hydrocephalic HTx Rats
(2020) Journal of Neuropathology and Experimental Neurology, 79 (6), pp. 626-640. 

Johanson, C.E.^a , Vío, K.^b , Guerra, M.^b , Salazar, P.^b , Jara, M.C.^b , Rodríguez, S.^b , Ortega, E.^c , Castañeyra-Ruiz, L.^d , McAllister, J.P.^e , Rodríguez, E.M.^b

^a Department of Neurosurgery, Alpert Medical School at Brown University, Providence, RI, United States
^b Instituto de Anatomía
^c Instituto de Neurociencias Clínicas
^d Facultad de Medicina, Universidad Austral de Chile, Valdivia, Chile; Departamento de Anatomía, Facultad de Medicina, Universidad de la Laguna, San Cristóbal de La Laguna, Spain
^e Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Choroid plexus (CP) may aid brain development and repair by secreting growth factors and neurotrophins for CSF streaming to ventricular and subventricular zones. Disrupted ventricular/subventricular zone progenitors and stem cells lead to CNS maldevelopment. Exploring models, we organ cultured the CP and transplanted fresh CP into a lateral ventricle of postnatal hydrocephalic (hyHTx) and nonhydrocephalic (nHTx) rats. After 60 days in vitro, the cultured choroid ependyma formed spherical rings with beating cilia. Cultured CP expressed endocytotic caveolin 1 and apical aquaporin 1 and absorbed horseradish peroxidase from medium. Transthyretin secretory protein was secreted by organ-cultured CP into medium throughout 60 days in vitro. Fresh CP, surviving at 1 week after lateral ventricle implantation of nHTx or hyHTx did not block CSF flow. Avascular 1-week transplants in vivo expressed caveolin 1, aquaporin 1, and transthyretin, indicating that grafted CP may secrete trophic proteins but not CSF. Our findings encourage further exploration on CP organ culture and grafting for translational strategies. Because transplanted CP, though not producing CSF, may secrete beneficial molecules for developing brain injured by hydrocephalus, we propose that upon CP removal in hydrocephalus surgery, the fractionated tissue could be transplanted back (ventricular autograft). © 2020 American Association of Neuropathologists, Inc. All rights reserved.

Author Keywords
Aquaporin 1;  Caveolin 1;  Cerebrospinal fluid;  Choroid plexus culture/grafting;  HTx rats;  Transthyretin;  Ventricular ependyma

Document Type: Article
Publication Stage: Final
Source: Scopus

Consensus guideline for the diagnosis and treatment of tetrahydrobiopterin (BH4) deficiencies
(2020) Orphanet Journal of Rare Diseases, 15 (1), art. no. 126, . 

Opladen, T.^a , López-Laso, E.^b , Cortès-Saladelafont, E.^{c d} , Pearson, T.S.^e , Sivri, H.S.^f , Yildiz, Y.^f , Assmann, B.^a , Kurian, M.A.^{g h} , Leuzzi, V.ⁱ , Heales, S.^j , Pope, S.^j , Porta, F.^k , García-Cazorla, A.^c , Honzík, T.^l , Pons, R.^m , Regal, L.ⁿ , Goez, H.^o , Artuch, R.^p , Hoffmann, G.F.^a , Horvath, G.^q , Thöny, B.^r , Scholl-Bürgi, S.^s , Burlina, A.^t , Verbeek, M.M.^u , Mastrangelo, M.ⁱ , Friedman, J.^v , Wassenberg, T.ⁿ , Jeltsch, K.^a , Kulhánek, J.^l , Kuseyri Hübschmann, O.^a

^a Division of Child Neurology and Metabolic Disorders, University Children’s Hospital, Heidelberg, Germany
^b Pediatric Neurology Unit, Department of Pediatrics, University Hospital Reina Sofía, IMIBIC and CIBERER, Córdoba, Spain
^c Inborn Errors of Metabolism Unit, Institut de Recerca Sant Joan de Déu, CIBERER-ISCIII, Barcelona, Spain
^d Unit of Pediatric Neurology and Metabolic Disorders, Department of Pediatrics, Hospital Germans Trias i Pujol, Faculty of Medicine, Universitat Autònoma de Barcelona, Badalona, Spain
^e Department of Neurology, Washington University, School of Medicine, St. Louis, United States
^f Department of Pediatrics, Section of Metabolism, Hacettepe University, Faculty of Medicine, Ankara, 06100, Turkey
^g Developmental Neurosciences, UCL Great Ormond Street-Institute of Child Health, London, United Kingdom
^h Department of Neurology, Great Ormond Street Hospital, London, United Kingdom
ⁱ Unit of Child Neurology and Psychiatry, Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
^j Neurometabolic Unit, National Hospital, Queen Square, London, United Kingdom
^k Department of Pediatrics, AOU Città della Salute e della Scienza, Torino, Italy
^l Department of Paediatrics and Adolescent Medicine, First Faculty of Medicine, Charles University, General University Hospital in Prague, Prague, Czech Republic
^m First Department of Pediatrics, University of Athens, Aghia Sofia Hospital, Athens, Greece
ⁿ Department of Pediatric, Pediatric Neurology and Metabolism Unit, UZ Brussel, Brussels, Belgium
^o Department of Pediatrics, University of Alberta, Glenrose Rehabilitation Hospital, Edmonton, Canada
^p Clinical Biochemistry Department, Institut de Recerca Sant Joan de Déu, CIBERER, MetabERN Hospital Sant Joan de Déu, Barcelona, Spain
^q Department of Pediatrics, Division of Biochemical Genetics, BC Children’s Hospital, University of British Columbia, Vancouver, BC, Canada
^r Division of Metabolism, University Children’s Hospital Zurich, Zürich, Switzerland
^s Clinic for Pediatrics i, Medical University of Innsbruck, Anichstr 35, Innsbruck, Austria
^t U.O.C. Malattie Metaboliche Ereditarie, Dipartimento della Salute della Donna e Del Bambino, Azienda Ospedaliera Universitaria di Padova, Campus Biomedico Pietro d’Abano, Padova, Italy
^u Departments of Neurology and Laboratory Medicine, Alzheimer Centre, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
^v UCSD Departments of Neuroscience and Pediatrics, Rady Children’s Hospital Division of Neurology, Rady Children’s Institute for Genomic Medicine, San Diego, United States

Abstract
Background: Tetrahydrobiopterin (BH4) deficiencies comprise a group of six rare neurometabolic disorders characterized by insufficient synthesis of the monoamine neurotransmitters dopamine and serotonin due to a disturbance of BH4 biosynthesis or recycling. Hyperphenylalaninemia (HPA) is the first diagnostic hallmark for most BH4 deficiencies, apart from autosomal dominant guanosine triphosphate cyclohydrolase I deficiency and sepiapterin reductase deficiency. Early supplementation of neurotransmitter precursors and where appropriate, treatment of HPA results in significant improvement of motor and cognitive function. Management approaches differ across the world and therefore these guidelines have been developed aiming to harmonize and optimize patient care. Representatives of the International Working Group on Neurotransmitter related Disorders (iNTD) developed the guidelines according to the SIGN (Scottish Intercollegiate Guidelines Network) methodology by evaluating all available evidence for the diagnosis and treatment of BH4 deficiencies. Conclusion: Although the total body of evidence in the literature was mainly rated as low or very low, these consensus guidelines will help to harmonize clinical practice and to standardize and improve care for BH4 deficient patients. © 2020 The Author(s).

Author Keywords
6-pyruvoyltetrahydropterin synthase deficiency;  BH4;  Consensus guidelines;  Dihydropteridine reductase deficiency;  Guanosine triphosphate cyclohydrolase deficiency;  Hyperphenylalaninemia;  iNTD;  Neurotransmitter;  Sepiapterin reductase deficiency, pterin-4-alpha-carbinolamine dehydratase deficiency;  SIGN;  Tetrahydrobiopterin deficiency

Document Type: Review
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Genome-Wide Meta-Analyses of FTND and TTFC Phenotypes
(2020) Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco, 22 (6), pp. 900-909. 

Chen, J.^a , Loukola, A.^{b c} , Gillespie, N.A.^d , Peterson, R.^d , Jia, P.^e , Riley, B.^d , Maes, H.^d , Dick, D.M.^f , Kendler, K.S.^d , Damaj, M.I.^g , Miles, M.F.^g , Zhao, Z.^e , Li, M.D.^h , Vink, J.M.^{i j} , Minica, C.C.^{i k l} , Willemsen, G.^{i k l} , Boomsma, D.I.^{i k l} , Qaiser, B.^{b c} , Madden, P.A.F.^m , Korhonen, T.^{b n} , Jousilahti, P.^o , Hällfors, J.^c , Gelernter, J.^p , Kranzler, H.R.^q , Sherva, R.^r , Farrer, L.^r , Maher, B.^s , Vanyukov, M.^t , Taylor, M.^u , Ware, J.J.^u , Munafò, M.R.^u , Lutz, S.M.^v , Hokanson, J.E.^v , Gu, F.^w , Landi, M.T.^w , Caporaso, N.E.^w , Hancock, D.B.^x , Gaddis, N.C.^y , Baker, T.B.^z , Bierut, L.J.^m , Johnson, E.O.^{x aa} , Chenoweth, M.^ab , Lerman, C.^ac , Tyndale, R.^ab , Kaprio, J.^{b c} , Chen, X.^{a d ad}

^a Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, NV, Las Vegas, Mexico
^b Department of Public Health, University of Helsinki, FI, Helsinki, Finland
^c Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
^d Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, VA, Richmond
^e School of Biomedical Informatics, University of Texas Health Science Center at Houston, TX, Houston
^f Department of Psychology, Virginia Commonwealth University, VA, Richmond
^g Department of Pharmacology and Toxicology, Virginia Commonwealth University, VA, Richmond
^h State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
ⁱ Netherlands Twin Register, Department of Biological Psychology, VU University, Netherlands
^j Behavioural Science Institute, Radboud University, Nijmegen, Netherlands
^k Neuroscience Campus Amsterdam, Netherlands
^l EMGO+ Institute for Health and Care Research, VU Medical Center, Amsterdam, Netherlands
^m Department of Psychiatry, Washington University, St. Louis, MO
ⁿ Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Finland
^o National Institute for Health and Welfare, Helsinki, Finland
^p Department of Psychiatry, Yale University, CT, New Haven, United States
^q Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
^r Section of Biomedical Genetics, Department of Medicine, Boston University School of Medicine, MA, Boston
^s Department of Mental Health, Johns Hopkins University, MD, Baltimore, United States
^t Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, United States
^u MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, BS, Bristol, United Kingdom
^v Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, CO, Aurora, United States
^w Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, United States Department of Health and Human Services, MD, Bethesda, United States
^x Behavioral Health and Criminal Justice Division, RTI International, Research Triangle Park
^y Research Computing Division, RTI International, Research Triangle Park
^z Center for Tobacco Research and Intervention, University of Wisconsin, WI, Madison, United States
^aa Fellow Program, RTI International, Research Triangle Park
^ab Centre for Addiction and Mental Health, Departments of Pharmacology and Toxicology, Psychiatry, University of Toronto, Toronto, Canada
^ac Center for Interdisciplinary Research on Nicotine Addiction, Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
^ad Department of Psychology, University of Nevada Las Vegas, NV, Las Vegas, Mexico

Abstract
INTRODUCTION: FTND (Fagerstrӧm test for nicotine dependence) and TTFC (time to smoke first cigarette in the morning) are common measures of nicotine dependence (ND). However, genome-wide meta-analysis for these phenotypes has not been reported. METHODS: Genome-wide meta-analyses for FTND (N = 19,431) and TTFC (N = 18,567) phenotypes were conducted for adult smokers of European ancestry from 14 independent cohorts. RESULTS: We found that SORBS2 on 4q35 (p = 4.05 × 10-8), BG182718 on 11q22 (p = 1.02 × 10-8), and AA333164 on 14q21 (p = 4.11 × 10-9) were associated with TTFC phenotype. We attempted replication of leading candidates with independent samples (FTND, N = 7010 and TTFC, N = 10 061), however, due to limited power of the replication samples, the replication of these new loci did not reach significance. In gene-based analyses, COPB2 was found associated with FTND phenotype, and TFCP2L1, RELN, and INO80C were associated with TTFC phenotype. In pathway and network analyses, we found that the interconnected interactions among the endocytosis, regulation of actin cytoskeleton, axon guidance, MAPK signaling, and chemokine signaling pathways were involved in ND. CONCLUSIONS: Our analyses identified several promising candidates for both FTND and TTFC phenotypes, and further verification of these candidates was necessary. Candidates supported by both FTND and TTFC (CHRNA4, THSD7B, RBFOX1, and ZNF804A) were associated with addiction to alcohol, cocaine, and heroin, and were associated with autism and schizophrenia. We also identified novel pathways involved in cigarette smoking. The pathway interactions highlighted the importance of receptor recycling and internalization in ND. IMPLICATIONS: Understanding the genetic architecture of cigarette smoking and ND is critical to develop effective prevention and treatment. Our study identified novel candidates and biological pathways involved in FTND and TTFC phenotypes, and this will facilitate further investigation of these candidates and pathways. © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved.For permissions, please e-mail: journals.permissions@oup.com.

Document Type: Article
Publication Stage: Final
Source: Scopus

Study protocol: Improving cognition in people with progressive multiple sclerosis: A multi-arm, randomized, blinded, sham-controlled trial of cognitive rehabilitation and aerobic exercise (COGEx)
(2020) BMC Neurology, 20 (1), art. no. 204, . 

Feinstein, A.^a , Amato, M.P.^{b c} , Brichetto, G.^{d e} , Chataway, J.^f , Chiaravalloti, N.^{g h} , Dalgas, U.ⁱ , Deluca, J.^{g h} , Feys, P.^j , Filippi, M.^{k l} , Freeman, J.^m , Meza, C.^a , Inglese, M.ⁿ , Motl, R.W.^o , Rocca, M.A.^k , Sandroff, B.M.^o , Salter, A.^p , Cutter, G.^q

^a Department of Psychiatry, University of Toronto and Sunnybrook Health Sciences Centre, Toronto, ON M5R 3B6, Canada
^b Department NEUROFARBA, Section Neurosciences, University of Florence, Largo Brambilla 3, Florence, 50134, Italy
^c IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
^d Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Via Operai 40, Genoa, 16149, Italy
^e AISM Rehabilitation Service, Italian Multiple Sclerosis Society (AISM), Via Operai 30, Genoa, 16149, Italy
^f Queen Square MS Centre, Department of Neuroinflammation, University College London (UCL) Queen Square Institute of Neurology, Faculty of Brain Sciences, UCL, London, United Kingdom
^g Kessler Foundation, East Hanover, NJ, United States
^h Department of Physical Medicine and Rehabilitation, Rutgers New Jersey Medical School, Newark, NJ, United States
ⁱ Section for Sport Science, Department of Public Health, Aarhus University, Dalgas Avenue 4, Aarhus, DK-8000, Denmark
^j Faculty of Rehabilitation Sciences, Hasselt University, Diepenbeek, Belgium
^k Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Neurology Unit, IRCCS, San Raffaele Scientific Institute, Via Olgettina 60, Milan, 20132, Italy
^l Vita-Salute San Raffaele University, Milan, Italy
^m Faculty of Health: Medicine, Dentistry and Human Sciences, University of Plymouth, Devon, United Kingdom
ⁿ Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Center of Excellence for Biomedical Research, University of Genoa, Genoa, Italy
^o Department of Physical Therapy, University of Alabama at Birmingham, Birmingham, United States
^p Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
^q Department of Biostatistics, University of Alabama at Birmingham, Birmingham, United States

Abstract
Background: Cognitive dysfunction affects up to 70% of people with progressive MS (PMS). It can exert a deleterious effect on activities of daily living, employment and relationships. Preliminary evidence suggests that performance can improve with cognitive rehabilitation (CR) and aerobic exercise (EX), but existing data are predominantly from people with relapsing-remitting MS without cognitive impairment. There is therefore a need to investigate whether this is also the case in people with progressive forms of the disease who have objectively identified cognitive impairment. It is hypothesized that CR and EX are effective treatments for people with PMS who have cognitive impairment, in particular processing speed (PS) deficits, and that a combination of these two treatments is more effective than each individual treatment given alone. We further hypothesize that improvements in PS will be associated with modifications of functional and/or structural plasticity within specific brain networks/regions involved in PS measured with advanced MRI techniques. Methods: This study is a multisite, randomized, double-blinded, sham controlled clinical trial of CR and aerobic exercise. Three hundred and sixty subjects from 11 sites will be randomly assigned into one of four groups: CR plus aerobic exercise; CR plus sham exercise; CR sham plus aerobic exercise and CR sham plus sham exercise. Subjects will participate in the assigned treatments for 12 weeks, twice a week. All subjects will have a cognitive and physical assessment at baseline, 12 weeks and 24 weeks. In an embedded sub-study, approximately 30% of subjects will undergo structural and functional MRI to investigate the neural mechanisms underlying the behavioral response. The primary outcome is the Symbol Digit Modalities Test (SDMT) measuring PS. Secondary outcome measures include: indices of verbal and non-verbal memory, depression, walking speed and a dual cognitive-motor task and MRI. Discussion: The study is being undertaken in 6 countries (11 centres) in multiple languages (English, Italian, Danish, Dutch); with testing material validated and standardized in these languages. The rationale for this approach is to obtain a robustly powered sample size and to demonstrate that these two interventions can be given effectively in multiple countries and in different languages. Trial registration: The trial was registered on September 20th 2018 at www.clinicaltrials.gov having identifier NCT03679468. Registration was performed before recruitment was initiated. © 2020 The Author(s).

Author Keywords
Aerobic exercise;  Cognitive training;  Progressive multiple sclerosis

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

A Multifunctional Chemical Agent as an Attenuator of Amyloid Burden and Neuroinflammation in Alzheimer’s Disease
(2020) ACS Chemical Neuroscience, 11 (10), pp. 1471-1481. 

Cho, H.-J.^a , Sharma, A.K.^b , Zhang, Y.^c , Gross, M.L.^c , Mirica, L.M.^{a d}

^a Department of Chemistry, University of Illinois at Urbana-Champaign, 600 S. Mathews Avenue, Urbana, IL 61801, United States
^b Department of Chemistry, Central University of Rajasthan, NH-8 ,Bandarsindri, Ajmer, Rajasthan 305817, India
^c Department of Chemistry, Washington University, One Brookings Drive, St. Louis, MO 63130, United States
^d Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, United States

Abstract
Alzheimer’s disease (AD) is the most common neurodegenerative disease, and its main hallmark is the deposition of amyloid beta (Aβ) peptides. However, several clinical trials focusing on Aβ-targeting agents have failed recently, and thus new therapeutic leads are focusing on alternate targets such as tau protein pathology, Aβ-metal induced oxidative stress, and neuroinflammation. To address these different pathological aspects of AD, we have employed a multifunctional compound, L1 [4-(benzo[d]thiazol-2-yl)-2-((4,7-dimethyl-1,4,7-triazonan-1-yl)methyl)-6-methoxyphenol], that integrates Aβ-interacting and metal-binding fragments in a single molecular framework, exhibits significant antioxidant activity and metal chelating ability, and also rescues neuroblastoma N2A cells from Cu2+-induced Aβ neurotoxicity. Along with demonstrating in vivo Aβ-binding and favorable brain uptake properties, L1 treatment of transgenic 5xFAD mice significantly reduces the amount of both amyloid plaques and associated phosphorylated tau (p-tau) aggregates in the brain by 40-50% versus the vehicle-treated 5xFAD mice. Moreover, L1 mitigates the neuroinflammatory response of the activated microglia during the Aβ-induced inflammation process. Overall, these multifunctional properties of L1 to attenuate the formation of amyloid plaques and associated p-tau aggregates while also reducing the microglia-mediated neuroinflammatory response are quite uncommon among the previously reported amyloid-targeting chemical agents, and thus L1 could be envisioned as a lead compound for the development of novel AD therapeutics.

Author Keywords
Alzheimer’s disease;  amyloid beta peptide;  amyloid plaques;  Aβ;  microglia activation;  neuroinflammation;  oxidative stress;  p-tau;  phosphorylated tau aggregation

Document Type: Article
Publication Stage: Final
Source: Scopus

A Spiking Neuron and Population Model Based on the Growth Transform Dynamical System
(2020) Frontiers in Neuroscience, 14, art. no. 425, . 

Gangopadhyay, A.^a , Mehta, D.^b , Chakrabartty, S.^a

^a Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, United States
^b Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States

Abstract
In neuromorphic engineering, neural populations are generally modeled in a bottom-up manner, where individual neuron models are connected through synapses to form large-scale spiking networks. Alternatively, a top-down approach treats the process of spike generation and neural representation of excitation in the context of minimizing some measure of network energy. However, these approaches usually define the energy functional in terms of some statistical measure of spiking activity (ex. firing rates), which does not allow independent control and optimization of neurodynamical parameters. In this paper, we introduce a new spiking neuron and population model where the dynamical and spiking responses of neurons can be derived directly from a network objective or energy functional of continuous-valued neural variables like the membrane potential. The key advantage of the model is that it allows for independent control over three neuro-dynamical properties: (a) control over the steady-state population dynamics that encodes the minimum of an exact network energy functional; (b) control over the shape of the action potentials generated by individual neurons in the network without affecting the network minimum; and (c) control over spiking statistics and transient population dynamics without affecting the network minimum or the shape of action potentials. At the core of the proposed model are different variants of Growth Transform dynamical systems that produce stable and interpretable population dynamics, irrespective of the network size and the type of neuronal connectivity (inhibitory or excitatory). In this paper, we present several examples where the proposed model has been configured to produce different types of single-neuron dynamics as well as population dynamics. In one such example, the network is shown to adapt such that it encodes the steady-state solution using a reduced number of spikes upon convergence to the optimal solution. In this paper, we use this network to construct a spiking associative memory that uses fewer spikes compared to conventional architectures, while maintaining high recall accuracy at high memory loads. © Copyright © 2020 Gangopadhyay, Mehta and Chakrabartty.

Author Keywords
adaptation;  associative memory;  dynamical system;  energy-minimization;  growth transforms;  network model;  neural dynamics;  spiking neuron model

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Cross-sectional analysis of backward, forward, and dual task gait kinematics in people with Parkinson disease with and without freezing of gait
(2020) Journal of Applied Biomechanics, 36 (2), pp. 85-95. 

Myers, P.S.^a , Rawson, K.S.^a , Harrison, E.C.^a , Horin, A.P.^a , Sutter, E.N.^{a b d} , McNeely, M.E.^{a c e} , Earhart, G.M.^a

^a Program in Physical Therapy, 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 Rehabilitation Medicine, University of Minnesota, Minneapolis, MN, United States
^d Department of Neuroscience, Washington University School of Medicine, St Louis, MO, United States
^e Unfold Productions, LLC, St Louis, MO, United States

Abstract
People with Parkinson disease demonstrate increased gait variability, but the primary variability sources are poorly understood. People with Parkinson disease and freezing of gait (freezers) have greater gait impairments than people with Parkinson disease without freezing of gait (nonfreezers), which may relate to cerebellar dysfunction. Thirteen freezers and 31 nonfreezers completed backward, forward, and forward with dual task gait trials. Sagittal joint angle waveforms were extracted for the hip, knee, and ankle using 3D motion capture. Decomposition indices were calculated for the 3 joint combinations. Principal component analysis extracted variance sources from the joint waveforms. Freezers had significantly greater decomposition between hip–ankle (F1,42 = 5.1, P = .03) and hip–knee (F1,42 = 5.3, P = .03) movements. The principal component analysis did not differentiate freezers and nonfreezers; however, primary variance sources differed between conditions. Primary variance during forward and forward with dual task gait came from joint angle magnitude and peak angle timing. Backward gait showed primary variance from joint angle magnitude and range of motion. The results show that freezers decompose movement more than nonfreezers, implicating cerebellar involvement in freezing of gait. Primary variance differs between gait conditions, and tailoring gait interventions to address variability sources may improve intervention efficacy. © 2020 Human Kinetics, Inc.

Author Keywords
Cerebellum;  Gait mechanics;  Principal component analysis

Document Type: Article
Publication Stage: Final
Source: Scopus

DNAJC6 Mutations Disrupt Dopamine Homeostasis in Juvenile Parkinsonism-Dystonia
(2020) Movement Disorders, . 

Ng, J.^{a b} , Cortès-Saladelafont, E.^a , Abela, L.^a , Termsarasab, P.^{c d} , Mankad, K.^e , Sudhakar, S.^e , Gorman, K.M.^{a f} , Heales, S.J.R.^g , Pope, S.^g , Biassoni, L.^e , Csányi, B.^a , Cain, J.^h , Rakshi, K.ⁱ , Coutts, H.ⁱ , Jayawant, S.^j , Jefferson, R.^k , Hughes, D.^l , García-Cazorla, À.^m , Grozeva, D.^{n o} , Raymond, F.L.^{n o} , Pérez-Dueñas, B.^{a p} , De Goede, C.^q , Pearson, T.S.^{c r} , Meyer, E.^a , Kurian, M.A.^{a f}

^a Molecular Neurosciences, Developmental Neurosciences Programme, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
^b Gene Transfer Technology Group, UCL Institute for Women’s Health, London, United Kingdom
^c Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, United States
^d Division of Neurology, Department of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
^e Department of Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
^f Department of Neurology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
^g Neurometabolic Unit, National Hospital for Neurology and Neurosurgery, London, United Kingdom
^h Department of Nuclear Medicine and Imaging, Lancashire Teaching Hospitals, NHS Foundation Trust, Preston, United Kingdom
ⁱ Department of Paediatrics, East Lancashire Hospital NHS TrustLancashire, United Kingdom
^j Department of Paediatric Neurology, John Radcliffe Hospital, Oxford University, NHS Foundation Trust, London, United Kingdom
^k Department of Paediatrics, Royal Berkshire Hospital, NHS Foundation Trust, Reading, United Kingdom
^l Molecular Neuroscience and Reta Lila Weston Laboratories, Institute of Neurology, Queen Square, London, United Kingdom
^m Department of Neurology, Neurometabolic Unit and CIBERER Hospital Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
ⁿ Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom
^o UK10K Project, Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
^p Hospital Vall d’Hebron, Institut de Recerca (VHIR), Barcelona, Spain
^q Department of Paediatric Neurology, Royal Preston Hospital, Lancashire Teaching Hospitals, NHS Foundation Trust, London, United Kingdom
^r Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Background: Juvenile forms of parkinsonism are rare conditions with onset of bradykinesia, tremor and rigidity before the age of 21 years. These atypical presentations commonly have a genetic aetiology, highlighting important insights into underlying pathophysiology. Genetic defects may affect key proteins of the endocytic pathway and clathrin-mediated endocytosis (CME), as in DNAJC6-related juvenile parkinsonism. Objective: To report on a new patient cohort with juvenile-onset DNAJC6 parkinsonism-dystonia and determine the functional consequences on auxilin and dopamine homeostasis. Methods: Twenty-five children with juvenile parkinsonism were identified from a research cohort of patients with undiagnosed pediatric movement disorders. Molecular genetic investigations included autozygosity mapping studies and whole-exome sequencing. Patient fibroblasts and CSF were analyzed for auxilin, cyclin G–associated kinase and synaptic proteins. Results: We identified 6 patients harboring previously unreported, homozygous nonsense DNAJC6 mutations. All presented with neurodevelopmental delay in infancy, progressive parkinsonism, and neurological regression in childhood. 123I-FP-CIT SPECT (DaTScan) was performed in 3 patients and demonstrated reduced or absent tracer uptake in the basal ganglia. CSF neurotransmitter analysis revealed an isolated reduction of homovanillic acid. Auxilin levels were significantly reduced in both patient fibroblasts and CSF. Cyclin G–associated kinase levels in CSF were significantly increased, whereas a number of presynaptic dopaminergic proteins were reduced. Conclusions: DNAJC6 is an emerging cause of recessive juvenile parkinsonism-dystonia. DNAJC6 encodes the cochaperone protein auxilin, involved in CME of synaptic vesicles. The observed dopamine dyshomeostasis in patients is likely to be multifactorial, secondary to auxilin deficiency and/or neurodegeneration. Increased patient CSF cyclin G–associated kinase, in tandem with reduced auxilin levels, suggests a possible compensatory role of cyclin G–associated kinase, as observed in the auxilin knockout mouse. DNAJC6 parkinsonism-dystonia should be considered as a differential diagnosis for pediatric neurotransmitter disorders associated with low homovanillic acid levels. Future research in elucidating disease pathogenesis will aid the development of better treatments for this pharmacoresistant disorder. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Author Keywords
auxilin;  DNAJC6;  dopamine;  dystonia;  parkinsonism

Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Access Type: Open Access

Retrospectively assessed subjective effects of initial opioid use differ between opioid misusers with opioid use disorder (OUD) and those who never progressed to OUD: Data from a pilot and a replication sample
(2020) Journal of Neuroscience Research, . 

Agrawal, A.^a , Jeffries, P.W.^a , Srivastava, A.B.^b , McCutcheon, V.V.^a , Lynskey, M.T.^c , Heath, A.C.^a , Nelson, E.C.^a

^a Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^b Division on Substance Use Disorders, Department of Psychiatry, Columbia University Medical Center/New York State Psychiatric Institute, New York, NY, United States
^c National Addictions Centre Addictions Department, Institute of Psychiatry, Psychology, and Neuroscience, King’s College, London, United Kingdom

Abstract
Attempts to identify opioid users with increased risk of escalating to opioid use disorder (OUD) have had limited success. Retrospectively assessed subjective effects of initial opioid misuse were compared in a pilot sample of opioid misusers (nonmedical use ≤60 times lifetime) who had never met criteria for OUD (N = 14) and heroin-addicted individuals in treatment for OUD (N = 15). Relative to opioid misusers without a lifetime OUD diagnosis, individuals with OUD reported greater euphoria and other positive emotions, activation, pruritus, and internalizing symptoms. Consistent with these findings, proxy Addiction Research Center Inventory (ARCI) Amphetamine Group, and Morphine Benzedrine Group scale mean item scores were significantly higher in those with OUD. Replication was attempted in opioid misusers with (N = 25) and without OUD (N = 25) who were assessed as part of an ongoing genetic study. We observed similar significant between-group differences in individual subjective effect items and ARCI scale mean item scores in the replication sample. We, thus confirm findings from prior reports that retrospectively assessed subjective responses to initial opioid exposure differ significantly between opioid users who do, and do not, progress to OUD. Our report extends these findings in comparisons limited to opioid misusers. Additional research will be necessary to examine prospectively whether the assessment of subjective effects after initial use has predictive utility in the identification of individuals more likely to progress to OUD. © 2020 Wiley Periodicals, Inc.

Author Keywords
initial opioid use;  opioid misusers;  opioid use disorder;  subjective effects

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Early post-traumatic seizure occurrence in pediatric patients receiving levetiracetam prophylaxis with severe traumatic brain injury
(2020) Journal of Pediatric Pharmacology and Therapeutics, 25 (3), pp. 241-245.

Kolf, M.J.^a , McPherson, C.C.^{a b} , Kniska, K.S.^a , Luecke, C.M.^a , Lahart, M.A.^a , Pineda, J.A.^b  

^a Department of Pharmacy, St. Louis Children’s Hospital, St. Louis, MO, United States
^b Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States

Abstract
OBJECTIVE Although levetiracetam is used for the prevention of early Post-traumatic seizures (EPTS) after traumatic brain injury (TBI), limited data exist describing the incidence of seizures in pediatric patients receiving levetiracetam prophylaxis. The objective of this research is to evaluate the prevalence of EPTS in children given prophylactic levetiracetam after severe TBI. METHODS This study was conducted at a Level 1 pediatric trauma center and included pediatric patients with severe TBI who received levetiracetam for EPTS prophylaxis. Demographics and clinical information were retrospectively collected and evaluated. The primary outcome was prevalence of clinical or electrographic seizures within 7 days of initial injury as noted in the EMR. RESULTS In 4 of 44 patients (9%), seizures developed despite levetiracetam prophylaxis. Concurrent use of other medications with antiepileptic properties was common (91%). There were no differences in demographic or baseline clinical characteristics between the group of patients experiencing seizures and those who did not. However, craniotomy was significantly more common in the seizure group (75% vs. 18%, p = 0.03). CONCLUSIONS Children receiving prophylaxis with levetiracetam after severe TBI had a lower incidence of seizures (9%) than had previously been reported in the literature (18%). Given the limited literature available supporting the use of levetiracetam for the prevention of EPTS in children experiencing severe TBI, further study is needed to support routine use. ABBREVIATIONS EEG, electroencephalogram; EMR, electronic medical record; EPTS, early post-traumatic seizures; FDA, US Food and Drug Administration; GCS, Glasgow Coma Scale; ICP, intracranial pressure; IV, intravenous; PICU, pediatric intensive care unit; TBI, traumatic brain injury. © Pediatric Pharmacy Association.

Author Keywords
Anticonvulsants;  Head injury;  Levetiracetam;  Pediatrics;  Prophylaxis;  Seizures;  Traumatic brain injury

Document Type: Article
Publication Stage: Final
Source: Scopus

Hippocampal-Sparing Radiotherapy for Patients with Glioblastoma and Grade II-III Gliomas
(2020) JAMA Oncology, . 

Verma, V.^a , Robinson, C.G.^b , Rusthoven, C.G.^c

^a Department of Radiation Oncology, Allegheny General Hospital, 320 E North Ave, Pittsburgh, PA 15212, United States
^b Department of Radiation Oncology, Washington University in St Louis, School of Medicine, St Louis, MO, United States
^c Department of Radiation Oncology, University of Colorado, School of Medicine, Aurora, United States

Document Type: Note
Publication Stage: Article in Press
Source: Scopus

Optimization of Ultrasound Backscatter Spectroscopy to Assess Neurotoxic Effects of Anesthesia in the Newborn Non-human Primate Brain
(2020) Ultrasound in Medicine and Biology, . 

Castañeda-Martinez, L.^a , Noguchi, K.K.^b , Ikonomidou, C.^c , Zagzebski, J.A.^d , Hall, T.J.^d , Rosado-Mendez, I.M.^{a d d}

^a Instituto de Fisica, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico
^b Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO, United States
^c Department of Neurology, University of Wisconsin—Madison, Madison, WI, United States
^d Department of Medical Physics, University of Wisconsin—Madison, Madison, WI, United States

Abstract
Studies in animal models have revealed that long exposures to anesthetics can induce apoptosis in the newborn and young developing brain. These effects have not been confirmed in humans because of the lack of a non-invasive, practical in vivo imaging tool with the ability to detect these changes. Following the successful use of ultrasound backscatter spectroscopy (UBS) to monitor in vivo cell death in breast tumors, we aimed to use UBS to assess the neurotoxicity of the anesthetic sevoflurane (SEVO) in a non-human primate (NHP) model. Sixteen 2- to 7-day-old rhesus macaques were exposed for 5 h to SEVO. Ultrasound scanning was done with a phased array transducer on a clinical ultrasound scanner operated at 10 MHz. Data consisting of 10–15 frames of radiofrequency (RF) echo signals from coronal views of the thalamus were obtained 0.5 and 6.0 h after initiating exposure. The UBS parameter “effective scatterer size” (ESS) was estimated by fitting a scattering form factor (FF) model to the FF measured from RF echo signals. The approach involved analyzing the frequency dependence of the measured FF to characterize scattering sources and selecting the FF model based on a χ2 goodness-of-fit criterion. To assess data quality, a rigorous acceptance criterion based on the analysis of prevalence of diffuse scattering (an assumption in the estimation of ESS) was established. ESS changes after exposure to SEVO were compared with changes in a control group of five primates for which ultrasound data were acquired at 0 and 10 min (no apoptosis expected). Over the entire data set, the average measured FF at 0.5 and 6.0 h monotonically decreased with frequency, justifying fitting a single FF over the analysis bandwidth. χ2 values of a (inhomogeneous continuum) Gaussian FF model were one-fifth those of the discrete fluid sphere model, suggesting that a continuum scatterer model better represents ultrasound scattering in the young rhesus brain. After application of the data quality criterion, only 5 of 16 subjects from the apoptotic group and 5 of 5 subjects from the control group fulfilled the acceptance criteria. All subjects in the apoptotic group that passed the acceptance criterion exhibited a significant ESS reduction at 6.0 h. These changes (–6.4%, 95% Interquartile Range: –14.3% to –3.3%) were larger than those in the control group (–0.8%, 95% Interquartile Range: –2.0% to 1.5%]). Data with a low prevalence of diffuse scattering corresponded to possibly biased results. Thus, ESS has the potential to detect changes in brain microstructure related to anesthesia-induced apoptosis. © 2020 World Federation for Ultrasound in Medicine & Biology

Author Keywords
Apoptosis;  Effective scatterer size;  Newborn brain;  Quantitative ultrasound;  Sevoflurane;  Thalamus

Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Access Type: Open Access

Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits
(2020) Nature Neuroscience, . 

Zhou, H.^{a b} , Sealock, J.M.^{c d} , Sanchez-Roige, S.^e , Clarke, T.-K.^f , Levey, D.F.^{a b} , Cheng, Z.^{a b} , Li, B.^g , Polimanti, R.^{a b} , Kember, R.L.^{h i} , Smith, R.V.^j , Thygesen, J.H.^k , Morgan, M.Y.^l , Atkinson, S.R.^m , Thursz, M.R.^m , Nyegaard, M.^{n o p q} , Mattheisen, M.^{n r s} , Børglum, A.D.^{n o p q} , Johnson, E.C.^{t u} , Justice, A.C.^{b u v} , Palmer, A.A.^{e w} , McQuillin, A.^k , Davis, L.K.^{c d x} , Edenberg, H.J.^{y z} , Agrawal, A.^t , Kranzler, H.R.^{i aa} , Gelernter, J.^{a b ab}

^a Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
^b Veterans Affairs Connecticut Healthcare System, West Haven, CT, United States
^c Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
^d Division of Medical Genetics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
^e Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
^f Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
^g Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States
^h Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
ⁱ Crescenz Veterans Affairs Medical Center, Philadelphia, PA, United States
^j University of Louisville School of Nursing, Louisville, KY, United States
^k Division of Psychiatry, University College London, London, United Kingdom
^l UCL Institute for Liver & Digestive Health, Division of Medicine, Royal Free Campus, University College London, London, United Kingdom
^m Department of Metabolism Digestion & Reproduction, Imperial College London, London, United Kingdom
ⁿ Department of Biomedicine, Aarhus University, Aarhus, Denmark
^o Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark
^p The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
^q Center for Genomics and Personalized Medicine, Aarhus, Denmark
^r Department of Psychiatry, Psychosomatics and Psychotherapy, University of Würzburg, Würzburg, Germany
^s Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
^t Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^u Department of Internal Medicine, Yale School of Medicine, New Haven, CT, United States
^v Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, United States
^w Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, United States
^x Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
^y Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, United States
^z Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
^aa Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
^ab Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, United States

Abstract
Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits. © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Automatic detection of contrast enhancement in T1-weighted brain MRI of human adults
(2020) Progress in Biomedical Optics and Imaging – Proceedings of SPIE, 11314, art. no. 113140F, . 

Milchenko, M., Lamontagne, P., Marcus, D.

Computational Imaging Lab, Mallinckrodt Institute of Radiology, Washington University in St Louis, School of Medicine, 4525 Scott Ave, St Louis, MO 63110, United States

Abstract
Retrospective neuro-oncology imaging research relies on standardization of large, heterogeneous sets of clinical images. In particular, many tumor segmentation algorithms require pre- and post- Gadolinium (Gd) T1-weighted MRI scans. Since the presence of contrast agent cannot be reliably inferred from image metadata, we propose an automatic imagebased classifier for this purpose. We proceed with aligning a T1-weighted MR image to a standard atlas space, by selecting one of eight affine transforms produced using different registration parameters and atlases. After resampling to the standard space, we normalize the intensity distribution and compute intensity characteristics inside a pre-built binary mask of likely enhancement. Using a labeled set of 1892 scans, we evaluated logistic regressions with mean, standard deviation, and 95th percentile as possible factors. A univariable logistic regression with standard deviation as factor was most accurate at 98.9% on testing data. The slope coefficient was highly robust with p<1e-6 and Cramer-Rao bound on variance of 1%. The resulting classification script is completely unsupervised. Accuracy on two validation datasets from different sources (totaling 1328 scans) was over 99% on scans with isotropic sampling. Accuracy was lower on highly anisotropic or otherwise lower quality scans. To our knowledge, this is the first attempt to build an automated Gd enhancement classifier for big data applications. We plan to integrate it into XNAT platform for automatic labeling, to enable Gd enhanced image search. The proposed detector performed well on a wide variety of acquisition parameters. Image anisotropy and acquisition artifacts may interfere with accurate detection. © 2020 SPIE.

Author Keywords
automatic labeling;  contrast detetection;  neuro-oncology mri;  spatial normalization

Document Type: Conference Paper
Publication Stage: Final
Source: Scopus

Changes in self-reported and observed parenting following a randomized control trial of parent–child interaction therapy for the treatment of preschool depression
(2020) Journal of Child Psychology and Psychiatry and Allied Disciplines, . 

Whalen, D.J., Gilbert, K.E., Luby, J.L.

Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, United States

Abstract
Background: Parenting in early childhood exerts substantial influence over children’s emotional health and development. Using data from a randomized controlled trial of a novel treatment for early childhood depression, Parent–Child Interaction Therapy Emotion Development (PCIT-ED), we explored two broad dimensions of parenting (behavior and affect) to determine whether any changes could be detected following treatment when compared to those in a waitlist control condition. Method: 229 caregiver–child dyads, 114 randomly assigned to PCIT-ED for preschool-onset depression, and 115 assigned to a waitlist completed two structured interaction tasks at baseline and post-treatment. Interactions were later coded by observer’s blind to diagnostic and treatment status. Results: Greater reductions were found in self-reported negative parenting behaviors and observed negative affect and greater increases in self-reported positive parenting behaviors and observed positive affect among the caregivers in the treatment group. Increases in the overall positivity of the observed interactional style of caregivers, but no observed parenting behavior change was found following treatment. Discrepancies between self-reported and observed parenting were greater among caregivers on the waitlist. Conclusions: Following PCIT-ED treatment, caregivers self-reported improvements in parenting practices and declines in punitive practices along with observed increases in positive affect and decreases in negative affect when interacting with their child. Moreover, coherence between self-reported and observed parenting was higher in the treatment group. These findings highlight the efficacy of PCIT-ED in improving parenting behaviors and the need to use multiple methods to assess parenting in treatment studies. © 2020 Association for Child and Adolescent Mental Health

Author Keywords
observational;  Parenting practices;  parent–child interaction;  parent–child interaction therapy;  preschool depression

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Ensemble perception without attention depends upon attentional control settings
(2020) Attention, Perception, and Psychophysics, . 

Chen, Z.^a , Zhuang, R.^a , Wang, X.^a , Ren, Y.^a , Abrams, R.A.^b

^a School of Psychology, Shandong Normal University, No. 1 Daxue Road, Changqing District, Jinan, 250358, China
^b Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, WA, United States

Abstract
People are able to rapidly extract summary statistical information about common patterns, or ensembles, that may exist in a scene, such as repeated textures or colors. Here we examined the extent to which such an ensemble perception can occur in the absence of focal visual attention using a method that has some advantages over methods previously used to study the issue. In particular, we assessed the extent to which ensembles can be processed without attention by measuring the indirect effect of a to-be-ignored ensemble on judgments of an attended ensemble. The results show that ensembles outside the focus of attention do influence judgments of attended ensembles when the to-be-ignored ensemble contains summary statistics that match a sought-for target category. Thus, an attentional control setting for specific summary statistical information permits the processing of ensembles outside of focal attention, facilitating the rapid perception of visual scenes. © 2020, The Psychonomic Society, Inc.

Author Keywords
Attentional control settings;  Ensemble perception;  Unattended processing;  Visual attention

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Comparison of anticoagulation and antiplatelet therapy for treatment of blunt cerebrovascular injury in children <10 years of age: a multicenter retrospective cohort study
(2020) Child’s Nervous System, . 

Ravindra, V.M.^{a b} , Bollo, R.J.^{a b} , Dewan, M.C.^{c d} , Riva-Cambrin, J.K.^e , Tonetti, D.^f , Awad, A.-W.^{a b} , Akbari, S.H.^{g h} , Gannon, S.^{c d} , Shannon, C.^{c d} , Birkas, Y.^{a b} , Limbrick, D.^{g h} , Jea, A.^{i j} , Naftel, R.P.^{c d} , Kestle, J.R.^{a b} , Grandhi, R.^{a b}

^a Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, 175 N. Medical Drive East, Salt Lake City, UT 84132, United States
^b Division of Pediatric Neurosurgery, Primary Children’s Hospital, Salt Lake City, UT, United States
^c Department of Neurosurgery, Vanderbilt University, Nashville, TN, United States
^d Division of Pediatric Neurosurgery, Monroe Carell Jr. Children’s Hospital at Vanderbilt, Nashville, TN, United States
^e Department of Clinical Neurosciences, Division of Pediatric Neurosurgery, University of Calgary, Calgary, AB, Canada
^f Department of Neurosurgery, Division of Pediatric Neurosurgery, University of Pittsburgh, Pittsburgh, PA, United States
^g Department of Neurosurgery, Washington University in St. Louis, St. Louis, MO, United States
^h Division of Pediatric Neurosurgery, St. Louis Children’s Hospital, St. Louis, MO, United States
ⁱ Department of Neurosurgery, Indiana University, Bloomington, IN, United States
^j Division of Pediatric Neurosurgery, Riley Children’s Hospital, Indianapolis, IN, United States

Abstract
Purpose: Blunt cerebrovascular injury (BCVI) is uncommon in the pediatric population. Among the management options is medical management consisting of antithrombotic therapy with either antiplatelets or anticoagulation. There is no consensus on whether administration of antiplatelets or anticoagulation is more appropriate for BCVI in children < 10 years of age. Our goal was to compare radiographic and clinical outcomes based on medical treatment modality for BCVI in children < 10 years. Methods: Clinical and radiographic data were collected retrospectively for children screened for BCVI with computed tomography angiography at 5 academic pediatric trauma centers. Results: Among 651 patients evaluated with computed tomography angiography to screen for BCVI, 17 patients aged less than 10 years were diagnosed with BCVI (7 grade I, 5 grade II, 1 grade III, 4 grade IV) and received anticoagulation or antiplatelet therapy for 18 total injuries: 11 intracranial carotid artery, 4 extracranial carotid artery, and 3 extracranial vertebral artery injuries. Eleven patients were treated with antiplatelets (10 aspirin, 1 clopidogrel) and 6 with anticoagulation (4 unfractionated heparin, 2 low-molecular-weight heparin, 1 transitioned from the former to the latter). There were no complications secondary to treatment. One patient who received anticoagulation died as a result of the traumatic injuries. In aggregate, children treated with antiplatelet therapy demonstrated healing on 52% of follow-up imaging studies versus 25% in the anticoagulation cohort. Conclusion: There were no observed differences in the rate of hemorrhagic complications between anticoagulation and antiplatelet therapy for BCVI in children < 10 years, with a nonsignificantly better rate of healing on follow-up imaging in children who underwent antiplatelet therapy; however, the study cohort was small despite including patients from 5 hospitals. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Author Keywords
Anticoagulation;  Antiplatelet;  Blunt;  Cerebrovascular;  Injury;  Pediatrics;  Trauma

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

A genome-wide association study of interhemispheric theta EEG coherence: implications for neural connectivity and alcohol use behavior
(2020) Molecular Psychiatry, . 

Meyers, J.L.^a , Zhang, J.^a , Chorlian, D.B.^a , Pandey, A.K.^a , Kamarajan, C.^a , Wang, J.-C.^{b c} , Wetherill, L.^d , Lai, D.^d , Chao, M.^b , Chan, G.^e , Kinreich, S.^a , Kapoor, M.^{b c} , Bertelsen, S.^{b c} , McClintick, J.^{d f} , Bauer, L.^e , Hesselbrock, V.^e , Kuperman, S.^g , Kramer, J.^g , Salvatore, J.E.^h , Dick, D.M.^h , Agrawal, A.ⁱ , Foroud, T.^d , Edenberg, H.J.^{d f} , Goate, A.^{b c j} , Porjesz, B.^a

^a Department of Psychiatry and the Henri Begleiter Neurodynamics Laboratory, State University of New York Downstate Medical Center, Brooklyn, NY 11203, United States
^b Departments of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
^c Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
^d Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, United States
^e Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT 06030, United States
^f Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN 46202, United States
^g Department of Psychiatry, Roy J and Lucille A Carver College of Medicine, University of Iowa, Iowa City, IA 52242, United States
^h Department of Psychology and the Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA 23284, United States
ⁱ Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
^j Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States

Abstract
Aberrant connectivity of large-scale brain networks has been observed among individuals with alcohol use disorders (AUDs) as well as in those at risk, suggesting deficits in neural communication between brain regions in the liability to develop AUD. Electroencephalographical (EEG) coherence, which measures the degree of synchrony between brain regions, may be a useful measure of connectivity patterns in neural networks for studying the genetics of AUD. In 8810 individuals (6644 of European and 2166 of African ancestry) from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a Multi-Trait Analyses of genome-wide association studies (MTAG) on parietal resting-state theta (3–7 Hz) EEG coherence, which previously have been associated with AUD. We also examined developmental effects of GWAS findings on trajectories of neural connectivity in a longitudinal subsample of 2316 adolescent/young adult offspring from COGA families (ages 12–30) and examined the functional and clinical significance of GWAS variants. Six correlated single nucleotide polymorphisms located in a brain-expressed lincRNA (ENSG00000266213) on chromosome 18q23 were associated with posterior interhemispheric low theta EEG coherence (3–5 Hz). These same variants were also associated with alcohol use behavior and posterior corpus callosum volume, both in a subset of COGA and in the UK Biobank. Analyses in the subsample of COGA offspring indicated that the association of rs12954372 with low theta EEG coherence occurred only in females, most prominently between ages 25 and 30 (p &lt; 2 × 10-9). Converging data provide support for the role of genetic variants on chromosome 18q23 in regulating neural connectivity and alcohol use behavior, potentially via dysregulated myelination. While findings were less robust, genome-wide associations were also observed with rs151174000 and parieto-frontal low theta coherence, rs14429078 and parieto-occipital interhemispheric high theta coherence, and rs116445911 with centro-parietal low theta coherence. These novel genetic findings highlight the utility of the endophenotype approach in enhancing our understanding of mechanisms underlying addiction susceptibility. © 2020, The Author(s), under exclusive licence to Springer Nature Limited.

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Synthesis and Characterization of Azido Aryl Analogs of IBNtxA for Radio-Photoaffinity Labeling Opioid Receptors in Cell Lines and in Mouse Brain
(2020) Cellular and Molecular Neurobiology, . 

Grinnell, S.G.^{b c} , Uprety, R.^b , Varadi, A.^{b c} , Subrath, J.^b , Hunkele, A.^b , Pan, Y.X.^{a b} , Pasternak, G.W.^{a b c d} , Majumdar, S.^e

^a Department of Neurology, Memorial Sloan-Kettering Cancer Center, New York, NY, United States
^b Molecular Pharmacology and Chemistry Program, Memorial Sloan-Kettering Cancer Center, New York, NY, United States
^c Neuroscience Graduate Program, Weill Cornell Graduate School of Medical Sciences, New York, NY, United States
^d Pharmacology Graduate Program, Weill Cornell Graduate School of Medical Sciences, New York, NY, United States
^e Center for Clinical Pharmacology, St Louis College of Pharmacy and Washington University School of Medicine, St Louis, MO, United States

Abstract
Mu opioid receptors (MOR-1) mediate the biological actions of clinically used opioids such as morphine, oxycodone, and fentanyl. The mu opioid receptor gene, OPRM1, undergoes extensive alternative splicing, generating multiple splice variants. One type of splice variants are truncated variants containing only six transmembrane domains (6TM) that mediate the analgesic action of novel opioid drugs such as 3′-iodobenzoylnaltrexamide (IBNtxA). Previously, we have shown that IBNtxA is a potent analgesic effective in a spectrum of pain models but lacks many side-effects associated with traditional opiates. In order to investigate the targets labeled by IBNtxA, we synthesized two arylazido analogs of IBNtxA that allow photolabeling of mouse mu opioid receptors (mMOR-1) in transfected cell lines and mMOR-1 protein complexes that may comprise the 6TM sites in mouse brain. We demonstrate that both allyl and alkyne arylazido derivatives of IBNtxA efficiently radio-photolabeled mMOR-1 in cell lines and MOR-1 protein complexes expressed either exogenously or endogenously, as well as found in mouse brain. In future, design and application of such radio-photolabeling ligands with a conjugated handle will provide useful tools for further isolating or purifying MOR-1 to investigate site specific ligand–protein contacts and its signaling complexes. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Author Keywords
Click;  IBNtxA;  Mu opioid receptor complex;  Opioid;  Photoaffinity labeling;  Radioligand binding

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Drug Dosing in Patients Undergoing Therapeutic Plasma Exchange
(2020) Neurocritical Care, . 

Mahmoud, S.H.^a , Buhler, J.^a , Chu, E.^a , Chen, S.A.^b , Human, T.^{b c}

^a Faculty of Pharmacy and Pharmaceutical Sciences, 3–142H, Katz Group Centre for Pharmacy and Health Research, University of Alberta, Edmonton, AB T6G 2E1, Canada
^b Barnes-Jewish Hospital, St. Louis, MO, United States
^c Washington University, St Louis, MO, United States

Abstract
Therapeutic plasma exchange (TPE) is an extracorporeal process in which a large volume of whole blood is taken from the patient’s vein. Plasma is then separated from the other cellular components of the blood and discarded while the remaining blood components may then be returned to the patient. Replacement fluids such as albumin or fresh-frozen plasma may or may not be used. TPE has been used clinically for the removal of pathologic targets in the plasma in a variety of conditions, such as pathogenic antibodies in autoimmune disorders. TPE is becoming more common in the neurointensive care space as autoimmunity has been shown to play an etiological role in many acute neurological disorders. It is important to note that not only does TPE removes pathologic elements from the plasma, but may also remove drugs, which may be an intended or unintended consequence. The objective of the current review is to provide an up-to-date summary of the available evidence pertaining to drug removal via TPE and provide relevant clinical suggestions where applicable. This review also aims to provide an easy-to-follow clinical tool in order to determine the possibility of a drug removal via TPE given the procedure-specific and pharmacokinetic drug properties. © 2020, Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.

Author Keywords
Apheresis;  Drug removal;  Plasmapheresis;  TPE plasma exchange

Document Type: Review
Publication Stage: Article in Press
Source: Scopus

Safety, Tolerability, and Efficacy of Viltolarsen in Boys with Duchenne Muscular Dystrophy Amenable to Exon 53 Skipping: A Phase 2 Randomized Clinical Trial
(2020) JAMA Neurology, . 

Clemens, P.R.^{a b} , Rao, V.K.^c , Connolly, A.M.^d , Harper, A.D.^e , Mah, J.K.^f , Smith, E.C.^g , McDonald, C.M.^h , Zaidman, C.M.ⁱ , Morgenroth, L.P.^j , Osaki, H.^k , Satou, Y.^k , Yamashita, T.^k , Hoffman, E.P.^{l m}

^a Department of Neurology, University of Pittsburgh School of Medicine, 3550 Terrace St, Pittsburgh, PA 15261, United States
^b Department of Veterans Affairs Medical Center, Pittsburgh, PA, United States
^c Division of Neurology, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, United States
^d Division of Neurology, Nationwide Children’s Hospital, Ohio State University College of Medicine, Columbus, United States
^e Children’s Hospital of Richmond, Virginia Commonwealth University, Richmond, United States
^f Department of Pediatrics, University of Calgary, Calgary, AB, Canada
^g Division of Pediatric Neurology, Duke University Medical Center, Durham, NC, United States
^h Department of Physical Medicine and Rehabilitation, Department of Pediatrics, UC Davis Health, University of California, Davis, Sacramento, United States
ⁱ Department of Neurology, Washington University at St Louis, St Louis, MO, United States
^j Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
^k NS Pharma, Paramus, NJ, United States
^l AGADA BioSciences, Dalhousie University, Halifax, NS, Canada
^m Department of Pharmaceutical Sciences, State University of New York at Binghamton, United States

Abstract
Importance: An unmet need remains for safe and efficacious treatments for Duchenne muscular dystrophy (DMD). To date, there are limited agents available that address the underlying cause of the disease. Objective: To evaluate the safety, tolerability, and efficacy of viltolarsen, a novel antisense oligonucleotide, in participants with DMD amenable to exon 53 skipping. Design, Setting, and Participants: This phase 2 study was a 4-week randomized clinical trial for safety followed by a 20-week open-label treatment period of patients aged 4 to 9 years with DMD amenable to exon 53 skipping. To enroll 16 participants, with 8 participants in each of the 2 dose cohorts, 17 participants were screened. Study enrollment occurred between December 16, 2016, and August 17, 2017, at sites in the US and Canada. Data were collected from December 2016 to February 2018, and data were analyzed from April 2018 to May 2019. Interventions: Participants received 40 mg/kg (low dose) or 80 mg/kg (high dose) of viltolarsen administered by weekly intravenous infusion. Main Outcomes and Measures: Primary outcomes of the trial included safety, tolerability, and de novo dystrophin protein production measured by Western blot in participants’ biceps muscles. Secondary outcomes included additional assessments of dystrophin mRNA and protein production as well as clinical muscle strength and function. Results: Of the 16 included boys with DMD, 15 (94%) were white, and the mean (SD) age was 7.4 (1.8) years. After 20 to 24 weeks of treatment, significant drug-induced dystrophin production was seen in both viltolarsen dose cohorts (40 mg/kg per week: mean [range] 5.7% [3.2-10.3] of normal; 80 mg/kg per week: mean [range] 5.9% [1.1-14.4] of normal). Viltolarsen was well tolerated; no treatment-emergent adverse events required dose reduction, interruption, or discontinuation of the study drug. No serious adverse events or deaths occurred during the study. Compared with 65 age-matched and treatment-matched natural history controls, all 16 participants treated with viltolarsen showed significant improvements in timed function tests from baseline, including time to stand from supine (viltolarsen:-0.19 s; control: 0.66 s), time to run/walk 10 m (viltolarsen: 0.23 m/s; control:-0.04 m/s), and 6-minute walk test (viltolarsen: 28.9 m; control:-65.3 m) at the week 25 visit. Conclusions and Relevance: Systemic treatment of participants with DMD with viltolarsen induced de novo dystrophin production, and clinical improvement of timed function tests was observed. © 2020 American Medical Association. All rights reserved.

Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Access Type: Open Access

Variability in the analysis of a single neuroimaging dataset by many teams
(2020) Nature, . 

Botvinik-Nezer, R.^{a b c} , Holzmeister, F.^d , Camerer, C.F.^e , Dreber, A.^{f g} , Huber, J.^d , Johannesson, M.^f , Kirchler, M.^d , Iwanir, R.^{a b} , Mumford, J.A.^h , Adcock, R.A.^{i j} , Avesani, P.^{k l} , Baczkowski, B.M.^m , Bajracharya, A.ⁿ , Bakst, L.^{o p} , Ball, S.^{q r} , Barilari, M.^s , Bault, N.^t , Beaton, D.^u , Beitner, J.^{v w} , Benoit, R.G.^x , Berkers, R.M.W.J.^x , Bhanji, J.P.^y , Biswal, B.B.^{z aa} , Bobadilla-Suarez, S.^ab , Bortolini, T.^ac , Bottenhorn, K.L.^ad , Bowring, A.^ae , Braem, S.^{af ag} , Brooks, H.R.^ah , Brudner, E.G.^y , Calderon, C.B.^af , Camilleri, J.A.^{ai aj} , Castrellon, J.J.^{i ak} , Cecchetti, L.^al , Cieslik, E.C.^{ai aj} , Cole, Z.J.^am , Collignon, O.^{l s} , Cox, R.W.^an , Cunningham, W.A.^ao , Czoschke, S.^ap , Dadi, K.^aq , Davis, C.P.^{ar as at} , Luca, A.D.^au , Delgado, M.R.^y , Demetriou, L.^{av aw} , Dennison, J.B.^ax , Di, X.^{z aa} , Dickie, E.W.^{ay az} , Dobryakova, E.^ba , Donnat, C.L.^bb , Dukart, J.^{ai aj} , Duncan, N.W.^{bc bd} , Durnez, J.^be , Eed, A.^bf , Eickhoff, S.B.^{ai aj} , Erhart, A.^ah , Fontanesi, L.^bg , Fricke, G.M.^bh , Fu, S.^{bi bj} , Galván, A.^bk , Gau, R.^s , Genon, S.^{ai aj} , Glatard, T.^bl , Glerean, E.^bm , Goeman, J.J.^bn , Golowin, S.A.E.^bc , González-García, C.^af , Gorgolewski, K.J.^bo , Grady, C.L.^u , Green, M.A.^{i ak} , Guassi Moreira, J.F.^bk , Guest, O.^{ab bp} , Hakimi, S.ⁱ , Hamilton, J.P.^bq , Hancock, R.^{as at} , Handjaras, G.^al , Harry, B.B.^br , Hawco, C.^bs , Herholz, P.^bt , Herman, G.^bs , Heunis, S.^{bu bv} , Hoffstaedter, F.^{ai aj} , Hogeveen, J.^{bw bx} , Holmes, S.^bb , Hu, C.-P.^by , Huettel, S.A.^ak , Hughes, M.E.^bz , Iacovella, V.^l , Iordan, A.D.^ca , Isager, P.M.^cb , Isik, A.I.^cc , Jahn, A.^cd , Johnson, M.R.^{am ce} , Johnstone, T.^bz , Joseph, M.J.E.^bs , Juliano, A.C.^cf , Kable, J.W.^{cg ch} , Kassinopoulos, M.^ci , Koba, C.^al , Kong, X.-Z.^cj , Koscik, T.R.^ck , Kucukboyaci, N.E.^{ba cl} , Kuhl, B.A.^cm , Kupek, S.^cn , Laird, A.R.^co , Lamm, C.^{cp cq} , Langner, R.^{ai aj} , Lauharatanahirun, N.^{cr cs} , Lee, H.^ct , Lee, S.^cg , Leemans, A.^au , Leo, A.^al , Lesage, E.^af , Li, F.^{cu cv} , Li, M.Y.C.^{ar as at cw} , Lim, P.C.^{am ce} , Lintz, E.N.^am , Liphardt, S.W.^cx , Losecaat Vermeer, A.B.^cp , Love, B.C.^{ab cy} , Mack, M.L.^ao , Malpica, N.^cz , Marins, T.^ac , Maumet, C.^da , McDonald, K.^ak , McGuire, J.T.^{o p} , Melero, H.^{cz db dc} , Méndez Leal, A.S.^bk , Meyer, B.^{by dd} , Meyer, K.N.^de , Mihai, G.^{df dg} , Mitsis, G.D.^dh , Moll, J.^{ac bo} , Nielson, D.M.^di , Nilsonne, G.^{dj dk} , Notter, M.P.^dl , Olivetti, E.^{k l} , Onicas, A.I.^al , Papale, P.^{al dm} , Patil, K.R.^{ai aj} , Peelle, J.E.ⁿ , Pérez, A.^bt , Pischedda, D.^{dn do dp} , Poline, J.-B.^{bt dq} , Prystauka, Y.^{ar as at} , Ray, S.^z , Reuter-Lorenz, P.A.^ca , Reynolds, R.C.^dr , Ricciardi, E.^al , Rieck, J.R.^u , Rodriguez-Thompson, A.M.^de , Romyn, A.^ao , Salo, T.^ad , Samanez-Larkin, G.R.^{i ak} , Sanz-Morales, E.^cz , Schlichting, M.L.^ao , Schultz, D.H.^{am ce} , Shen, Q.^{bi bj} , Sheridan, M.A.^de , Silvers, J.A.^bk , Skagerlund, K.^{ds dt} , Smith, A.^{q r} , Smith, D.V.^ax , Sokol-Hessner, P.^ah , Steinkamp, S.R.^du , Tashjian, S.M.^bk , Thirion, B.^aq , Thorp, J.N.^dv , Tinghög, G.^{dw dx} , Tisdall, L.^{bo dy} , Tompson, S.H.^cr , Toro-Serey, C.^{o p} , Torre Tresols, J.J.^aq , Tozzi, L.^dz , Truong, V.^{bc bd} , Turella, L.^l , van ‘t Veer, A.E.^ea , Verguts, T.^af , Vettel, J.M.^{eb ec ed} , Vijayarajah, S.^ao , Vo, K.^{i ak} , Wall, M.B.^{ee ef eg} , Weeda, W.D.^ea , Weis, S.^{ai aj} , White, D.J.^eh , Wisniewski, D.^af , Xifra-Porxas, A.^ci , Yearling, E.A.^{ar as at} , Yoon, S.^ei , Yuan, R.^dz , Yuen, K.S.L.^{by dd} , Zhang, L.^cp , Zhang, X.^{as at ej} , Zosky, J.E.^{am ce} , Nichols, T.E.^ae , Poldrack, R.A.^bo , Schonberg, T.^{a b}

^a Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
^b Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
^c Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States
^d Department of Banking and Finance, University of Innsbruck, Innsbruck, Austria
^e HSS and CNS, California Institute of Technology, Pasadena, CA, United States
^f Department of Economics, Stockholm School of Economics, Stockholm, Sweden
^g Department of Economics, University of Innsbruck, Innsbruck, Austria
^h Center for Healthy Minds, University of Wisconsin–Madison, Madison, WI, United States
ⁱ Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
^j Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
^k Neuroinformatics Laboratory, Fondazione Bruno Kessler, Trento, Italy
^l Center for Mind/Brain Sciences – CIMeC, University of Trento, Rovereto, Italy
^m Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
ⁿ Department of Otolaryngology, Washington University in St. Louis, St. Louis, MO, United States
^o Department of Psychological and Brain Sciences, Boston University, Boston, MA, United States
^p Center for Systems Neuroscience, Boston University, Boston, MA, United States
^q Department of Economics, Virginia Tech, Blacksburg, VA, United States
^r School of Neuroscience, Virginia Tech, Blacksburg, VA, United States
^s Crossmodal Perception and Plasticity Laboratory, Institutes for Research in Psychology (IPSY) and Neurosciences (IoNS), UCLouvain, Louvain-la-Neuve, Belgium
^t School of Psychology, University of Plymouth, Plymouth, United Kingdom
^u Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, ON, Canada
^v Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
^w Department of Psychology, Goethe University, Frankfurt am Main, Germany
^x Max Planck Research Group: Adaptive Memory, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
^y Department of Psychology, Rutgers University–Newark, Newark, NJ, United States
^z Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
^aa School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
^ab Department of Experimental Psychology, University College London, London, United Kingdom
^ac D’Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
^ad Department of Psychology, Florida International University, Miami, FL, United States
^ae Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
^af Department of Experimental Psychology, Ghent University, Ghent, Belgium
^ag Department of Psychology, Vrije Universiteit Brussel, Brussels, Belgium
^ah Department of Psychology, University of Denver, Denver, CO, United States
^ai Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
^aj Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
^ak Department of Psychology and Neuroscience, Duke University, Durham, NC, United States
^al MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
^am Department of Psychology, University of Nebraska–Lincoln, Lincoln, NE, United States
^an National Institute of Mental Health (NIMH), National Institutes of Health, Bethesda, MD, United States
^ao Department of Psychology, University of Toronto, Toronto, ON, Canada
^ap Institute of Medical Psychology, Goethe University, Frankfurt am Main, Germany
^aq Inria, CEA, Université Paris-Saclay, Palaiseau, France
^ar Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States
^as Brain Imaging Research Center, University of Connecticut, Storrs, CT, United States
^at Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, United States
^au PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
^av Section of Endocrinology and Investigative Medicine, Faculty of Medicine, Imperial College London, London, United Kingdom
^aw Nuffield Department of Women’s and Reproductive Health, University of Oxford, Oxford, United Kingdom
^ax Department of Psychology, Temple University, Philadelphia, PA, United States
^ay Krembil Centre for Neuroinformatics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
^az Department of Psychiatry, University of Toronto, Toronto, ON, Canada
^ba Center for Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ, United States
^bb Department of Statistics, Stanford University, Stanford, CA, United States
^bc Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
^bd Brain and Consciousness Research Centre, TMU-ShuangHo Hospital, New Taipei City, Taiwan
^be Department of Psychology and Stanford Center for Reproducible Neuroscience, Stanford University, Stanford, CA, United States
^bf Instituto de Neurociencias, CSIC-UMH, Alicante, Spain
^bg Faculty of Psychology, University of Basel, Basel, Switzerland
^bh Computer Science Department, University of New Mexico, Albuquerque, NM, United States
^bi School of Management, Zhejiang University of Technology, Hangzhou, China
^bj Institute of Neuromanagement, Zhejiang University of Technology, Hangzhou, China
^bk Department of Psychology, University of California Los Angeles, Los Angeles, CA, United States
^bl Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, Canada
^bm Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
^bn Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
^bo Department of Psychology, Stanford University, Stanford, CA, United States
^bp Research Centre on Interactive Media, Smart Systems and Emerging Technologies – RISE, Nicosia, Cyprus
^bq Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
^br The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Sydney, NSW, Australia
^bs Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
^bt McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), Faculty of Medicine, McGill University, Montreal, QC, Canada
^bu Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
^bv Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, Netherlands
^bw Department of Psychology, University of New Mexico, Albuquerque, NM, United States
^bx Psychology Clinical Neuroscience Center, University of New Mexico, Albuquerque, NM, United States
^by Leibniz-Institut für Resilienzforschung (LIR), Mainz, Germany
^bz School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC, Australia
^ca Department of Psychology, University of Michigan, Ann Arbor, MI, United States
^cb Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands
^cc Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany
^cd fMRI Laboratory, University of Michigan, Ann Arbor, MI, United States
^ce Center for Brain, Biology and Behavior, University of Nebraska–Lincoln, Lincoln, NE, United States
^cf Center for Neuropsychology and Neuroscience Research, Kessler Foundation, East Hanover, NJ, United States
^cg Department of Psychology, University of Pennsylvania, Philadelphia, PA, United States
^ch MindCORE, University of Pennsylvania, Philadelphia, PA, United States
^ci Graduate Program in Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
^cj Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
^ck Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, United States
^cl Department of Physical Medicine and Rehabilitation, Rutgers New Jersey Medical School, Newark, NJ, United States
^cm Department of Psychology, University of Oregon, Eugene, OR, United States
^cn Faculty of Economics and Statistics, University of Innsbruck, Innsbruck, Austria
^co Department of Physics, Florida International University, Miami, FL, United States
^cp Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
^cq Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria
^cr US CCDC Army Research Laboratory, Human Research and Engineering Directorate, Aberdeen Proving Ground, MD, United States
^cs Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, United States
^ct Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, United States
^cu Fralin Biomedical Research Institute, Roanoke, VA, United States
^cv Economics Experimental Lab, Nanjing Audit University, Nanjing, China
^cw Haskins Laboratories, New Haven, CT, United States
^cx Biology Department, University of New Mexico, Albuquerque, NM, United States
^cy The Alan Turing Institute, London, United Kingdom
^cz Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain
^da Inria, Univ Rennes, CNRS, Inserm, IRISA UMR 6074, Empenn ERL U 1228, Rennes, France
^db Departamento de Psicobiología, División de Psicología, CES Cardenal Cisneros, Madrid, Spain
^dc Northeastern University Biomedical Imaging Center, Northeastern University, Boston, MA, United States
^dd Neuroimaging Center (NIC), Focus Program Translational Neurosciences (FTN), Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
^de Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^df Max Planck Research Group: Neural Mechanisms of Human Communication, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
^dg Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
^dh Department of Bioengineering, McGill University, Montreal, QC, Canada
^di Data Science and Sharing Team, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
^dj Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
^dk Department of Psychology, Stockholm University, Stockholm, Sweden
^dl The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland
^dm Department of Vision and Cognition, Netherlands Institute for Neuroscience, Amsterdam, Netherlands
^dn Bernstein Center for Computational Neuroscience and Berlin Center for Advanced Neuroimaging and Clinic for Neurology, Charité Universitätsmedizin, corporate member of Freie Universität Berlin, Humboldt Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
^do Cluster of Excellence Science of Intelligence, Technische Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
^dp NeuroMI – Milan Center for Neuroscience, Milan, Italy
^dq Henry H. Wheeler, Jr. Brain Imaging Center, Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, United States
^dr Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
^ds Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden
^dt Center for Social and Affective Neuroscience, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
^du Institute of Neuroscience and Medicine, Cognitive Neuroscience (INM-3), Research Centre Jülich, Jülich, Germany
^dv Department of Psychology, Columbia University, New York, NY, United States
^dw Department of Management and Engineering, Linköping University, Linköping, Sweden
^dx Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
^dy Center for Cognitive and Decision Sciences, University of Basel, Basel, Switzerland
^dz Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
^ea Methodology and Statistics Unit, Institute of Psychology, Leiden University, Leiden, Netherlands
^eb US Combat Capabilities Development Command Army Research Laboratory, Aberdeen, MD, United States
^ec University of California Santa Barbara, Santa Barbara, CA, United States
^ed University of Pennsylvania, Philadelphia, PA, United States
^ee Invicro, London, United Kingdom
^ef Faculty of Medicine, Imperial College London, London, United Kingdom
^eg Clinical Psychopharmacology Unit, University College London, London, United Kingdom
^eh Centre for Human Psychopharmacology, Swinburne University, Hawthorn, VIC, Australia
^ei Department of Management and Marketing, School of Business, University of Dayton, Dayton, OH, United States
^ej Biomedical Engineering Department, University of Connecticut, Storrs, CT, United States

Abstract
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2–5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed. © 2020, The Author(s), under exclusive licence to Springer Nature Limited.

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Increased Cerebrospinal Fluid Amyloid-β during Sleep Deprivation in Healthy Middle-Aged Adults Is Not Due to Stress or Circadian Disruption
(2020) Journal of Alzheimer’s Disease, 75 (2), pp. 471-482. 

Blattner, M.S.^a , Panigrahi, S.K.^b , Toedebusch, C.D.^a , Hicks, T.J.^a , McLeland, J.S.^a , Banks, I.R.^a , Schaibley, C.^a , Ovod, V.^a , Mawuenyega, K.G.^a , Bateman, R.J.^{a c d} , Wardlaw, S.L.^b , Lucey, B.P.^{a c} , Naismith, S.^e

^a Department of Neurology, Washington University School of Medicine, St Louis, MO, United States
^b Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, United States
^c Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, United States
^d Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, United States

Abstract
Background: Concentrations of soluble amyloid-β (Aβ) oscillate with the sleep-wake cycle in the interstitial fluid of mice and cerebrospinal fluid (CSF) of humans. Further, the concentration of Aβ in CSF increases during sleep deprivation. Stress and disruption of the circadian clock are additional mechanisms hypothesized to increase CSF Aβ levels. Cortisol is a marker for stress and has an endogenous circadian rhythm. Other factors such as glucose and lactate have been associated with changes in sleep-wake activity and/or Aβ. Objective: In this exploratory study, we used samples collected in a previous study to examine how sleep deprivation affects Aβ, cortisol, lactate, and glucose in plasma and CSF from healthy middle-Aged adults (N=11). Methods: Eleven cognitively normal participants without evidence of sleep disturbance were randomized to sleep deprivation or normal sleep control. All participants were invited to repeat the study. Cortisol, lactate, glucose, and Aβ were measured in 2-h intervals over a 36-h period in both plasma and CSF. All concentrations were normalized to the mean prior to calculating mesor, amplitude, acrophase, and other parameters. Results: One night of sleep deprivation increases the overnight concentration of Aβ in CSF approximately 10%, but does not significantly affect cortisol, lactate, or glucose concentrations in plasma or CSF between the sleep-deprived and control conditions. Conclusion: These data suggest that sleep deprivation-related changes in CSF Aβ are not mediated by stress or circadian disruption as measured by cortisol. © 2020-IOS Press and the authors. All rights reserved.

Author Keywords
Amyloid-β;  cortisol;  sleep deprivation

Document Type: Article
Publication Stage: Final
Source: Scopus