WashU weekly Neuroscience publications

VCP suppresses proteopathic seeding in neurons
(2022) Molecular Neurodegeneration, 17 (1), art. no. 30, . 

Zhu, J.^a , Pittman, S.^a , Dhavale, D.^a , French, R.^b , Patterson, J.N.^a , Kaleelurrrahuman, M.S.^a , Sun, Y.^c , Vaquer-Alicea, J.^d , Maggiore, G.^d , Clemen, C.S.^e f , Buscher, W.J.^g , Bieschke, J.^c , Kotzbauer, P.^a , Ayala, Y.^b , Diamond, M.I.^d , Davis, A.A.^a , Weihl, C.^a

^a Department of Neurology, Hope Center for Neurological Diseases, Washington University School of Medicine, St Louis, MO 63110, United States
^b Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, St. Louis, MO, United States
^c Medical Research Council Prion Unit / UCL Institute of Prion Diseases, University College London, London, United Kingdom
^d Center for Alzheimer’s and Neurodegenerative Diseases, Peter O’ Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, United States
^e Institute of Aerospace Medicine, German Aerospace Center, Cologne, Germany
^f Center for Physiology and Pathophysiology, Institute of Vegetative Physiology, Medical Faculty, University of Cologne, Cologne, Germany
^g Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Background: Neuronal uptake and subsequent spread of proteopathic seeds, such as αS (alpha-synuclein), Tau, and TDP-43, contribute to neurodegeneration. The cellular machinery participating in this process is poorly understood. One proteinopathy called multisystem proteinopathy (MSP) is associated with dominant mutations in Valosin Containing Protein (VCP). MSP patients have muscle and neuronal degeneration characterized by aggregate pathology that can include αS, Tau and TDP-43. Methods: We performed a fluorescent cell sorting based genome-wide CRISPR-Cas9 screen in αS biosensors. αS and TDP-43 seeding activity under varied conditions was assessed using FRET/Flow biosensor cells or immunofluorescence for phosphorylated αS or TDP-43 in primary cultured neurons. We analyzed in vivo seeding activity by immunostaining for phosphorylated αS following intrastriatal injection of αS seeds in control or VCP disease mutation carrying mice. Results: One hundred fifty-four genes were identified as suppressors of αS seeding. One suppressor, VCP when chemically or genetically inhibited increased αS seeding in cells and neurons. This was not due to an increase in αS uptake or αS protein levels. MSP-VCP mutation expression increased αS seeding in cells and neurons. Intrastriatal injection of αS preformed fibrils (PFF) into VCP-MSP mutation carrying mice increased phospho αS expression as compared to control mice. Cells stably expressing fluorescently tagged TDP-43 C-terminal fragment FRET pairs (TDP-43 biosensors) generate FRET when seeded with TDP-43 PFF but not monomeric TDP-43. VCP inhibition or MSP-VCP mutant expression increases TDP-43 seeding in TDP-43 biosensors. Similarly, treatment of neurons with TDP-43 PFFs generates high molecular weight insoluble phosphorylated TDP-43 after 5 days. This TDP-43 seed dependent increase in phosphorlyated TDP-43 is further augmented in MSP-VCP mutant expressing neurons. Conclusion: Using an unbiased screen, we identified the multifunctional AAA ATPase VCP as a suppressor of αS and TDP-43 aggregate seeding in cells and neurons. VCP facilitates the clearance of damaged lysosomes via lysophagy. We propose that VCP’s surveillance of permeabilized endosomes may protect against the proteopathic spread of pathogenic protein aggregates. The spread of distinct aggregate species may dictate the pleiotropic phenotypes and pathologies in VCP associated MSP. © 2022, The Author(s).

Author Keywords
Alpha-synuclein;  CRISPR screen;  Frontotemporal dementia;  Seeding;  TDP-43

Funding details
Universität Duisburg-EssenUDE

Post-stroke reorganization of transient brain activity characterizes deficits and recovery of cognitive functions
(2022) NeuroImage, 255, art. no. 119201, . 

Pirondini, E.^{a b c d e} , Kinany, N.^a b f , Sueur, C.L.^b , Griffis, J.C.^g , Shulman, G.L.^g , Corbetta, M.^{g h i j k l} , Ville, D.V.D.^a b

^a Department of Radiology and Medical Informatics, University of Geneva, Geneva, 1211, Switzerland
^b Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, 1202, Switzerland
^c Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, United States
^d Rehabilitation Neural Engineering Laboratories, University of Pittsburgh, Pittsburgh, United States
^e Department of BioEngineering, University of Pittsburgh, Pittsburgh, United States
^f Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, Institute of Bioengineerin, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, 1202, Switzerland
^g Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
^h Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
ⁱ Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110, United States
^j Department of Bioengineering, Washington University School of Medicine, St. Louis, MO 63110, United States
^k Department of Neuroscience and Padua Neuroscience Center, University of Padua, Padua, Italy
^l Venetian Institute of Molecular Medicine (VIMM), Padua, Italy

Abstract
Functional magnetic resonance imaging (fMRI) has been widely employed to study stroke pathophysiology. In particular, analyses of fMRI signals at rest were directed at quantifying the impact of stroke on spatial features of brain networks. However, brain networks have intrinsic time features that were, so far, disregarded in these analyses. In consequence, standard fMRI analysis failed to capture temporal imbalance resulting from stroke lesions, hence restricting their ability to reveal the interdependent pathological changes in structural and temporal network features following stroke. Here, we longitudinally analyzed hemodynamic-informed transient activity in a large cohort of stroke patients (n = 103) to assess spatial and temporal changes of brain networks after stroke. Metrics extracted from the hemodynamic-informed transient activity were replicable within- and between-individuals in healthy participants, hence supporting their robustness and their clinical applicability. While large-scale spatial patterns of brain networks were preserved after stroke, their durations were altered, with stroke subjects exhibiting a varied pattern of longer and shorter network activations compared to healthy individuals. Specifically, patients showed a longer duration in the lateral precentral gyrus and anterior cingulum, and a shorter duration in the occipital lobe and in the cerebellum. These temporal alterations were associated with white matter damage in projection and association pathways. Furthermore, they were tied to deficits in specific behavioral domains as restoration of healthy brain dynamics paralleled recovery of cognitive functions (attention, language and spatial memory), but was not significantly correlated to motor recovery. These findings underscore the critical importance of network temporal properties in dissecting the pathophysiology of brain changes after stroke, thus shedding new light on the clinical potential of time-resolved methods for fMRI analysis. © 2022

Author Keywords
Dynamic functional connectivity;  fMRI;  Stroke;  Test-retest reliability

Cross-trial prediction of depression remission using problem-solving therapy: A machine learning approach
(2022) Journal of Affective Disorders, 308, pp. 89-97. 

Kannampallil, T.^a b c , Dai, R.^c , Lv, N.^d , Xiao, L.^e , Lu, C.^c , Ajilore, O.A.^f , Snowden, M.B.^g , Venditti, E.M.^h , Williams, L.M.ⁱ , Kringle, E.A.^d , Ma, J.^d

^a Department of Anesthesiology, Washington University in Saint Louis, United States
^b Institute for Informatics, School of Medicine, Washington University in Saint Louis, United States
^c Deparment of Computer Science and Engineering, McKelvey School of Engineering, Washington University in Saint Louis, United States
^d Department of Medicine, University of Illinois at Chicago, United States
^e Department of Epidemiology and Population Health, Stanford University, United States
^f Department of Psychiatry, University of Illinois at Chicago, United States
^g Department of Psychiatry and Behavioral Sciences, University of Washington, United States
^h Department of Psychiatry, University of Pittsburgh, United States
ⁱ Department of Psychiatry and Behavioral Sciences, Stanford University, United States

Abstract
Background: Psychotherapy is a standard depression treatment; however, determining a patient’s prognosis with therapy relies on clinical judgment that is subject to trial-and-error and provider variability. Purpose: To develop machine learning (ML) algorithms to predict depression remission for patients undergoing 6 months of problem-solving therapy (PST). Method: Using data from the treatment arm of 2 randomized trials, ML models were trained and validated on ENGAGE-2 (ClinicalTrials.gov, #NCT03841682) and tested on RAINBOW (ClinicalTrials.gov, #NCT02246413) for predictions at baseline and at 2-months. Primary outcome was depression remission using the Depression Symptom Checklist (SCL-20) score < 0.5 at 6 months. Predictor variables included baseline characteristics (sociodemographic, behavioral, clinical, psychosocial) and intervention engagement through 2-months. Results: Of the 26 candidate variables, 8 for baseline and 11 for 2-months were predictive of depression remission, and used to train the models. The best-performing model predicted remission with an accuracy significantly greater than chance in internal validation using the ENGAGE-2 cohort, at baseline [72.6% (SD = 3.6%), p < 0.0001] and at 2-months [72.3% (5.1%), p < 0.0001], and in external validation with the RAINBOW cohort at baseline [58.3% (0%), p < 0.0001] and at 2-months [62.3% (0%), p < 0.0001]. Model-agnostic explanations highlighted key predictors of depression remission at the cohort and patient levels, including female sex, lower self-reported sleep disturbance, lower sleep-related impairment, and lower negative problem orientation. Conclusions: ML models using clinical and patient-reported data can predict depression remission for patients undergoing PST, affording opportunities for prospective identification of likely responders, and for developing personalized early treatment optimization along the patient care trajectory. © 2022 Elsevier B.V.

Author Keywords
Clinical trials;  Machine learning;  Precision medicine;  Prediction models;  Problem-solving therapy

Funding details
National Heart, Lung, and Blood InstituteNHLBIR01HL119453, UH2HL132368

Ethnic/Racial Disparities in Longitudinal Neurocognitive Decline in People With HIV
(2022) Journal of Acquired Immune DeficiencySsyndromes (1999), 90 (1), pp. 97-105. 

Wei-Ming Watson, C.^a , Kamalyan, L.^a , Tang, B.^a , Hussain, M.A.^a , Cherner, M.^a , Rivera Mindt, M.^b c , Byrd, D.A.^c d , Franklin, D.R.^a , Collier, A.C.^e , Clifford, D.B.^f , Gelman, B.^g , Morgello, S.^h , McCutchan, J.A.^a , Ellis, R.J.^a , Grant, I.^a , Heaton, R.K.^a , Marquine, M.J.ⁱ , CHARTER Group^j

^a Department of Psychiatry, University of California, San Diego, San Diego, CA
^b Department of Psychology, Latin American Latina/o Studies Institute, Department of African and African American Studies, Fordham University, NY, NY
^c Department of Neurology, Icahn School of Medicine at Mount Sinai, NY, NY
^d Department of Psychology, Queens College, CUNY
^e Department of Medicine, University of Washington School of Medicine, Seattle, WA
^f Department of Neurology, Washington University School of Medicine, St. Louis, MO
^g Department of Pathology, University of Texas Medical Branch, TX, Galveston, United States
^h Departments of Neurology, Neuroscience and Pathology, Icahn School of Medicine at Mount Sinai, New York, NY; and
ⁱ Department of Medicine, Department of Psychiatry, University of California San Diego, San Diego, CA

Abstract
BACKGROUND: To examine longitudinal neurocognitive decline among Latino, non-Latino Black, and non-Latino White people with HIV (PWH) and factors that may explain ethnic/racial disparities in neurocognitive decline. METHODS: Four hundred ninety nine PWH (13.8% Latino, 42.7% Black, 43.5% White; baseline age: M = 43.5) from the CNS HIV Anti-Retroviral Therapy Effects Research (CHARTER) study completed neurocognitive, neuromedical, and laboratory assessments every 6-12 months with up to 5 years of follow-up. Longitudinal neurocognitive change was determined via published regression-based norms. Survival analyses investigated the relationship between ethnicity/race and neurocognitive change, and baseline and time-dependent variables that may explain ethnic/racial disparities in neurocognitive decline, including socio-demographic, HIV-disease, medical, psychiatric, and substance use characteristics. RESULTS: In Cox proportional hazard models, hazard ratios for neurocognitive decline were increased for Latino compared with White PWH (HR = 2.25, 95% CI = 1.35 to 3.73, P = 0.002), and Latino compared with Black PWH (HR = 1.86, 95% CI = 1.14 to 3.04, P = 0.013), with no significant differences between Black and White PWH (P = 0.40). Comorbidities, including cardiometabolic factors and more severe neurocognitive comorbidity classification, accounted for 33.6% of the excess hazard for Latino compared with White PWH, decreasing the hazard ratio associated with Latino ethnicity (HR = 1.83, 95% CI = 1.06 to 3.16, P = 0.03), but did not fully account for elevated risk of decline. CONCLUSIONS: Latino PWH may be at higher risk of early neurocognitive decline compared with Black and White PWH. Comorbidities accounted for some, but not all, of this increased risk among Latino PWH. Future research examining institutional, sociocultural, and biomedical factors, including structural discrimination and age-related biomarkers, may further explain the observed disparities. Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.

Effects of Framingham 10-Year Cardiovascular Risk Score and Viral Load on Brain Integrity in Persons With HIV
(2022) Journal of Acquired Immune Deficiency Syndromes (1999), 90 (1), pp. 79-87. 

Glans, M.^a , Cooley, S.A.^a , Vaida, F.^b , Boerwinkle, A.^a , Tomov, D.^a , Petersen, K.J.^a , Rosenow, A.^a , Paul, R.H.^c , Ances, B.M.^a d e

^a Department of Neurology, Washington University in Saint Louis, MO, Saint Louis, Seychelles
^b Department of Family Medicine and Public Health, University of California, San Diego, CA
^c Department of Psychology, University of Missouri, MO, Saint Louis, Seychelles
^d Department of Radiology, Washington University in Saint Louis, Saint Louis, MO; and
^e Hope Center for Neurological Disorders, Washington University in Saint Louis, MO, Saint Louis, Seychelles

Abstract
BACKGROUND: Combination antiretroviral therapy (cART) has allowed for viral load (VL) suppression and increased life expectancy for persons with HIV (PWH). Altered brain integrity, measured by neuropsychological (NP) performance and neuroimaging, is still prevalent among virally suppressed PWH. Age-related conditions such as cardiovascular disease may also affect brain integrity. This study investigated the effects of cardiovascular risk, VL, and HIV serostatus on cerebral blood flow (CBF), brain volumetrics, and cognitive function in PWH and persons without HIV (PWoH). METHODS: Ten-year cardiovascular risk, using the Framingham Heart Study criteria, was calculated in PWH (n = 164) on cART with undetectable (≤20 copies/mL; n = 134) or detectable (>20 copies/mL; n = 30) VL and PWoH (n = 66). The effects of cardiovascular risk on brain integrity (CBF, volume, and cognition) were compared for PWH (undetectable and detectable VL) and PWoH. RESULTS: PWH had smaller brain volumes and worse NP scores than PWoH. PWH with detectable and undetectable VL had similar brain integrity measures. Higher cardiovascular risk was associated with smaller volumes and lower CBF in multiple brain regions for PWH and PWoH. Significant interactions between HIV serostatus and cardiovascular risk on brain volumes were observed in frontal, orbitofrontal, and motor regions. Cardiovascular risk was not associated with cognition for PWH or PWoH. CONCLUSIONS: Neuroimaging, but not cognitive measures, was associated with elevated cardiovascular risk. HIV serostatus was associated with diminished brain volumes and worse cognition while CBF remained unchanged, reflecting potential protective effects of cART. Neuroimaging measures of structure (volume) and function (CBF) may identify contributions of comorbidities, but future longitudinal studies are needed. Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.

Quantifying stability of parameter estimates forin vivonearly incompressible transversely-isotropic brain MR elastography
(2022) Biomedical Physics & Engineering Express, 8 (3), . 

Jyoti, D.^a , McGarry, M.^a , Van Houten, E.^b , Sowinski, D.^a , Bayly, P.V.^c , Johnson, C.L.^d , Paulsen, K.^a e

^a Thayer School of Engineering, Dartmouth CollegeHanover NH 03755, United States
^b Université de Sherbrooke, QC, Sherbrooke, J1K 2R1, Canada
^c Washington University in St Louis, St Louis, MO, 63130, United States of America
^d University of Delaware, Newark, DE 19716, United States of America
^e Dartmouth-Hitchcock Medical CenterNH 03756, United States

Abstract
Easily computable quality metrics for measured medical data at point-of-care are important for imaging technologies involving offline reconstruction. Accordingly, we developed a new data quality metric forin vivotransversely-isotropic (TI) magnetic resonance elastography (MRE) based on a generalization of the widely accepted octahedral shear-strain calculation. The metric uses MRE displacement data and an estimate of the TI property field to yield a ‘stability map’ which predicts regions of low versus high accuracy in the resulting material property reconstructions. We can also calculate an average TI parameter stability (TIPS) score over all voxels in a region of interest for a given measurement to indicate how reliable the recovered mechanical property estimate for the region is expected to be. The calculation is rapid and places little demand on computing resources compared to the computationally intensive material property reconstruction from non-linear inversion (TI-NLI) of displacement fields, making it ideal for point-of-care evaluation of data quality. We test the predictions of the stability map for both simulated phantoms andin vivohuman brain data. We used a range of different displacement datasets from vibrations applied in the anterior-posterior (AP), left-right (LR) and combined AP + LR directions. The TIPS and variability maps (noise sensitivity or variation from the mean of repeated MRE scans) were consistently anti-correlated. Notably, Spearman correlation coefficients ∣R∣>0.6 were found between variability and TIPS score for individual white matter tracts within vivodata. These observations demonstrate the reliability and promise of this data quality metric to screen data rapidly in realistic clinical MRE applications. © 2022 IOP Publishing Ltd.

Author Keywords
anisotropy;  brain;  data quality metric;  in vivo;  material property reconstruction;  MR elastography;  octahedral shear strain

Association of Prenatal Exposure to Early-Life Adversity with Neonatal Brain Volumes at Birth
(2022) JAMA Network Open, p. E227045. 

Triplett, R.L.^a , Lean, R.E.^b , Parikh, A.^c , Miller, J.P.^d , Alexopoulos, D.^a , Kaplan, S.^a , Meyer, D.^a , Adamson, C.^e f , Smyser, T.A.^b , Rogers, C.E.^b g , Barch, D.M.^b h i , Warner, B.^g , Luby, J.L.^b , Smyser, C.D.^a g i

^a Department of Neurology, Washington University in St Louis, 660 S Euclid Ave, Campus Box 8111, St Louis, MO 63110, United States
^b Department of Psychiatry, Washington University in St Louis, St Louis, MO, United States
^c School of Medicine, Washington University in St Louis, St Louis, MO, United States
^d Department of Biostatistics, Washington University in St Louis, St Louis, MO, United States
^e Developmental Imaging, Murdoch Children’s Institute, Melbourne, Australia
^f Electrical and Electronic Engineering, University of Melbourne, Melbourne, Australia
^g Department of Pediatrics, Washington University in St Louis, St Louis, MO, United States
^h Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, MO, United States
ⁱ Department of Radiology, Washington University in St Louis, St Louis, MO, United States

Abstract
Importance: Exposure to early-life adversity alters the structural development of key brain regions underlying neurodevelopmental impairments. The association between prenatal exposure to adversity and brain structure at birth remains poorly understood. Objective: To examine whether prenatal exposure to maternal social disadvantage and psychosocial stress is associated with neonatal global and regional brain volumes and cortical folding. Design, Setting, and Participants: This prospective, longitudinal cohort study included 399 mother-infant dyads of sociodemographically diverse mothers recruited in the first or early second trimester of pregnancy and their infants, who underwent brain magnetic resonance imaging in the first weeks of life. Mothers were recruited from local obstetric clinics in St Louis, Missouri from September 1, 2017, to February 28, 2020. Exposures: Maternal social disadvantage and psychosocial stress in pregnancy. Main Outcomes and Measures: Confirmatory factor analyses were used to create latent constructs of maternal social disadvantage (income-to-needs ratio, Area Deprivation Index, Healthy Eating Index, educational level, and insurance status) and psychosocial stress (Perceived Stress Scale, Edinburgh Postnatal Depression Scale, Everyday Discrimination Scale, and Stress and Adversity Inventory). Neonatal cortical and subcortical gray matter, white matter, cerebellum, hippocampus, and amygdala volumes were generated using semiautomated, age-specific, segmentation pipelines. Results: A total of 280 mothers (mean [SD] age, 29.1 [5.3] years; 170 [60.7%] Black or African American, 100 [35.7%] White, and 10 [3.6%] other race or ethnicity) and their healthy, term-born infants (149 [53.2%] male; mean [SD] infant gestational age, 38.6 [1.0] weeks) were included in the analysis. After covariate adjustment and multiple comparisons correction, greater social disadvantage was associated with reduced cortical gray matter (unstandardized β = -2.0; 95% CI, -3.5 to -0.5; P =.01), subcortical gray matter (unstandardized β = -0.4; 95% CI, -0.7 to -0.2; P =.003), and white matter (unstandardized β = -5.5; 95% CI, -7.8 to -3.3; P <.001) volumes and cortical folding (unstandardized β = -0.03; 95% CI, -0.04 to -0.01; P <.001). Psychosocial stress showed no association with brain metrics. Although social disadvantage accounted for an additional 2.3% of the variance of the left hippocampus (unstandardized β = -0.03; 95% CI, -0.05 to -0.01), 2.3% of the right hippocampus (unstandardized β = -0.03; 95% CI, -0.05 to -0.01), 3.1% of the left amygdala (unstandardized β = -0.02; 95% CI, -0.03 to -0.01), and 2.9% of the right amygdala (unstandardized β = -0.02; 95% CI, -0.03 to -0.01), no regional effects were found after accounting for total brain volume. Conclusions and Relevance: In this baseline assessment of an ongoing cohort study, prenatal social disadvantage was associated with global reductions in brain volumes and cortical folding at birth. No regional specificity for the hippocampus or amygdala was detected. Results highlight that associations between poverty and brain development begin in utero and are evident early in life. These findings emphasize that preventive interventions that support fetal brain development should address parental socioeconomic hardships.. © 2022 American Medical Association. All rights reserved.

Short-Duration, Pulsatile, Electrical Stimulation Therapy Accelerates Axon Regeneration and Recovery following Tibial Nerve Injury and Repair in Rats
(2022) Plastic and Reconstructive Surgery, 149 (4), pp. 681E-690E. 

Roh, J.^a b , Schellhardt, L.^a b , Keane, G.C.^a b , Hunter, D.A.^a b , Moore, A.M.^a b , Snyder-Warwick, A.K.^a b , MacKinnon, S.E.^a b , Wood, M.D.^a b

^a Division of Plastic and Reconstructive Surgery, Washington University School of Medicine, Saint Louis, MO, United States
^b Department of Plastic and Reconstructive Surgery, The Ohio State University, Wexner Medical Center, Columbus, OH, United States

Abstract
Background: Repair of nerve injuries can fail to achieve adequate functional recovery. Electrical stimulation applied at the time of nerve repair can accelerate axon regeneration, which may improve the likelihood of recovery. However, widespread use of electrical stimulation may be limited by treatment protocols that increase operative time and complexity. This study evaluated whether a short-duration electrical stimulation protocol (10 minutes) was efficacious to enhance regeneration following nerve repair using rat models. Methods: Lewis and Thy1-green fluorescent protein rats were randomized to three groups: 0 minutes of electrical stimulation (no electrical stimulation; control), 10 minutes of electrical stimulation, and 60 minutes of electrical stimulation. All groups underwent tibial nerve transection and repair. In the intervention groups, electrical stimulation was delivered after nerve repair. Outcomes were assessed using immunohistochemistry, histology, and serial walking track analysis. Results: Two weeks after nerve repair, Thy1-green fluorescent protein rats demonstrated increased green fluorescent protein-positive axon outgrowth from the repair site with electrical stimulation compared to no electrical stimulation. Serial measurement of walking tracks after nerve repair revealed recovery was achieved more rapidly in both electrical stimulation groups as compared to no electrical stimulation. Histologic analysis of nerve distal to the repair at 8 weeks revealed robust axon regeneration in all groups. Conclusions: As little as 10 minutes of intraoperative electrical stimulation therapy increased early axon regeneration and facilitated functional recovery following nerve transection with repair. Also, as early axon outgrowth increased following electrical stimulation with nerve repair, these findings suggest electrical stimulation facilitated recovery because of earlier axon growth across the suture-repaired site into the distal nerve to reach end-organ targets. Clinical Relevance Statement: Brief (10-minute) electrical stimulation therapy can provide similar benefits to the 60-minute protocol in an acute sciatic nerve transection/repair rat model and merit further studies, as they represent a translational advantage. © 2022 Lippincott Williams and Wilkins. All rights reserved.

Funding details
National Institute of Neurological Disorders and StrokeNINDSK08NS096232

Using Patient-Reported Outcome Measures to Screen for Cognitive Function Deficits and Stigma in Patients with Single-Suture Craniosynostosis
(2022) Plastic and Reconstructive Surgery, 149 (4), pp. 743E-748E. 

Said, A.M.^a b , Skolnick, G.B.^a b , Girresch-Ward, S.^a b , Cradock, M.M.^a b , Naidoo, S.D.^a b , Smyth, M.^a b , Patel, K.B.^a b

^a Division of Plastic and Reconstructive Surgery, Department of Surgery, Department of Neurosurgery, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
^b Department of Psychology, St. Louis Children’s Hospital, St. Louis, MO, United States

Abstract
Summary: Children with single-suture craniosynostosis have small but significant deficits in appearance ratings and neurodevelopment. Traditionally, these parameters are studied using a full battery of examinations, which are very time consuming. This study evaluated a convenient method to measure psychosocial parameters in this population by utilizing patient-reported outcomes measures to evaluate cognitive function and stigma. Stigma and cognitive function were measured, using the Patient-Reported Outcomes Measurement Information System and Quality of Life in Neurological Disorders questionnaires, in 59 consecutive patients at least 5 years old presenting to clinic from July of 2018 to January of 2020 with repaired single-suture craniosynostosis. Parents completed parent proxy cognitive function surveys for patients under age 8. Questionnaires were administered electronically as part of clinical care. Scores were automatically transferred to the electronic medical record and correlated with previously acquired Child Behavior Checklist results. Median time to complete the questionnaires was 57 and 49 seconds, respectively. Stigma and cognitive function were significantly correlated with the associated Child Behavior Checklist subscores (Spearman’s rho, -0.384, p = 0.023; and Spearman’s rho, -0.683, p = 0.001, respectively). The Patient-Reported Outcomes Measurement Information System and Quality of Life in Neurological Disorders questionnaires offer a convenient method of screening psychosocial parameters in children with single-suture craniosynostosis that otherwise would be difficult to obtain during standard visits. Short completion times and electronic scoring increase clinical utility. CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, II. © 2022 Lippincott Williams and Wilkins. All rights reserved.

Differential impact of Kv8.2 loss on rod and cone signaling and degeneration
(2022) Human Molecular Genetics, 31 (7), pp. 1035-1050. 

Inamdar, S.M.^a , Lankford, C.K.^a , Poria, D.^b c , Laird, J.G.^a , Solessio, E.^d , Kefalov, V.J.^b c e , Baker, S.A.^a f

^a Department of Biochemistry and Molecular Biology, University of IowaIA, United States
^b Department of Ophthalmology and Visual Sciences, Washington University, St. Louis, MO 63110, USA
^c Gavin Herbert Eye Institute, School of Medicine, Irvine, CA 92697, USA
^d Department of Ophthalmology and Visual Sciences, Center for Vision Research, SUNY Upstate Medical University, Syracuse, NY 13210, USA
^e Department of Physiology and Biophysics, University of California, Irvine, CA 92697, USA
^f Department of Ophthalmology and Visual Sciences, University of IowaIA, United States

Abstract
Heteromeric Kv2.1/Kv8.2 channels are voltage-gated potassium channels localized to the photoreceptor inner segment. They carry IKx, which is largely responsible for setting the photoreceptor resting membrane potential. Mutations in Kv8.2 result in childhood-onset cone dystrophy with supernormal rod response (CDSRR). We generated a Kv8.2 knockout (KO) mouse and examined retinal signaling and photoreceptor degeneration to gain deeper insight into the complex phenotypes of this disease. Using electroretinograms, we show that there were delayed or reduced signaling from rods depending on the intensity of the light stimulus, consistent with reduced capacity for light-evoked changes in membrane potential. The delayed response was not seen ex vivo where extracellular potassium levels were controlled by the perfusion buffer, so we propose the in vivo alteration is influenced by genotype-associated ionic imbalance. We observed mild retinal degeneration. Signaling from cones was reduced but there was no loss of cone density. Loss of Kv8.2 altered responses to flickering light with responses attenuated at high frequencies and altered in shape at low frequencies. The Kv8.2 KO line on an all-cone retina background had reduced cone-driven ERG b wave amplitudes and underwent degeneration. Altogether, we provide insight into how a deficit in the dark current affects the health and function of photoreceptors. © The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

AMIGO1 Promotes Axon Growth and Territory Matching in the Retina
(2022) The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 42 (13), pp. 2678-2689. 

Soto, F.^a , Shen, N.^b , Kerschensteiner, D.^c d e f

^a John F. Hardesty, MD, Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO 63110, United States
^b John F. Hardesty, MD, Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO 63110, United States
^c John F. Hardesty, MD, Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO 63110, United States
^d Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States
^e Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, United States
^f Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, United States

Abstract
Dendrite and axon arbor sizes are critical to neuronal function and vary widely between different neuron types. The relative dendrite and axon sizes of synaptic partners control signal convergence and divergence in neural circuits. The developmental mechanisms that determine cell-type-specific dendrite and axon size and match synaptic partners’ arbor territories remain obscure. Here, we discover that retinal horizontal cells express the leucine-rich repeat domain cell adhesion molecule AMIGO1. Horizontal cells provide pathway-specific feedback to photoreceptors-horizontal cell axons to rods and horizontal cell dendrites to cones. AMIGO1 selectively expands the size of horizontal cell axons. When Amigo1 is deleted in all or individual horizontal cells of either sex, their axon arbors shrink. By contrast, horizontal cell dendrites and synapse formation of horizontal cell axons and dendrites are unaffected by AMIGO1 removal. The dendrites of rod bipolar cells, which do not express AMIGO1, shrink in parallel with horizontal cell axons in Amigo1 knockout (Amigo1 KO) mice. This territory matching maintains the function of the rod bipolar pathway, preserving bipolar cell responses and retinal output signals in Amigo1 KO mice. We previously identified AMIGO2 as a scaling factor that constrains retinal neurite arbors. Our current results identify AMIGO1 as a scaling factor that expands retinal neurite arbors and reveal territory matching as a novel homeostatic mechanism. Territory matching interacts with other homeostatic mechanisms to stabilize the development of the rod bipolar pathway, which mediates vision near the threshold.SIGNIFICANCE STATEMENT Neurons send and receive signals through branched axonal and dendritic arbors. The size of these arbors is critical to the function of a neuron. Axons and dendrites grow during development and are stable at maturity. The mechanisms that determine axon and dendrite size are not well understood. Here, we identify a cell surface protein, AMIGO1, that selectively promotes axon growth of horizontal cells, a retinal interneuron. Removal of AMIGO1 reduces the size of horizontal cell axons without affecting the size of their dendrites or the ability of both arbors to form connections. The changes in horizontal cell axons are matched by changes in synaptic partner dendrites to stabilize retinal function. This identifies territory matching as a novel homeostatic plasticity mechanism. Copyright © 2022 the authors.

Author Keywords
arbor size;  circuit development;  horizontal cell;  LRR protein;  rod bipolar pathway

The Enantiomer of Allopregnanolone Prevents Pressure-Mediated Retinal Degeneration Via Autophagy
(2022) Frontiers in Pharmacology, 13, art. no. 855779, . 

Ishikawa, M.^a b , Nakazawa, T.^a b c d , Kunikata, H.^b c , Sato, K.^a d , Yoshitomi, T.^e f , Krishnan, K.^g , Covey, D.F.^g h i j , Zorumski, C.F.^i j k , Izumi, Y.^i j k

^a Department of Ophthalmic Imaging and Information Analytics, Tohoku University Graduate School of Medicine, Sendai, Japan
^b Department of Ophthalmology, Tohoku University Graduate School of Medicine, Sendai, Japan
^c Department of Retinal Disease Control, Tohoku University Graduate School of Medicine, Sendai, Japan
^d Department of Advanced Ophthalmic Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan
^e Department of Orthoptics, Fukuoka International University of Health and Welfare, Fukuoka, Japan
^f Department of Ophthalmology, Akita University School of Medicine, Akita, Japan
^g Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, United States
^h Department of Anesthesiology, Washington University School of Medicine, St. Louis, MO, United States
ⁱ Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, St. Louis, MO, United States
^j Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^k Center for Brain Research in Mood Disorders, Washington University School of Medicine, St. Louis, MO, United States

Abstract
In an ex vivo rat ocular hypertension (OHT) model, the neurosteroid allopregnanolone (AlloP) exerts neuroprotective effects via enhancement of both GABAA receptors and autophagy. We now examine whether its enantiomer (ent-AlloP), which is largely inactive at GABA receptors, offers similar neuroprotection in ex vivo and in vivo rat OHT models. Ex vivo rat retinal preparations were incubated in a hyperbaric condition (10 and 75 mmHg) for 24 h. An in vivo ocular hypertension (OHT) model was induced by intracameral injection of polystyrene microbeads. We examined pharmacological effects of AlloP, ent-AlloP, picrotoxin (a GABAA receptor antagonist), and 3-MA (an autophagy inhibitor) histologically and biochemically. We found that both AlloP and ent-AlloP have marked neuroprotective effects in the retina, but effects of the unnatural enantiomer are independent of GABAA receptors. Electron microscopic analyses show that pressure elevation significantly increased autophagosomes (APs) in the nerve fiber layer and addition of AlloP also increased APs and degenerative autophagic vacuoles (AVds). ent-AlloP markedly increased APs and AVds compared to AlloP. Examination of LC3B-II and SQSTM1 protein levels using immunoblotting revealed that AlloP increased LC3B-II, and ent-AlloP further enhanced LC3B-II and suppressed SQSTM1, indicating that autophagy is a major mechanism underlying neuroprotection by ent-AlloP. In an rat in vivo OHT model, single intravitreal ent-AlloP injection prevented apoptotic cell death of retinal ganglion cells similar to AlloP. However, even in this model, ent-AlloP was more effective in activating autophagy than AlloP. We conclude that ent-AlloP may be a prototype of potential therapeutic for treatment of glaucoma as an autophagy enhancer without affecting GABA receptors. Copyright © 2022 Ishikawa, Nakazawa, Kunikata, Sato, Yoshitomi, Krishnan, Covey, Zorumski and Izumi.

Author Keywords
allopregnanolone;  autophagy;  enantiomer;  glaucoma;  intraocular pressure;  neurosteroid

Funding details
National Institute of Mental HealthNIMHMH101874, MH122379
Kowa Company
Japan Society for the Promotion of ScienceKAKEN18K09438

A Bayesian Network to Predict the Risk of Post Influenza Vaccination Guillain-Barré Syndrome:Development and Validation Study
(2022) JMIR Public Health and Surveillance, 8 (3), art. no. e25658, . 

Huang, Y.^a b , Luo, C.^c d , Jiang, Y.^e , Du, J.^f , Tao, C.^f , Chen, Y.^c , Hao, Y.^a g

^a Department of Medical Statistics, Sun Yat-Sen University, Guangzhou, China
^b Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
^c Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, United States
^d Division of Public Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
^e Department of Neurology, Multiple Sclerosis Research Center, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
^f School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States
^g Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China

Abstract
Background: Identifying the key factors of Guillain-Barré syndrome (GBS) and predicting its occurrence are vital for improving the prognosis of patients with GBS. However, there are scarcely any publications on a forewarning model of GBS. A Bayesian network (BN) model, which is known to be an accurate, interpretable, and interaction-sensitive graph model in many similar domains, is worth trying in GBS risk prediction. Objective: The aim of this study is to determine the most significant factors of GBS and further develop and validate a BN model for predicting GBS risk. Methods: Large-scale influenza vaccine postmarketing surveillance data, including 79,165 US (obtained from the Vaccine Adverse Event Reporting System between 1990 and 2017) and 12,495 European (obtained from the EudraVigilance system between 2003 and 2016) adverse events (AEs) reports, were extracted for model development and validation. GBS, age, gender, and the top 50 prevalent AEs were included for initial BN construction using the R package bnlearn. Results: Age, gender, and 10 AEs were identified as the most significant factors of GBS. The posttest probability of GBS suggested that male vaccinees aged 50-64 years and without erythema should be on the alert or be warned by clinicians about an increased risk of GBS, especially when they also experience symptoms of asthenia, hypesthesia, muscular weakness, or paresthesia. The established BN model achieved an area under the receiver operating characteristic curve of 0.866 (95% CI 0.865-0.867), sensitivity of 0.752 (95% CI 0.749-0.756), specificity of 0.882 (95% CI 0.879-0.885), and accuracy of 0.882 (95% CI 0.879-0.884) for predicting GBS risk during the internal validation and obtained values of 0.829, 0.673, 0.854, and 0.843 for area under the receiver operating characteristic curve, sensitivity, specificity, and accuracy, respectively, during the external validation. Conclusions: The findings of this study illustrated that a BN model can effectively identify the most significant factors of GBS, improve understanding of the complex interactions among different postvaccination symptoms through its graphical representation, and accurately predict the risk of GBS. The established BN model could further assist clinical decision-making by providing an estimated risk of GBS for a specific vaccinee or be developed into an open-access platform for vaccinees’ self-monitoring. © 2022 JMIR Publications Inc.. All Rights Reserved.

Author Keywords
adverse events;  Bayesian network;  Guillain-Barré syndrome;  risk prediction;  trivalent influenza vaccine

Funding details
National Natural Science Foundation of ChinaNSFC81973150
Sun Yat-sen UniversitySYSU

Importance of the intersection of age and sex to understand variation in incidence and survival for primary malignant gliomas
(2022) Neuro-oncology, 24 (2), pp. 302-310. 

Wang, G.-M.^a b , Cioffi, G.^a b c d , Patil, N.^d e , Waite, K.A.^a b c d , Lanese, R.^a b , Ostrom, Q.T.^d f , Kruchko, C.^d , Berens, M.E.^g , Connor, J.R.^h , Lathia, J.D.^i j , Rubin, J.B.^k , Barnholtz-Sloan, J.S.^{a b c d j l m}

^a Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, United States
^b Case Western Reserve University School of Medicine, Cleveland, OH, United States
^c Cleveland Center for Health Outcomes Research (CCHOR), Cleveland, OH, United States
^d Central Brain Tumor Registry of the United States (CBTRUS), Hinsdale, IL, United States
^e Research and Education Institute, University Hospitals Health System (UHHS), Cleveland, OH, United States
^f Department of Neurosurgery, Duke University School of Medicine, Durham, NC, United States
^g Cancer and Cell Biology Division, Translational Genomics Research Institute (TGEN), Phoenix, AZ, United States
^h Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, United States
ⁱ Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
^j Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, United States
^k Departments of Pediatrics and Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
^l Cleveland Institute for Computational Biology, Cleveland, OH, United States
^m Research Health Analytics and Informatics, University Hospitals Health System (UHHS), Cleveland, OH, United States

Abstract
BACKGROUND: Gliomas are the most common type of malignant brain and other CNS tumors, accounting for 80.8% of malignant primary brain and CNS tumors. They cause significant morbidity and mortality. This study investigates the intersection between age and sex to better understand variation of incidence and survival for glioma in the United States. METHODS: Incidence data from 2000 to 2017 were obtained from CBTRUS, which obtains data from the NPCR and SEER, and survival data from the CDC’s NPCR. Age-adjusted incidence rate ratios (IRR) per 100 000 were generated to compare male-to-female incidence by age group. Cox proportional hazard models were performed by age group, generating hazard ratios to assess male-to-female survival differences. RESULTS: Overall, glioma incidence was higher in males. Male-to-female incidence was lowest in ages 0-9 years (IRR: 1.04, 95% CI: 1.01-1.07, P = .003), increasing with age, peaking at 50-59 years (IRR: 1.56, 95% CI: 1.53-1.59, P < .001). Females had worse survival for ages 0-9 (HR: 0.93, 95% CI: 0.87-0.99), though male survival was worse for all other age groups, with the difference highest in those 20-29 years (HR: 1.36, 95% CI: 1.28-1.44). Incidence and survival differences by age and sex also varied by histological subtype of glioma. CONCLUSIONS: To better understand the variation in glioma incidence and survival, investigating the intersection of age and sex is key. The current work shows that the combined impact of these variables is dependent on glioma subtype. These results contribute to the growing understanding of sex and age differences that impact cancer incidence and survival. © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.

Author Keywords
age;  CBTRUS;  glioma;  incidence;  sex differences;  survival

Identifying Visual Attention Features Accurately Discerning Between Autism and Typically Developing: a Deep Learning Framework
(2022) Interdisciplinary Sciences: Computational Life Sciences, . 

Xie, J.^a b , Wang, L.^a , Webster, P.^e , Yao, Y.^a , Sun, J.^a b , Wang, S.^d , Zhou, H.^a c

^a The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
^b University of Chinese Academy of Sciences, Beijing, 100049, China
^c The Research Center for Artificial Intelligence, Peng Cheng Laboratory, No. 2 Xingke First Street, Nanshan District, Shenzhen, 518000, China
^d Department of Radiology, Washington University in St. Louis, St. Louis, MO 63130, United States
^e Department of Chemical and Biomedical Engineering and Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, United States

Abstract
Atypical visual attention is a hallmark of autism spectrum disorder (ASD). Identifying the attention features accurately discerning between people with ASD and typically developing (TD) at the individual level remains a challenge. In this study, we developed a new systematic framework combining high accuracy deep learning classification, deep learning segmentation, image ablation and a direct measurement of classification ability to identify the discriminative features for autism identification. Our two-stream model achieved the state-of-the-art performance with a classification accuracy of 0.95. Using this framework, two new categories of features, Food & drink and Outdoor-objects, were identified as discriminative attention features, in addition to the previously reported features including Center-object and Human-faces, etc. Altered attention to the new categories helps to understand related atypical behaviors in ASD. Importantly, the area under curve (AUC) based on the combined top-9 features identified in this study was 0.92, allowing an accurate classification at the individual level. We also obtained a small but informative dataset of 12 images with an AUC of 0.86, suggesting a potentially efficient approach for the clinical diagnosis of ASD. Together, our deep learning framework based on VGG-16 provides a novel and powerful tool to recognize and understand abnormal visual attention in ASD, which will, in turn, facilitate the identification of biomarkers for ASD. Graphical abstract: [Figure not available: see fulltext.] © 2022, International Association of Scientists in the Interdisciplinary Areas.

Author Keywords
Autism spectrum disorder;  Deep learning;  Eye movement;  Visual attention

Funding details
National Natural Science Foundation of ChinaNSFC31671108, 62027804
Chinese Academy of SciencesCASGJJSTD20180002
National Key Research and Development Program of ChinaNKRDPC2017YFC1307500

Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia
(2022) Nature Genetics, . 

Palmer, D.S.^a b , Howrigan, D.P.^a b , Chapman, S.B.^b , Adolfsson, R.^c , Bass, N.^d , Blackwood, D.^e , Boks, M.P.M.^f , Chen, C.-Y.^a b g , Churchhouse, C.^a b h , Corvin, A.P.ⁱ , Craddock, N.^j , Curtis, D.^k l , Di Florio, A.^m , Dickerson, F.ⁿ , Freimer, N.B.^o p , Goes, F.S.^q , Jia, X.^r , Jones, I.^j s , Jones, L.^t , Jonsson, L.^u v , Kahn, R.S.^w , Landén, M.^u x , Locke, A.E.^y , McIntosh, A.M.^e , McQuillin, A.^d , Morris, D.W.^z , O’Donovan, M.C.^j , Ophoff, R.A.^o p aa , Owen, M.J.^j , Pedersen, N.L.^x , Posthuma, D.^ab , Reif, A.^ac , Risch, N.^ad ae , Schaefer, C.^ae , Scott, L.^af , Singh, T.^a b , Smoller, J.W.^ag ah , Solomonson, M.^h , Clair, D.S.^ai , Stahl, E.A.^aj , Vreeker, A.^ak , Walters, J.T.R.^j , Wang, W.^aj , Watts, N.A.^a h , Yolken, R.^al , Zandi, P.P.^q , Neale, B.M.^a b h

^a Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States
^b Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, United States
^c Department of Clinical Sciences, Psychiatry, Umea University, Umea, Sweden
^d Division of Psychiatry, University College London, London, United Kingdom
^e Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
^f Department of Psychiatry, Brain Center UMC Utrecht, Utrecht, Netherlands
^g Biogen, Cambridge, MA, United States
^h Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, United States
ⁱ Trinity College Dublin, Dublin, Ireland
^j MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
^k UCL Genetics Institute, University College London, London, United Kingdom
^l Centre for Psychiatry, Queen Mary University of London, London, United Kingdom
^m Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
ⁿ Sheppard Pratt, Baltimore, MD, United States
^o Department of Psychiatry and Biobehavioral Science, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
^p Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
^q Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
^r Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
^s National Centre for Mental Health, Division of Psychiatry and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
^t Department of Psychological Medicine, University of Worcester, Worcester, United Kingdom
^u Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
^v Department of Pharmacology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
^w Division of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
^x Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
^y Division of Genomics & Bioinformatics and McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, United States
^z Centre for Neuroimaging, Cognition and Genomics, Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
^aa Department of Psychiatry, Erasmus Medical Center, Erasmus University, Rotterdam, Netherlands
^ab Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, Netherlands
^ac Department of Psychiatry, Psychosomatic Medicine and Psychiatry, University Hospital Frankfurt – Goethe University, Frankfurt, Germany
^ad Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, United States
^ae Division of Research, Kaiser Permanente Northern California, Oakland, CA, United States
^af Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, United States
^ag Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, United States
^ah Department of Psychiatry, Harvard Medical School, Boston, MA, United States
^ai Institute for Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom
^aj Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
^ak Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC Sophia Children Hospital, Erasmus University, Rotterdam, Netherlands
^al Stanley Division of Developmental Neurovirology, Johns Hopkins University, Baltimore, MD, United States

Abstract
We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from genome-wide association studies (GWASs) of BD, however, are not significantly enriched for ultra-rare PTVs. Combining gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (odds ratio (OR) = 7.06, P = 2.83 × 10−9). At the protein level, AKAP-11 interacts with GSK3B, the hypothesized target of lithium, a primary treatment for BD. Our results lend support to BD’s polygenicity, demonstrating a role for rare coding variation as a significant risk factor in BD etiology. © 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.

Funding details
National Institutes of HealthNIHR01 CA194393, R01 MH085542, R37 MH107649
National Institute of Mental HealthNIMHR01 MH090553, R01 MH095034, U01 MH105578
Stanley Medical Research InstituteSMRI
Janssen Pharmaceuticals
Dalio FoundationR01 MH085543, R01 MH110437, RC2 AG036607
Sackler Trust
Medical Research CouncilMRCG1000708, MR/L010305/1, MR/P005748/1