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Several recent studies have applied machine learning techniques to develop risk algorithms that predict subsequent suicidal behavior based on electronic health record data. In this study we used a retrospective cohort study design to test whether developing more tailored predictive models-within specific subpopulations of patients-would improve predictive accuracy. A retrospective cohort of 15,117 patients diagnosed with multiple sclerosis (MS), a diagnosis associated with increased risk of suicidal behavior, was used. The cohort was randomly divided into equal sized training and validation sets. Overall, suicidal behavior was identified among 191 (1.3%) of the patients with MS. A Naïve Bayes Classifier model was trained on the training set to predict future suicidal behavior. With 90% specificity, the model detected 37% of subjects who later demonstrated suicidal behavior, on average 4.6 years before the first suicide attempt. The performance of a model trained only on MS patients was better at predicting suicide in MS patients than that a model trained on a general patient sample of a similar size (AUC of 0.77 vs. 0.66). Unique risk factors for suicidal behavior among patients with MS included pain-related codes, gastroenteritis and colitis, and history of smoking. Future studies are needed to further test the value of developing population-specific risk models., Competing Interests: NO authors have competing interests., (Copyright: © 2023 Barak-Corren et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Nucleolin (NCL/C23; OMIM: 164035) is a major nucleolar protein that plays a critical role in multiple processes, including ribosome assembly and maturation, chromatin decondensation, and pre-rRNA transcription. Due to its diverse functions, nucleolin has frequently been implicated in pathological processes, including cancer and viral infection. We recently identified a de novo frameshifting indel mutation of NCL , p.Gly664Glufs*70, through whole-exome sequencing of autism spectrum disorder trios. Through the transfection of constructs encoding either a wild-type human nucleolin or a mutant nucleolin with the same C-terminal sequence predicted for the autism proband, and by using co-localization with the nucleophosmin (NPM; B23) protein, we have shown that the nucleolin mutation leads to mislocalization of the NCL protein from the nucleolus to the nucleoplasm. Moreover, a construct with a nonsense mutation at the same residue, p.Gly664*, shows a very similar effect on the location of the NCL protein, thus confirming the presence of a predicted nucleolar location signal in this region of the NCL protein. Real-time fluorescence recovery experiments show significant changes in the kinetics and mobility of mutant NCL protein in the nucleoplasm of HEK293Tcells. Several other studies also report de novo NCL mutations in ASD or neurodevelopmental disorders. The altered mislocalization and dynamics of mutant NCL (p.G664Glufs*70/p.G664*) may have relevance to the etiopathlogy of NCL -related ASD and other neurodevelopmental phenotypes.

Aims: The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure., Methods and Results: The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 × 10 -8 under an additive genetic model., Conclusions: HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction., (© 2021 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Substantial genetic liability is shared across psychiatric disorders but less is known about risk variants that are specific to a given disorder. We used multi-trait conditional and joint analysis (mtCOJO) to adjust GWAS summary statistics of one disorder for the effects of genetically correlated traits to identify putative disorder-specific SNP associations. We applied mtCOJO to summary statistics for five psychiatric disorders from the Psychiatric Genomics Consortium-schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit hyperactivity disorder (ADHD) and autism (AUT). Most genome-wide significant variants for these disorders had evidence of pleiotropy (i.e., impact on multiple psychiatric disorders) and hence have reduced mtCOJO conditional effect sizes. However, subsets of genome-wide significant variants had larger conditional effect sizes consistent with disorder-specific effects: 15 of 130 genome-wide significant variants for schizophrenia, 5 of 40 for major depression, 3 of 11 for ADHD and 1 of 2 for autism. We show that decreased expression of VPS29 in the brain may increase risk to SCZ only and increased expression of CSE1L is associated with SCZ and MD, but not with BIP. Likewise, decreased expression of PCDHA7 in the brain is linked to increased risk of MD but decreased risk of SCZ and BIP., (© 2020. The Author(s), under exclusive licence to Springer Nature Limited.)

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.

The role of leptin receptor (OB-R) signaling in linking pluripotency with growth and development and the consequences of dysfunctional leptin signaling on progression of metabolic disease is poorly understood. Using a global unbiased proteomics approach we report that embryonic fibroblasts (MEFs) carrying the db/db mutation exhibit metabolic abnormalities, while their reprogrammed induced pluripotent stem cells (iPSCs) show altered expression of proteins involved in embryonic development. An upregulation in expression of eukaryotic translation initiation factor 4e (Eif4e) and Stat3 binding to the Eif4e promoter was supported by enhanced protein synthesis in mutant iPSCs. Directed differentiation of db/db iPSCs toward the neuronal lineage showed defects. Gene editing to correct the point mutation in db/db iPSCs using CRISPR-Cas9, restored expression of neuronal markers and protein synthesis while reversing the metabolic defects. These data imply a direct role for OB-R in regulating metabolism in embryonic fibroblasts and key developmental pathways in iPSCs., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Recognizing that health outcomes are influenced by and occur within multiple social and physical contexts, researchers have used multilevel modeling techniques for decades to analyze hierarchical or nested data. Cross-Classified Multilevel Models (CCMM) are a statistical technique proposed in the 1990s that extend standard multilevel modeling and enable the simultaneous analysis of non-nested multilevel data. Though use of CCMM in empirical health studies has become increasingly popular, there has not yet been a review summarizing how CCMM are used in the health literature. To address this gap, we performed a scoping review of empirical health studies using CCMM to: (a) evaluate the extent to which this statistical approach has been adopted; (b) assess the rationale and procedures for using CCMM; and (c) provide concrete recommendations for the future use of CCMM. We identified 118 CCMM papers published in English-language literature between 1994 and 2018. Our results reveal a steady growth in empirical health studies using CCMM to address a wide variety of health outcomes in clustered non-hierarchical data. Health researchers use CCMM primarily for five reasons: (1) to statistically account for non-independence in clustered data structures; out of substantive interest in the variance explained by (2) concurrent contexts, (3) contexts over time, and (4) age-period-cohort effects; and (5) to apply CCMM alongside other techniques within a joint model. We conclude by proposing a set of recommendations for use of CCMM with the aim of improved clarity and standardization of reporting in future research using this statistical approach., (© 2020 The Author(s).)

In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait's heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments., (Copyright © 2020 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Natriuretic peptides are cardiac-derived hormones that enhance insulin sensitivity and reduce fat accumulation. Low natriuretic peptide levels are associated with increased risk of type 2 diabetes mellitus (DM2); a condition with variable prevalence across racial/ethnic groups. Few studies have examined whether circulating natriuretic peptide levels and their response to preventive interventions for DM2 differ by race/ethnicity. The Diabetes Prevention Program (DPP) is a clinical trial (July 31, 1996- July 31, 2001) that randomized participants to preventive interventions for DM2. Using stored serum samples, we examined N-terminus pro-B-type natriuretic peptide (NT-proBNP) levels in 3,220 individuals (56% white; 19% African-American; 15% Hispanic; 5% American-Indian; 5% Asian). The influence of race/ethnicity on NT-proBNP concentrations at baseline and after two years of treatment with placebo, lifestyle, or metformin was examined with multivariable-adjusted regression. At baseline, NT-proBNP differed significantly by race (P < .001), with the lowest values in African-American individuals. Hispanic individuals also had lower baseline NT-proBNP levels compared with whites (P< .001), while NT-proBNP levels were similar between white, American-Indian, and Asian individuals. At two years of follow-up, NT-proBNP levels decreased in African-Americans in each of the DPP study arms, whereas they were stable or increased in the other racial/ethnic groups. In the DPP, African-American individuals had lower circulating NT-proBNP levels compared with individuals in other racial/ethnic groups at baseline and after two years of preventive interventions. Further studies should examine the cardio-metabolic implications of lower natriuretic peptide levels in African-Americans. Trial Registration: ClinicalTrials.gov NCT00004992., Competing Interests: Merck KGaA provides medication for DPPOS. DPP/DPPOS have also received donated materials from Bristol-Myers Squibb, Parke-Davis, and LifeScan Inc. This research was also supported, in part, by the intramural research program of the NIDDK. LifeScan Inc., Health O Meter, Hoechst Marion Roussel, Inc., Merck-Medco Managed Care, Inc., Merck and Co., Nike Sports Marketing, Slim Fast Foods Co., and Quaker Oats Co. donated materials, equipment, or medicines for concomitant conditions. McKesson BioServices Corp., Matthews Media Group, Inc., and the Henry M. Jackson Foundation provided support services under subcontract with the Coordinating Center. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products to declare.

Schizophrenia has been characterized as a neurodevelopmental disorder, with structural brain abnormalities reported at all stages. However, at present, it remains unclear whether gray and white matter abnormalities represent related or independent pathologies in schizophrenia. In this study, we present findings from an integrative analysis exploring the morphological relationship between gray and white matter in 45 schizophrenia participants and 49 healthy controls. We utilized mutual information (MI), a measure of how much information two variables share, to assess the morphological dependence between gray and white matter in three segments of the corpus callsoum, and the gray matter regions these segments connect: (1) the genu and the left and right rostral middle frontal gyrus (rMFG), (2) the isthmus and the left and right superior temporal gyrus (STG), (3) the splenium and the left and right lateral occipital gyrus (LOG). We report significantly reduced MI between white matter tract dispersion of the right hemispheric callosal connections to the STG and both cortical thickness and area in the right STG in schizophrenia patients, despite a lack of group differences in cortical thickness, surface area, or dispersion. We believe that this reduction in morphological dependence between gray and white matter may reflect a possible decoupling of the developmental processes that shape morphological features of white and gray matter early in life. The present study also demonstrates the importance of studying the relationship between gray and white matter measures, as opposed to restricting analyses to gray and white matter measures independently., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

While nearly all common genomic variants associated with schizophrenia have no known function, one corresponds to a missense variant associated with change in efficiency of a metal ion transporter, ZIP8, coded by SLC39A8. This variant has been linked to a range of phenotypes and is believed to be under recent selection pressure, but its impact on health is poorly understood. We sought to understand phenotypic implications of this variant in a large genomic biobank using an unbiased phenome-wide approach. Specifically, we generated 50 topics based on diagnostic codes using latent Dirichlet allocation, and examined them for association with the risk variant. Then, any significant topics were further characterized by examining association with individual diagnostic codes contributing to the topic. Among 50 topics, 1 was associated at an experiment-wide significance threshold (beta = 0.003, uncorrected p = 0.00049), comprising predominantly brain-related codes, including intracranial hemorrhage, cerebrovascular disease, and delirium/dementia. These results suggest that a functional variant previously associated with schizophrenia risk also increases liability to cerebrovascular disease. They further illustrate the utility of a topic-based approach to phenome-wide association.

White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery. In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95; p < 0.01) and Pearson correlation of total brain volume (r = 0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N = 2783) and identify a decrease in total brain volume of -2.4 cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing. Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

In the version of this article originally published, the name of author Martin H. de Borst was coded incorrectly in the XML. The error has now been corrected in the HTML version of the paper.

The neurodegenerative Huntington's disease (HD) is caused by a polyglutamine (polyQ) amplification in the huntingtin protein (HTT). Currently there is no effective therapy available for HD; however, several efforts are directed to develop and optimize HTT-lowering methods to improve HD phenotypes. To validate these approaches, there is an immediate need for reliable, sensitive, and easily accessible methods to quantify HTT expression. Using the AlphaLISA platform, we developed two novel sensitive and robust assays for quantification of HTT in biological samples using commercially available antibodies. The first, a polyQ-independent assay, measures the total pool of HTT, while the second, a polyQ-dependent assay, preferentially detects the mutant form of HTT. Using purified HTT protein standards and brain homogenates from an HD mouse model, we determine a lower limit of quantification of 1 and 3 pm and optimal reproducibility with CV values lower than 7% for intra- and 20% for interassay. In addition, we used the assays to quantify HTT in neural stem cells generated from patient-derived induced pluripotent stem cells in vitro and in human brain tissue lysates. Finally, we could detect changes in HTT levels in a mouse model where mutant HTT was conditionally deleted in neural tissue, verifying the potential to monitor the outcome of HTT-lowering strategies. This analytical platform is ideal for high-throughput screens and thus has an added value for the HD community as a tool to optimize novel therapeutic approaches aimed at modulating HTT protein levels.

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

Background: Genome-wide association studies conducted on QRS duration, an electrocardiographic measurement associated with heart failure and sudden cardiac death, have led to novel biological insights into cardiac function. However, the variants identified fall predominantly in non-coding regions and their underlying mechanisms remain unclear., Results: Here, we identify putative functional coding variation associated with changes in the QRS interval duration by combining Illumina HumanExome BeadChip genotype data from 77,898 participants of European ancestry and 7695 of African descent in our discovery cohort, followed by replication in 111,874 individuals of European ancestry from the UK Biobank and deCODE cohorts. We identify ten novel loci, seven within coding regions, including ADAMTS6, significantly associated with QRS duration in gene-based analyses. ADAMTS6 encodes a secreted metalloprotease of currently unknown function. In vitro validation analysis shows that the QRS-associated variants lead to impaired ADAMTS6 secretion and loss-of function analysis in mice demonstrates a previously unappreciated role for ADAMTS6 in connexin 43 gap junction expression, which is essential for myocardial conduction., Conclusions: Our approach identifies novel coding and non-coding variants underlying ventricular depolarization and provides a possible mechanism for the ADAMTS6-associated conduction changes.

Transcription factor programming of pluripotent stem cells (PSCs) has emerged as an approach to generate human neurons for disease modeling. However, programming schemes produce a variety of cell types, and those neurons that are made often retain an immature phenotype, which limits their utility in modeling neuronal processes, including synaptic transmission. We report that combining NGN2 programming with SMAD and WNT inhibition generates human patterned induced neurons (hpiNs). Single-cell analyses showed that hpiN cultures contained cells along a developmental continuum, ranging from poorly differentiated neuronal progenitors to well-differentiated, excitatory glutamatergic neurons. The most differentiated neurons could be identified using a CAMK2A::GFP reporter gene and exhibited greater functionality, including NMDAR-mediated synaptic transmission. We conclude that utilizing single-cell and reporter gene approaches for selecting successfully programmed cells for study will greatly enhance the utility of hpiNs and other programmed neuronal populations in the modeling of nervous system disorders., (Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.)

Event-related potential (ERP) components have been used to assess cognitive functions in patients with psychotic illness. Evidence suggests that among patients with psychosis there is a distinct heritable neurophysiologic phenotypic subtype captured by impairments across a range of ERP measures. In this study, we investigated the genetic basis of this "globally impaired" ERP cluster and its relationship to psychosis and cognitive abilities. We applied K-means clustering to six ERP measures to re-derive the globally impaired (n = 60) and the non-globally impaired ERP clusters (n = 323) in a sample of cases with schizophrenia (SCZ = 136) or bipolar disorder (BPD = 121) and healthy controls (n = 126). We used genome-wide association study (GWAS) results for SCZ, BPD, college completion, and childhood intelligence as the discovery datasets to derive polygenic risk scores (PRS) in our study sample and tested their associations with globally impaired ERP. We conducted mediation analyses to estimate the proportion of each PRS effect on severity of psychotic symptoms that is mediated through membership in the globally impaired ERP. Individuals with globally impaired ERP had significantly higher PANSS-positive scores (β = 3.95, P = 0.005). The SCZ-PRS was nominally associated with globally impaired ERP (unadjusted P = 0.01; R 2  = 3.07%). We also found a significant positive association between the college-PRS and globally impaired ERP (FDR-corrected P = 0.004; R 2  = 6.15%). The effect of college-PRS on PANSS positivity was almost entirely (97.1%) mediated through globally impaired ERP. These results suggest that the globally impaired ERP phenotype may represent some aspects of brain physiology on the path between genetic influences on educational attainment and psychotic symptoms.

Thiazide diuretics, commonly used antihypertensives, may cause QT interval (QT) prolongation, a risk factor for highly fatal and difficult to predict ventricular arrhythmias. We examined whether common single-nucleotide polymorphisms (SNPs) modified the association between thiazide use and QT or its component parts (QRS interval, JT interval) by performing ancestry-specific, trans-ethnic and cross-phenotype genome-wide analyses of European (66%), African American (15%) and Hispanic (19%) populations (N=78 199), leveraging longitudinal data, incorporating corrected standard errors to account for underestimation of interaction estimate variances and evaluating evidence for pathway enrichment. Although no loci achieved genome-wide significance (P<5 × 10 -8 ), we found suggestive evidence (P<5 × 10 -6 ) for SNPs modifying the thiazide-QT association at 22 loci, including ion transport loci (for example, NELL1, KCNQ3). The biologic plausibility of our suggestive results and simulations demonstrating modest power to detect interaction effects at genome-wide significant levels indicate that larger studies and innovative statistical methods are warranted in future efforts evaluating thiazide-SNP interactions.

Genome-wide association studies (GWAS) for schizophrenia have identified over 100 loci encoding >500 genes. It is unclear whether any of these genes, other than dopamine receptor D 2 , are immediately relevant to antipsychotic effects or represent novel antipsychotic targets. We applied an in vivo molecular approach to this question by performing RNA sequencing of brain tissue from mice chronically treated with the antipsychotic haloperidol or vehicle. We observed significant enrichments of haloperidol-regulated genes in schizophrenia GWAS loci and in schizophrenia-associated biological pathways. Our findings provide empirical support for overlap between genetic variation underlying the pathophysiology of schizophrenia and the molecular effects of a prototypical antipsychotic.

Molecular characterization of balanced chromosomal abnormalities constitutes a powerful tool in understanding the pathogenic mechanisms of complex genetic disorders. Here we report a male with severe global developmental delay in the presence of a complex karyotype and normal microarray and exome studies. The subject, referred to as DGAP294, has two de novo apparently balanced translocations involving chromosomes 1 and 14, and chromosomes 4 and 10, disrupting several different transcripts of adhesion G protein-coupled receptor L2 (ADGRL2) and protocadherin 15 (PCDH15). In addition, a maternally inherited inversion disrupts peptidyl arginine deiminase types 3 and 4 (PADI3 and PADI4) on chromosome 1. None of these gene disruptions explain the patient's phenotype. Using genome regulatory annotations and chromosome conformation data, we predict a position effect ~370 kb upstream of a translocation breakpoint located at 14q12. The position effect involves forkhead box G1 (FOXG1), mutations in which are associated with the congenital form of Rett syndrome and FOXG1 syndrome. We believe the FOXG1 position effect largely accounts for the clinical phenotype in DGAP294, which can be classified as FOXG1 syndrome like. Our findings emphasize the significance of not only analyzing disrupted genes by chromosomal rearrangements, but also evaluating potential long-range position effects in clinical diagnoses.

Neuroimaging studies demonstrate gray matter (GM) macrostructural abnormalities in patients with schizophrenia (SCZ). While ex-vivo and genetic studies suggest cellular pathology associated with abnormal neurodevelopmental processes in SCZ, few in-vivo measures have been proposed to target microstructural GM organization. Here, we use diffusion heterogeneity- to study GM microstructure in SCZ. Structural and diffusion magnetic resonance imaging (MRI) were acquired on a 3 Tesla scanner in 46 patients with SCZ and 37 matched healthy controls (HC). After correction for free water, diffusion heterogeneity as well as commonly used diffusion measures FA and MD and volume were calculated for the four cortical lobes on each hemisphere, and compared between groups. Patients with early course SCZ exhibited higher diffusion heterogeneity in the GM of the frontal lobes compared to controls. Diffusion heterogeneity of the frontal lobe showed excellent discrimination between patients and HC, while none of the commonly used diffusion measures such as FA or MD did. Higher diffusion heterogeneity in the frontal lobes in early SCZ may be due to abnormal brain maturation (migration, pruning) before and during adolescence and early adulthood. Further studies are needed to investigate the role of heterogeneity as potential biomarker for SCZ risk.

Scope: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption., Methods and Results: A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10 -7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 10 -8) such that each serving of low-fat dairy was associated with 0.225 kg m -2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure., Conclusion: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight., (© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Candida spp. are the fourth leading cause of nosocomial blood stream infections in North America. Candida glabrata is the second most frequently isolated species, and rapid development of antifungal resistance has made treatment a challenge. In this study, we investigate the therapeutic potential of metformin, a biguanide with well-established action for diabetes, as an antifungal agent against C. glabrata. Both wild type and antifungal-resistant isolates of C. glabrata were subjected to biguanide and biguanide-antifungal combination treatment. Metformin, as well as other members of the biguanide family, were found to have antifungal activity against C. glabrata, with MIC 50 of 9.34 ± 0.16 mg/mL, 2.09 ± 0.04 mg/mL and 1.87 ± 0.05 mg/mL for metformin, phenformin and buformin, respectively. We demonstrate that biguanides enhance the activity of several antifungal drugs, including voriconazole, fluconazole, and amphotericin, but not micafungin. The biguanide-antifungal combinations allowed for additional antifungal effects, with fraction inhibition concentration indexes ranging from 0.5 to 1. Furthermore, metformin was able to lower antifungal MIC 50 in voriconazole and fluconazole-resistant clinical isolates of C. glabrata. We also observed growth reduction of C. glabrata with rapamycin and an FIC of 0.84 ± 0.09 when combined with metformin, suggesting biguanide action in C. glabrata may be related to inhibition of the mTOR complex. We conclude that the biguanide class has direct antifungal therapeutic potential and enhances the activity of select antifungals in the treatment of resistant C. glabrata isolates. These data support the further investigation of biguanides in the combination treatment of serious fungal infections.

Biobanks and national registries represent a powerful tool for genomic discovery, but rely on diagnostic codes that may be unreliable and fail to capture the relationship between related diagnoses. We developed an efficient means of conducting genome-wide association studies using combinations of diagnostic codes from electronic health records (EHR) for 10845 participants in a biobanking program at two large academic medical centers. Specifically, we applied latent Dirichilet allocation to fit 50 disease topics based on diagnostic codes, then conducted genome-wide common-variant association for each topic. In sensitivity analysis, these results were contrasted with those obtained from traditional single-diagnosis phenome-wide association analysis, as well as those in which only a subset of diagnostic codes are included per topic. In meta-analysis across three biobank cohorts, we identified 23 disease-associated loci with p<1e-15, including previously associated autoimmune disease loci. In all cases, observed significant associations were of greater magnitude than for single phenome-wide diagnostic codes, and incorporation of less strongly-loading diagnostic codes enhanced association. This strategy provides a more efficient means of phenome-wide association in biobanks with coded clinical data.

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci ( P < 5 × 10 -8 ), including variants near the GLP2R , GIP , and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology., (© 2017 by the American Diabetes Association.)

Objective: The relationship between insomnia symptoms and cognitive performance is unclear, particularly at the population level. We conducted the largest examination of this association to date through analysis of the UK Biobank, a large population-based sample of adults aged 40-69 years. We also sought to determine associations between cognitive performance and self-reported chronotype, sleep medication use and sleep duration., Methods: This cross-sectional, population-based study involved 477,529 participants, comprising 133,314 patients with frequent insomnia symptoms (age: 57.4 ± 7.7 years; 62.1% female) and 344,215 controls without insomnia symptoms (age: 56.1 ± 8.2 years; 52.0% female). Cognitive performance was assessed by a touchscreen test battery probing reasoning, basic reaction time, numeric memory, visual memory, and prospective memory. Adjusted models included relevant demographic, clinical, and sleep variables., Results: Frequent insomnia symptoms were associated with cognitive impairment in unadjusted models; however, these effects were reversed after full adjustment, leaving those with frequent insomnia symptoms showing statistically better cognitive performance over those without. Relative to intermediate chronotype, evening chronotype was associated with superior task performance, while morning chronotype was associated with the poorest performance. Sleep medication use and both long (>9 h) and short (<7 h) sleep durations were associated with impaired performance., Conclusions: Our results suggest that after adjustment for potential confounding variables, frequent insomnia symptoms may be associated with a small statistical advantage, which is unlikely to be clinically meaningful, on simple neurocognitive tasks. Further work is required to examine the mechanistic underpinnings of an apparent evening chronotype advantage in cognitive performance and the impairment associated with morning chronotype, sleep medication use, and sleep duration extremes., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes., Methods & Findings: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 × 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants., Conclusions: As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.

Objective: To examine the impact of pharmacologic treatment for depression on obstetric outcomes in women treated for depression during the 2 years prior to pregnancy., Study Design: Observational cohort study among 2859 women treated for depression during the 2 years prior to pregnancy. The primary exposure was any antidepressant treatment during pregnancy. Secondary analyses examined the impact of treatment by period of antidepressant exposure. Multivariable logistic regression models as well as propensity score analysis was utilized., Results: Among 2859 women, 1648 (58%) were treated with antidepressant medication during pregnancy. Women who received antidepressants had no difference in preterm and early-term deliveries, Apgar scores, and small for gestational age (SGA); they had a lower likelihood of breastfeeding (adjusted odds ratio (AOR) 0.69, (95% confidence interval (CI): 0.51 to 0.94)). In secondary analysis, women who used antidepressants all three trimesters who delivered at term were more likely to deliver early term (AOR 1.36, (95% CI: 1.09 to 1.72)). Women who were treated with antidepressants only during the first and second trimesters had a reduced likelihood of SGA (AOR: 0.51 (95% CI: 0.32 to 0.83)). Generally similar results were observed with propensity score analysis., Conclusion: Antidepressant exposure during pregnancy does not confer an increased risk of preterm birth nor growth restriction in women recently treated for depression, but also does not appear to markedly improve these outcomes.

Identifying appropriate molecular targets is a critical step in drug development. Despite many advantages, the traditional tools of observational epidemiology and cellular or animal models of disease can be misleading in identifying causal pathways likely to lead to successful therapeutics. Here, we review some favorable aspects of human genetics studies that have the potential to accelerate drug target discovery. These include using genetic studies to identify pathways relevant to human disease, leveraging human genetics to discern causal relationships between biomarkers and disease, and studying genetic variation in humans to predict the potential efficacy and safety of inhibitory compounds aimed at molecular targets. We present some examples taken from studies of plasma lipids and coronary artery disease to highlight how human genetics can accelerate therapeutics development., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Schizophrenia is characterized by neuropsychological deficits across many cognitive domains. Cognitive phenotypes with high heritability and genetic overlap with schizophrenia liability can help elucidate the mechanisms leading from genes to psychopathology. We performed a meta-analysis of 170 published twin and family heritability studies of >800 000 nonpsychiatric and schizophrenia subjects to accurately estimate heritability across many neuropsychological tests and cognitive domains. The proportion of total variance of each phenotype due to additive genetic effects (A), shared environment (C), and unshared environment and error (E), was calculated by averaging A, C, and E estimates across studies and weighting by sample size. Heritability ranged across phenotypes, likely due to differences in genetic and environmental effects, with the highest heritability for General Cognitive Ability (32%-67%), Verbal Ability (43%-72%), Visuospatial Ability (20%-80%), and Attention/Processing Speed (28%-74%), while the lowest heritability was observed for Executive Function (20%-40%). These results confirm that many cognitive phenotypes are under strong genetic influences. Heritability estimates were comparable in nonpsychiatric and schizophrenia samples, suggesting that environmental factors and illness-related moderators (eg, medication) do not substantially decrease heritability in schizophrenia samples, and that genetic studies in schizophrenia samples are informative for elucidating the genetic basis of cognitive deficits. Substantial genetic overlap between cognitive phenotypes and schizophrenia liability (average rg = -.58) in twin studies supports partially shared genetic etiology. It will be important to conduct comparative studies in well-powered samples to determine whether the same or different genes and genetic variants influence cognition in schizophrenia patients and the general population., (© The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Hyperglycemia is a common complication after ischemic stroke, but its link to worse outcome is not well understood. We hypothesized that hyperglycemia may reflect an impaired metabolic response that is associated with worse cytotoxic brain injury. We performed retrospective analysis of magnetic resonance imaging from a cohort of acute ischemic stroke patients prospectively collected from 2006 to 2010 with baseline demographic and laboratory data as well as three-month outcomes. The severity of cytotoxic injury was quantified in vivo using apparent diffusion coefficient imaging by measuring the signal intensity within the stroke relative to the normal signal intensity of the contralateral hemisphere. Both hyperglycemia and lower apparent diffusion coefficient signal were associated with worse outcome after ischemic stroke (OR 0.239, p = 0.017; OR 1.11, p < 0.0001, respectively). Hyperglycemia was also associated with lower apparent diffusion coefficient (r = -0.32, p < 0.001). In multivariate analysis, apparent diffusion coefficient but not hyperglycemia was associated with outcome, suggesting that cytotoxicity may mediate the effect of hyperglycemia. For interventions designed to target hyperglycemia in acute ischemic stroke, a concomitant effect on the evolution of apparent diffusion coefficient may provide insight into whether hyperglycemia leads to or reflects worse cytotoxic injury.

Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. Genome-wide association study analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation. This study aims to discover new genetic loci associated with heart rate from Exome Chip meta-analyses.Heart rate was measured from either elecrtrocardiograms or pulse recordings. We meta-analysed heart rate association results from 104 452 European-ancestry individuals from 30 cohorts, genotyped using the Exome Chip. Twenty-four variants were selected for follow-up in an independent dataset (UK Biobank, N = 134 251). Conditional and gene-based testing was undertaken, and variants were investigated with bioinformatics methods.We discovered five novel heart rate loci, and one new independent low-frequency non-synonymous variant in an established heart rate locus (KIAA1755). Lead variants in four of the novel loci are non-synonymous variants in the genes C10orf71, DALDR3, TESK2 and SEC31B. The variant at SEC31B is significantly associated with SEC31B expression in heart and tibial nerve tissue. Further candidate genes were detected from long-range regulatory chromatin interactions in heart tissue (SCD, SLF2 and MAPK8). We observed significant enrichment in DNase I hypersensitive sites in fetal heart and lung. Moreover, enrichment was seen for the first time in human neuronal progenitor cells (derived from embryonic stem cells) and fetal muscle samples by including our novel variants.Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies., (© The Author 2017. Published by Oxford University Press.)

Little is known about the unique contribution of schools vs neighborhoods in driving adolescent marijuana use. This study examined the relative contribution of each setting and the influence of school and neighborhood socioeconomic status on use. We performed a series of cross-classified multilevel logistic models predicting past 30-day adolescent (N = 18 329) and young adult (N = 13 908) marijuana use using data from Add Health. Marijuana use differed by age, sex, race/ethnicity, and public assistance in adjusted models. Variance parameters indicated a high degree of clustering by school (σ2 = 0.30) and less pronounced clustering by neighborhood (σ2 = 0.06) in adolescence when accounting for both levels simultaneously in a cross-classified multilevel model. Clustering by school persisted into young adulthood (σ2 = 0.08). Parental receipt of public assistance increased the likelihood of use during adolescence (odds ratio = 1.39; 95% confidence interval: 1.19-1.59), and higher parental education was associated with increased likelihood of use in young adulthood. These findings indicate that both contexts may be promising locations for intervention., Competing Interests: DECLARATION OF CONFLICTING INTERESTS: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Copy number variants (CNVs) are major contributors to genomic imbalance disorders. Phenotyping of 137 unrelated deletion and reciprocal duplication carriers of the distal 16p11.2 220 kb BP2-BP3 interval showed that these rearrangements are associated with autism spectrum disorders and mirror phenotypes of obesity/underweight and macrocephaly/microcephaly. Such phenotypes were previously associated with rearrangements of the non-overlapping proximal 16p11.2 600 kb BP4-BP5 interval. These two CNV-prone regions at 16p11.2 are reciprocally engaged in complex chromatin looping, as successfully confirmed by 4C-seq, fluorescence in situ hybridization and Hi-C, as well as coordinated expression and regulation of encompassed genes. We observed that genes differentially expressed in 16p11.2 BP4-BP5 CNV carriers are concomitantly modified in their chromatin interactions, suggesting that disruption of chromatin interplays could participate in the observed phenotypes. We also identified cis- and trans-acting chromatin contacts to other genomic regions previously associated with analogous phenotypes. For example, we uncovered that individuals with reciprocal rearrangements of the trans-contacted 2p15 locus similarly display mirror phenotypes on head circumference and weight. Our results indicate that chromosomal contacts' maps could uncover functionally and clinically related genes.

Obsessive-compulsive disorder (OCD) is a chronic, disabling condition with inadequate treatment options that leave most patients with substantial residual symptoms. Structural, neurochemical, and behavioral findings point to a significant role for basal ganglia circuits and for the glutamate system in OCD. Genetic linkage and association studies in OCD point to SLC1A1 , which encodes the neuronal glutamate/aspartate/cysteine transporter excitatory amino acid transporter 3 (EAAT3)/excitatory amino acid transporter 1 (EAAC1). However, no previous studies have investigated EAAT3 in basal ganglia circuits or in relation to OCD-related behavior. Here, we report a model of Slc1a1 loss based on an excisable STOP cassette that yields successful ablation of EAAT3 expression and function. Using amphetamine as a probe, we found that EAAT3 loss prevents expected increases in ( i ) locomotor activity, ( ii ) stereotypy, and ( iii ) immediate early gene induction in the dorsal striatum following amphetamine administration. Further, Slc1a1 -STOP mice showed diminished grooming in an SKF-38393 challenge experiment, a pharmacologic model of OCD-like grooming behavior. This reduced grooming is accompanied by reduced dopamine D 1 receptor binding in the dorsal striatum of Slc1a1 -STOP mice. Slc1a1 -STOP mice also exhibit reduced extracellular dopamine concentrations in the dorsal striatum both at baseline and following amphetamine challenge. Viral-mediated restoration of Slc1a1 /EAAT3 expression in the midbrain but not in the striatum results in partial rescue of amphetamine-induced locomotion and stereotypy in Slc1a1 -STOP mice, consistent with an impact of EAAT3 loss on presynaptic dopaminergic function. Collectively, these findings indicate that the most consistently associated OCD candidate gene impacts basal ganglia-dependent repetitive behaviors., Competing Interests: Conflict of interest statement: C.K. has received research funding from Forest. C.K.J. has received research funding from AstraZeneca, Johnson & Johnson, Bristol-Myers Squibb, and Seaside Therapeutics. J.V. has consulted or served on advisory boards for Roche, Novartis, and SynapDx and has received research funding from Roche, Novartis, SynapDx, Seaside Therapeutics, and Forest.

Huntington's disease (HD) reflects dominant consequences of a CAG repeat expansion mutation in HTT. Expanded CAG repeat size is the primary determinant of age at onset and age at death in HD. Although HD pathogenesis is driven by the expanded CAG repeat, whether the mutation influences the expression levels of mRNA and protein from the disease allele is not clear due to the lack of sensitive allele-specific quantification methods and the presence of confounding factors. To determine the impact of CAG expansion at the molecular level, we have developed novel allele-specific HTT mRNA and protein quantification methods based on principles of multiplex ligation-dependent probe amplification and targeted MS/MS parallel reaction monitoring, respectively. These assays, exhibiting high levels of specificity and sensitivity, were designed to distinguish allelic products based upon expressed polymorphic variants in HTT, including rs149 109 767. To control for other cis-haplotype variations, we applied allele-specific quantification assays to a panel of HD lymphoblastoid cell lines, each carrying the major European disease haplotype (i.e. hap.01) on the mutant chromosome. We found that steady state levels of HTT mRNA and protein were not associated with expanded CAG repeat length. Rather, the products of mutant and normal alleles, both mRNA and protein, were balanced, thereby arguing that a cis-regulatory effect of the expanded CAG repeat is not a critical component of the underlying mechanism of HD. These robust allele-specific assays could prove valuable for monitoring the impact of allele-specific gene silencing strategies currently being explored as therapeutic interventions in HD., (© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Cockayne syndrome is an autosomal recessive disorder principally characterized by postnatal growth failure and progressive neurological dysfunction, due primarily to mutations in ERCC6 and ERCC8. Here, we report our diagnostic experience for two patients in a Chinese family suspected on clinical grounds to have Cockayne syndrome. Using multiple molecular techniques, including whole exome sequencing, array comparative genomic hybridization and quantitative polymerase chain reaction, we identified compound heterozygosity for a maternal splicing variant (chr5:60195556, NM&#95;000082:c.618-2A > G) and a paternal complex deletion/inversion/deletion rearrangement removing exon 4 of ERCC8, confirming the suspected pathogenesis in these two subjects. Microhomology (TAA and AGCT) at the breakpoints indicated that microhomology-mediated FoSTeS events were involved in this complex ERCC8 rearrangement. This diagnostic experience illustrates the value of high-throughput genomic technologies combined with detailed phenotypic assessment in clinical genetic diagnosis.

Intron retention (IR) occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA. We have developed a program and database called IRFinder to accurately detect IR from mRNA sequencing data. Analysis of 2573 samples showed that IR occurs in all tissues analyzed, affects over 80% of all coding genes and is associated with cell differentiation and the cell cycle. Frequently retained introns are enriched for specific RNA binding protein sites and are often retained in clusters in the same gene. IR is associated with lower protein levels and intron-retaining transcripts that escape nonsense-mediated decay are not actively translated.

Objective: We sought to identify genetic causes of early onset epileptic encephalopathies with burst suppression (Ohtahara syndrome and early myoclonic encephalopathy) and evaluate genotype-phenotype correlations., Methods: We enrolled 33 patients with a referral diagnosis of Ohtahara syndrome or early myoclonic encephalopathy without malformations of cortical development. We performed detailed phenotypic assessment including seizure presentation, electroencephalography, and magnetic resonance imaging. We confirmed burst suppression in 28 of 33 patients. Research-based exome sequencing was performed for patients without a previously identified molecular diagnosis from clinical evaluation or a research-based epilepsy gene panel., Results: In 17 of 28 (61%) patients with confirmed early burst suppression, we identified variants predicted to be pathogenic in KCNQ2 (n = 10), STXBP1 (n = 2), SCN2A (n = 2), PNPO (n = 1), PIGA (n = 1), and SEPSECS (n = 1). In 3 of 5 (60%) patients without confirmed early burst suppression, we identified variants predicted to be pathogenic in STXBP1 (n = 2) and SCN2A (n = 1). The patient with the homozygous PNPO variant had a low cerebrospinal fluid pyridoxal-5-phosphate level. Otherwise, no early laboratory or clinical features distinguished the cases associated with pathogenic variants in specific genes from each other or from those with no prior genetic cause identified., Interpretation: We characterize the genetic landscape of epileptic encephalopathy with burst suppression, without brain malformations, and demonstrate feasibility of genetic diagnosis with clinically available testing in >60% of our cohort, with KCNQ2 implicated in one-third. This electroclinical syndrome is associated with pathogenic variation in SEPSECS. Ann Neurol 2017;81:419-429., (© 2017 American Neurological Association.)

Objective: Genome-wide association studies (GWAS) have been successful at identifying associations with stroke and stroke subtypes, but have not yet identified any associations solely with small vessel stroke (SVS). SVS comprises one quarter of all ischemic stroke and is a major manifestation of cerebral small vessel disease, the primary cause of vascular cognitive impairment. Studies across neurological traits have shown that younger-onset cases have an increased genetic burden. We leveraged this increased genetic burden by performing an age-at-onset informed GWAS meta-analysis, including a large younger-onset SVS population, to identify novel associations with stroke., Methods: We used a three-stage age-at-onset informed GWAS to identify novel genetic variants associated with stroke. On identifying a novel locus associated with SVS, we assessed its influence on other small vessel disease phenotypes, as well as on messenger RNA (mRNA) expression of nearby genes, and on DNA methylation of nearby CpG sites in whole blood and in the fetal brain., Results: We identified an association with SVS in 4,203 cases and 50,728 controls on chromosome 16q24.2 (odds ratio [OR; 95% confidence interval {CI}] = 1.16 [1.10-1.22]; p = 3.2 × 10 -9 ). The lead single-nucleotide polymorphism (rs12445022) was also associated with cerebral white matter hyperintensities (OR [95% CI] = 1.10 [1.05-1.16]; p = 5.3 × 10 -5 ; N = 3,670), but not intracerebral hemorrhage (OR [95% CI] = 0.97 [0.84-1.12]; p = 0.71; 1,545 cases, 1,481 controls). rs12445022 is associated with mRNA expression of ZCCHC14 in arterial tissues (p = 9.4 × 10 -7 ) and DNA methylation at probe cg16596957 in whole blood (p = 5.3 × 10 -6 )., Interpretation: 16q24.2 is associated with SVS. Associations of the locus with expression of ZCCHC14 and DNA methylation suggest the locus acts through changes to regulatory elements. Ann Neurol 2017;81:383-394., (© 2016 The Authors. Annals of Neurology published by Wiley Periodicals, Inc. on behalf of American Neurological Association.)

Although the pathogenesis of schizophrenia (SCZ) is proposed to involve alterations of neural circuits via synaptic dysfunction, the underlying molecular mechanisms remain poorly understood. Recent exome sequencing studies of SCZ have uncovered numerous single-nucleotide variants (SNVs); however, the majority of these SNVs have unknown functional consequences, leaving their disease relevance uncertain. Filling this knowledge gap requires systematic application of quantitative and scalable assays to assess known and novel biological functions of genes. Here we demonstrate loss-of-function effects of multiple rare coding SNVs found in SCZ subjects in the GIT1 (G protein-coupled receptor kinase interacting ArfGAP 1) gene using functional cell-based assays involving coexpression of GIT1 and PAK3 (p21 protein (Cdc42/Rac)-activated kinase 3). Most notably, a GIT1-R283W variant reported in four independent SCZ cases was defective in activating PAK3 as well as MAPK (mitogen-activated protein kinase). Similar functional deficits were found for a de novo SCZ variant GIT1-S601N. Additional assays revealed deficits in the capacity of GIT1-R283W to stimulate PAK phosphorylation in cultured hippocampal neurons. In addition, GIT1-R283W showed deficits in the induction of GAD1 (glutamate decarboxylase 1) protein expression. Extending these functional assays to 10 additional rare GIT1 variants revealed the existence of an allelic series with the majority of the SCZ case variants exhibiting loss of function toward MAPK activation in a manner correlated with loss of PAK3 activation. Taken together, we propose that rare variants in GIT1, along with other genetic and environmental factors, cause dysregulation of PAK3 leading to synaptic deficits in SCZ.

Neuropsychiatric disorders are common health problems affecting approximately 1% of the population. Twin, adoption, and family studies have displayed a strong genetic component for many of these disorders; however, the underlying pathophysiological mechanisms and neural substrates remain largely unknown. Given the critical need for new diagnostic markers and disease-modifying treatments, expanding the focus of genomic studies of neuropsychiatric disorders to include the role of non-coding RNAs (ncRNAs) is of growing interest. Of known types of ncRNAs, microRNAs (miRNAs) are 20-25-nucleotide, single-stranded, molecules that regulate gene expression through post-transcriptional mechanisms and have the potential to coordinately regulate complex regulatory networks. In this review, we summarize the current knowledge on miRNA alteration/dysregulation in neuropsychiatric disorders, with a special emphasis on schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). With an eye toward the future, we also discuss the diagnostic and prognostic potential of miRNAs for neuropsychiatric disorders in the context of personalized treatments and network medicine., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Variants at microRNA-137 (MIR137), one of the most strongly associated schizophrenia risk loci identified to date, have been associated with poorer cognitive performance. As microRNA-137 is known to regulate the expression of ~1900 other genes, including several that are independently associated with schizophrenia, we tested whether this gene set was also associated with variation in cognitive performance. Our analysis was based on an empirically derived list of genes whose expression was altered by manipulation of MIR137 expression. This list was cross-referenced with genome-wide schizophrenia association data to construct individual polygenic scores. We then tested, in a sample of 808 patients and 192 controls, whether these risk scores were associated with altered performance on cognitive functions known to be affected in schizophrenia. A subgroup of healthy participants also underwent functional imaging during memory (n=108) and face processing tasks (n=83). Increased polygenic risk within the empirically derived miR-137 regulated gene score was associated with significantly lower performance on intelligence quotient, working memory and episodic memory. These effects were observed most clearly at a polygenic threshold of P=0.05, although significant results were observed at all three thresholds analyzed. This association was found independently for the gene set as a whole, excluding the schizophrenia-associated MIR137 SNP itself. Analysis of the spatial working memory fMRI task further suggested that increased risk score (thresholded at P=10 -5 ) was significantly associated with increased activation of the right inferior occipital gyrus. In conclusion, these data are consistent with emerging evidence that MIR137 associated risk for schizophrenia may relate to its broader downstream genetic effects.

Genetic variants affecting hematopoiesis can influence commonly measured blood cell traits. To identify factors that affect hematopoiesis, we performed association studies for blood cell traits in the population-based Estonian Biobank using high-coverage whole-genome sequencing (WGS) in 2,284 samples and SNP genotyping in an additional 14,904 samples. Using up to 7,134 samples with available phenotype data, our analyses identified 17 associations across 14 blood cell traits. Integration of WGS-based fine-mapping and complementary epigenomic datasets provided evidence for causal mechanisms at several loci, including at a previously undiscovered basophil count-associated locus near the master hematopoietic transcription factor CEBPA The fine-mapped variant at this basophil count association near CEBPA overlapped an enhancer active in common myeloid progenitors and influenced its activity. In situ perturbation of this enhancer by CRISPR/Cas9 mutagenesis in hematopoietic stem and progenitor cells demonstrated that it is necessary for and specifically regulates CEBPA expression during basophil differentiation. We additionally identified basophil count-associated variation at another more pleiotropic myeloid enhancer near GATA2, highlighting regulatory mechanisms for ordered expression of master hematopoietic regulators during lineage specification. Our study illustrates how population-based genetic studies can provide key insights into poorly understood cell differentiation processes of considerable physiologic relevance., Competing Interests: The authors declare no conflict of interest.

We performed a genome-wide association study of 6447 bipolar disorder (BD) cases and 12 639 controls from the International Cohort Collection for Bipolar Disorder (ICCBD). Meta-analysis was performed with prior results from the Psychiatric Genomics Consortium Bipolar Disorder Working Group for a combined sample of 13 902 cases and 19 279 controls. We identified eight genome-wide significant, associated regions, including a novel associated region on chromosome 10 (rs10884920; P=3.28 × 10 -8 ) that includes the brain-enriched cytoskeleton protein adducin 3 (ADD3), a non-coding RNA, and a neuropeptide-specific aminopeptidase P (XPNPEP1). Our large sample size allowed us to test the heritability and genetic correlation of BD subtypes and investigate their genetic overlap with schizophrenia and major depressive disorder. We found a significant difference in heritability of the two most common forms of BD (BD I SNP-h 2 =0.35; BD II SNP-h 2 =0.25; P=0.02). The genetic correlation between BD I and BD II was 0.78, whereas the genetic correlation was 0.97 when BD cohorts containing both types were compared. In addition, we demonstrated a significantly greater load of polygenic risk alleles for schizophrenia and BD in patients with BD I compared with patients with BD II, and a greater load of schizophrenia risk alleles in patients with the bipolar type of schizoaffective disorder compared with patients with either BD I or BD II. These results point to a partial difference in the genetic architecture of BD subtypes as currently defined.

Objective: Recent studies have shown that positron emission tomography (PET) tracer AV-1451 exhibits high binding affinity for paired helical filament (PHF)-tau pathology in Alzheimer's brains. However, the ability of this ligand to bind to tau lesions in other tauopathies remains controversial. Our goal was to examine the correlation of in vivo and postmortem AV-1451 binding patterns in three autopsy-confirmed non-Alzheimer tauopathy cases., Methods: We quantified in vivo retention of [F-18]-AV-1451 and performed autoradiography, [H-3]-AV-1451 binding assays, and quantitative tau measurements in postmortem brain samples from two progressive supranuclear palsy (PSP) cases and a MAPT P301L mutation carrier. They all underwent [F-18]-AV-1451 PET imaging before death., Results: The three subjects exhibited [F-18]-AV-1451 in vivo retention predominantly in basal ganglia and midbrain. Neuropathological examination confirmed the PSP diagnosis in the first two subjects; the MAPT P301L mutation carrier had an atypical tauopathy characterized by grain-like tau-containing neurites in gray and white matter with heaviest burden in basal ganglia. In all three cases, autoradiography failed to show detectable [F-18]-AV-1451 binding in multiple brain regions examined, with the exception of entorhinal cortex (reflecting incidental age-related neurofibrillary tangles) and neuromelanin-containing neurons in the substantia nigra (off-target binding). The lack of a consistent significant correlation between in vivo [F-18]-AV-1541 retention and postmortem in vitro binding and tau measures in these cases suggests that this ligand has low affinity for tau lesions primarily made of straight tau filaments., Interpretation: AV-1451 may have limited utility for in vivo selective and reliable detection of tau aggregates in these non-Alzheimer tauopathies. ANN NEUROL 2017;81:117-128., (© 2016 American Neurological Association.)