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      Genome-Wide and Gene-Based Association Studies of Anxiety Disorders in European and African American Samples

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          Abstract

          Anxiety disorders (ADs) are common mental disorders caused by a combination of genetic and environmental factors. Since ADs are highly comorbid with each other, partially due to shared genetic basis, studying AD phenotypes in a coordinated manner may be a powerful strategy for identifying potential genetic loci for ADs. To detect these loci, we performed genome-wide association studies (GWAS) of ADs. In addition, as a complementary approach to single-locus analysis, we also conducted gene- and pathway-based analyses. GWAS data were derived from the control sample of the Molecular Genetics of Schizophrenia (MGS) project (2,540 European American and 849 African American subjects) genotyped on the Affymetrix GeneChip 6.0 array. We applied two phenotypic approaches: (1) categorical case-control comparisons (CC) based upon psychiatric diagnoses, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. Linear and logistic models were used to analyse the association with ADs using FS and CC traits, respectively. At the single locus level, no genome-wide significant association was found. A trans-population gene-based meta-analysis across both ethnic subsamples using FS identified three genes ( MFAP3L on 4q32.3, NDUFAB1 and PALB2 on 16p12) with genome-wide significance (false discovery rate (FDR] <5%). At the pathway level, several terms such as transcription regulation, cytokine binding, and developmental process were significantly enriched in ADs (FDR <5%). Our approaches studying ADs as quantitative traits and utilizing the full GWAS data may be useful in identifying susceptibility genes and pathways for ADs.

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          Most cited references32

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          Control of BRCA2 cellular and clinical functions by a nuclear partner, PALB2.

          BRCA2 mutations predispose carriers to breast and ovarian cancer and can also cause other cancers and Fanconi anemia. BRCA2 acts as a "caretaker" of genome integrity by enabling homologous recombination (HR)-based, error-free DNA double-strand break repair (DSBR) and intra-S phase DNA damage checkpoint control. Described here is the identification of PALB2, a BRCA2 binding protein. PALB2 colocalizes with BRCA2 in nuclear foci, promotes its localization and stability in key nuclear structures (e.g., chromatin and nuclear matrix), and enables its recombinational repair and checkpoint functions. In addition, multiple, germline BRCA2 missense mutations identified in breast cancer patients but of heretofore unknown biological/clinical consequence appear to disrupt PALB2 binding and disable BRCA2 HR/DSBR function. Thus, PALB2 licenses key cellular biochemical properties of BRCA2 and ensures its tumor suppression function.
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            Diagnostic interview for genetic studies. Rationale, unique features, and training. NIMH Genetics Initiative.

            This article reports on the development and reliability of the Diagnostic Interview for Genetic Studies (DIGS), a clinical interview especially constructed for the assessment of major mood and psychotic disorders and their spectrum conditions. The DIGS, which was developed and piloted as a collaborative effort of investigators from sites in the National Institute of Mental Health (NIMH) Genetics Initiative, has the following additional features: (1) polydiagnostic capacity; (2) a detailed assessment of the course of the illness, chronology of psychotic and mood syndromes, and comorbidity; (3) additional phenomenologic assessments of symptoms; and (4) algorithmic scoring capability. The DIGS is designed to be employed by interviewers who exercise significant clinical judgment and who summarize information in narrative form as well as in ratings. A two-phase test-retest (within-site, between-site) reliability study was carried out for DSM-III-R criteria-based major depression, bipolar disorder, schizophrenia, and schizoaffective disorder. Reliabilities using algorithms were excellent (0.73 to 0.95), except for schizoaffective disorder, for which disagreement on estimates of duration of mood syndromes relative to psychosis reduced reliability. A final best-estimate process using medical records and information from relatives as well as algorithmic diagnoses is expected to be more reliable in making these distinctions. The DIGS should be useful as part of archival data gathering for genetic studies of major affective disorders, schizophrenia, and related conditions.
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              Common disorders are quantitative traits.

              After drifting apart for 100 years, the two worlds of genetics - quantitative genetics and molecular genetics - are finally coming together in genome-wide association (GWA) research, which shows that the heritability of complex traits and common disorders is due to multiple genes of small effect size. We highlight a polygenic framework, supported by recent GWA research, in which qualitative disorders can be interpreted simply as being the extremes of quantitative dimensions. Research that focuses on quantitative traits - including the low and high ends of normal distributions - could have far-reaching implications for the diagnosis, treatment and prevention of the problematic extremes of these traits.

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                12 November 2014
                : 9
                : 11
                : e112559
                Affiliations
                [1 ]Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
                [2 ]Department of Neuropsychiatry, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
                [3 ]Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
                [4 ]Department of Pharmacy, Center for Biomarker Research and Personalized Medicine, Virginia Commonwealth University, Richmond, Virginia, United States of America
                University Of São Paulo, Brazil
                Author notes

                Competing Interests: One of the co-authors, Brion S. Maher, is a PLOS ONE Editorial Board member. This does not alter the authors' adherence to PLOS ONE Editorial policies and criteria.

                Conceived and designed the experiments: TO BSM EJV JMH. Analyzed the data: TO BSM SHA JLM. Wrote the paper: TO BSM SHA JLM EJV JMH.

                Article
                PONE-D-14-33613
                10.1371/journal.pone.0112559
                4229211
                25390645
                d0a698ac-f8b5-4906-b9ec-a05b3d74114d
                Copyright @ 2014

                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.

                History
                : 29 July 2014
                : 7 October 2014
                Page count
                Pages: 8
                Funding
                This research was supported by NIH grant R01MH087646 (JMH). Samples and associated phenotype data for the MGS study were collected under the following grants: NIMH Schizophrenia Genetics Initiative U01s: MH046276 (CR Cloninger), MH46289 (C Kaufmann), and MH46318 (MT Tsuang); and MGS Part 1 (MGS1) and Part 2 (MGS2) R01s: MH67257 (NG Buccola), MH59588 (BJ Mowry), MH59571 (PV Gejman), MH59565 (Robert Freedman), MH59587 (F Amin), MH60870 (WF Byerley), MH59566 (DW Black), MH59586 (JM Silverman), MH61675 (DF Levinson), and MH60879 (CR Cloninger). TO was supported by a research fellowship from the Japan Society for the Promotion of Science (no. 21–8373). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Clinical Genetics
                Epidemiology
                Biomarker Epidemiology
                Genetic Epidemiology
                Mental Health and Psychiatry
                Neuropsychiatric Disorders
                Anxiety Disorders
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Factor Analysis
                Multivariate Analysis
                Research and Analysis Methods
                Database and Informatics Methods
                Health Informatics
                Mathematical and Statistical Techniques
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files.

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                Uncategorized

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