Schizophrenia (SZ) represents a significant and costly public health burden. Recently, we have witnessed the emergence of the first molecular insights into the etiopathogenic mechanisms of SZ, via the first genome-wide association studies (GWAS) with sufficient case-control sample sizes to detect allelic effects. Importantly, a polygenic signature, which includes genome-wide significant common genetic variants of small effect, has been clearly demonstrated to influence SZ risk. The availability of well-defined risk factors makes it possible, for the first time, to address several critical questions about the genetic architecture of SZ and its component phenotypes and endophenotypes. The overarching goals of this K01 proposal are 1) to test polygenic risk score prediction of dimensional SZ and schizotypy phenotypes across large case, high-density SZ pedigree, and prodromal-aged GWAS samples, and 2) to develop and test, with leaders of the Psychiatric Genomics Consortium, innovative statistical methods to identify and characterize genetic subtypes of SZ. This proposal delineates a series of training and research goals for the candidate that incorporates strengths from phenotypic assessment, statistical genetics, and molecular genetics and combines samples reflecting a broad range of genetic risk. The candidate will capitalize on previously established expertise in schizotypy and clinical risk assessment, as well as expertise in the familial transmission of dimensional traits, to establish a program of translational research wherein the application of statistical genetic/bioinformatic techniques to genetic subtyping analyses will be used to generate promising candidates for further exploration in human genomic data. Empirically-based genetic subtyping methods will be developed and tested in the largest SZ case sample to date, and subtypes will be characterized with respect to dimensional phenotypic traits. Top loci hits in subtype analyses of dimensional symptoms will be validated in secondary analyses of differential gene expression in post-mortem SZ brain. This will allow for a detailed analysis of function at both the SNP and gene levels, and will provide the candidate with substantive training in both statistical and molecular genetics methods. The institutional environment is ideal for the candidate's goal of developing a comprehensive program in SZ research, and the proposed research represents an important contribution toward advancing the understanding of SZ through a combination of clinical, statistical, molecular, and translational methods, consistent with the mission of the NIMH.
Mental illnesses such as schizophrenia constitute 13% of the global burden of disease and schizophrenia, although relatively rare, is highly heritable (80%) and one of the most severe mental disorders. This project aims to elucidate the influence of genetic factors and gene function on dimensional schizophrenia and schizotypy symptoms with multiple measures, across multiple samples of varying genetic risk. Insights gained from this research will inform prediction, prevention, intervention, and treatment efforts by clarifying the biological mechanisms underlying SZ symptoms.
|Hopwood, Christopher J; Kotov, Roman; Krueger, Robert F et al. (2017) The time has come for dimensional personality disorder diagnosis. Personal Ment Health :|
|Edwards, A C; Docherty, A R; Moscati, A et al. (2017) Polygenic risk for severe psychopathology among Europeans is associated with major depressive disorder in Han Chinese women. Psychol Med :1-13|
|Moore, Ashlee A; Sawyers, Chelsea; Adkins, Daniel E et al. (2017) Opportunities for an enhanced integration of neuroscience and genomics. Brain Imaging Behav :|
|Docherty, Anna R; Edwards, Alexis C; Yang, Fuzhong et al. (2017) Age of onset and family history as indicators of polygenic risk for major depression. Depress Anxiety 34:446-452|
|Merrill, Anne M; Karcher, Nicole R; Cicero, David C et al. (2017) Evidence that communication impairment in schizophrenia is associated with generalized poor task performance. Psychiatry Res 249:172-179|
|Docherty, Anna R (2017) Leveraging psychiatric and medical genetics to understand comorbid depression and obesity. Br J Psychiatry 211:61-62|
|Docherty, Anna R; Moscati, Arden; Dick, Danielle et al. (2017) Polygenic prediction of the phenome, across ancestry, in emerging adulthood. Psychol Med :1-10|
|Docherty, Anna R; Moscati, Arden A; Fanous, Ayman H (2016) Cross-Disorder Psychiatric Genomics. Curr Behav Neurosci Rep 3:256-263|
|Edwards, Alexis C; Aggen, Steven H; Cai, Na et al. (2016) CHRONICITY OF DEPRESSION AND MOLECULAR MARKERS IN A LARGE SAMPLE OF HAN CHINESE WOMEN. Depress Anxiety :|
|Docherty, Anna R (2016) Genomic Approaches to Phenotype Prediction. JAMA Psychiatry 73:536|
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