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.

Public Health Relevance

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.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01MH109765-03
Application #
9243309
Study Section
Behavioral Genetics and Epidemiology Study Section (BGES)
Program Officer
Van'T Veer, Ashlee V
Project Start
2016-03-15
Project End
2020-02-29
Budget Start
2017-03-01
Budget End
2018-02-28
Support Year
3
Fiscal Year
2017
Total Cost
$158,132
Indirect Cost
$11,411
Name
University of Utah
Department
Psychiatry
Type
Schools of Medicine
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112
Coon, Hilary; Darlington, Todd M; DiBlasi, Emily et al. (2018) Genome-wide significant regions in 43 Utah high-risk families implicate multiple genes involved in risk for completed suicide. Mol Psychiatry :
Krueger, Robert F; Kotov, Roman; Watson, David et al. (2018) Progress in achieving quantitative classification of psychopathology. World Psychiatry 17:282-293
Hopwood, Christopher J; Kotov, Roman; Krueger, Robert F et al. (2018) The time has come for dimensional personality disorder diagnosis. Personal Ment Health 12:82-86
Moore, Ashlee A; Sawyers, Chelsea; Adkins, Daniel E et al. (2018) Opportunities for an enhanced integration of neuroscience and genomics. Brain Imaging Behav 12:1211-1219
Anderson, John S; Shade, Jess; DiBlasi, Emily et al. (2018) Polygenic risk scoring and prediction of mental health outcomes. Curr Opin Psychol 27:77-81
Docherty, Anna R; Fonseca-Pedrero, Eduardo; Debbané, Martin et al. (2018) Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative. Schizophr Bull 44:S460-S467
Docherty, Anna R; Moscati, Arden; Dick, Danielle et al. (2018) Polygenic prediction of the phenome, across ancestry, in emerging adulthood. Psychol Med 48:1814-1823
Zhou, Han-Yu; Wong, Keri Ka-Yee; Shi, Li-Juan et al. (2018) Suspiciousness in young minds: Convergent evidence from non-clinical, clinical and community twin samples. Schizophr Res 199:135-141
Edwards, A C; Docherty, A R; Moscati, A et al. (2018) Polygenic risk for severe psychopathology among Europeans is associated with major depressive disorder in Han Chinese women. Psychol Med 48:777-789
Docherty, Anna R (2017) Leveraging psychiatric and medical genetics to understand comorbid depression and obesity. Br J Psychiatry 211:61-62

Showing the most recent 10 out of 16 publications