Recently we have produced the first genetic atlas of the human cortex based on magnetic resonance imaging (MRI) data of twins using fuzzy clustering. This finding not only confirms that human brain phenotypes are heritable traits but also demonstrates a very clear region-specific genetic pattern in which the cortex can be subdivided into various pleiotropic regions. In this project, we will extend this approach further and apply it to a uniquely large in-house sample with both MRI and single nucleotide polymorphism (SNP) data, in order to generate SNP-based atlases. We will adopt a statistical framework developed by Visscher and colleagues (Yang et al. 2010, Deary et al. 2012) to examine the contribution of all SNPs to phenotypic variation in aggregate. This approach is analogous to twin modeling which examines aggregate genetic influences on a trait, and captures a much larger portion of heritability than the conventional gene-wide association study (GWAS) approach. However, neither the twin nor the Visscher methods is informative about specific genetic variants underlying each genetic division. Next, we will take the genetic maps and find SNPs associated with each genetic division using new statistical methods to establish a database tool that has information about contribution of specific genetic variants to phenotypic variation in different parts of the brain. Finally, it is well-recognized that psychiatric and substance use disorders affect both brain and behavior. We will study the genetic variants and mechanisms that are involved in disease or symptom pathogenesis with benefit from incorporating the knowledge of polygenic basis of the brain.
The Specific Aims of the proposal are:
Aim 1 : Generate genetic atlases of the human cortex based on MRI and SNP data. We will take a novel approach of implementing a method developed by Yang et al, with its strength for estimating aggregate genetic effects of all SNPs, to generate genetic maps of cortical surface area and thickness by fuzzy clustering.
Aim 2 : Discover SNPs associated with individual genetic divisions of the cortical cluster maps and individual subcortical structures. We will parcel the cortex into genetic brain regions defined by the twin-based genetic atlases and find SNPs or genes associated with each brain region.
Aim 3 : Identify genetic basis of psychiatric and substance use disorders with a focus on SNPs associated with neural systems implicated in the disorders. The information regarding SNPs associated with brain phenotypes will be further applied to enhance our ability in identifying disease- related SNPs in individuals with psychiatric disorders (including schizophrenia, and bipolar and unipolar disorders) and substance dependence (including alcohol and nicotine dependence).

Public Health Relevance

Many devastating human diseases, such as schizophrenia and bipolar disorder are heritable, but the genetic basis of these disorders is not well understood. Through application of genetically-based novel brain phenotypes and state-of-the-art statistical approaches in a large sample with brain imaging and genotyping data, we will increase understanding of the genetic basis of the human brain and psychiatric disorders, which could lead to new insight into disease mechanisms and identify novel therapeutic targets. The information of the genetic basis of these disorders can be used for generalization performance of predictive models for patient stratification with potential usage in clinical medicine.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Molecular Neurogenetics Study Section (MNG)
Program Officer
Addington, Anjene M
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University of California San Diego
Schools of Medicine
La Jolla
United States
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Wang, Yunpeng; Thompson, Wesley K; Schork, Andrew J et al. (2016) Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS. PLoS Genet 12:e1005803
Yin, Xianyong; Wineinger, Nathan E; Wang, Kai et al. (2016) Common susceptibility variants are shared between schizophrenia and psoriasis in the Han Chinese population. J Psychiatry Neurosci 41:413-421
Standish, Kristopher A; Carland, Tristan M; Lockwood, Glenn K et al. (2015) Group-based variant calling leveraging next-generation supercomputing for large-scale whole-genome sequencing studies. BMC Bioinformatics 16:304
Fjell, Anders M; Grydeland, HÃ¥kon; Krogsrud, Stine K et al. (2015) Development and aging of cortical thickness correspond to genetic organization patterns. Proc Natl Acad Sci U S A 112:15462-7
Desikan, R S; Schork, A J; Wang, Y et al. (2015) Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus. Mol Psychiatry 20:1588-95
Fan, Chun Chieh; Bartsch, Hauke; Schork, Andrew J et al. (2015) Modeling the 3D geometry of the cortical surface with genetic ancestry. Curr Biol 25:1988-92
Minassian, Arpi; Maihofer, Adam X; Baker, Dewleen G et al. (2015) Association of Predeployment Heart Rate Variability With Risk of Postdeployment Posttraumatic Stress Disorder in Active-Duty Marines. JAMA Psychiatry 72:979-86
Chen, Chi-Hua; Peng, Qian; Schork, Andrew J et al. (2015) Large-scale genomics unveil polygenic architecture of human cortical surface area. Nat Commun 6:7549
Desikan, Rahul S; Schork, Andrew J; Wang, Yunpeng et al. (2015) Polygenic Overlap Between C-Reactive Protein, Plasma Lipids, and Alzheimer Disease. Circulation 131:2061-9
Yin, Xianyong; Cheng, Hui; Lin, Yan et al. (2015) A weighted polygenic risk score using 14 known susceptibility variants to estimate risk and age onset of psoriasis in Han Chinese. PLoS One 10:e0125369

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