title: Independent component analysis of SNPs reflects polygenic risk scores for schizophrenia.
abstract: Schizophrenia is a psychiatric disorder with high heritability. Recent genome-wide association studies have provided a list of risk loci reliably derived from unprecedentedly large samples. However, further delineation of the diagnosis-associated susceptibility variants is needed to better characterize the genetic architecture given the disease's complex nature. In this sense, a data-driven approach might hold promise for identifying functionally related clusters of genetic variants that might not be captured by hypothesis-based models. In the current study, independent component analysis (ICA) was applied to the Psychiatric Genomics Consortium's schizophrenia-related single nucleotide polymorphisms (SNPs) in 104 schizophrenia patients and 142 healthy controls of European Ancestry. We found that, for 13 out of 16 extracted independent components, the associated loadings correlated highly (r>0.5) with the polygenic risk scores for SZ of the corresponding SNPs. These correlations were likely not inflated by the linkage disequilibrium structure (permutation p<0.001). In brief, we demonstrate an example of ICA analysis on SNP data yielding functionally meaningful clusters, which motivates further application of data-driven approaches as a complimentary tool for hypothesis-based methods to enrich our knowledge on the genetic basis of complex disorders.
authors.affiliation: The Mind Research Network, Albuquerque, NM, USA. Electronic address: jchen@mrn.org.
authors.forename: Jiayu
authors.initials: J
authors.lastname: Chen
authors.affiliation: The Mind Research Network, Albuquerque, NM, USA; Department of Electrical Engineering, University of New Mexico, Albuquerque, NM, USA.
authors.forename: Vince D
authors.initials: VD
authors.lastname: Calhoun
authors.affiliation: Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA; Departments of Psychiatry and Neuroscience, Yale University, New Haven, CT, USA.
authors.forename: Godfrey D
authors.initials: GD
authors.lastname: Pearlson
authors.affiliation: Departments of Neurosciences and Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM, USA.
authors.forename: Nora I
authors.initials: NI
authors.lastname: Perrone-Bizzozero
authors.affiliation: The Mind Research Network, Albuquerque, NM, USA; Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA, USA.
authors.forename: Jessica A
authors.initials: JA
authors.lastname: Turner
authors.affiliation: Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Germany; MGH/MIT/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Psychiatry, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Stefan
authors.initials: S
authors.lastname: Ehrlich
authors.affiliation: Department of Psychiatry, University of Iowa, Iowa City, IA, USA.
authors.forename: Beng-Choon
authors.initials: BC
authors.lastname: Ho
authors.affiliation: The Mind Research Network, Albuquerque, NM, USA; Department of Electrical Engineering, University of New Mexico, Albuquerque, NM, USA.
authors.forename: Jingyu
authors.initials: J
authors.lastname: Liu
mesh_terms: D016000:Cluster Analysis; D015331:Cohort Studies; D020022:Genetic Predisposition to Disease; D006801:Humans; D015810:Linkage Disequilibrium; D020412:Multifactorial Inheritance; D020641:Polymorphism, Single Nucleotide; D018570:Risk Assessment; D012559:Schizophrenia / Q000235:genetics*; D044465:White People / Q000235:genetics
keywords: ICA; PGC; Polygenic risk score; Schizophrenia