The recent development of microarray platforms, capable of genotyping hundreds of thousands of single nucleotide polymorphisms (SNPs), has resulted in the rapid identification of novel susceptibility genes for a number of complex diseases. However, recent data from several large-scale genome-wide association studies (GWAS) of schizophrenia (SCZ) have been disappointing;it is clear that identification of even several common variants of very modest effect will leave considerable genetic variance in SCZ unexplained. In this EUREKA application, we challenge the implicit assumptions underlying GWAS: that multiple common alleles of additive effect combine to produce the phenotype, and suggest a complementary hypothesis: that a proportion of cases of schizophrenia may be characterized by a simpler genetic architecture, and that one or more homogeneous molecular subtypes may co-exist alongside the polygenic pool of cases. Support for this model comes from a novel statistical approach to analyzing GWAS data, which we have termed """"""""whole genome homozygosity analysis"""""""" (WGHA). Applied to our own SCZ dataset (PI: Anil Malhotra), WGHA has identified several rare recessive loci of high penetrance, encompassing several chromosomal regions (of approximately 200kb-2MB) that have been identified in prior SCZ linkage and association studies. This EUREKA proposal aims to extend this initial finding in several stages. First, we will apply WGHA analysis to a much larger SCZ dataset derived from the Genetic Analysis Information Network (GAIN) initiative. Next, we will re-analyze data from a whole genome linkage dataset (PI: Hugh Gurling), results of which will guide a novel SNP-based linkage study of SCZ pedigrees from the NIMH repository. Analysis of linkage data will be focused on identifying small clusters of pedigrees with strongly recessive transmission of similar loci. Highly penetrant recessive loci identified and replicated across these analyses will then be interrogated in both case and control samples using next-generation high-throughput deep resequencing technology (Illumina 1G platform), in collaboration with Cold Spring Harbor Laboratory (PI: W. Richard McCombie). By the end of the first half of the proposed 3-year funding period, we aim to have characterized one or more recessive subtypes of schizophrenia, accounting for up to 10% of all cases. At the completion of the project in Year 3, we aim to have identified, through deep resequencing, one or more highly penetrant mutations underlying these cases. Schizophrenia (SCZ) constitutes the fifth leading cause of disability in the US.
We aim to use novel statistical approaches and state-of-the-art genomic sequencing technology to characterize one or more homogeneous genetic subtypes of schizophrenia, and to identify the causal mutation(s) underlying such subtype(s). Findings will create new opportunities for diagnosis and prediction of schizophrenia, and for understanding its biology.

Public Health Relevance

Schizophrenia (SCZ) constitutes the fifth leading cause of disability in the US. We aim to use novel statistical approaches and state-of-the-art genomic sequencing technology to characterize one or more homogeneous genetic subtypes of schizophrenia, and to identify the causal mutation(s) underlying such subtype(s). Findings will create new opportunities for diagnosis and prediction of schizophrenia, and for understanding its biology.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH084098-03
Application #
7803674
Study Section
Special Emphasis Panel (ZNS1-SRB-P (44))
Program Officer
Koester, Susan E
Project Start
2008-08-01
Project End
2012-03-31
Budget Start
2010-04-01
Budget End
2012-03-31
Support Year
3
Fiscal Year
2010
Total Cost
$332,890
Indirect Cost
Name
Feinstein Institute for Medical Research
Department
Type
DUNS #
110565913
City
Manhasset
State
NY
Country
United States
Zip Code
11030
Baskovich, Brett; Hiraki, Susan; Upadhyay, Kinnari et al. (2016) Expanded genetic screening panel for the Ashkenazi Jewish population. Genet Med 18:522-8
Franke, Barbara; Stein, Jason L; Ripke, Stephan et al. (2016) Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nat Neurosci 19:420-431
Carmi, Shai; Hui, Ken Y; Kochav, Ethan et al. (2014) Sequencing an Ashkenazi reference panel supports population-targeted personal genomics and illuminates Jewish and European origins. Nat Commun 5:4835
Mukherjee, Semanti; Guha, Saurav; Ikeda, Masashi et al. (2014) Excess of homozygosity in the major histocompatibility complex in schizophrenia. Hum Mol Genet 23:6088-95
Guha, Saurav; Rees, Elliott; Darvasi, Ariel et al. (2013) Implication of a rare deletion at distal 16p11.2 in schizophrenia. JAMA Psychiatry 70:253-60
Lencz, Todd; Guha, Saurav; Liu, Chunyu et al. (2013) Genome-wide association study implicates NDST3 in schizophrenia and bipolar disorder. Nat Commun 4:2739
Lee, S Hong; DeCandia, Teresa R; Ripke, Stephan et al. (2012) Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs. Nat Genet 44:247-50
Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium (2011) Genome-wide association study identifies five new schizophrenia loci. Nat Genet 43:969-76
Rosenfeld, Jeffrey A; Malhotra, Anil K; Lencz, Todd (2010) Novel multi-nucleotide polymorphisms in the human genome characterized by whole genome and exome sequencing. Nucleic Acids Res 38:6102-11
Lencz, Todd; Szeszko, Philip R; DeRosse, Pamela et al. (2010) A schizophrenia risk gene, ZNF804A, influences neuroanatomical and neurocognitive phenotypes. Neuropsychopharmacology 35:2284-91