Bipolar affective disorder is a life-long, often recurring, chronic mental illness which typically appears in young adulthood and is characterized by fluctuations in mood, including recurrent episodes of mania or hypomania and depression. Lifetime prevalence estimates for bipolar disorders are 1 - 3.7%, and tragically, approximately 10-15% of affected individuals die of suicide. A long term goal of our studies is to identify the molecular events that underlie bipolar disorder. To complement ongoing large-scale genome-wide association studies, we focus on an exceptionally large Amish family with high incidence/prevalence and risk of developing bipolar disorder to identify common and rare variants, single nucleotide polymorphisms and structural variants associated with disease susceptibility. We propose to combine high-density SNP genotyping (on all individuals) with next- generation sequencing (on a selected subset) to extract maximum value from the complete understanding of genetic variation in this genetic isolate. To achieve this goal, we propose a three- step strategy: a) to establish a high-density genotype map for all 450 well-phenotyped family members in the pedigree segregating bipolar disorder using Illumina Omni2.5-Quad arrays;b) to generate, in an unbiased way, a full spectrum of genetic variants by whole genome sequencing of 60 individuals (20 parent-child trios), from genomically defined subfamilies and with different disease status (affected and unaffected);and c) to infer a spectrum of identified mutations (rare single nucleotide polymorphisms and structural variants) to the entire pedigree, specifically to unsequenced family members that harbor overlapping haplotypes, (Li et al., 2009;Howie et al., 2010). This variant imputation will use correlation between SNP markers on the genotype platform available for all 450 subjects and SNPs identified by deep sequencing, to predict positions and genotypes of novel common and rare variants. Functional annotation of risk alleles (single variants and combinations of alleles) in the large number of affected and unaffected family members, combined with the variation identified through the 1000 Genome Project, should accelerate identification of disease genes. This project will use and further develop high throughput genomic approaches for a combined analysis of genotypes and whole genome sequence that should be applicable to the analysis of other psychiatric disorders and studies of large families. The identification of etiological basis of bipolar disorder in a genetic isolate will shed light on the gene pathways that are involved in this disorder in the general population.

Public Health Relevance

This project will potentially reveal the genetic architecture of bipolar disorder using a novel approach that combines whole genome sequencing of selected family members from an extended Amish pedigree, with high-density SNP genotypes on a larger number of related family members. Common and rare genetic variants identified in this project may impact future development of therapies for bipolar and other related psychiatric disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH093415-02
Application #
8334562
Study Section
Special Emphasis Panel (ZRG1-GGG-C (02))
Program Officer
Addington, Anjene M
Project Start
2011-09-20
Project End
2015-06-30
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
2
Fiscal Year
2012
Total Cost
$887,344
Indirect Cost
$127,263
Name
University of Pennsylvania
Department
Genetics
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Georgi, Benjamin; Craig, David; Kember, Rachel L et al. (2014) Genomic view of bipolar disorder revealed by whole genome sequencing in a genetic isolate. PLoS Genet 10:e1004229
Strauss, Kevin A; Markx, Sander; Georgi, Benjamin et al. (2014) A population-based study of KCNH7 p.Arg394His and bipolar spectrum disorder. Hum Mol Genet 23:6395-406
Georgi, Benjamin; Voight, Benjamin F; Bucan, Maja (2013) From mouse to human: evolutionary genomics analysis of human orthologs of essential genes. PLoS Genet 9:e1003484