A strong genetic basis for bipolar disorder has been demonstrated by family and twin studies, yet classical genetic linkage analyses have yet to define relevant loci. Thus, multiple genes, each conferring a moderate increase in risk may underlie susceptibility to this disorder. We propose using large-scale association studies (of the transmission disequilibrium design) to identify alleles conferring increased risk for bipolar disease. This approach is complementary to linkage analyses and takes advantage of data from linkage analyses. We hypothesize that certain areas which have yielded linkage signals in three or more whole genome scans may harbor disease alleles of moderate individual impact, but of large potential population impact. Thus, we will focus on genes/SNPs from these areas. Additionally, in selecting further genes for our association studies, we will take into account biochemical and mRNA expression studies that are beyond the scope of this grant, but which will likely identify additional interesting genes to genotype. Thus, triangulating on candidate genes using knowledge obtained from linkage analysis, biochemical and expression studies is a promising approach to identifying risk alleles for bipolar disease. We have developed a robust, inexpensive genotyping method, have gained access to extensive, patient-parent trios, will benefit from the analytical and informatics expertise of the Whitehead Institute Center for Genome Research and are therefore poised to proceed with a rationally designed, large-scale association study of bipolar disease which will include analyses of upwards of 2,000,000 genotypes.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH062137-03
Application #
6726121
Study Section
Genome Study Section (GNM)
Program Officer
Moldin, Steven Owen
Project Start
2002-05-01
Project End
2007-04-30
Budget Start
2004-05-01
Budget End
2005-04-30
Support Year
3
Fiscal Year
2004
Total Cost
$302,750
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Ruderfer, Douglas M; Charney, Alexander W; Readhead, Ben et al. (2016) Polygenic overlap between schizophrenia risk and antipsychotic response: a genomic medicine approach. Lancet Psychiatry 3:350-7
Curtis, David; Vine, Anna E; McQuillin, Andrew et al. (2011) Case-case genome-wide association analysis shows markers differentially associated with schizophrenia and bipolar disorder and implicates calcium channel genes. Psychiatr Genet 21:1-4
Petryshen, T L; Sabeti, P C; Aldinger, K A et al. (2010) Population genetic study of the brain-derived neurotrophic factor (BDNF) gene. Mol Psychiatry 15:810-5
Perlis, Roy H; Smoller, Jordan W; Ferreira, Manuel A R et al. (2009) A genomewide association study of response to lithium for prevention of recurrence in bipolar disorder. Am J Psychiatry 166:718-25
Ferreira, Manuel A R; O'Donovan, Michael C; Meng, Yan A et al. (2008) Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet 40:1056-8
Sklar, P; Smoller, J W; Fan, J et al. (2008) Whole-genome association study of bipolar disorder. Mol Psychiatry 13:558-69
Fan, Jinbo; Sklar, Pamela (2008) Genetics of bipolar disorder: focus on BDNF Val66Met polymorphism. Novartis Found Symp 289:60-72;discussion 72-3, 87-93
Perlis, Roy H; Purcell, Shaun; Fagerness, Jesen et al. (2008) Family-based association study of lithium-related and other candidate genes in bipolar disorder. Arch Gen Psychiatry 65:53-61