This collaboration has developed a bipolar disorder family resource that has proven to be uniquely valuable in testing clinically-based hypotheses about the genetic heterogeneity of the illness. We have ascertained and assessed about 150 nuclear families with a bipolar I proband and two or more siblings with a major affective disorder. The analysis of clinical features in the ascertained families has revealed important patterns, including bipolar II, psychotic bipolar disorder, and panic disorder comorbidity. One important goal is to derive and test genetically meaningful phenotypic subtypes. Tests of familial aggregation of variables and factors are also being performed, and positive results will be followed by covariate analyses of genetic linkage and association data. We previously reported results of an association study of close to 5000 SNP markers on chromosomes 13, 18, and 22, as well as in selected candidate genes. Preliminary results implicated several genes in bipolar disorder that are good candidates for replication in independent samples. We have found evidence that risk of bipolar disorder in these families is associated with genetic variation in the gene encoding FKBP5, genes encoding proteins involved in the Wnt signaling pathway, and genes that influence circadian rhythms. We have also performed association studies through SNP genotyping (using the Illumina platform) in 4 chromosomal regions: 6q21-23, 13q31-33, 18q21-22 and 22q12. Analyses of the SNP data have revealed several signals, but these have not generally been supported by genome-wide association studies. We have generated a database of clinical variables, The Bipolar Disorder Phenome Database, based in part on this sample. The database contains several hundred clinical variables, harmonized with those collected by the NIMH Genetics Initiative, describing the course, symptoms, and clinical picture of bipolar disorder. We have made the database available to the scientific community to support research into the genetics of bipolar disorder and related conditions. For example, we used these data to demonstrate that postpartum mood symptoms aggregate in bipolar disorder pedigrees, suggesting that these symptoms may help define a familial subtype of the disorder. In recent years, in collaboration with scientists at Cold Spring Harbor Laboratory, we have used cutting-edge genetic tools to search for relatively small structural variations in chromosomes, known as copy number variants(CNVs), that may play a role in bipolar disorder. Using these tools, we found evidence that some CNVs strongly over-represented among people with schizophrenia may also play a role in bipolar disorder. Work has so far focussed on detecting de novo CNVs that may give rise to bipolar disorder, especially in an early-onset form, among the offspring of parents who do not suffer from the condition. We postulate that singleton probands with unaffected parents may be enriched for rare, de novo CNVs, but these are scarce, so we have pulled together 4 other groups to help us with sample collection and diagnostic assessment. CNV screening was done in Jonathan Sebat's lab. We found a significant excess transmission of the large chromosome 16p11.2 microduplication in 161 trio families. Subsequent analyses of data based on arrays that can detect smaller, de novo CNVs also indicated a significant increase in de novo CNVs in bipolar disorer, albeit less than that observed in schizophrenia. In order to better interpret the impact of genetic variation on the function of genes in bipolar disorder, we are pursuing a variety of functional genomics studies, including brain imaging, gene expression and RNA-seq in post-mortem brain tissue, and cellular phenotyping of neurons derived from induced pluripotent stem cells induced in skin samples collected from research volunteers who carry functional genetic variants that may play a causal role in bipolar disorder.

Project Start
Project End
Budget Start
Budget End
Support Year
9
Fiscal Year
2012
Total Cost
$215,561
Indirect Cost
Name
U.S. National Institute of Mental Health
Department
Type
DUNS #
City
State
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Zip Code
McMahon, Francis J (2016) Genetic association studies in psychiatry: time for pay-off. Lancet Psychiatry 3:309-10
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