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We had previously identified the clock gene D-box binding protein (Dbp) as a potential candidate gene for bipolar disorder and for alcoholism, using a Convergent Functional Genomics (CFG) approach. Here we report that mice with a homozygous deletion of DBP have lower locomotor activity, blunted responses to stimulants, and gain less weight over time. In response to a chronic stress paradigm, these mice exhibit a diametric switch in these phenotypes. DBP knockout mice are also activated by sleep deprivation, similar to bipolar patients, and that activation is prevented by treatment with the mood stabilizer drug valproate. Moreover, these mice show increased alcohol intake following exposure to stress. Microarray studies of brain and blood reveal a pattern of gene expression changes that may explain the observed phenotypes. CFG analysis of the gene expression changes identified a series of novel candidate genes and blood biomarkers for bipolar disorder, alcoholism, and stress reactivity.

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Phenomic, Convergent Functional Genomic, and biomarker studies in a stress‐reactive genetic animal model of bipolar disorder and co‐morbid alcoholism

Le-Niculescu

McFarland

Ogden

et al. 2008

American J of Med Genetics Pt B

101

112

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Convergent functional genomics of genome‐wide association data for bipolar disorder: Comprehensive identification of candidate genes, pathways and mechanisms

Le-Niculescu

Patel

Bhat

et al. 2008

American J of Med Genetics Pt B

180

165

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Given the mounting convergent evidence implicating many more genes in complex disorders such as bipolar disorder than the small number identified unambiguously by the firstgeneration Genome-Wide Association studies (GWAS) to date, there is a strong need for improvements in methodology. One strategy is to include in the next generation GWAS larger numbers of subjects, and/or to pool independent studies into meta-analyses. We propose and provide proof of principle for the use of a complementary approach, convergent functional genomics (CFG), as a way of mining the existing GWAS datasets for signals that are there already, but did not reach significance using a genetics-only approach. With the CFG approach, the integration of genetics with genomics, of human and animal model data, and of multiple independent lines of evidence converging on the same genes offers a way of extracting signal from noise and prioritizing candidates. In essence our analysis is the most comprehensive integration of genetics and functional genomics to date in the field of bipolar disorder, yielding a series of novel (such as Klf12, Aldh1a1, A2bp1, Ak3l1, Rorb, Rora) and previously known (such as Bdnf, Arntl, Gsk3b, Disc1, Nrg1, Htr2a) candidate genes, blood biomarkers, as well as a comprehensive identification of pathways and mechanisms. These become prime targets for hypothesis driven follow-up studies, new drug development and personalized medicine approaches.

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Genetics of Psychiatric Disorders

Nürnberger¹,

Berrettini²,

Niculescu³

2016

The Medical Basis of Psychiatry

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Abstract: Recent genomic studies suggest a role for growth factors in mood disorders such as depression.

Cited by 13 publications

References 34 publications

Phenomic, Convergent Functional Genomic, and biomarker studies in a stress‐reactive genetic animal model of bipolar disorder and co‐morbid alcoholism

Phenomic, Convergent Functional Genomic, and biomarker studies in a stress‐reactive genetic animal model of bipolar disorder and co‐morbid alcoholism

Convergent functional genomics of genome‐wide association data for bipolar disorder: Comprehensive identification of candidate genes, pathways and mechanisms

Genetics of Psychiatric Disorders

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