Evidence of association between brain-derived neurotrophic factor gene and bipolar disorder

Liu, Lixiang; Foroud, Tatiana; Xuei, Xiaoling; Berrettini, Wade H.; Byerley, William; Coryell, William; El‐Mallakh, Rif S.; Gershon, Elliot S.; Kelsoe, John R.; Lawson, William B.; MacKinnon, Dean F.; McInnis, Melvin G.; McMahon, Francis J.; Murphy, Dennis L.; Rice, John P.; Scheftner, William A.; Zandi, Peter; Lohoff, Falk W.; Niculescu, Alexander B.; Meyer, Eric T.; Edenberg, Howard J.; Nürnberger, John I.

doi:10.1097/ypg.0b013e3283060f59

Cited by 54 publications

(47 citation statements)

References 61 publications

(90 reference statements)

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“…BDNF has been previously implicated in a variety of neuropsychiatric disorders, by both animal model and human studies: depression [Pezawas et al, 2008;Sen et al, 2008], bipolar disorder [Ogden et al, 2004], anxiety, alcoholism [Rodd et al, 2007], and schizophrenia [Le- Niculescu et al, 2007a;Chao et al, 2008]. Notably, there are several candidate gene association studies to date implicating BDNF in bipolar disorder Liu et al, 2008].…”

Section: Discussionmentioning

confidence: 99%

Coming to grips with complex disorders: Genetic risk prediction in bipolar disorder using panels of genes identified through convergent functional genomics

Patel

Le-Niculescu

Koller

et al. 2010

American J of Med Genetics Pt B

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We previously proposed and provided proof of principle for the use of a complementary approach, convergent functional genomics (CFG), combining gene expression and genetic data, from human and animal model studies, 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 [Le-Niculescu et al., 2009b]. CFG provides a fit-to-disease prioritization of genes that leads to generalizability in independent cohorts, and counterbalances the fit-to-cohort prioritization inherent in classic genetic-only approaches, which have been plagued by poor reproducibility across cohorts. We have now extended our previous work to include more datasets of GWAS, and more recent evidence from other lines of work. In essence our analysis is the most comprehensive integration of genetics and functional genomics to date in the field of bipolar disorder. Biological pathway analyses identified top canonical pathways, and epistatic interaction testing inside these pathways has identified genes that merit future follow-up as direct interactors (intra-pathway epistasis, INPEP). Moreover, we have put together a panel of best P-value single nucleotide polymorphisms (SNPs), based on the top candidate genes we identified. We have developed a genetic risk prediction score (GRPS) based on our panel, and demonstrate how in two independent test cohorts the GRPS differentiates between subjects with bipolar disorder and normal controls, in both European-American and African-American populations. Lastly, we describe a prototype of how such testing could be used to categorize disease risk in individuals and aid personalized medicine approaches, in psychiatry and beyond.

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Section: Discussionmentioning

confidence: 99%

Coming to grips with complex disorders: Genetic risk prediction in bipolar disorder using panels of genes identified through convergent functional genomics

Patel

Le-Niculescu

Koller

et al. 2010

American J of Med Genetics Pt B

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“…This SNP results in the substitution of valine (Val) to methionine (Met) [53]. Although the BDNF gene consists of several polymorphisms many are in high linkage disequilibrium and highly correlated [54,55].…”

Section: Bdnf and Life Stress In Depressionmentioning

confidence: 99%

Interaction between stress and the BDNF Val66Met polymorphism in depression: A systematic review and meta-analysis

Hosang¹,

Shiles²,

McGuffin³

et al. 2014

Comprehensive Psychiatry

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Background: Major depression is a disabling psychiatric illness with complex origins. Life stress (childhood adversity and recent stressful events) is a robust risk factor for depression. The relationship between life stress and Val66Met polymorphism in the brain-derived neurotrophic factor (BDNF) gene has received much attention. The aim of the present work was to review and conduct a meta-analysis on the results from published studies examining this interaction. Methods: A literature search was conducted using PsychINFO and PubMed databases until 22 November 2013. A total of 22 studies with a pooled total of 14,233 participants met the inclusion criteria, the results of which were combined and a meta-analysis performed using the Liptak-Stouffer z-score method. Results: The results suggest that the Met allele of BDNF Val66Met significantly moderates the relationship between life stress and depression (P = 0.03). When the studies were stratified by type of environmental stressor, the evidence was stronger for an interaction with stressful life events (P = 0.01) and weaker for interaction of BDNF Val66Met with childhood adversity (P = 0.051). Conclusions:The interaction between BDNF and life stress in depression is stronger for stressful life events rather than childhood adversity. Methodological limitations of existing studies include poor measurement of life stress.

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“…Circadian rhythm and sleep abnormalities have long been described in bipolar disorder-excessive sleep in the depressive phase, reduced need for sleep in the manic phase [Bauer et al, 2006]. Sleep deprivation is one of the more powerful and rapid acting treatment modalities for severe depression, and can lead to precipitation of manic episodes [Ogden et al, 2004] 11p14.1 (Assoc) BP [Sklar et al, 2002;Liu et al, 2008, in press] (Assoc) MDD [Schumacher et al, 2005] (D) MDD [Duman and Monteggia, 2006] (D) BP [Knable et al, 2004;Torrey et al, 2005] (D) BP [Karege et al, 2004] 8.0 [Pennington et al, 2007] 8.0…”

Section: à3mentioning

confidence: 99%

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

176

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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Evidence of association between brain-derived neurotrophic factor gene and bipolar disorder

Cited by 54 publications

References 61 publications

Coming to grips with complex disorders: Genetic risk prediction in bipolar disorder using panels of genes identified through convergent functional genomics

Coming to grips with complex disorders: Genetic risk prediction in bipolar disorder using panels of genes identified through convergent functional genomics

Interaction between stress and the BDNF Val66Met polymorphism in depression: A systematic review and meta-analysis

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

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