Genome-wide association study of bipolar disorder accounting for effect of body mass index identifies a new risk allele in TCF7L2

S. J. Winham, A. B. Cuellar-Barboza, A. Oliveros, S. L. McElroy, S. Crow, C. Colby, D. S. Choi, M. Chauhan, M. Frye, J. M. Biernacka

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67 Scopus citations


Bipolar disorder (BD) is associated with higher body mass index (BMI) and increased metabolic comorbidity. Considering the associated phenotypic traits in genetic studies of complex diseases, either by adjusting for covariates or by investigating interactions between genetic variants and covariates, may help to uncover the missing heritability. However, obesity-related traits have not been incorporated in prior genome-wide analyses of BD as covariates or potential interacting factors. To investigate the genetic factors underlying BD while considering BMI, we conducted genome-wide analyses using data from the Genetic Association Information Network BD study. We analyzed 729 454 genotyped single-nucleotide polymorphism (SNP) markers on 388 European-American BD cases and 1020 healthy controls with available data for maximum BMI. We performed genome-wide association analyses of the genetic effects while accounting for the effect of maximum BMI, and also evaluated SNP-BMI interactions. A joint test of main and interaction effects demonstrated significant evidence of association at the genome-wide level with rs12772424 in an intron of TCF7L2 (P=2.85E-8). This SNP exhibited interaction effects, indicating that the bipolar susceptibility risk of this SNP is dependent on BMI. TCF7L2 codes for the transcription factor TCF/LF, part of the Wnt canonical pathway, and is one of the strongest genetic risk variants for type 2 diabetes (T2D). This is consistent with BD pathophysiology, as the Wnt pathway has crucial implications in neurodevelopment, neurogenesis and neuroplasticity, and is involved in the mechanisms of action of BD and depression treatments. We hypothesize that genetic risk for BD is BMI dependent, possibly related to common genetic risk with T2D.

Original languageEnglish (US)
Pages (from-to)1010-1016
Number of pages7
JournalMolecular psychiatry
Issue number9
StatePublished - Sep 11 2014

Bibliographical note

Funding Information:
This study was supported by funding from the Marriott Family Foundation and Mayo Clinic’s Center for Individualized Medicine. Funding support for the Whole Genome Association Study of Bipolar Disorder was provided by the National Institute of Mental Health (NIMH) and the genotyping of samples was provided through the Genetic Association Information Network (GAIN). The data sets used for the analyses described in this manuscript were obtained from the database of Genotypes and Phenotypes (dbGaP) found at through dbGaP accession number phs000017.v3.p1. Samples and associated phenotype data for the Collaborative Genomic Study of Bipolar Disorder were provided by the NIMH Genetics Initiative for Bipolar Disorder.

Funding Information:
Dr McElroy is a consultant to or member of the scientific advisory boards of Alkermes, Bracket, Corcept, MedAvante, Shire, and Teva. She is a principal or co-investigator on studies sponsored by Alkermes, AstraZeneca, Cephalon, Eli Lilly and Company, Forest, Marriott Foundation, Orexigen Therapeutics, Inc., Pfizer, Shire, Takeda Pharmaceutical Company Ltd, and Transcept Pharmaceutical, Inc. She is also an inventor on United States Patent No. 6,323,236 B2, Use of Sulfamate Derivatives for Treating Impulse Control Disorders, and along with the patient’s assignee, University of Cincinnati, Cincinnati, Ohio, has received payments from Johnson & Johnson, which has exclusive rights under the patent. Dr Crow has received research grants from Shire, Alkermes and Phillips Respironics. Dr Frye has had grant support from Pfizer and Myriad, and has served as an unpaid consultant for Allergan, Myriad, Sunovion and Teva Pharmaceuticals. The remaining authors declare no conflict of interest.

Publisher Copyright:
© 2014 Macmillan Publishers Limited All rights reserved.


  • bipolar disorder
  • body mass index
  • genome-wide association study
  • interaction
  • network analysis


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