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Transl Psychiatry. 2016 Aug 16;6:e870. doi: 10.1038/tp.2016.138.

Leveraging electronic health records to study pleiotropic effects on bipolar disorder and medical comorbidities.

Author information

1
Department of Psychiatry and Psychology, Mayo Clinic College of Medicine, Rochester, MN, USA.
2
Universidad de los Andes, Facultad de Medicina, Departamento de Psiquiatría, Santiago, Chile.
3
Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA.
4
Department of Psychiatry, Universidad Autónoma de Nuevo León, Nuevo León, Mexico.
5
Division of Health Informatics, Weill Cornell Medical College, Cornell University, New York, NY, USA.
6
Lindner Center of HOPE, Mason, OH, USA.
7
Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA.

Abstract

Patients with bipolar disorder (BD) have a high prevalence of comorbid medical illness. However, the mechanisms underlying these comorbidities with BD are not well known. Certain genetic variants may have pleiotropic effects, increasing the risk of BD and other medical illnesses simultaneously. In this study, we evaluated the association of BD-susceptibility genetic variants with various medical conditions that tend to co-exist with BD, using electronic health records (EHR) data linked to genome-wide single-nucleotide polymorphism (SNP) data. Data from 7316 Caucasian subjects were used to test the association of 19 EHR-derived phenotypes with 34 SNPs that were previously reported to be associated with BD. After Bonferroni multiple testing correction, P<7.7 × 10(-5) was considered statistically significant. The top association findings suggested that the BD risk alleles at SNP rs4765913 in CACNA1C gene and rs7042161 in SVEP1 may be associated with increased risk of 'cardiac dysrhythmias' (odds ratio (OR)=1.1, P=3.4 × 10(-3)) and 'essential hypertension' (OR=1.1, P=3.5 × 10(-3)), respectively. Although these associations are not statistically significant after multiple testing correction, both genes have been previously implicated with cardiovascular phenotypes. Moreover, we present additional evidence supporting these associations, particularly the association of the SVEP1 SNP with hypertension. This study shows the potential for EHR-based analyses of large cohorts to discover pleiotropic effects contributing to complex psychiatric traits and commonly co-occurring medical conditions.

PMID:
27529678
PMCID:
PMC5022084
DOI:
10.1038/tp.2016.138
[Indexed for MEDLINE]
Free PMC Article

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