Molecular genetic overlap in bipolar disorder, schizophrenia, and major depressive disorder

Abstract

Objectives. Genome-wide association studies (GWAS) in complex phenotypes, including psychiatric disorders, have yielded many replicated findings, yet individual markers account for only a small fraction of the inherited differences in risk. We tested the performance of polygenic models in discriminating between cases and healthy controls and among cases with distinct psychiatric diagnoses. Methods. GWAS results in bipolar disorder (BD), major depressive disorder (MDD), schizophrenia (SZ), and Parkinson's disease (PD) were used to assign weights to individual alleles, based on odds ratios. These weights were used to calculate allele scores for individual cases and controls in independent samples, summing across many single nucleotide polymorphisms (SNPs). How well allele scores discriminated between cases and controls and between cases with different disorders was tested by logistic regression. Results. Large sets of SNPs were needed to achieve even modest discrimination between cases and controls. The most informative SNPs were overlapping in BD, SZ, and MDD, with correlated effect sizes. Little or no overlap was seen between allele scores for psychiatric disorders and those for PD. Conclusions. BD, SZ, and MDD all share a similar polygenic component, but the polygenic models tested lack discriminative accuracy and are unlikely to be useful for clinical diagnosis.

Key words::

• Genome-wide association
• polygenic model
• allele burden
• psychosis
• prediction

Acknowledgements

The authors are greatly indebted to Naomi Wray for highly inspirational discussions. Ioline Henter provided outstanding editorial assistance. Funded by the Intramural Research Program of the National Institute of Mental Health (NIMH), National Institutes of Health, Department of Health and Human Services (IRP-NIMH-NIH-DHHS), Deutsche Forschungsgemeinschaft (DFG), the National German Genome Research Network (NGFN), NARSAD (Independent/Junior Investigator Awards to FJM/TGS), and the Alfried Krupp von Bohlen und Halbach-Stiftung. Genotyping of the GAIN BD, GAIN MDD, and GAIN SZ samples was provided through the Genetic Association Information Network (GAIN). The datasets used for the analyses described in this manuscript were obtained from the database of Genotypes and Phenotypes (dbGaP). Samples and associated phenotype data were provided by the contributing studies. We thank the Wellcome Trust Case Control Consortium, The Netherlands Study of Depression and Anxiety, and the Netherlands Twin Registry for making data/results available for analysis. The contributions of ABS and MAN were supported by the Intramural Research Program of the National Institute on Aging, National Institutes of Health, Department of Health and Human Services (project Z01 AG000932-02, human subjects protocols 2004-147 and 2003-081).

Statement of Interest

None to declare.

Supplementary material available online at http://informahealthcare.com/doi/abs/10.3109/15622975.2012.662282

Samples

GAIN BD

WTCCC BD

German BD

GAIN MDD

GAIN SZ

NIA/NINDS PD

Whole-genome imputation