Study Report

Reference	Ruderfer, D. M., 2013 PMID: 24280982
Citation	Winham, S. J., A. B. Cuellar-Barboza, et al. (2013). "Genome-wide association study of bipolar disorder accounting for effect of body mass index identifies a new risk allele in TCF7L2." Mol Psychiatry.
Disease Type	Bipolar Disorder & Schizophrenia
Study Design	case-control
Study Type	Genome-wide association study
Sample Size	19 779 cases (9369 SCZ plus 10 410 BP) versus 19423 controls for combined GWAS, 7129 SCZ cases versus 9252 BP cases for a direct comparison GWAS
SNP/Region/Marker Size	1.1 million SNP dosages
Predominant Ethnicity

Sample Diagnosis	RDC (Research Diagnostic Criteria), DSM-III-R (Diagnostic and Statistical Manual of Mental Disorders) DSM-IV or International Classification of Diseases-10 (ICD-10).
Sample Status	This study combines individual genotype data published in 2011 by the Psychiatric GWAS Consortium (PGC) Bipolar Disorder and the Schizophrenia Working Groups. In addition, four bipolar data sets not included in the primary meta-analysis (although used for the replication phase) are now included: three previously not published bipolar data sets including additional samples from Thematically Organized Psychoses (401 cases, 171 controls), French (451 cases, 1631 controls), FaST STEP2/TGEN (1860 cases) and one published data set Sweden (824 cases, 2084 controls).
Technique	Raw individual genotype data from all samples were uploaded to the Genetic Cluster Computer hosted by the Dutch National Computing and Networking Services. Imputation was performed using the HapMap Phase3 CEU+TSI data and BEAGLE by sample on random subsets of 300 subjects. All analyses were performed using Plink.
Statistical Method	The primary association analysis was logistic regression on the imputed dosages from BEAGLE on case-control status with 13 multidimensional scaling components and sample grouping as covariates. Additionally, for the BP+SCZ meta-analysis, we tested heterogeneity between BP vs controls and SCZ vs controls odds ratios (OR) using the Cochran's Q test. We employed a method used by the International Schizophrenia Consortium and developed by Purcell et al. to calculate both BP polygenic scores in SCZ cases and SCZ polygenic scores in BP cases.
Result Summary	In our case-control analysis, we identify five previously identified regions reaching genome-wide significance (CACNA1C, IFI44L, MHC, TRANK1 and MAD1L1) and a novel locus near PIK3C2A. We create a polygenic risk score that is significantly different between BP and SCZ and show a significant correlation between a BP polygenic risk score and the clinical dimension of mania in SCZ patients. Our results indicate that first, combining diseases with similar genetic risk profiles improves power to detect shared risk loci and second, that future direct comparisons of BP and SCZ are likely to identify loci with significant differential effects. Identifying these loci should aid in the fundamental understanding of how these diseases differ biologically. These findings also indicate that combining clinical symptom dimensions and polygenic signatures could provide additional information that may someday be used clinically.