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Chunk #10 — Methods — Association analysis

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Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia.
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The primary association analysis was logistic regression on the imputed dosages from BEAGLE on case-control status with 13 MDS components and sample grouping as covariates. We performed four association tests: 1) a combined meta-analysis of BP and SCZ (19,779 BP and SCZ cases, 19,423 controls) to identify variants shared across both disorders, 2) SCZ only (SCZ n=9,369, vs controls n=8,723), and 3) BP only (BP n=10,410, controls n=10,700) for comparison to dimensional phenotypes and 4) case only BP vs SCZ (SCZ n=7,129, BP n=9,252) to identify loci with differential effects between these two disorders (Table 1). We retained SNPs after imputation with INFO > 0.6. We calculated genomic inflation factors both without normalization for these analyses (λ): 1.26 (BP+SCZ vs controls), 1.19 (SCZ vs controls), 1.15 (BP vs controls) and 1.11 (BP vs SCZ) and normalized to 1,000 cases and 1,000 controls for direct comparison (λ1000 SCZ). Additionally, for the BP+SCZ meta-analysis, we tested heterogeneity between BP vs controls and SCZ vs controls odds ratios using the Cochrane’s Q test. Association regions were defined by an LD clumping procedure for