Identifying loci with different allele frequencies among cases of eight psychiatric disorders using CC-GWAS

Abstract

Psychiatric disorders are highly genetically correlated, but little research has been conducted on the genetic differences between disorders. We developed a new method (case-case genome-wide association study; CC-GWAS) to test for differences in allele frequency between cases of two disorders using summary statistics from the respective case-control GWAS, transcending current methods that require individual-level data. Simulations and analytical computations confirm that CC-GWAS is well powered with effective control of type I error. We applied CC-GWAS to publicly available summary statistics for schizophrenia, bipolar disorder, major depressive disorder and five other psychiatric disorders. CC-GWAS identified 196 independent case-case loci, including 72 CC-GWAS-specific loci that were not significant at the genome-wide level in the input case-control summary statistics; two of the CC-GWAS-specific loci implicate the genes KLF6 and KLF16 (from the Krüppel-like family of transcription factors), which have been linked to neurite outgrowth and axon regeneration. CC-GWAS loci replicated convincingly in applications to datasets with independent replication data.

Figure 1.. Genetic distance between cases and/or controls of SCZ, BIP and MDD.

We report genetic distances for (A) an illustrative example, (B) SCZ vs. BIP, (C) SCZ vs. MDD and (D) SCZ vs. BIP. Genetic distances are displayed as $\sqrt{m*F_{ST,causal}}$, derived based on the respective population prevalences, SNP-based heritabilities and genetic correlations reported in Table 1 (m, number of independent causal variants; see Methods). Approximate standard errors of m * F_{ST,causal,A1B1} are 0.04 for SCZ vs. BIP, 0.02 for SCZ vs. MDD and 0.03 for BIP vs. MDD (see Methods). For SCZ and BIP, despite the large genetic correlation (r_g = 0.7), the genetic distance between SCZ cases and BIP cases is only slightly smaller ($\sqrt{m*F_{ST,causal}}=0.49$) than the case-control distances for SCZ (0.66) and BIP (0.60), because of the doubly strong ascertainment (due to low disorder prevalences) in SCZ cases and BIP cases and because a genetic correlation of 0.7 is still considerably smaller than a genetic correlation of e.g. 0.9 (Supplementary Figure 20). For SCZ and MDD (r_g = 0.31), the genetic distance between MDD cases and SCZ cases (0.63) is larger than for MDD case-control (0.29) (Panel C) owing to the larger prevalence and lower heritability of MDD. For MDD and BIP (r_g = 0.33), genetic distances are similar to MDD and SCZ (Panel D). Numerical results are reported in Supplementary Table 11.

Figure 2.. Power and type I error of CC-GWAS.

We report (A) the power to detect SNPs with effect sizes following a bivariate normal distribution, (B) the type I error rate for loci with no effect on A1A0 or B1B0 (“null-null” SNPs) and (C) the type I error rate for SNPs with the same allele frequency in A1 vs. B1 that explain 0.10% of variance in A1 vs. A0 and 0.29% of variance in B1 vs. B0 (“stress test” SNPs), for each of four methods: CC-GWAS, the CC-GWAS_OLS component, the CC-GWAS_Exact component, and a naïve Delta method (see text). Default parameter settings are: h²=0.2, prevalence K=0.01, and sample size 100,000 cases + 100,000 controls for disorder A; liability-scale h²=0.1, prevalence K=0.15, and sample size 100,000 cases + 100,000 controls for disorder B; m=5,000 causal SNPs for each disorder; and genetic correlation r_g=0.5 between disorders. Numerical results of these analytical computations are reported in Supplementary Table 1, and confirmed with simulation results in Supplementary Table 2.

Figure 3.. Type I error of CC-GWAS due to differential tagging of a causal stress test SNP.

(A) Illustrative example of how differential tagging of a causal stress test SNP can lead to type I error. (B) Simulation results of type I error due to differential tagging. We report the per-locus type I error rate, defined as the number of loci with at least one genome-wide significant tagging SNP divided by the number of loci tested, for each of four methods/scenarios: CC-GWAS, causal stress test SNP genotyped/imputed (denoted CC-GWAS-causal-typed); CC-GWAS, causal stress test SNP not genotyped/imputed (denoted CC-GWAS-causal-untyped); CC-GWAS, no filter; and Direct case-case GWAS (see text). Default parameter settings are: h²=0.2, prevalence K=0.01, and sample size 100,000 cases + 100,000 controls for disorder A; liability-scale h²=0.1, prevalence K=0.15, and sample size 100,000 cases + 100,000 controls for disorder B; m=5,000 causal SNPs for each disorder; and genetic correlation r_g=0.5 between disorders. Per-locus type I error rates <5×10⁻⁸ were truncated to 5×10⁻⁸ for visualization purposes. All simulation standard errors were 0 for CC-GWAS-causal-typed (zero false positives across all simulations performed); ≤2.7×10⁻⁵ for CC-GWAS-causal-untyped; ≤1.7×10⁻³ for CC-GWAS, no filter; and ≤2.1×10⁻³ for Direct case-case GWAS. Numerical results are reported in Supplementary Table 7.

Figure 4.. Case-control effect sizes at CC-GWAS loci for SCZ, BIP and MDD.

We report the respective case-control effect sizes for lead SNPs at CC-GWAS loci for (A) SCZ vs. BIP, (B) SCZ vs. MDD and (C) BIP vs. MDD. Effect sizes are reported on the standardized observed scale based on 50/50 case-control ascertainment. Red points denote CC-GWAS-specific loci, and black points denote remaining loci. Dashed lines denote effect-size thresholds for genome-wide significance. All red points (denoting lead SNPs for CC-GWAS-specific loci) lie inside the dashed lines for both disorders; in panel A, one black point (denoting the lead SNP for a CC-GWAS locus that is not CC-GWAS-specific) lies inside the dashed lines for both SCZ and BIP, because the lead SNP is not genome-wide significant for SCZ but is in LD with a SNP that is genome-wide significant for SCZ. Numerical results are reported in Supplementary Table 13. SCZ, schizophrenia; BIP, bipolar disorder; MDD, major depressive disorder.

Figure 5.. Independent replication of CC-GWAS results.

We report replication case-case CC-GWAS_OLS effect sizes vs. discovery case-case CC-GWAS_OLS effect sizes for (A) schizophrenia (SCZ) vs. major depressive disorder (MDD), (B) three autoimmune disorders, (C) SCZ vs. MDD and three autoimmune disorders, restricting to CC-GWAS-specific loci, and (D) SCZ vs. MDD and three autoimmune disorders, restricting to remaining loci. We also report regression slopes (SE in parentheses), effect sign concordance, and effect sign concordance together with replication P_OLS<0.05. Red points denote CC-GWAS-specific loci, and black points denote remaining loci. Numerical results are reported in Supplementary Table 27, and corresponding case-control replication results are reported in Supplementary Figure 15 and Supplementary Table 28.