Medical Records-Based Genetic Studies of the Complement System

Abstract

Background: Genetic variants in complement genes have been associated with a wide range of human disease states, but well-powered genetic association studies of complement activation have not been performed in large multiethnic cohorts.

Methods: We performed medical records-based genome-wide and phenome-wide association studies for plasma C3 and C4 levels among participants of the Electronic Medical Records and Genomics (eMERGE) network.

Results: In a GWAS for C3 levels in 3949 individuals, we detected two genome-wide significant loci: chr.1q31.3 (CFH locus; rs3753396-A; β=0.20; 95% CI, 0.14 to 0.25; P=1.52x10^-11) and chr.19p13.3 (C3 locus; rs11569470-G; β=0.19; 95% CI, 0.13 to 0.24; P=1.29x10^-8). These two loci explained approximately 2% of variance in C3 levels. GWAS for C4 levels involved 3998 individuals and revealed a genome-wide significant locus at chr.6p21.32 (C4 locus; rs3135353-C; β=0.40; 95% CI, 0.34 to 0.45; P=4.58x10^-35). This locus explained approximately 13% of variance in C4 levels. The multiallelic copy number variant analysis defined two structural genomic C4 variants with large effect on blood C4 levels: C4-BS (β=-0.36; 95% CI, -0.42 to -0.30; P=2.98x10^-22) and C4-AL-BS (β=0.25; 95% CI, 0.21 to 0.29; P=8.11x10^-23). Overall, C4 levels were strongly correlated with copy numbers of C4A and C4B genes. In comprehensive phenome-wide association studies involving 102,138 eMERGE participants, we cataloged a full spectrum of autoimmune, cardiometabolic, and kidney diseases genetically related to systemic complement activation.

Conclusions: We discovered genetic determinants of plasma C3 and C4 levels using eMERGE genomic data linked to electronic medical records. Genetic variants regulating C3 and C4 levels have large effects and multiple clinical correlations across the spectrum of complement-related diseases in humans.

Keywords: autoimmunity; complement system; electronic health records; genome wide association study; phenome wide association study.

Figure 1.

Study design and workflow summary. Analytical workflow for GWAS for C3 and C4 levels in the eMERGE network (primary analysis; top); refinement of genome-wide significant loci by conditional analysis, imputation, annotations, and single-locus PheWAS (secondary analyses; bottom right); and derivation of polygenic scores for C3 and C4 followed by a polygenic score–based PheWAS (exploratory analyses; bottom left). QC, quality control.

Figure 2.

GWAS for C3 levels. (A) Manhattan plot, (B) regional plot for the CFH locus, and (C) regional plot for the C3 locus. The y axis represents −log-transformed P values, and the x axis represents genomic position. The 1000 Genomes Europeans reference panel was used for LD reference.

Figure 3.

Genome-wide genetic correlations of GWAS results for C3 and C4 levels with infectious, autoimmune, and cardiometabolic traits. (A) global genetic correlations of C3 levels, (B) genetic correlations of C3 levels without the HLA region, (C) global genetic correlations of C4 levels, and (D) genetic correlations of C4 levels without the HLA region.

Figure 4.

PheWAS for polygenic predictors of C3 and C4 levels in 102,138 eMERGE participants. (A and B) Phenome-wide associations of polygenic predictor of C3 levels (A) with HLA region included and (B) without HLA. (C and D) Polygenic predictor of C4 levels (C) with HLA included and (D) without HLA. Selected significant associations are labeled across various organ systems. The red horizontal lines indicate phenome-wide significance level (P=2.8x10^-5) after accounting for the number of phecodes tested.

Figure 5.

GWAS for C4 levels. (A) Manhattan plot and (B) regional plot of the C4 (MHC class 3) locus. The y axis represents −log-transformed P values, and the x axis represents genomic location. The 1000 Genome Europeans reference panel was used for LD reference.

Figure 6.

Structural forms of the C4 locus and their associations with blood C4 levels. (A) The effects of common structural C4 haplotypes on blood C4 protein levels (β; 95% CIs), haplotype frequencies, and association P values. C4A and C4B differ only by four amino acids, and the human endogenous retroviral (HERV) element is integrated in intron 9 of the C4A and C4B genes, contributing to interlocus and interallelic length heterogeneity of C4 genes. (B) Heat map of blood C4 levels as a function of ten common combinations of C4A and C4B gene copy numbers; the path from left to right on the plot corresponds to the increasing C4A gene copy, and the path from bottom to top corresponds to the increasing C4B gene copy numbers. Mutually adjusted per-copy effects on blood C4 levels and the corresponding P values are also depicted.