Common variants in HSPB7 and FRMD4B associated with advanced heart failure

Abstract

Background: Heart failure results from abnormalities in multiple biological processes that contribute to cardiac dysfunction. We tested the hypothesis that inherited variation in genes of known importance to cardiovascular biology would thus contribute to heart failure risk.

Methods and results: We used the ITMAT/Broad/CARe cardiovascular single-nucleotide polymorphism array to screen referral populations of patients with advanced heart failure for variants in approximately 2000 genes of predicted importance to cardiovascular biology. Our design was a 2-stage case-control study. In stage 1, genotypes in Caucasian patients with heart failure (n=1590; ejection fraction, 32+/-16%) were compared with those in unaffected controls (n=577; ejection fraction, 67+/-8%) who were recruited from the same referral centers. Associations were tested for independent replication in stage 2 (308 cases and 2314 controls). Two intronic single-nucleotide polymorphisms showed replicated associations with all-cause heart failure as follows: rs1739843 in HSPB7 (combined P=3.09x10(-6)) and rs6787362 in FRMD4B (P=6.09x10(-6)). For both single-nucleotide polymorphisms, the minor allele was protective. In subgroup analyses, rs1739843 associated with both ischemic and nonischemic heart failure, whereas rs6787362 associated principally with ischemic heart failure. Linkage disequilibrium surrounding rs1739843 suggested that the causal variant resides in a region containing HSPB7 and a neighboring gene, CLCNKA, whereas the causal variant near rs6787362 is probably within FRMD4B. Allele frequencies for these single-nucleotide polymorphisms were substantially different in African Americans (635 cases and 714 controls) and showed no association with heart failure in this population.

Conclusions: Our findings identify regions containing HSPB7 and FRMD4B as novel susceptibility loci for advanced heart failure. More broadly, in an era of genome-wide association studies, we demonstrate how knowledge of candidate genes can be leveraged as a complementary strategy to discern the genetics of complex disorders.

Figure 1. Genomic regions containing our top associated SNPs

The upper panels show strength of association in the Stage 1 Caucasian discovery population using IBC data; genotyped IBC SNPs are indicated with diamonds and imputed SNPs with squares. The lower panels demonstrate LD(R 2) and recombination rates using HapMap CEU data alone; vertical dashed lines demarcate an LD block in which R²> 0.8.