Data from: Regional heritability mapping method helps explain missing heritability of blood lipid traits in isolated populations

Single single-nucleotide polymorphism (SNP) genome-wide association
studies (SSGWAS) may fail to identify loci with modest effects on a trait.
The recently developed regional heritability mapping (RHM) method can
potentially identify such loci. In this study, RHM was compared with the
SSGWAS for blood lipid traits (high-density lipoprotein (HDL), low-density
lipoprotein (LDL), plasma concentrations of total cholesterol (TC) and
triglycerides (TG)). Data comprised 2246 adults from isolated populations
genotyped using ~300 000 SNP arrays. The results were compared with large
meta-analyses of these traits for validation. Using RHM, two significant
regions affecting HDL on chromosomes 15 and 16 and one affecting LDL on
chromosome 19 were identified. These regions covered the most significant
SNPs associated with HDL and LDL from the meta-analysis. The chromosome 19
region was identified in our data despite the fact that the most
significant SNP in the meta-analysis (or any SNP tagging it) was not
genotyped in our SNP array. The SSGWAS identified one SNP associated with
HDL on chromosome 16 (the top meta-analysis SNP) and one on chromosome 10
(not reported by RHM or in the meta-analysis and hence possibly a false
positive association). The results further confirm that RHM can have
better power than SSGWAS in detecting causal regions including regions
containing crucial ungenotyped variants. This study suggests that RHM can
be a useful tool to explain some of the ‘missing heritability’ of complex
trait variation.