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.单核苷酸多态性（single-nucleotide polymorphism, SNP）单SNP全基因组关联研究（single SNP genome-wide association studies, SSGWAS）通常难以识别对性状具有微弱效应的基因座。近期提出的区域遗传力定位（regional heritability mapping, RHM）方法则有望实现这类基因座的鉴定。本研究针对血脂性状——涵盖高密度脂蛋白（high-density lipoprotein, HDL）、低密度脂蛋白（low-density lipoprotein, LDL）、血浆总胆固醇（total cholesterol, TC）与甘油三酯（triglycerides, TG）浓度——对比分析了RHM与SSGWAS的分析效果。研究数据包含来自隔离人群的2246名成人受试者，其基因组采用约30万个SNP芯片完成分型。本研究结果通过针对上述血脂性状的大型荟萃分析（meta-analyses）进行验证。借助RHM方法，我们在15号与16号染色体上各鉴定出一个影响HDL的显著区域，在19号染色体上鉴定出一个影响LDL的显著区域。上述区域覆盖了荟萃分析中与HDL和LDL关联最显著的SNP。值得关注的是，尽管荟萃分析中最显著的SNP（或与其连锁的标签SNP）未在本研究的SNP芯片中进行分型，但我们仍成功检测到了19号染色体上的该区域。SSGWAS仅鉴定出16号染色体上一个与HDL相关的SNP（即荟萃分析中的顶级关联SNP），以及10号染色体上的一个SNP——该位点未被RHM报道，也未出现在上述荟萃分析中，因此大概率为假阳性关联。本研究结果进一步证实，RHM在检测因果区域方面具备比SSGWAS更优异的效力，包括那些包含关键未分型变异的区域。本研究表明，RHM可作为解释复杂性状变异中部分“缺失遗传力”的有效工具。