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）单变量全基因组关联研究（Single single-nucleotide polymorphism genome-wide association studies, SSGWAS）往往难以识别对性状具有中等效应的基因座。近期提出的区域遗传力定位（Regional Heritability Mapping, RHM）方法则有望识别这类基因座。本研究以血脂性状——高密度脂蛋白（High-density Lipoprotein, HDL）、低密度脂蛋白（Low-density Lipoprotein, LDL）、总胆固醇（Total Cholesterol, TC）血浆浓度及甘油三酯（Triglycerides, TG）——为分析对象，对比了RHM与SSGWAS的分析表现。研究数据集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芯片进行分型。为验证分析结果，本研究将其与上述血脂性状的大型荟萃分析结果进行了比对。采用RHM方法，本研究共识别出2个分别定位于15号和16号染色体的HDL相关显著区域，以及1个定位于19号染色体的LDL相关显著区域。上述区域覆盖了荟萃分析中与HDL及LDL关联最显著的SNP位点。尽管荟萃分析中最显著的SNP（或与其存在连锁不平衡的任意SNP）未在本研究的SNP芯片中完成分型，但我们仍在数据中成功识别出了19号染色体上的上述区域。SSGWAS则仅识别出1个位于16号染色体上与HDL相关的SNP（即荟萃分析中的顶级显著SNP），以及1个位于10号染色体的位点，该位点未被RHM或荟萃分析报道，因此可能为假阳性关联。本研究结果进一步证实，相较于SSGWAS，RHM在检测因果区域（包括包含关键未分型变异的区域）时具备更优的统计效力。本研究表明，RHM可作为一种实用工具，用于解释复杂性状变异中部分“缺失的遗传力”。