Applying exome sequencing to populations with unique genetic architecture has the potential to reveal novel genes and variants associated with traits and diseases. We sequenced and analyzed the exomes of 6,716 individuals from a Southwestern American Indian (SWAI) population with well-characterized metabolic traits. We found that the SWAI population has distinct allelic architecture compared to populations of European and East Asian ancestry, and there were many predicted loss-of-function (pLOF) and nonsynonymous variants that were highly enriched or private in the SWAI population. We used pLOF and nonsynonymous variants in the SWAI population to evaluate gene-burden associations of candidate genes from European genome-wide association studies (GWASs) for type 2 diabetes, body mass index, and four major plasma lipids. We found 19 significant gene-burden associations for 11 genes, providing additional evidence for prioritizing candidate effector genes of GWAS signals. Interestingly, these associations were mainly driven by pLOF and nonsynonymous variants that are unique or highly enriched in the SWAI population. Particularly, we found four pLOF or nonsynonymous variants in APOB, APOE, PCSK9, and TM6SF2 that are private or enriched in the SWAI population and associated with low-density lipoprotein (LDL) cholesterol levels. Their large estimated effects on LDL cholesterol levels suggest strong impacts on protein function and potential clinical implications of these variants in cardiovascular health. In summary, our study illustrates the utility and potential of exome sequencing in genetically unique populations, such as the SWAI population, to prioritize candidate effector genes within GWAS loci and to find additional variants in known disease genes with potential clinical impact.

将外显子组测序应用于具有独特遗传结构的种群有可能揭示与性状和疾病相关的新基因和变异体。我们对来自西南美洲印第安人（SWAI）人群的6716个个体的外显子组进行了测序和分析，这些个体具有良好的代谢特征。我们发现，与欧洲和东亚血统的种群相比，SWAI种群具有独特的等位基因结构，并且在SWAI种群中有许多预测的功能丧失（pLOF）和非同义词变体。我们在SWAI人群中使用了pLOF和非同义词变体来评估来自欧洲全基因组关联研究（GWAS）的2型糖尿病，体重指数和四种主要血脂的候选基因的基因负担关联。我们发现了11个基因的19个重要的基因负担关联，为确定GWAS信号的候选效应基因的优先顺序提供了其他证据。有趣的是，这些关联主要是由SWIF人群中独特或高度丰富的pLOF和非同义词变体驱动的。特别是，我们发现了四个pLOF或非同义变体APOB，APOE，PCSK9和TM6SF2是私有的或在SWAI人群中富集的，并且与低密度脂蛋白（LDL）胆固醇水平相关。他们对LDL胆固醇水平的巨大估计影响表明，这些蛋白对心血管功能的蛋白质功能和这些临床潜在临床意义具有重大影响。总而言之，我们的研究说明了基因组独特的群体（如SWAI群体）中外显子组测序的实用性和潜力，可以在GWAS基因座内对候选效应基因进行优先排序，并在已知疾病基因中寻找具有潜在临床影响的其他变异。