Division of Genetics, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Division of Pulmonary Medicine, Boston Children's Hospital, Boston, Massachusetts, United States of America.
PLoS Genet. 2022 Dec 27;18(12):e1010557. doi: 10.1371/journal.pgen.1010557. eCollection 2022 Dec.
Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 (PRIM1) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV1/FVC), and an eQTL of matrix metallopeptidase 15 (MMP15) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 (HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases.
由于所需表型的成本和负担,许多源于生理测试的遗传性特征的遗传关联研究通常样本量较小。这降低了统计能力,并限制了多个遗传关联的发现。我们提出了一种利用特征之间的多效性来发现新基因座并提供潜在病理生理学机制假说的策略。具体来说,我们将共定位测试与基因座水平的多效性测试相结合。在模拟中,我们表明这种方法对于识别由相同因果变异驱动的真正多效性非常具有选择性,从而提高了在无力量化验证队列中复制关联的机会,并导致更高的可解释性。在这里,作为一个范例,我们使用阻塞性睡眠呼吸暂停(OSA),这是一种使用过夜多通道生理测试诊断的常见疾病。我们利用与相关细胞和心脏代谢特征以及基因表达特征的多效性来绘制功率不足的 OSA GWAS 中的新风险基因座。我们确定了几个多效性基因座,这些基因座与 OSA 存在提示性关联,与其他特征存在全基因组显著关联,并表明它们在不同种族的独立队列中的 OSA 关联得到了复制。通过研究多效性基因座,我们的策略允许提出有关许多生理层面对 OSA 病理生物学的新假说。例如,我们在血小板计数、OSA 和免疫细胞中 DNA 聚合酶亚基 1(PRIM1)的 eQTL 之间识别并复制了多效性。我们发现 OSA 与肺功能(FEV1/FVC)的一个衡量标准之间存在提示性联系,以及肺组织中基质金属蛋白酶 15(MMP15)的一个 eQTL 之间存在提示性联系。我们还将 OSA 在己糖激酶 1(HK1)基因座中的先前全基因组显著峰与血细胞比容和其他与红细胞相关的特征联系起来。因此,多效性关联的分析有可能将多种表型组合成一个机械假说链,从而深入了解复杂人类疾病的发病机制。