利用分离群体发现哮喘的代谢物数量性状基因座。
Discovering metabolite quantitative trait loci in asthma using an isolated population.
机构信息
Division of Biomedical Informatics and Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colo.
Division of Biomedical Informatics and Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colo.
出版信息
J Allergy Clin Immunol. 2022 May;149(5):1807-1811.e16. doi: 10.1016/j.jaci.2021.11.002. Epub 2021 Nov 12.
BACKGROUND
Integration of metabolomics with genetics may advance understanding of disease pathogenesis but has been underused in asthma genetic studies.
OBJECTIVE
We sought to discover new genetic effects in asthma and to characterize the molecular consequences of asthma genetic risk through integration with the metabolome in a homogeneous population.
METHODS
From fasting serum samples collected on 348 Tangier Island residents, we quantified 2612 compounds using untargeted metabolomics. Genotyping was performed using Illumina's MEGA array imputed to the TOPMed reference panel. To prioritize metabolites for genome-wide association analysis, we performed a metabolome-wide association study with asthma, selecting asthma-associated metabolites with heritability q value less than 0.01 for genome-wide association analysis. We also tested the association between all metabolites and 8451 candidate asthma single nucleotide polymorphisms previously associated with asthma in the UK Biobank. We followed up significant associations by characterizing shared genetic signal for metabolites and asthma using colocalization analysis. For detailed Methods, please see this article's Online Repository at www.jacionline.org.
RESULTS
A total of 60 metabolites were associated with asthma (P < .01), including 40 heritable metabolites tested in genome-wide association analysis. We observed a strong association peak for the endocannabinoid linoleoyl ethanolamide on chromosome 6 in VNN1 (P < 2.7 × 10). We found strong evidence (colocalization posterior probability >75%) for a shared causal variant between 3 metabolites and asthma, including the polyamine acisoga and variants in LPP, and derivative leukotriene B4 and intergenic variants in chr10p14.
CONCLUSIONS
We identified novel metabolite quantitative trait loci with asthma associations. Identification and characterization of these genetically driven metabolites may provide insight into the functional consequences of genetic risk factors for asthma.
背景
代谢组学与遗传学的结合可能有助于深入了解疾病发病机制，但在哮喘遗传学研究中应用不足。
目的
我们旨在通过在同质人群中与代谢组学相结合，发现哮喘的新遗传效应，并描述哮喘遗传风险的分子后果。
方法
我们从 348 名 Tangier 岛居民的空腹血清样本中，使用非靶向代谢组学技术定量检测了 2612 种化合物。使用 Illumina 的 MEGA 阵列进行基因分型，并将其遗传信息内插至 TOPMed 参考面板。为了优先对全基因组关联分析的代谢物进行分析，我们针对哮喘进行了代谢组全基因组关联研究，选择遗传力 q 值小于 0.01 的与哮喘相关的代谢物进行全基因组关联分析。我们还测试了所有代谢物与先前在英国生物库中与哮喘相关的 8451 个候选哮喘单核苷酸多态性之间的关联。我们通过共定位分析，对代谢物和哮喘的共享遗传信号进行特征描述，对显著关联进行了后续分析。详细方法请见本文在线知识库（www.jacionline.org）。
结果
共有 60 种代谢物与哮喘相关（P <.01），其中 40 种可遗传代谢物在全基因组关联分析中进行了测试。我们在 VNN1 染色体 6 上观察到内源性大麻素 linoleoyl 乙醇酰胺的强烈关联峰（P < 2.7 × 10）。我们发现 3 种代谢物与哮喘之间存在强烈的因果变异共享证据（共定位后验概率>75%），包括多胺 acisoga 以及 LPP 中的变体和衍生白三烯 B4 以及 chr10p14 中的基因间变体。
结论
我们确定了与哮喘相关的新型代谢物数量性状基因座。这些遗传驱动代谢物的鉴定和特征描述可能为哮喘遗传风险因素的功能后果提供新的认识。
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