Collective effects of human genomic variation on microbiome function.
Collective effects of human genomic variation on microbiome function.
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DOI：
10.1038/s41598-022-07632-3
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发表时间：
2022-03-09
影响因子：
4.6
通讯作者：
Brito IL
中科院分区：
文献类型：
--
作者：
New FN;Baer BR;Clark AG;Wells MT;Brito IL
宿主遗传学对肠道微生物组组成影响的研究主要集中在个体单核苷酸多态性（SNP）对肠道微生物组组成的影响，而没有考虑它们的集体影响或微生物组的特定功能。为了评估人类遗传学对肠道微生物组组成和功能的总体作用，我们应用稀疏典型相关分析 (sCCA)，这是一种灵活的多变量数据集成方法。宏基因组数据的一个关键属性是其稀疏性，在这里我们建议应用 Tweedie 分布来适应这一点。我们利用 TwinsUK 队列分析了 250 名个体的肠道微生物组和人类变异。稀疏 CCA（或 sCCA）鉴定了微生物组相关代谢特征（BMI、血压）和微生物组相关疾病（2 型糖尿病、某些神经系统疾病）和某些癌症中的 SNP。发现常见和罕见的微生物功能（例如分泌系统蛋白或抗生素耐药性）与宿主遗传学有关。 sCCA 应用于微生物物种丰度发现了已知的关联（例如双歧杆菌物种）以及新的关联。尽管我们的样本量很小，但我们的方法不仅可以识别以前已知的关联，还可以识别新的关联。总的来说，我们提出了一个新的、灵活的框架来检查宿主-微生物组遗传相互作用，并为当前围绕人类遗传学对肠道微生物组的作用的争论提供了一个新的维度。
Studies of the impact of host genetics on gut microbiome composition have mainly focused on the impact of individual single nucleotide polymorphisms (SNPs) on gut microbiome composition, without considering their collective impact or the specific functions of the microbiome. To assess the aggregate role of human genetics on the gut microbiome composition and function, we apply sparse canonical correlation analysis (sCCA), a flexible, multivariate data integration method. A critical attribute of metagenome data is its sparsity, and here we propose application of a Tweedie distribution to accommodate this. We use the TwinsUK cohort to analyze the gut microbiomes and human variants of 250 individuals. Sparse CCA, or sCCA, identified SNPs in microbiome-associated metabolic traits (BMI, blood pressure) and microbiome-associated disorders (type 2 diabetes, some neurological disorders) and certain cancers. Both common and rare microbial functions such as secretion system proteins or antibiotic resistance were found to be associated with host genetics. sCCA applied to microbial species abundances found known associations such as Bifidobacteria species, as well as novel associations. Despite our small sample size, our method can identify not only previously known associations, but novel ones as well. Overall, we present a new and flexible framework for examining host-microbiome genetic interactions, and we provide a new dimension to the current debate around the role of human genetics on the gut microbiome.
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影响因子：
7.7
作者：
Beghini F;McIver LJ;Blanco-Míguez A;Dubois L;Asnicar F;Maharjan S;Mailyan A;Manghi P;Scholz M;Thomas AM;Valles-Colomer M;Weingart G;Zhang Y;Zolfo M;Huttenhower C;Franzosa EA;Segata N
通讯作者：
Segata N
影响因子：
9.2
作者：
Chang CC;Chow CC;Tellier LC;Vattikuti S;Purcell SM;Lee JJ
通讯作者：
Lee JJ
影响因子：
28.3
作者：
Brito, Ilana L.;Gurry, Thomas;Alm, Eric J.
通讯作者：
Alm, Eric J.
影响因子：
46.9
作者：
Costea, Paul I.;Zeller, Georg;Bork, Peer
通讯作者：
Bork, Peer
影响因子：
30.3
作者：
Hildebrand F;Gossmann TI;Frioux C;Özkurt E;Myers PN;Ferretti P;Kuhn M;Bahram M;Nielsen HB;Bork P
通讯作者：
Bork P