The Relationship Between the Human Genome and Microbiome Comes into View.
The Relationship Between the Human Genome and Microbiome Comes into View.
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DOI：
10.1146/annurev-genet-110711-155532
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发表时间：
2017-11-27
影响因子：
11.1
通讯作者：
Ley RE
中科院分区：
文献类型：
--
作者：
Goodrich JK;Davenport ER;Clark AG;Ley RE
微生物组在健康和疾病中的作用，以及其组成和功能的复杂性，使得考虑影响微生物组组成的人类遗传因素变得有趣。基因可能通过促进肠道中稳定的微生物群落的能力来影响健康。遗传力的研究产生了受基因影响的微生物的一致子集，但使用全基因组关联研究（GWAS）来识别与微生物群表型相关的特定遗传变异已被证明具有挑战性。将微生物组数据集处理成需要建模的特征，减少多次测试的负担只是微生物组GWAS的一些技术障碍。根据GWAS标准，迄今为止的研究规模很小，这使得交叉研究比较和验证在识别真实信号方面尤为重要。交叉研究比较受到分析方法差异的阻碍。然而，在人群之间出现了一些一致的联系，最明显的是双歧杆菌和乳糖酶非持久性基因型之间的联系。这些早期的成功为将微生物组纳入量化基因型、环境和微生物组之间相互作用以预测疾病易感性的研究开辟了道路。
The microbiome’s involvement in health and disease, and the complexity of its composition and function, make it intriguing to consider human genetic factors that impact microbiome composition. Genes may influence health through their ability to promote a stable microbial community in the gut. Studies of heritability yield a consistent subset of microbes that are impacted by genes, but the use of genome-wide association studies (GWAS) to identify specific genetic variants associated with microbiota phenotypes has proven challenging. Processing microbiome datasets into traits to be modeled and reducing the burden of multiple testing are just some of the technical hurdles in microbiome GWAS. Studies to date are small by GWAS standards, making cross-study comparisons and validations particularly important in identifying authentic signals. Cross-study comparisons are hampered by differences in analytical approaches. Nevertheless, some consistent associations have emerged between populations, most notably between Bifidobacteria and the lactase non-persister genotype. These early successes open the way for the microbiome to be incorporated into studies that quantify interactions among genotype, environment, and the microbiome for predicting disease susceptibility.
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影响因子：
10.9
作者：
Hand, Timothy W.;Vujkovic-Cvijin, Ivan;Ridaura, Vanessa K.;Belkaid, Yasmine
通讯作者：
Belkaid, Yasmine
影响因子：
3.7
作者：
Armougom F;Henry M;Vialettes B;Raccah D;Raoult D
通讯作者：
Raoult D
影响因子：
3.9
作者：
Han, Shuxin;Chiang, John Y. L.
通讯作者：
Chiang, John Y. L.
影响因子：
30.8
作者：
Enattah, NS;Sahi, T;Järvelä, I
通讯作者：
Järvelä, I
DOI：
10.1073/pnas.1219451110
发表时间：
2013-05-28
影响因子：
11.1
作者：
Everard, Amandine;Belzer, Clara;Cani, Patrice D.
通讯作者：
Cani, Patrice D.