Genome-wide associations of human gut microbiome variation and implications for causal inference analyses (Nature Microbiology 2020)

報告日期: 2020/12/11
報告時間: 16:00/16:50
報告學生: Liya Paramita
講評老師: 鄧景浩

Genome-wide associations of human gut microbiome variation and implications for causal inference analyses

Hughes DA, et al. Nature Microbiology. 2020 Sep;5(9):1079-1087.

DOI: 10.1038/s41564-020-0743-8. Epub 2020 Jun 22. PMID: 32572223.

Speaker: Liya Paramita                        Time: 16.10 – 17.00

Commentator: Ching-Hao Teng             Room: Collage of Medicine 602


The microbiome genome-wide association study (mGWAS) has been developed to identify and validate the host’s genetic polymorphisms that interact with its microbiome. Moreover, mGWAS has linked host genotypes and identified pathways with inter-individual variability in microbiome composition in states of health and diseases. The gut microbiome that inhabit the human body exists in a synergistic relationship with the human host, performing several important roles in metabolism and homoeostasis.


To study the association between human host genotype and gut microbiome variation.


Microbial traits (MTs) loci were identified by using faecal 16S ribosomal RNA gene sequences and host genotype data were obtained from the Flemish Gut Flora Project and two German cohorts.


Meta analyses showed the strong association between Ruminococcus and rs150018970 (RAPGEF1 gene) on chromosome 9. RAPGEF1 encodes a protein factor that transduces signals from G-protein-coupled receptors (GPCRs), which are probably involved in the regulation of gastrointestinal tract physiology. GPCRs detect metabolites derived from commensal bacteria and have been proposed to be key mediators of host–microbial interactions. Exploratory analyses were undertaken using 11 other genome-wide associations with strong evidence for association and a previously reported signal of association between rs4988235 (MCM6/LCT) and Bifidobacterium. Across these 14 single-nucleotide polymorphisms there was evidence of signal overlap with other genome-wide association studies, including those for age at menarche and cardiometabolic traits. However, the strongest evidence suggested that a lower Bifidobacterium abundance associated with increases waist circumference and body mass index.


Environmental effects are likely to preside over host genetics as a source of variation, even in the presence of unavoidable study-based heterogeneity, standardized and appropriate analytical protocols allow signal detection. Future large-scale meta-analyses need to be done by providing larger catalogues of genetic variants associated with the microbiome.


Awany, D. et al. Host and Microbiome Genome-Wide Association Studies: Current State and Challenges. Frontiers in Genetics 9, doi:10.3389/fgene.2018.00637 (2019).

Emily, R. et al. Genome-Wide Association Studies of the Human Gut Microbiota. PLOS ONE. (2015).