Microbiome-wide association studies on large population cohorts have highlighted associations between the gut microbiome and complex traits, including type 2 diabetes (T2D) and obesity. However, the causal relationships remain largely unresolved. We leveraged information from 952 normoglycemic individuals for whom genome-wide genotyping, gut metagenomic sequence and fecal short-chain fatty acid (SCFA) levels were available, then combined this information with genome-wide-association summary statistics for 17 metabolic and anthropometric traits. Using a state-of-the-art statistical genetics method called Mendelian Randomisation (MR), we provided evidence of a causal effect of specific gut microbiome components on metabolic traits. During my presentation, I will explain the rational and framework of this method and the results we obtained. Finally, I will highlight the power and limitations for the use of MR as a means to elucidate causal relationships from microbiome-wide association findings in the future.
Causal relationship among the gut microbiome, short chain fatty acids and metabolic diseases
Serena Sanna
2020
Abstract
Microbiome-wide association studies on large population cohorts have highlighted associations between the gut microbiome and complex traits, including type 2 diabetes (T2D) and obesity. However, the causal relationships remain largely unresolved. We leveraged information from 952 normoglycemic individuals for whom genome-wide genotyping, gut metagenomic sequence and fecal short-chain fatty acid (SCFA) levels were available, then combined this information with genome-wide-association summary statistics for 17 metabolic and anthropometric traits. Using a state-of-the-art statistical genetics method called Mendelian Randomisation (MR), we provided evidence of a causal effect of specific gut microbiome components on metabolic traits. During my presentation, I will explain the rational and framework of this method and the results we obtained. Finally, I will highlight the power and limitations for the use of MR as a means to elucidate causal relationships from microbiome-wide association findings in the future.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.