Exploring the causal effects of the gut microbiome on serum lipid levels: A two-sample Mendelian randomization analysis
Gongjie Guo, Gongjie Guo, Gongjie Guo and 25 more
Frontiers in Microbiology · 2023
doi:10.3389/fmicb.2023.1113334 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
BackgroundThe gut microbiome was reported to be associated with dyslipidemia in previous observational studies. However, whether the composition of the gut microbiome has a causal effect on serum lipid levels remains unclear.ObjectiveA two-sample Mendelian randomization (MR) analysis was conducted to investigate the potential causal relationships between gut microbial taxa and serum lipid levels, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and log-transformed triglyceride (TG) levels.Materials and methodsSummary statistics of genome-wide association studies (GWASs) for the gut microbiome and four blood lipid traits were obtained from public datasets. Five recognized MR methods were applied to assess the causal estimates, among which, the inverse-variance weighted (IVW) regression was used as the primary MR method. A series of sensitivity analyses were performed to test the robustness of the causal estimates.ResultsThe combined results from the five MR methods and sensitivity analysis showed 59 suggestive causal associations and four significant causal associations. In particular, genus Terrisporobacter was associated with higher LDL-C (PIVW = 3.01 × 10−6) and TC levels (PIVW = 2.11 × 10−4), phylum Actinobacteria was correlated with higher LDL-C level (PIVW = 4.10 × 10−4), and genus Oscillospira was associated with lower TG level (PIVW = 2.19 × 10−6).ConclusionThis research may provide novel insights into the causal relationships of the gut microbiome on serum lipid levels and new therapeutic or prevention strategies for dyslipidemia.
Abstract licence: CC BY
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.