{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Duan Y"],"funding":["\"Pioneer\" and \"Leading Goose\" R&D Program of Zhejiang","the National Key R&D Program of China"],"pagination":["146"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11892230"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["23(1)"],"pubmed_abstract":["<h4>Background</h4>Individuals who smoke tend to have a lower body mass index (BMI) but face an increased risk of obesity-related diseases. This study investigates this paradox from the perspective of gut microbiota.<h4>Methods</h4>We conducted microbiome analyses to identify smoking-related microbial genera and created a smoking-related microbiota index (SMI) using 16S rRNA sequencing data from 4000 male participants in WELL-China cohort and Lanxi cohort. We employed logistic regression to explore the association between SMI and obesity indices derived from dual-energy X-ray absorptiometry. Cox regression analyses were conducted to explore the association of SMI with incident of obesity-related diseases. To further control for unmeasured familial confounders, sibling comparison analyses w"],"journal":["BMC medicine"],"pubmed_title":["Smoking-related gut microbiota alteration is associated with obesity and obesity-related diseases: results from two cohorts with sibling comparison analyses."],"pmcid":["PMC11892230"],"funding_grant_id":["Grant No. 2024C03180","Grant No. 2022YFC2705300","Grant No. 2022YFC2705303"],"pubmed_authors":["Xu N","Yu M","Myers A","Lu Y","Xu C","Zheng W","Delzell E","Wu YH","Gong W","Hsing AW","He W","Wang W","Wang X","Zhong J","Chu L","Duan Y","Zhu S"],"additional_accession":[]},"is_claimable":false,"name":"Smoking-related gut microbiota alteration is associated with obesity and obesity-related diseases: results from two cohorts with sibling comparison analyses.","description":"<h4>Background</h4>Individuals who smoke tend to have a lower body mass index (BMI) but face an increased risk of obesity-related diseases. This study investigates this paradox from the perspective of gut microbiota.<h4>Methods</h4>We conducted microbiome analyses to identify smoking-related microbial genera and created a smoking-related microbiota index (SMI) using 16S rRNA sequencing data from 4000 male participants in WELL-China cohort and Lanxi cohort. We employed logistic regression to explore the association between SMI and obesity indices derived from dual-energy X-ray absorptiometry. Cox regression analyses were conducted to explore the association of SMI with incident of obesity-related diseases. To further control for unmeasured familial confounders, sibling comparison analyses w","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Mar","modification":"2025-04-22T11:08:57.894Z","creation":"2025-04-05T23:53:49.947Z"},"accession":"S-EPMC11892230","cross_references":{"pubmed":["40059170"],"doi":["10.1186/s12916-025-03969-4"]}}