Diabetes mellitus and idiopathic pulmonary fibrosis: a Mendelian randomization study

被引:8
作者
Kang, Quou [1 ,2 ]
Ren, Jing [1 ,2 ]
Cong, Jinpeng [1 ]
Yu, Wencheng [1 ]
机构
[1] Qingdao Univ, Affiliated Hosp, Dept Pulm & Crit Care Med, Qingdao, Peoples R China
[2] Qingdao Univ, Med Dept, Qingdao, Peoples R China
关键词
Idiopathic pulmonary fibrosis; Diabetes mellitus; Type; 1; diabetes; 2; Mendelian randomization; Hyperglycemia; RISK; CITRULLINATION; AUTOIMMUNE; VARIANTS; CELLS;
D O I
10.1186/s12890-024-02961-7
中图分类号
R56 [呼吸系及胸部疾病];
学科分类号
摘要
BackgroundThe question as to whether or not diabetes mellitus increases the risk of idiopathic pulmonary fibrosis (IPF) remains controversial. This study aimed to investigate the causal association between type 1 diabetes (T1D), type 2 diabetes (T2D), and IPF using Mendelian randomization (MR) analysis.MethodsWe used two-sample univariate and multivariate MR (MVMR) analyses to investigate the causal relationship between T1D or T2D and IPF. We obtained genome-wide association study (GWAS) data for T1D and T2D from the European Bioinformatics Institute, comprising 29,652 T1D samples and 101,101 T1D single nucleotide polymorphisms (SNPs) and 655,666 T2D samples and 5,030,727 T2D SNPs. We also used IPF GWAS data from the FinnGen Biobank comprising 198,014 IPF samples and 16,380,413 IPF SNPs. All cases and controls in these datasets were derived exclusively from European populations. In the univariate MR analysis, we employed inverse variance-weighted (IVW), weighted median (WM), and MR-Egger regression methods. For the MVMR analysis, we used the multivariate IVW method primarily, and supplemented it with multivariate MR-Egger and multivariate MR- least absolute shrinkage and selection operator methods. Heterogeneity tests were conducted using the MR-IVW and MR-Egger regression methods, whereas pleiotropic effects were assessed using the MR-Egger intercept. The results of MR and sensitivity analyses were visualized using forest, scatter, leave-one-out, and funnel plots.ResultsUnivariate MR revealed a significant causal relationship between T1D and IPF (OR = 1.118, 95% CI = 1.021-1.225, P = 0.016); however, no significant causal relationship was found between T2D and IPF (OR = 0.911, 95% CI = 0.796-1.043, P = 0.178). MVMR analysis further confirmed a causal association between T1D and IPF (OR = 1.133, 95% CI = 1.011-1.270, P = 0.032), but no causal relationship between T2D and IPF (OR = 1.009, 95% CI = 0.790-1.288, P = 0.950). Sensitivity analysis results validated the stability and reliability of our findings.ConclusionUnivariate and multivariate analyses demonstrated a causal relationship between T1D and IPF, whereas no evidence was found to support a causal relationship between T2D and IPF. Therefore, in clinical practice, patients with T1D should undergo lung imaging for early detection of IPF.
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页数:11
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