• Intern Emerg Med · Aug 2024

    Mendelian randomization did not support the causal effect of diabetes on aortic diseases.

    • Tao Yang, Xin Yuan, Wei Gao, Meng-Jin Hu, Min-Jie Lu, and Han-Song Sun.
    • Department of Cardiovascular Surgery, Cardiovascular Institute and Fu Wai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, No. 167 North Lishi Road, Xicheng District, Beijing, 100037, China.
    • Intern Emerg Med. 2024 Aug 29.

    AbstractObservational studies revealed paradoxically inverse associations between diabetes and aortic diseases (aortic aneurysm or aortic dissection), yet the causality remains to be determined. To investigate the causal associations between diabetes and aortic diseases using Mendelian randomization (MR) analyses. Summary-level data for exposures (type 1 diabetes, type 2 diabetes, fasting glucose, fasting insulin, glycated hemoglobin) and outcomes (aortic dissection and aortic aneurysm) were obtained from public genome-wide association study data. The principal analysis was the inverse-variance weighted (IVW) method. Sensitivity analyses were also carried out, including weighted median, MR-Egger, and multivariable MR methods. According to IVW results, type 1 diabetes (odds ratio [OR]: 0.99; 95% confidence interval [CI] 0.93-1.07; P = 0.87), type 2 diabetes (OR: 0.97; 95% CI 0.77-1.20; P = 0.75), fasting glucose (OR: 1.16; 95% CI 0.48-2.84; P = 0.74), fasting insulin (OR: 2.75; 95% CI 0.53-14.26; P = 0.23), or glycated hemoglobin (OR: 0.33; 95% CI 0.09-1.17; P = 0.09) had no causal effect on aortic dissection. Similarly, type 1 diabetes, type 2 diabetes, fasting glucose, fasting insulin, or glycated hemoglobin had no causal effect on aortic aneurysm. Sensitivity analyses revealed consistent results. MR-Egger method and funnel plot yielded no indication of directional pleiotropy. Diabetes had no causal associations with aortic dissection or aortic aneurysm. The observed inverse associations in previous cohort studies may be explained by confounding factors or reverse causation.© 2024. The Author(s), under exclusive licence to Società Italiana di Medicina Interna (SIMI).

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