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  • Causal associations between type 1 diabetes and COVID-19 infection and prognosis: a two-sample Mendelian randomization study

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Epidemiology/Health services research
Causal associations between type 1 diabetes and COVID-19 infection and prognosis: a two-sample Mendelian randomization study

Authors

  • Xin-Ling Ma Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaJiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China PubMed articlesGoogle scholar articles
  • Qi-Yun Shi Department of Endocrinology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China PubMed articlesGoogle scholar articles
  • Qi-Gang Zhao Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaJiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China PubMed articlesGoogle scholar articles
  • Qian Xu Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaJiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China PubMed articlesGoogle scholar articles
  • Shan-Shan Yan Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaJiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China PubMed articlesGoogle scholar articles
  • Bai-Xue Han Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaJiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China PubMed articlesGoogle scholar articles
  • Chen Fang Department of Endocrinology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China PubMed articlesGoogle scholar articles
  • Lei Zhang Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaCenter for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China PubMed articlesGoogle scholar articles
  • Yu-Fang Pei Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaJiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, China PubMed articlesGoogle scholar articles
  1. Correspondence to Dr Yu-Fang Pei; ypei{at}suda.edu.cn; Lei Zhang; lzhang6{at}suda.edu.cn
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Citation

Ma X, Shi Q, Zhao Q, et al
Causal associations between type 1 diabetes and COVID-19 infection and prognosis: a two-sample Mendelian randomization study
BMJ Open Diabetes Research and Care 2023;11:e003167. doi: 10.1136/bmjdrc-2022-003167

Publication history

  • Received October 6, 2022
  • Accepted May 20, 2023
  • First published June 13, 2023.
Online issue publication 
July 09, 2023

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

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© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.