Case Control Study
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Diabetes. Dec 15, 2021; 12(12): 2073-2086
Published online Dec 15, 2021. doi: 10.4239/wjd.v12.i12.2073
Genome-wide association study reveals novel loci for adult type 1 diabetes in a 5-year nested case-control study
Yan Gao, Shi Chen, Wen-Yong Gu, Chen Fang, Yi-Ting Huang, Yue Gao, Yan Lu, Jian Su, Ming Wu, Jun Zhang, Ming Xu, Zeng-Li Zhang
Yan Gao, Zeng-Li Zhang, Department of Occupational and Environmental Health, School of Public Health, Medical College of Soochow University, Suzhou 215123, Jiangsu Province, China
Yan Gao, Yan Lu, Jun Zhang, Institute of Suzhou Biobank, Suzhou Center for Disease Prevention and Control, Suzhou 215004, Jiangsu Province, China
Shi Chen, Department of Public Health Sciences, University of North Carolina Charlotte, NC 28223, United States
Shi Chen, School of Data Science, University of North Carolina Charlotte, NC 28223, United States
Wen-Yong Gu, Department of Ultrasound, The Second Affiliated Hospital of Soochow University, Suzhou 215004, Jiangsu Province, China
Chen Fang, Department of Endocrinology, The Second Affiliated Hospital of Soochow University, Suzhou 215004, Jiangsu Province, China
Chen Fang, Department of Clinical Nutrition, The Second Affiliated Hospital of Soochow University, Suzhou 215004, Jiangsu Province, China
Yi-Ting Huang, Clinical Nutrition Department, The Second Affiliated Hospital of Soochow University, Suzhou 215004, Jiangsu Province, China
Yue Gao, Ming Xu, Department of Occupational Disease Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, Jiangsu Province, China
Yue Gao, Ming Xu, Public Health Research Institute of Jiangsu Province, Nanjing 210009, Jiangsu Province, China
Jian Su, Ming Wu, Department of Chronic Disease Prevention and Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, Jiangsu Province, China
Author contributions: Xu M and Zhang ZL designed the present study; Gao Y, Gu WY, Fang C, Huang YT, Lu Y and Su J performed the sample and data collection; Gao Y, Chen S and Xu M finished the analysis of data; Chen S and Gao Y wrote the article; Wu M, Zhang J, Gao Y, Xu M and Wu M mainly supported the costing of GWAS analysis.
Supported by the National Science Foundation for Young Scientists of China (No. 81602919); the National Science Foundation for Young Scientists of China (No. 82070814); the Suzhou Science and Technology Development Plan (No. SYS2018099); and the 5th Suzhou Health Talent Program (No. GSWS2019071).
Institutional review board statement: This study was reviewed and approved by the Research Ethics Committee of Jiangsu Provincial Center for Disease Control and Prevention (No. 2012025).
Informed consent statement: All patients gave informed consent.
Conflict-of-interest statement: The authors declare no conflict of interest in this study.
Data sharing statement: Technical appendix, statistical code, and dataset are available from the corresponding author at zhangzengli@suda.edu.cn with the permission of government.
STROBE statement: The authors have read the STROBE statement—checklist of items, and the manuscript was prepared and revised according to the STROBE statement—checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (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 and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Zeng-Li Zhang, MD, PhD, Academic Fellow, Chief Doctor, Department of Occupational and Environmental Health, School of Public Health, Medical College of Soochow University, No. 199 Ren’ai Road, Suzhou 215123, Jiangsu Province, China. zhangzengli@suda.edu.cn
Received: April 21, 2021
Peer-review started: April 21, 2021
First decision: July 15, 2021
Revised: August 3, 2021
Accepted: November 3, 2021
Article in press: October 31, 2021
Published online: December 15, 2021
Processing time: 238 Days and 14.1 Hours
Abstract
BACKGROUND

Type 1 diabetes (T1D) is a severe and prevalent metabolic disease. Due to its high heredity, an increasing number of genome-wide association studies have been performed, most of which were from hospital-based case-control studies with a relatively small sample size. The association of single nucleotide polymorphisms (SNPs) and T1D has been less studied and is less understood in natural cohorts.

AIM

To investigate the significant variants of T1D, which could be potential biomarkers for T1D prediction or even therapy.

METHODS

A genome-wide association study (GWAS) of adult T1D was performed in a nested case-control study (785 cases vs 804 controls) from a larger 5-year cohort study in Suzhou, China. Potential harmful or protective SNPs were evaluated for T1D. Subsequent expression and splicing quantitative trait loci (eQTL and sQTL) analyses were carried out to identify target genes modulated by these SNPs.

RESULTS

A harmful SNP for T1D, rs3117017 [odds ratio (OR) = 3.202, 95% confidence interval (CI): 2.296-4.466, P = 9.33 × 10-4] and three protective SNPs rs55846421 (0.113, 0.081-0.156, 1.76 × 10-9), rs75836320 (0.283, 0.205-0.392, 1.07 × 10-4), rs362071 (0.568, 0.495-0.651, 1.66 × 10-4) were identified. Twenty-two genes were further identified as potential candidates for T1D onset.

CONCLUSION

We identified a potential genetic basis of T1D, both protective and harmful, using a GWAS in a larger nested case-control study of a Chinese population.

Keywords: Type 1 diabetes; Genome-wide association study; Nested case-control study; Polymorphism

Core Tip: Type 1 diabetes (T1D) is a severe and prevalent metabolic disease. Due to its high heredity, an increasing number of genome-wide association studies have been performed, most of which were from hospital-based case-control studies with a relatively small sample size. The aim of this study was to investigate the significant variants of T1D, which could be potential biomarkers for T1D prediction or even therapy. The effects of different polymorphisms in Chinese T1D patients were determined in a healthy population cohort study. The results showed 4 novel variants highly associated with the onset of T1D, namely rs3117017, rs55846421, rs75836320, and rs362071.