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Identification of novel functional CpG-SNPs associated with type 2 diabetes and coronary artery disease

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Abstract

Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D) and coronary artery disease (CAD), respectively. Nevertheless, these studies were generally performed for single-trait/disease and failed to assess the pleiotropic role of the identified variants. To identify novel functional loci and the pleiotropic relationship between CAD and T2D, the targeted cFDR analysis on CpG-SNPs was performed by integrating two independent large and multi-centered GWASs with summary statistics of T2D (26,676 cases and 132,532 controls) and CAD (60,801 cases and 123,504 controls). Applying the cFDR significance threshold of 0.05, we observed a pleiotropic enrichment between T2D and CAD by incorporating pleiotropic effects into a conditional analysis framework. We identified 79 novel CpG-SNPs for T2D, 61 novel CpG-SNPs for CAD, and 18 novel pleiotropic loci for both traits. Among these novel CpG-SNPs, 33 of them were annotated as methylation quantitative trait locus (meQTL) in whole blood, and ten of them showed expression QTL (eQTL), meQTL, and metabolic QTL (metaQTL) effects simultaneously. To the best of our knowledge, we performed the first targeted cFDR analysis on CpG-SNPs, and our findings provided novel insights into the shared biological mechanisms and overlapped genetic heritability between T2D and CAD.

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Data availability

The sequencing data generated from the “whole-genome high-coverage deep re-sequencing study (Shen et al. 2013)” and the list of identified CpG-SNP are available from the corresponding author on request. The T2D GWAS dataset used in this study was obtained from DIAGRAM Consortium (https://diagram-consortium.org/downloads.html). The CAD GWAS dataset used in this study was obtained from CARDIoGRAM Consortium (https://www.cardiogramplusc4d.org/data-downloads/).

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Funding

This research was partially supported or benefited by grants from the National Institutes of Health (R01AR059781, P20GM109036, R01MH107354, R01MH104680, R01GM109068, R01AR069055, U19AG055373, R01AG061917), the Franklin D. Dickson/Missouri Endowment, and the Edward G. Schlieder Endowment and the Drs. W. C. Tsai and P. T. Kung Professorship in Biostatistics from Tulane University, the National Natural Science Foundation of China (Nos. 81370974, 81500056), the Natural Science Foundation of Hunan Province, China (No. 2016JJ3182), and Central South Univesity (2018zzts886).

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Author notes

  1. Zun Wang and Chuan Qiu contributed equally to this work.

Authors and Affiliations

  1. Xiangya Nursing School, Central South University, Changsha, 410013, Hunan, People’s Republic of China

    Zun Wang, Qian Wang, Wei Liu & Si-Yuan Tang

  2. Department of Biostatistics and Data Science, Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA

    Chuan Qiu, Xu Lin, Lan-Juan Zhao, Kelvin Li, Hong-Wen Deng & Hui Shen

  3. College of Life Sciences and Bioengineering, School of Science, Beijing Jiaotong University, Beijing, 100044, People’s Republic of China

    Yong Liu

  4. Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, 410078, People’s Republic of China

    Xinrui Wu

  5. School of Basic Medical Science, Central South University, Changsha, 410013, People’s Republic of China

    Hong-Wen Deng

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  1. Zun Wang
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  2. Chuan Qiu
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Corresponding authors

Correspondence to Si-Yuan Tang or Hui Shen.

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Conflict of interest

ZW and CQ wrote the main manuscript text; XL, YL, and XW conducted data analysis; WL, QW prepared all figures; LJZ and KL prepared supplementary information; the study was designed and supervised by HS, HWD, and SYT. All authors reviewed the manuscript. All authors have no conflicts of interest to declare.

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Wang, Z., Qiu, C., Lin, X. et al. Identification of novel functional CpG-SNPs associated with type 2 diabetes and coronary artery disease. Mol Genet Genomics 295, 607–619 (2020). https://doi.org/10.1007/s00438-020-01651-3

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