Gene-diet interaction analysis using novel weighted food scores discovers the adipocytokine signaling pathway associated with the development of type 2 diabetes

Catherine Apio; Wonil Chung; Min Kyong Moon; Oran Kwon; Taesung Park

doi:10.3389/fendo.2023.1165744

Gene-diet interaction analysis using novel weighted food scores discovers the adipocytokine signaling pathway associated with the development of type 2 diabetes

Front Endocrinol (Lausanne). 2023 Aug 23:14:1165744. doi: 10.3389/fendo.2023.1165744. eCollection 2023.

Authors

Catherine Apio¹, Wonil Chung², Min Kyong Moon³, Oran Kwon⁴, Taesung Park⁵

Affiliations

¹ Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
² Department of Statistics and Actuarial Science, Soongsil University, Seoul, Republic of Korea.
³ Department of Internal Medicine, College of Medicine, Seoul National University, Seoul, Republic of Korea.
⁴ Department of Nutritional Science and Food Management, Ewha Womans University, Seoul, Republic of Korea.
⁵ Department of Statistics, Seoul National University, Seoul, Republic of Korea.

Abstract

Introduction: The influence of dietary patterns measured using Recommended Food Score (RFS) with foods with high amounts of antioxidant nutrients for Type 2 diabetes (T2D) was analyzed. Our analysis aims to find associations between dietary patterns and T2D and conduct a gene-diet interaction analysis related to T2D.

Methods: Data analyzed in the current study were obtained from the Korean Genome and Epidemiology Study Cohort. The dietary patterns of 46 food items were assessed using a validated food frequency questionnaire. To maximize the predictive power of the RFS, we propose two weighted food scores, namely HisCoM-RFS calculated using the novel Hierarchical Structural Component model (HisCoM) and PLSDA-RFS calculated using Partial Least Squares-Discriminant Analysis (PLS-DA) method.

Results: Both RFS (OR: 1.11; 95% CI: 1.03- 1.20; P = 0.009) and PLSDA-RFS (OR: 1.10; 95% CI: 1.02-1.19, P = 0.011) were positively associated with T2D. Mapping of SNPs (P < 0.05) from the interaction analysis between SNPs and the food scores to genes and pathways yielded some 12 genes (CACNA2D3, RELN, DOCK2, SLIT3, CTNNA2, etc.) and pathways associated with T2D. The strongest association was observed with the adipocytokine signalling pathway, highlighting 32 genes (STAT3, MAPK10, MAPK8, IRS1, AKT1-3, ADIPOR2, etc.) most likely associated with T2D. Finally, the group of the subjects in low, intermediate and high using both the food scores and a polygenic risk score found an association between diet quality groups with issues at high genetic risk of T2D.

Conclusion: A dietary pattern of poor amounts of antioxidant nutrients is associated with the risk of T2D, and diet affects pathway mechanisms involved in developing T2D.

Keywords: case-control study; dietary patterns; polygenic risk scores; recommended food score; type 2 diabetes.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adipokines
Antioxidants
Diabetes Mellitus, Type 2* / epidemiology
Diabetes Mellitus, Type 2* / genetics
Diet
Humans
Signal Transduction / genetics

Substances

Antioxidants
Adipokines

Grants and funding

This work was funded by a Bio-Synergy Research Project funding award (2013M3A9C4078158), as bestowed by the Ministry of Science, ICT, and Future Planning, through the Korean National Research Foundation.