Identification of Novel Genetic Variants and Food Intake Factors Associated with Type 2 Diabetes in South Korean Adults, Using an Illness–Death Model
Abstract
1. Introduction
2. Results
2.1. Demographic and Lifestyle Characteristics
2.2. Association Between Food Intake and T2D
2.3. Association Between SNP and T2D
2.4. Functional Annotation
3. Discussion
3.1. Food Intake Factors
3.2. Genetic Variants
3.3. Strengths and Limitations
4. Materials and Methods
4.1. Study Population
4.2. General Characteristics and Anthropometric Measurements
4.3. Definition of Type 2 Diabetes and Prediabetes
4.4. Assessment of Dietary Intake
4.5. Genotyping and Quality Control
4.6. Statistical Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variables | NGT to PD | NGT to T2D | PD to T2D | |||
---|---|---|---|---|---|---|
HR (95% CI) | p-Value | HR (95% CI) | p-Value | HR (95% CI) | p-Value | |
Fruit | ||||||
Tertile 1 | Ref | Ref | Ref | |||
Tertile 2 | 0.27 (0.21–0.34) | <0.001 | 0.68 (0.46–1.02) | 0.063 | 0.92 (0.68–1.24) | 0.570 |
Tertile 3 | 0.18 (0.14–0.24) | <0.001 | 0.60 (0.39–0.93) | 0.022 | 0.99 (0.72–1.36) | 0.951 |
Vegetable | ||||||
Tertile 1 | Ref | Ref | Ref | |||
Tertile 2 | 0.97 (0.85–1.10) | 0.601 | 0.68 (0.45–1.03) | 0.067 | 0.96 (0.69–1.33) | 0.810 |
Tertile 3 | 1.11 (0.97–1.27) | 0.118 | 0.63 (0.40–1.00) | 0.048 | 1.25 (0.90–1.73) | 0.188 |
Red meat | ||||||
Tertile 1 | Ref | Ref | Ref | |||
Tertile 2 | 1.07 (0.83–1.38) | 0.584 | 0.90 (0.59–1.38) | 0.636 | 1.15 (0.83–1.58) | 0.396 |
Tertile 3 | 1.41 (1.08–1.85) | 0.012 | 0.88 (0.54–1.45) | 0.624 | 1.16 (0.80–1.67) | 0.435 |
White meat | ||||||
Tertile 1 | Ref | Ref | Ref | |||
Tertile 2 | 1.05 (0.83–1.34) | 0.673 | 1.04 (0.70–1.55) | 0.828 | 0.95 (0.71–1.29) | 0.757 |
Tertile 3 | 1.61 (1.26–2.07) | <0.001 | 1.21 (0.77–1.90) | 0.415 | 0.98 (0.71–1.37) | 0.925 |
Grain | ||||||
Tertile 1 | Ref | Ref | Ref | |||
Tertile 2 | 0.95 (0.84–1.07) | 0.402 | 0.96 (0.62–1.47) | 0.845 | 0.90 (0.66–1.23) | 0.527 |
Tertile 3 | 1.00 (0.88–1.13) | 0.971 | 1.32 (0.88–1.96) | 0.177 | 1.00 (0.74–1.35) | 0.992 |
Fish | ||||||
Tertile 1 | Ref | Ref | Ref | |||
Tertile 2 | 0.86 (0.68–1.10) | 0.235 | 0.98 (0.63–1.53) | 0.923 | 0.88 (0.63–1.23) | 0.454 |
Tertile 3 | 1.17 (0.91–1.51) | 0.217 | 1.62 (1.00–2.62) | 0.048 | 1.05 (0.74–1.50) | 0.770 |
Dairy | ||||||
Tertile 1 | Ref | Ref | Ref | |||
Tertile 2 | 0.62 (0.49–0.78) | <0.001 | 1.22 (0.82–1.80) | 0.333 | 0.92 (0.68–1.24) | 0.583 |
Tertile 3 | 1.02 (0.81–1.28) | 0.887 | 1.12 (0.73–1.74) | 0.605 | 0.92 (0.67–1.26) | 0.596 |
Model | Chr a | Pos b | SNP c | Alleles d | Nearest Gene | HR (95% CI) e | p-Value | q-Value |
---|---|---|---|---|---|---|---|---|
NGT f → PD g | 7 | 44235668 | rs4607517 | G/A | GCK | 1.27 (1.17–1.37) | 1.37 × 10−9 | 0.0006 |
7 | 44257943 | rs758982 | C/T | CAMK2B | 1.27 (1.18–1.38) | 2.38 × 10−8 | 0.0006 | |
NGT → T2D h | 15 | 42733571 | rs145386384 | A/G | ZNF106 | 3.77 (2.36–6.00) | 2.41 × 10−8 | 0.0123 |
19 | 50360989 | rs59595912 | A/G | PTOV1 | 2.64 (1.85–3.77) | 8.22 × 10−8 | 0.0210 | |
2 | 83637190 | rs7575023 | T/C | LOC105374834 | 1.88 (1.49–2.38) | 1.49 × 10−7 | 0.0253 | |
13 | 95600085 | rs35566993 | A/G | LINC00557 | 2.76 (1.86–4.09) | 4.74 × 10−7 | 0.0445 | |
20 | 17374513 | rs11698919 | A/G | PCSK2 | 2.06 (1.55–2.73) | 6.23 × 10−7 | 0.0445 | |
1 | 47931749 | rs59813747 | C/T | FOXD2 | 3.66 (2.20–6.10) | 6.29 × 10−7 | 0.0445 | |
16 | 58700803 | rs4784964 | C/T | SLC38A7 | 3.15 (2.00–4.94) | 6.47 × 10−7 | 0.0445 | |
1 | 72341074 | rs147467153 | A/G | NEGR1 | 4.31 (2.42–7.67) | 6.97 × 10−7 | 0.0445 |
Model | Chr a | Pos b | SNP c | Nearest Gene | CADD Score d | DANN Score e |
---|---|---|---|---|---|---|
NGT f PD g | 7 | 44235668 | rs4607517 | GCK | 14.470 | 0.877 |
7 | 44257943 | rs758982 | CAMK2B | 8.908 | 0.743 | |
NGT T2D h | 15 | 42733571 | rs145386384 | ZNF106 | 5.721 | 0.715 |
19 | 50360989 | rs59595912 | PTOV1 | 1.083 | 0.481 | |
2 | 83637190 | rs7575023 | LOC105374834 | 0.025 | 0.573 | |
13 | 95600085 | rs35566993 | LINC00557 | 0.695 | 0.391 | |
20 | 17374513 | rs11698919 | PCSK2 | 5.039 | 0.318 | |
1 | 47931749 | rs59813747 | FOXD2 | 12.890 | 0.994 | |
16 | 58700803 | rs4784964 | SLC38A7 | 4.847 | 0.802 | |
1 | 72341074 | rs147467153 | NEGR1 | 0.733 | 0.481 |
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Oh, J.; Cha, J.; Choi, S. Identification of Novel Genetic Variants and Food Intake Factors Associated with Type 2 Diabetes in South Korean Adults, Using an Illness–Death Model. Int. J. Mol. Sci. 2025, 26, 2597. https://doi.org/10.3390/ijms26062597
Oh J, Cha J, Choi S. Identification of Novel Genetic Variants and Food Intake Factors Associated with Type 2 Diabetes in South Korean Adults, Using an Illness–Death Model. International Journal of Molecular Sciences. 2025; 26(6):2597. https://doi.org/10.3390/ijms26062597
Chicago/Turabian StyleOh, Jeongmin, Junho Cha, and Sungkyoung Choi. 2025. "Identification of Novel Genetic Variants and Food Intake Factors Associated with Type 2 Diabetes in South Korean Adults, Using an Illness–Death Model" International Journal of Molecular Sciences 26, no. 6: 2597. https://doi.org/10.3390/ijms26062597
APA StyleOh, J., Cha, J., & Choi, S. (2025). Identification of Novel Genetic Variants and Food Intake Factors Associated with Type 2 Diabetes in South Korean Adults, Using an Illness–Death Model. International Journal of Molecular Sciences, 26(6), 2597. https://doi.org/10.3390/ijms26062597