Association between COL4A3 Variant rs55703767 and Susceptibility to Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients: Insights from the INDEED Cohort Study

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Association between COL4A3 Variant rs55703767 and Susceptibility to Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients: Insights from the INDEED Cohort Study

Introduction

Diabetic kidney disease (DKD) is a significant global health concern as it is the leading cause of end-stage renal disease. Understanding its genetic underpinnings is crucial for better diagnosis and management. A previous genome-wide association study in Europeans found that a common missense variant in COL4A3, rs55703767, had a protective role in DKD in type 1 diabetes mellitus, and this effect was related to blood glucose levels. However, data regarding its role in type 2 diabetes mellitus (T2DM) were scarce. This study aimed to explore the association between the COL4A3 variant rs55703767 and DKD susceptibility in T2DM patients.

Study Design and Participants

This was a case-control study that enrolled patients with T2DM from the INDEED (Incidence, Development, and Prognosis of Diabetic Kidney Disease) study. The research adhered to the Declaration of Helsinki and was approved by the Ethics Committee of Peking University First Hospital. Informed consent was obtained from each participant.

Patients were diagnosed with T2DM according to the American Diabetic Association criteria. Among them, those who developed kidney damage (estimated glomerular filtration rate [eGFR] 3.0 mg/mmol for >3 months) excluding coexisting non-diabetic-related renal diseases were classified as T2DM with the DKD group. All patients were required to have a minimum diabetes duration of 10 years. Finally, a total of 1311 T2DM patients, including 580 with DKD and 731 without DKD, were recruited.

Data Collection and Analyses

Demographic data were collected using standardized questionnaires. Laboratory tests included triglyceride, total cholesterol, high-density lipoprotein, low-density lipoprotein, fasting blood glucose (FBG), urinary creatinine, uACR, and urinary a1-microglobulin. DNA was extracted from peripheral blood samples, and TaqMan SNP Genotyping Assay was used for genotyping rs55703767.

Categorical variables, allele and genotype frequencies were compared using the x² test. Continuous variables were compared using the Student’s t-test. The Hardy-Weinberg equilibrium (HWE) was tested using the Chi-square test. Statistical power was calculated by QUANTO, and data analysis was done using SPSS version 23.0.

Results

  • General Data: Patients with DKD had significantly higher levels of systolic and diastolic blood pressure, abdominal circumference, body mass index, triglycerides, total cholesterol, FBG, and serum creatinine, and lower eGFR compared to those without DKD. Both groups were in accordance with the HWE, indicating suitability for genetic analysis.
  • Genotype and Allele Frequencies: The frequency distributions of COL4A3 variant rs55703767 (G/T) genotypes in T2DM without DKD group were: GG, 589 (80.6%); GT, 135 (18.5%); and TT, 7 (0.9%). In the T2DM with DKD group: GG, 451 (77.8%); GT, 124 (21.4%); and TT, 5 (0.9%). There was no significant difference in genotypic distribution between the two groups. Minor allele frequencies (MAFs) for the “T” allele of rs55703767 were 0.116 in T2DM without DKD and 0.102 in T2DM with DKD, consistent with the Asian population frequency.
  • Genetic Model Analyses: Dominant, recessive, overdominant, and additive model analyses for the COL4A3 variant rs55703767 showed no significant difference in genotypic distribution between the two groups in any model. However, in T2DM with the DKD group, individuals with TT genotype had a significantly higher level of HbAlc compared to those with GT/GG genotypes (P = 0.025).
  • Association with DKD Risk Stratified by HbA1c: Association analysis between rs55703767 and the risk of DKD by stratifying HbA1c below or above 7.5% showed no significant difference. Further analysis by stratifying different cut-off levels of HbA1c (6.0% – 9.0%) also showed no significant difference.

Discussion of Differences with Previous Studies

The different results regarding hyperglycemia specificity compared to Salem et al.’s study could be due to several reasons. First, the hyperglycemia specificity of the renal protective effect of rs55703767 might vary among different races. Second, this study focused on type 2 diabetes, while Salem et al.’s study was on type 1 diabetes, with different etiologies and pathogeneses. Third, the association between glucose level and rs55703767 could be affected by confounding factors like hypoglycemic drugs.

Study Limitations

  • Diabetes Duration Information: Although patients had a minimum diabetes duration of 10 years, the exact diabetes duration information was lacking.
  • Statistical Power: The statistical power to detect the association was only 25.59%, indicating a need for larger sample sizes in future studies.
  • Single SNP Study: Being a single SNP study, false-negative results could occur due to population structure.

Conclusion

This study from the INDEED cohort suggested that there was no detectable association between the COL4A3 variant rs55703767 and susceptibility to DKD in the Chinese T2DM population.

Funding and Conflicts of Interest

This study was supported by grants from the National Natural Science Foundation of China, the CAMS Innovation Fund for Medical Sciences, and the China International Medical Foundation-Renal Anemia Fund. There were no conflicts of interest.

References

  1. Tuttle KR, Bakris GL, Bilous RW, et al. Diabetic kidney disease: a report from an ADA consensus conference. Diabetes Care 2014;37:2864–2883. doi:10.2337/dc14-1296.
  2. Chatterjee S, Khunti K, Davies MJ. Type 2 diabetes. Lancet (London, England) 2017;389:2239–2251. doi:10.1016/s0140-6736(17)30058-2.
  3. Salem RM, Todd JN, Sandholm N, et al. Genome-wide association study of diabetic kidney disease highlights biology involved in glomerular basement membrane collagen. J Am Soc Nephrol 2019;30:2000–2016. doi: 10.1681/asn.2019030218.
  4. Yang YZ, Wang JW, Wang F, et al. Incidence, development, and prognosis of diabetic kidney disease in China: design and methods. Chin Med J 2017;130:199–202. doi:10.4103/0366-6999.198002.
  5. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care 2004;27 (Suppl 1):S15–S35. doi: 10.2337/diac-are.27.2007.s15.

doi.org/10.1097/CM9.0000000000001955

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