“Predicting diabetic kidney disease in youth with type 1 diabetes: Insights from genetic risk assessment”

Abstract

Objective

Diabetic kidney disease (DKD) is influenced by multiple factors, yet its precise progression mechanisms remain largely unclear. This study aimed to create a clinical risk-scoring system based on genetic polymorphisms in the AFF3, CARS, CERS2, ERBB4, GLRA3, RAET1L, TMPO, and ZMIZ1 genes.

Methods

The study included a DKD group diagnosed with diabetic kidney disease before age 18 and a WDC group matched by age, gender, and age at diabetes diagnosis. Genetic data and clinical data from diabetes diagnosis to moderately increased albuminuria (MIA) detection were compared between the groups.

Results

Among 43 DKD cases, 22 were girls and 21 were boys. At MIA diagnosis, mean body weight SDS was −0.24 ± 0.94, height SDS was 0.34 ± 1.15, and BMI SDS was −0.26 ± 0.94. Systolic blood pressure was at the 72nd percentile (2–99), and diastolic blood pressure was at the 74th percentile (33–99). Significant differences in rs267734, rs267738, and rs942263 polymorphisms were found between DKD and non-complication diabetic groups (13[30.2 %] vs 5[11.6 %], p = 0.034; 14[32.6 %] vs 5[11.6 %], p = 0.019; 26[60.5 %] vs 40[93 %], p < 0.001).

Conclusion

Several factors were identified as significant in DKD onset, including low follow-up weight SDS, elevated diastolic blood pressure, presence of rs267734, and absence of rs942263 polymorphisms. The model demonstrated a specificity of 81.4 % and a sensitivity of 74.4 %.