FREQUENCY OF PATHOGENIC VARIANTS OF CONGENITAL KIDNEY DISEASE IN DIABETIC PATIENTS WITH OR WITHOUT DIABETIC KIDNEY DISEASE

 

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FREQUENCY OF PATHOGENIC VARIANTS OF CONGENITAL KIDNEY DISEASE IN DIABETIC PATIENTS WITH OR WITHOUT DIABETIC KIDNEY DISEASE

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Yosuke
Hirakawa
Yosuke Hirakawa yhirakawa@g.ecc.u-tokyo.ac.jp the University of Tokyo Hospital Division of Nephrology and Endocrinology Tokyo Japan *
Yuka Sugawara ysuga-tky@m.u-tokyo.ac.jp the University of Tokyo Hospital Division of Nephrology and Endocrinology Tokyo Japan -
Masaomi Nangaku mnangaku@m.u-tokyo.ac.jp the University of Tokyo School of Medicine Division of Nephrology and Endocrinology Tokyo Japan -
 
 
 
 
 
 
 
 
 
 
 
 

Diabetic kidney disease (DKD) is a multifactorial condition, and genetic factors play a major role in its development. Several recent studies have examined the effects of pathogenic variants associated with other kidney diseases and found that a substantial proportion of DKD patients carry pathogenic variants, suggesting that these variants may contribute to the development of DKD itself or that some patients diagnosed with DKD may in fact have underlying kidney diseases other than DKD. However, these studies investigated the frequency of pathogenic variants only among DKD patients; therefore, it remains unclear whether the higher prevalence of pathogenic variants related to other kidney diseases is truly specific to the DKD population. To address this issue, we conducted a comparative analysis of the prevalence of pathogenic variants between diabetic patients with DKD and those without.

We analyzed whole-genome sequence data available in the the Japan Agency for Medical Research and Development (AMED) Data Utilization Platform. This platform provides genomic data linked with information such as age, sex, and comorbidities. All participants were of Japanese origin. Only genomic data from patients diagnosed with type 2 diabetes were included, and the patients were classified according to the presence or absence of DKD. Variants classified as “Pathogenic,” “Pathogenic/Likely pathogenic,” or “Likely pathogenic” based on the ACMG/AMP criteria (as annotated in ClinVar, version released on October 2025) were extracted for each patient. We focused on genes known to cause the following representative congenital kidney diseases: Alport syndrome, autosomal dominant or recessive polycystic kidney disease, congenital nephrotic syndrome, autosomal dominant tubulointerstitial kidney disease, nephronophthisis, and Fabry disease. Finally, the proportion of patients with pathogenic variants was compared between the groups.

A total of 2,177 patients with type 2 diabetes were included in the analysis, of whom 753 had DKD. The median age was 67 years (interquartile range, 59–73), and 68% of the participants were male. There were no significant differences in age or sex between patients with and without DKD. All pathogenic variants identified were heterozygous. The proportions of patients carrying pathogenic variants in each disease category did not differ between the groups across all modes of inheritance (Table). Only pathogenic variants in the GLA gene, which is well known for its association with Fabry disease, tended to be more frequent in the DKD group.

Although several studies have reported that a substantial number of pathogenic variants related to kidney diseases exist in patients with DKD, our comparative analysis showed that the frequency of pathogenic variants in representative kidney disease genes was not higher in diabetes patients with DKD than those without, underscoring the necessity of comparative analyses. For a better understanding of the involvement of rare variants in the development of DKD or CKD, using an appropriate control group is essential.


Acknowledgement: This work was supported by the Japan Agency for Medical Research and Development (AMED 25tm0424230h0002). The data used in this research were collected in the AMED data utilization platform project of Japan Agency for Medical Research and Development (AMED) and provided through the AMED Data Utilization Platform.

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