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T2DM/CKD genetic risk scores and the progression of diabetic kidney disease in T2DM subjects
D. Galuška, L. Pácal, K. Chalásová, P. Divácká, J. Řehořová, J. Svojanovský, JA. Hubáček, V. Lánská, K. Kaňková
Jazyk angličtina Země Nizozemsko
Typ dokumentu časopisecké články
- MeSH
- celogenomová asociační studie MeSH
- chronická renální insuficience * genetika patologie MeSH
- diabetes mellitus 2. typu * genetika komplikace MeSH
- diabetické nefropatie * genetika MeSH
- genetická predispozice k nemoci * MeSH
- genetické rizikové skóre MeSH
- jednonukleotidový polymorfismus * MeSH
- lidé středního věku MeSH
- lidé MeSH
- progrese nemoci * MeSH
- rizikové faktory MeSH
- senioři MeSH
- sfingosin-N-acyltransferasa genetika MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
This study aimed at understanding the predictive potential of genetic risk scores (GRS) for diabetic kidney disease (DKD) progression in patients with type 2 diabetes mellitus (T2DM) and Major Cardiovascular Events (MCVE) and All-Cause Mortality (ACM) as secondary outcomes. We evaluated 30 T2DM and CKD GWAS-derived single nucleotide polymorphisms (SNPs) and their association with clinical outcomes in a central European cohort (n = 400 patients). Our univariate Cox analysis revealed significant associations of age, duration of diabetes, diastolic blood pressure, total cholesterol and eGFR with progression of DKD (all P < 0.05). However, no single SNP was conclusively associated with progression to DKD, with only CERS2 and SHROOM3 approaching statistical significance. While a single SNP was associated with MCVE - WSF1 (P = 0.029), several variants were associated with ACM - specifically CANCAS1, CERS2 and C9 (all P < 0.02). Our GRS did not outperform classical clinical factors in predicting progression to DKD, MCVE or ACM. More precisely, we observed an increase only in the area under the curve (AUC) in the model combining genetic and clinical factors compared to the clinical model alone, with values of 0.582 (95 % CI 0.487-0.676) and 0.645 (95 % CI 0.556-0.735), respectively. However, this difference did not reach statistical significance (P = 0.06). This study highlights the complexity of genetic predictors and their interplay with clinical factors in DKD progression. Despite the promise of personalised medicine through genetic markers, our findings suggest that current clinical factors remain paramount in the prediction of DKD. In conclusion, our results indicate that GWAS-derived GRSs for T2DM and CKD do not offer improved predictive ability over traditional clinical factors in the studied Czech T2DM population.
3rd Department of Internal Medicine 1 Faculty of Medicine Charles University Prague Czech Republic
Department of Biochemistry Faculty of Medicine Masaryk University Brno Czech Republic
Department of Data Science Institute for Clinical and Experimental Medicine Prague Czech Republic
Department of Gastroenterology University Hospital Brno Bohunice Brno Czech Republic
Department of Internal Medicine St Anne's University Hospital Brno Czech Republic
Department of Pathophysiology Faculty of Medicine Masaryk University Brno Czech Republic
Experimental Medicine Centre Institute for Clinical and Experimental Medicine Prague Czech Republic
Citace poskytuje Crossref.org
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- $a Galuška, David $u Department of Pathophysiology, Faculty of Medicine, Masaryk University, Brno, Czech Republic; Department of Biochemistry, Faculty of Medicine, Masaryk University, Brno, Czech Republic. Electronic address: 423585@mail.muni.cz
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- $a This study aimed at understanding the predictive potential of genetic risk scores (GRS) for diabetic kidney disease (DKD) progression in patients with type 2 diabetes mellitus (T2DM) and Major Cardiovascular Events (MCVE) and All-Cause Mortality (ACM) as secondary outcomes. We evaluated 30 T2DM and CKD GWAS-derived single nucleotide polymorphisms (SNPs) and their association with clinical outcomes in a central European cohort (n = 400 patients). Our univariate Cox analysis revealed significant associations of age, duration of diabetes, diastolic blood pressure, total cholesterol and eGFR with progression of DKD (all P < 0.05). However, no single SNP was conclusively associated with progression to DKD, with only CERS2 and SHROOM3 approaching statistical significance. While a single SNP was associated with MCVE - WSF1 (P = 0.029), several variants were associated with ACM - specifically CANCAS1, CERS2 and C9 (all P < 0.02). Our GRS did not outperform classical clinical factors in predicting progression to DKD, MCVE or ACM. More precisely, we observed an increase only in the area under the curve (AUC) in the model combining genetic and clinical factors compared to the clinical model alone, with values of 0.582 (95 % CI 0.487-0.676) and 0.645 (95 % CI 0.556-0.735), respectively. However, this difference did not reach statistical significance (P = 0.06). This study highlights the complexity of genetic predictors and their interplay with clinical factors in DKD progression. Despite the promise of personalised medicine through genetic markers, our findings suggest that current clinical factors remain paramount in the prediction of DKD. In conclusion, our results indicate that GWAS-derived GRSs for T2DM and CKD do not offer improved predictive ability over traditional clinical factors in the studied Czech T2DM population.
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