T2DM/CKD genetic risk scores and the progression of diabetic kidney disease in T2DM subjects

•30 SNPs were determined in a Czech Republic population to create genetic risk score.•WSF1 polymorphism were associated with MCVE and CANCAS1, CERS2 and C9 gene with ACM.•Predictive ability of observed endpoints of genetic and clinical model were compared.•Clinical model lightly improves predictive...

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Published inGene Vol. 927; p. 148724
Main Authors Galuška, David, Pácal, Lukáš, Chalásová, Katarína, Divácká, Petra, Řehořová, Jitka, Svojanovský, Jan, Hubáček, Jaroslav A., Lánská, Věra, Kaňková, Kateřina
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 15.11.2024
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Online AccessGet full text
ISSN0378-1119
1879-0038
1879-0038
DOI10.1016/j.gene.2024.148724

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Abstract •30 SNPs were determined in a Czech Republic population to create genetic risk score.•WSF1 polymorphism were associated with MCVE and CANCAS1, CERS2 and C9 gene with ACM.•Predictive ability of observed endpoints of genetic and clinical model were compared.•Clinical model lightly improves predictive ability but not statistically significant. 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.
AbstractList 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.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.
•30 SNPs were determined in a Czech Republic population to create genetic risk score.•WSF1 polymorphism were associated with MCVE and CANCAS1, CERS2 and C9 gene with ACM.•Predictive ability of observed endpoints of genetic and clinical model were compared.•Clinical model lightly improves predictive ability but not statistically significant. 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.
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.
ArticleNumber 148724
Author Galuška, David
Řehořová, Jitka
Svojanovský, Jan
Divácká, Petra
Pácal, Lukáš
Chalásová, Katarína
Hubáček, Jaroslav A.
Lánská, Věra
Kaňková, Kateřina
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Keywords eGFR
ESRD
MCVE
T2DM
GWAS
Diabetes mellitus
ACM
Genetic risk score
uACR
Genetic predisposition
CVD
PRS
TG
w/uGRS
UAE
Single nucleotide polymorphism
DKD
CKD
Diabetic kidney disease
Language English
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Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.
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Snippet •30 SNPs were determined in a Czech Republic population to create genetic risk score.•WSF1 polymorphism were associated with MCVE and CANCAS1, CERS2 and C9...
This study aimed at understanding the predictive potential of genetic risk scores (GRS) for diabetic kidney disease (DKD) progression in patients with type 2...
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SubjectTerms Aged
Diabetes mellitus
Diabetes Mellitus, Type 2 - complications
Diabetes Mellitus, Type 2 - genetics
Diabetic kidney disease
Diabetic Nephropathies - genetics
Disease Progression
Female
Genetic predisposition
Genetic Predisposition to Disease
Genetic Risk Score
Genome-Wide Association Study
Humans
Male
Middle Aged
Polymorphism, Single Nucleotide
Renal Insufficiency, Chronic - genetics
Renal Insufficiency, Chronic - pathology
Risk Factors
Single nucleotide polymorphism
Sphingosine N-Acyltransferase - genetics
Title T2DM/CKD genetic risk scores and the progression of diabetic kidney disease in T2DM subjects
URI https://dx.doi.org/10.1016/j.gene.2024.148724
https://www.ncbi.nlm.nih.gov/pubmed/38909968
https://www.proquest.com/docview/3071515456
Volume 927
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