Dataset Information

Genetic risk score for risk prediction of diabetic nephropathy in Han Chinese type 2 diabetes patients.

ABSTRACT: We evaluated whether genetic information could offer improvement on risk prediction of diabetic nephropathy (DN) while adding susceptibility variants into a risk prediction model with conventional risk factors in Han Chinese type 2 diabetes patients. A total of 995 (including 246 DN cases) and 519 (including 179 DN cases) type 2 diabetes patients were included in derivation and validation sets, respectively. A genetic risk score (GRS) was constructed with DN susceptibility variants based on findings of our previous genome-wide association study. In derivation set, areas under the receiver operating characteristics (AUROC) curve (95% CI) for model with clinical risk factors only, model with GRS only, and model with clinical risk factors and GRS were 0.75 (0.72-0.78), 0.64 (0.60-0.68), and 0.78 (0.75-0.81), respectively. In external validation sample, AUROC for model combining conventional risk factors and GRS was 0.70 (0.65-0.74). Additionally, the net reclassification improvement was 9.98% (P?=?0.001) when the GRS was added to the prediction model of a set of clinical risk factors. This prediction model enabled us to confirm the importance of GRS combined with clinical factors in predicting the risk of DN and enhanced identification of high-risk individuals for appropriate management of DN for intervention.

SUBMITTER: Liao LN

PROVIDER: S-EPMC6934611 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Genetic risk score for risk prediction of diabetic nephropathy in Han Chinese type 2 diabetes patients.

Liao Li-Na LN Li Tsai-Chung TC Li Chia-Ing CI Liu Chiu-Shong CS Lin Wen-Yuan WY Lin Chih-Hsueh CH Yang Chuan-Wei CW Chen Ching-Chu CC Chang Chiz-Tzung CT Yang Ya-Fei YF Liu Yao-Lung YL Kuo Huey-Liang HL Tsai Fuu-Jen FJ Lin Cheng-Chieh CC

Scientific reports 20191227 1

We evaluated whether genetic information could offer improvement on risk prediction of diabetic nephropathy (DN) while adding susceptibility variants into a risk prediction model with conventional risk factors in Han Chinese type 2 diabetes patients. A total of 995 (including 246 DN cases) and 519 (including 179 DN cases) type 2 diabetes patients were included in derivation and validation sets, respectively. A genetic risk score (GRS) was constructed with DN susceptibility variants based on find ...[more]

PMID: 31882689

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Project description:BackgroundFunctional mutations or polymorphisms affecting forkhead box P3 (FOXP3) can lead to their abnormal FOXP3 gene expression and/or defective Treg cells generation, thus resulting in autoimmune disease and inflammatory disorders. FOXP3 also plays a key role in Type 2 diabetes mellitus (T2DM) and its complications, because the disease usually involves chronic low-grade inflammatory disorders and is associated with long-term immune system imbalance. This study aimed to investigate the association between FOXP3 polymorphisms and the susceptibility to T2DM and type 2 diabetes nephropathy (T2DN) within the Han Chinese populations.MethodsPolymorphisms in rs3761548C/A and rs2294021C/T were examined in 400 patients (which include an equal number of T2DM and T2DN groups) and 200 healthy controls using PCR-HRM and sequence analysis.ResultsThe genotype and allelic frequencies of the two single nucleotide polymorphisms (SNPs) were significantly different in T2DM and the progression of diabetes developing to T2DN. The further gender-based evaluation showed that in female subjects, rs3761548C/A was associated with an approximately 3-fold higher threat for T2DM and 4.5-fold for T2DN, while there was no noticeable association with rs2294021C/T; in males, the promoter polymorphism showed an increased predisposition of 5.4-fold and 3.4-fold predisposition to T2DM and T2DN, respectively, while rs2294021 polymorphism could impart a nearly 2-fold risk of developing T2DN. An additional analysis of combined genotypes (rs3761548 C/A-rs2294021C/T) revealed that CC-CC and CC-CT can be considered protective combinations in the predisposition of males with diabetes towards T2DN, while AA-CC and AA-TT have the opposite effect.ConclusionsThis study demonstrated the possible involvement of individual and combined genetic associations of rs3761548C/A and rs2294021C/T polymorphisms with the susceptibility to diabetes and diabetic nephropathy in the Han Chinese population, as well as gender bias.

Project description:BackgroundAcylcarnitines play a role in type 2 diabetes mellitus (T2DM), but the relationship between acylcarnitine and diabetic nephropathy was unclear. We aimed to explore the association of acylcarnitine metabolites with diabetic nephropathy and estimate the predictive value of acylcarnitine for diabetic nephropathy.MethodsA total of 1032 (mean age: 57.24 ± 13.82) T2DM participants were derived from Liaoning Medical University First Affiliated Hospital. Mass Spectrometry was utilized to measure levels of 25 acylcarnitine metabolites in fasting plasma. Diabetic nephropathy was ascertained based on the medical records. Factor analysis was used to reduce the dimensions and extract factors of the 25 acylcarnitine metabolites. Logistic regression was used to estimate the relationship between factors extracted from the 25 acylcarnitine metabolites and diabetic nephropathy. Receiver operating characteristic curves were used to test the predictive values of acylcarnitine factors for diabetic nephropathy.ResultsAmong all T2DM participants, 138 (13.37%) patients had diabetic nephropathy. Six factors were extracted from 25 acylcarnitines, which account for 69.42% of the total variance. In multi-adjusted logistic regression models, the odds ratio (OR, 95% confidence interval [CI]) of diabetic nephropathy on factor 1 (including butyrylcarnitine/glutaryl-carnitine/hexanoylcarnitine/octanoylcarnitine/decanoylcarnitine/lauroylcarnitine/tetradecenoylcarnitine), factor 2 (including propionylcarnitine/palmitoylcarnitine/hydroxypalmitoleyl-carnitine/octadecanoylcarnitine/arachidiccarnitine), and factor 3 (including tetradecanoyldiacylcarnitine/behenic carnitine/tetracosanoic carnitine/hexacosanoic carnitine) were 1.33 (95%CI 1.12-1.58), 0.76 (95%CI 0.62-0.93), and 1.24 (95%CI 1.05-1.47), respectively. The area under the curve for diabetic nephropathy prediction was significantly increased after the complement of factors 1, 2, and 3 in traditional factors model (P < 0.01).ConclusionsSome plasma acylcarnitine metabolites extracted in factors 1 and 3 were higher in diabetic nephropathy, while factor 2 was lower in diabetic nephropathy among T2DM patients. The addition of acylcarnitine to traditional factors model improved the predictive value for diabetic nephropathy.

Dataset Information

Genetic risk score for risk prediction of diabetic nephropathy in Han Chinese type 2 diabetes patients.

Publications

Genetic risk score for risk prediction of diabetic nephropathy in Han Chinese type 2 diabetes patients.

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