Dataset Information

Association and interaction analysis of PPARGC1A and serum uric acid on type 2 diabetes mellitus in Chinese Han population.

ABSTRACT:

Background

Peroxisome proliferator-activated receptor gamma coactivator-1α (PPARGC1A/ PGC-1α) is a ligand-activated transcription factor belonging to the nuclear hormone receptor superfamily. The activity of PGC-1α or genetic variations in the gene encoding the enzyme may contribute to individual variations in mitochondrial function and insulin resistance or diabetes. The objective of this study was to assess the extent to which PPARGC1A (rs8192678) and serum uric acid (UA) and its interaction impact on T2DM susceptibility in Chinese Han population.

Method

We conducted a study in a cohort that included 1166 T2DM patients and 1135 controls, and was genotyped for the presence of the PPARGC1A rs8192678 polymorphisms. Genotyping was performed by iPLEX technology. The association between rs8192678 or UA and T2DM was assessed by univariate and multivariate logistic regression (MLR) analysis controlling for confounders. The interaction between rs8192678 and UA for T2DM susceptibility was also assessed by MLR analysis.

Results

The generalized linear regression analysis failed to show an association between the PPARGC1A rs8192678 polymorphisms and T2DM. Interestingly, the present study provided data suggesting that the minor A-allele of PPARGC1A (rs8192678) had a protective effect against T2DM in subjects with higher level of UA (ORint =1.50 95% CI: 1.06-2.12 for allele and P = 0.02, ORint =1.63 95% CI: 1.17-2.26 for genotype and P = 0.004).

Conclusion

The combination of higher level of UA and PPARGC1A (rs8192678) was an independent predictor for T2DM.

SUBMITTER: Wu HH

PROVIDER: S-EPMC4190481 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Association and interaction analysis of PPARGC1A and serum uric acid on type 2 diabetes mellitus in Chinese Han population.

Wu Hui-Hui HH Liu Nai-Jia NJ Yang Zhen Z Tao Xiao-Ming XM Du Yan-Ping YP Wang Xuan-Chun XC Lu Bin B Zhang Zhao-Yun ZY Hu Ren-Ming RM Wen Jie J

Diabetology & metabolic syndrome 20141001 1

<h4>Background</h4>Peroxisome proliferator-activated receptor gamma coactivator-1α (PPARGC1A/ PGC-1α) is a ligand-activated transcription factor belonging to the nuclear hormone receptor superfamily. The activity of PGC-1α or genetic variations in the gene encoding the enzyme may contribute to individual variations in mitochondrial function and insulin resistance or diabetes. The objective of this study was to assess the extent to which PPARGC1A (rs8192678) and serum uric acid (UA) and its inter ...[more]

PMID: 25302081

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Project description:Diabetes mellitus is a metabolic disease closely related to a disordered gut microbiome. Diabetic patients usually suffer from various metabolic disorders, such as increased serum uric acid levels. Although serum uric acid levels depend partially on intestine excretion, the relationship between uric acid and gut microbiome in diabetic patients remains unknown. We collected a total of 126 fecal samples from diabetic patients for 16S ribosomal RNA gene amplicon sequencing and recorded clinical data. We analyzed the correlation between clinical indicators and gut microbiota of diabetic patients using Spearman analysis. Since uric acid was the most prominent one, we classified diabetic patients based on their uric acid levels to find the microbiome associated with uric acid disturbance. We constructed Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway profiles using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) to identify variations between the different groups. Among all the clinical indicators, uric acid had the strongest correlation with gut microbiota. First, we divided the patients into three groups according to their uric acid levels. The two low uric acid groups were similar, while the elevated uric acid group had significant differences in gut microbiota and metabolic pathways. The elevated uric acid group had a significantly lower gut microbiota diversity. At the genus level, this group had remarkably higher Escherichia-Shigella amounts and notably lower Faecalibacterium, Oscillospiraceae_UCG-002, and Oscillospiraceae_UCG-005 amounts. The gut microbiota of the high uric acid group was predicted to be enriched in metabolism, human diseases, and lipopolysaccharide biosynthesis. Since the two low uric acid groups were similar, we regrouped and matched the abnormal uric acid patients with normal uric acid patients. The differences in gut microbiota and metabolic pathways related to nucleotide metabolism became more significant. The serum uric acid levels were associated with gut microbiome changes. This might be related to uric acid metabolism by gut microbes. Our study indicates that targeting the gut microbiome could help manage elevated uric acid levels.

Dataset Information

Association and interaction analysis of PPARGC1A and serum uric acid on type 2 diabetes mellitus in Chinese Han population.

Background

Method

Results

Conclusion

Publications

Association and interaction analysis of PPARGC1A and serum uric acid on type 2 diabetes mellitus in Chinese Han population.

Similar Datasets

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