Association between PPARγrs1801282 polymorphism with diabetic nephropathy and type-2 diabetes mellitus susceptibility in south India and a meta-analysis

Association between Genetic Polymorphisms and Risk of Kidney Posttransplant Diabetes Mellitus: A Systematic Review and Meta-Analysis

OBJECTIVES

The purpose of this study was to clarify the role of genetic factors on posttransplant diabetes mellitus (PTDM) risk.

METHODS

Relevant publications were systematically retrieved from PubMed, EMBASE, and the Cochrane Library up to December 2020. Data from eligible case-control and cohort studies were extracted for qualitative and quantitative analyses. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to estimate the association between gene polymorphisms and PTDM in the quantitative meta-analysis.

RESULTS

A total of 43 eligible articles were identified, and 16 studies on 9 DNA variants from 8 genes were included in the meta-analysis. TCF7L2 rs7903146 was significantly associated with PTDM risk in 5 genetic models (OR (95% CI): allelic: 1.59 (1.17-2.16), P=0.003; dominant recessive: 1.62 (1.14, 2.31), P=0.007; recessive: 1.87 (1.18, 2.94), P=0.007; homozygote: 2.21 (1.23, 3.94), P=0.008; and heterozygote 1.50 (1.08, 2.10), P=0.017). KCNQ1 rs2237892 was significantly correlated with PTDM risk in 3 genetic models (allelic: 0.68 (0.58, 0.81), P < 0.001; dominant: 0.6 (049, 0.74), P < 0.001; and heterozygote: 0.61 (0.48, 0.76), P < 0.001). KCNJ11 rs5219 was significantly linked with PTDM in the recessive genetic model (1.59 (1.01, 2.50), P=0.047). No significant correlations of PTDM with TCF7L2 rs12255372, SLC30A8 rs13266634, PPARγ rs1801282, CDKN2A/B rs10811661, HHEX rs1111875, and IGF2BP2 rs4402960 polymorphisms were found.

CONCLUSIONS

The gene polymorphisms of TCF7L2 rs7903146, KCNQ1 rs2237892, and KCNJ11 rs5219 may predispose kidney transplant recipients to PTDM. Large sample size studies on diverse ethnic populations were warranted to confirm our findings.

Intervention Value of Path-Type Health Education on Cognition and Renal Function of Patients with Diabetic Nephropathy

OBJECTIVE

Analyze and examine the effectiveness of path-based health education for patients with diabetic nephropathy and renal function.

METHODS

The 162 diabetic nephropathy patients admitted to our hospital from January 2018 to January 2021 were selected, and participants were randomly assigned to groups: study group (n = 79) and control group (n = 83). The control group received routine nursing care, whereas the study group received path-type health education. GQOLI-74, MUIS-A scores, biochemical indicators, dietary indicators, cognition, blood glucose levels, and renal function were compared between the two groups.

RESULTS

The GQOLI-74 score of the two groups was substantially higher, while the MUIS-A score was significantly lower, although the study group changed more significantly (P < 0.05) than the control group. The biochemical markers in both groups decreased significantly, but the study group changed more dramatically (P0.05) than the control group; the nutritional index values of both groups increased significantly, but the study group's nutritional index values increased significantly (P0.05) when compared to those of the control group; the control group's awareness of drug treatment, basic knowledge, exercise, and diet was 79.4 percent, 78.9 percent, 73.4 percent, and 91.0 percent, respectively, and the study group's awareness of drug treatment, basic knowledge, exercise, and diet was 90.3%, 96.4%, 92.8%, and 94.0%. The study group exhibited greater awareness (P0.05) than the control group. The blood glucose indices of both groups were dramatically lowered; however, the study group's blood glucose level declined more significantly (P0.05) than the control group. The renal function indices of both groups were considerably lower, but the study group's renal function indexes were significantly lower (P0.05) than those of the control group.

CONCLUSION

Pathway health education is a new nursing method that can adjust nutritional indicators, improve blood sugar and kidney function, and significantly increase patients' awareness of the disease, which can further improve patient compliance with treatment. This nursing method has high application feasibility and high clinical value.

Genomics, Proteomics and Metabolomics Approaches for Predicting Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients

BACKGROUND

There is a continuous rise in the prevalence of type 2 diabetes mellitus (T2DM) worldwide and most patients are unaware of the presence of this chronic disease at the early stages. T2DM is associated with complications related to long-term damage and failure of multiple organ systems caused by vascular changes associated with glycated end products, oxidative stress, mild inflammation, and neovascularization. Among the most frequent complications of T2DM observed in about 20-40% of T2DM patients is diabetes nephropathy (DN).

METHODS

A literature search was made in view of highlighting the novel applications of genomics, proteomics and metabolomics, as the new prospective strategy for predicting DN in T2DM patients.

RESULTS

The complexity of DN requires a comprehensive and unbiased approach to investigate the main causes of disease and identify the most important mechanisms underlying its development. With the help of evolving throughput technology, rapidly evolving information can now be applied to clinical practice.

DISCUSSION

DN is also the leading cause of end-stage renal disease and comorbidity independent of T2DM. In terms of the comorbidity level, DN has many phenotypes; therefore, timely diagnosis is required to prevent these complications. Currently, urine albumin-to-creatinine ratio and estimated glomerular filtration rate (eGFR) are gold standards for assessing glomerular damage and changes in renal function. However, GFR estimation based on creatinine is limited to hyperfiltration status; therefore, this makes albuminuria and eGFR indicators less reliable for early-stage diagnosis of DN.

CONCLUSION

The combination of genomics, proteomics, and metabolomics assays as suitable biological systems can provide new and deeper insights into the pathogenesis of diabetes, as well as discover prospects for developing suitable and targeted interventions.