Dataset Information

PPARG (Pro12Ala) genetic variant and risk of T2DM: a systematic review and meta-analysis.

ABSTRACT: Type 2 diabetes mellitus (T2DM) is a complex disease caused by the interaction between genetic and environmental factors. A growing number of evidence suggests that the peroxisome proliferator-activated receptor gamma (PPARG) gene plays a major role in T2DM development. Meta-analysis of genetic association studies is an efficient tool to gain a better understanding of multifactorial diseases and potentially to provide valuable insights into gene-disease interactions. The present study was focused on assessing the association between Pro12Ala variation in the PPARG and T2DM risk through a comprehensive meta-analysis. We searched PubMed, WoS, Embase, Scopus and ProQuest from 1990 to 2017. The fixed-effect or random-effect model was used to evaluate the pooled odds ratios (ORs) and 95% confidence intervals (CIs) depending on the heterogeneity among studies. The sources of heterogeneity and publication bias among the included studies were assessed using I2 statistics and Egger's tests. A total of 73 studies, involving 62,250 cases and 69,613 controls were included. The results showed that the minor allele (G) of the rs1801282 variant was associated with the decreased risk of T2DM under different genetic models. Moreover, the protective effect of minor allele was detected to be significantly more in some ethnicities including the European (18%), East Asian (20%), and South East Asian (18%). And the reduction of T2DM risk in Ala12 carriers was stronger in individuals from North Europe rather than Central and South Europe. Our findings indicated that the rs1801282 variant may contribute to decrease of T2DM susceptibility in different ancestries.

SUBMITTER: Sarhangi N

PROVIDER: S-EPMC7391673 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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PPARG (Pro12Ala) genetic variant and risk of T2DM: a systematic review and meta-analysis.

Sarhangi Negar N Sharifi Farshad F Hashemian Leila L Hassani Doabsari Maryam M Heshmatzad Katayoun K Rahbaran Marzieh M Jamaldini Seyed Hamid SH Aghaei Meybodi Hamid Reza HR Hasanzad Mandana M

Scientific reports 20200729 1

Type 2 diabetes mellitus (T2DM) is a complex disease caused by the interaction between genetic and environmental factors. A growing number of evidence suggests that the peroxisome proliferator-activated receptor gamma (PPARG) gene plays a major role in T2DM development. Meta-analysis of genetic association studies is an efficient tool to gain a better understanding of multifactorial diseases and potentially to provide valuable insights into gene-disease interactions. The present study was focuse ...[more]

PMID: 32728045

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Project description:BackgroundMobile health interventions (mHealth) based on smartphone applications (apps) are promising tools to help improve diabetes care and self-management; however, more evidence on the efficacy of mHealth in diabetes care is needed. The objective of this study was to conduct a systematic review and meta-analysis of randomized controlled trials (RCTs) assessing the effect of mHealth apps on changes in hemoglobin A1c (HbA1c), blood glucose, blood pressure, serum lipids, and body weight in type 2 diabetes mellitus (T2DM) patients.MethodsTwo independent reviewers searched three online databases (PubMed, the Cochrane Library, and EMBASE) to identify relevant studies published between January 2005 and June 2016. Of the 2,596 articles retrieved, 13 RCTs were included. We used random effects model to estimate the pooled results.ResultsThirteen studies were selected for the systematic review, six of which with data available containing 1,022 patients were included for the meta-analysis. There was a moderate effect on glycemic control after the mHealth app-based interventions. The overall effect on HbA1c shown as mean difference (MD) was -0.40% (-4.37 mmol/mol) (95% confidence interval [CI] -0.69 to -0.11% [-7.54 to -1.20 mmol/mol]; p = 0.007) and standardized mean differences (SMD) was -0.40% (-4.37 mmol/mol) (95% confidence interval [CI] -0.69 to -0.10% [-7.54 to -1.09 mmol/mol]; p = 0.008). A subgroup analysis showed a similar effect with -0.33% (-3.61 mmol/mol) (95% CI -0.59 to -0.06% [-6.45 to -0.66 mmol/mol]; p = 0.02) in MD and -0.38% (-4.15 mmol/mol) (95% CI -0.71 to -0.05% [-7.76 to -0.55 mmol/mol]; p = 0.02) in SMD in studies where patients' baseline HbA1c levels were less than 8.0%. No effects of mHealth app interventions were found on blood pressure, serum lipids, or weight. Assessment of overall study quality and publication bias demonstrated a low risk of bias among the six studies.ConclusionsSmartphone apps offered moderate benefits for T2DM self-management. However, more research with valid study designs and longer follow-up is needed to evaluate the impact of mHealth apps for diabetes care and self-management.

Project description:Chronic postsurgical pain (CPSP) is a significant detriment to postsurgical recovery and a risk factor for prolonged opioid use. Emerging evidence suggests the estimated heritability for chronic pain is 45% and that genetic factors partially explain individual susceptibility to CPSP. The aim of this study was to systematically review, assess quality, and summarize the studies in humans that have investigated genetic factors associated with CPSP. We also conducted a meta-analysis to derive a single effect size for evaluable genetic associations with CPSP. Our comprehensive literature search included review of 21 full-text articles evaluating variants of 69 genes for association with CPSP. We found significant gene variant associations reported for variants/haplotypes of 26 genes involved in neurotransmission, pain signaling, immune responses and neuroactive ligand-receptor interaction, with CPSP. Six variants of 5 genes (COMT: rs4680 and rs6269, OPRM1: rs1799971, GCH1: rs3783641, KCNS1: rs734784 and TNFA: rs1800629), were evaluated by more than one study and were included in the meta-analysis. At rs734784 (A>G) of KCNS1, presence of G allele marginally increased risk of CPSP (Additive genetic model; Odds ratio: 1.511; 95% CI 1-2.284; P value: .050), while the other variants did not withstand meta-analyses criteria. Our findings demonstrate the role of genetic factors with different functions in CPSP, and also emphasize that single genetic factors have small effect sizes in explaining complex conditions like CPSP. Heterogeneity in surgical cohorts, population structure, and outcome definitions, as well as small number of available studies evaluating same variants, limit the meta-analysis. There is a need for large-scale, homogenous, replication studies to validate candidate genes, and understand the underlying biological networks underpinning CPSP. PERSPECTIVE: Our systematic review comprehensively describes 21 studies evaluating genetic association with CPSP, and limitations thereof. A meta-analysis of 6 variants (5 genes) found marginally increased risk for CPSP associated with rs734784 A>G of the potassium voltage-gated channel gene (KCNS1). Understanding genetic predisposition for CPSP will enable prediction and personalized management.

Dataset Information

PPARG (Pro12Ala) genetic variant and risk of T2DM: a systematic review and meta-analysis.

Publications

PPARG (Pro12Ala) genetic variant and risk of T2DM: a systematic review and meta-analysis.

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