Individual effects of GSTM1 and GSTT1 polymorphisms on cervical or ovarian cancer risk: An updated meta-analysis

Background: Studies have shown that glutathione S-transferase M1 (GSTM1) and. glutathione S-transferase T1 (GSTT1) null genotype may increase the risk of cervical cancer (CC) or ovarian cancer (OC), however, the results of published original studies and meta-analyses are inconsistent. Objectives: To investigate the association between GSTM1 present/null and GSTT1 present/null polymorphisms, with the risk of cervical cancer or ovarian cancer. Methods: The odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the association between GSTM1 present/null and GSTT1 present/null polymorphisms and the risk of cervical cancer or ovarian cancer. To assess the confidence of statistically significant associations, we applied false positive reporting probability (FPRP) and bayesian false discovery probability (BFDP) tests. Results: Overall analysis showed that GSTM1 null was associated with an increased risk of cervical cancer, and subgroup analysis showed a significant increase in cervical cancer risk in Indian and Chinese populations; GSTT1 was not found null genotype are significantly associated with cervical cancer. Overall analysis showed that GSTM1 and GSTT1 null were not associated with the risk of ovarian cancer, subgroup analysis showed that GSTM1 null was associated with an increased risk of OC in East Asia, and GSTT1 null was associated with an increased risk of OC in South America. However, when we used false positive reporting probability and bayesian false discovery probability to verify the confidence of a significant association, all positive results showed "low confidence" (FPRP > .2, BFDP > .8). Conclusion: Overall, this study strongly suggests that all positive results should be interpreted with caution and are likely a result of missing plausibility rather than a true association.

Association between OPG polymorphisms and osteoporosis risk: An updated meta-analysis

Background: Numerous studies have demonstrated an association between osteoprotegerin (OPG) polymorphisms (A163G (rs3102735), T245G (rs3134069), T950C (rs2073617), G1181C (rs2073618)) and osteoporosis risk. However, their conclusions are inconsistent. In addition, some new studies have been updated, and more importantly, previous meta-analyses have not tested for false-positive results. In order to further explore these associations, we recently conducted a meta-analysis. Objectives: To study the relationship between OPG polymorphisms A163G, T245G, T950C, G1181C and the risk of osteoporosis. Methods: PubMed, Medline, International Statistical Institute (ISI), China National Knowledge Infrastructure (CNKI) and China Wanfang Database were used for research searches. Associations were assessed with five genetic models using odds ratios (ORs) with 95% confidence intervals (CIs). In addition, confidence in statistically significant associations was assessed using false-positive report probability (FPRP), Bayesian probability of False discovery (BFDP), and Venice criteria. Results: On the whole, the OPG A163G polymorphism was not significantly associated with risk of osteoporosis. However, in a subgroup analysis, we found that the OPG A163G polymorphism increased the risk of osteoporosis in Caucasians (AG + GG vs AA: OR = 1.35, 95% CI = 1.06-1.73; AA + GG vs AG: OR = 0.64, 95% CI = 0.49-0.82) and the female (G vs A: OR = 1.30, 95% CI = 1.03-1.64; AG + GG vs AA: OR = 1.42, 95% CI = 1.18-1.71). At the same time, the OPG G1181C polymorphism reduces the risk of osteoporosis (C vs G: OR = 0.84, 95% CI = 0.74-0.95; CC vs GG: OR = 0.75, 95% CI = 0.60-0.93; GC + CC vs GG: OR = 0.80, 95% CI = 0.67-0.95; CC vs GG + GC: OR = 0.84, 95% CI = 0.70-1.00). Moreover, a significantly decreased risk of osteoporosis was also discovered in Asian (C vs G: OR = 0.80, 95% CI = 0.66-0.98; CC vs GG: OR = 0.67, 95% CI = 0.47-0.95; GC + CC vs GG: OR = 0.74, 95% CI = 0.58-0.95) and the female (C vs G: OR = 0.85, 95% CI = 0.75-0.97; CC vs GG: OR = 0.77, 95% CI = 0.61-0.96; GC + CC vs GG: OR = 0.79, 95% CI = 0.66-0.95). Finally, we did not find a close association between OPG T245G and T950C polymorphisms and osteoporosis risk. However, when we retained only studies in the control group that was consistent with Hardy-Weinberg equilibrium (HWE) and high-quality scores, we observed that the OPG A163G polymorphism increased the risk of osteoporosis in the overall analysis (G vs A: OR = 1.40, 95% CI = 1.16-1.68; GG vs AA: OR = 1.96, 95% CI = 1.20-3.21; AG + GG vs AA: OR = 1.45, 95% CI = 1.22-1.72). Finally, after the credibility assessment, we concluded that all statistically significant association results in the meta-analysis in this study and those in the previous study were 'positive results with low confidence'. Conclusion: In conclusion, our study concluded that all meaningful results between OPG A163G and G1181C polymorphisms and osteoporosis risk were false-positive results rather than true associations.

Association Between MTHFR Polymorphisms and the Risk of Essential Hypertension: An Updated Meta-analysis

BACKGROUND

Since the 1990s, there have been a lot of research on single-nucleotide polymorphism (SNP) and different diseases, including many studies on 5,10-methylenetetrahydrofolate reductase (MTHFR) polymorphism and essential hypertension (EH). Nevertheless, their conclusions were controversial. So far, six previous meta-analyses discussed the internal relationship between the MTHFR polymorphism and EH, respectively. However, they did not evaluate the credibility of the positive associations. To build on previous meta-analyses, we updated the literature by including previously included papers as well as nine new articles, improved the inclusion criteria by also considering the quality of the papers, and applied new statistical techniques to assess the observed associations.

OBJECTIVES

This study aims to explore the degree of risk correlation between two MTHFR polymorphisms and EH.

METHODS

PubMed, EMBASE, the Cochrane Library, CNKI, and Wan Fang electronic databases were searched to identify relevant studies. We evaluated the relation between the MTHFR C677T (rs1801133) and A1298C (rs1801131) polymorphisms and EH by calculating the odds ratios (OR) as well as 95% confidence intervals (CI). Here we used subgroup analysis, sensitivity analysis, cumulative meta-analysis, assessment of publication bias, meta-regression meta, False-positive report probability (FPRP), Bayesian false discovery probability (BFDP), and Venice criterion.

RESULTS

Overall, harboring the variant of MTHFR C677T was associated with an increased risk of EH in the overall populations, East Asians, Southeast Asians, South Asians, Caucasians/Europeans, and Africans. After the sensitivity analysis, positive results were found only in the overall population (TT vs. CC: OR = 1.14, 95% CI: 1.00-1.30, P _h = 0.032, I ² = 39.8%; TT + TC vs. CC: OR = 1.15, 95% CI: 1.01-1.29, P _h = 0.040, I ² = 38.1%; T vs. C: OR = 1.14, 95% CI: 1.04-1.25, P _h = 0.005, I ² = 50.2%) and Asian population (TC vs. CC: OR = 1.14, 95% CI: 1.01-1.28, P _h = 0.265, I ² = 16.8%; TT + TC vs. CC: OR = 1.17, 95% CI: 1.04-1.30, P _h = 0.105, I ² = 32.9%; T vs. C: OR = 1.10, 95% CI: 1.02-1.19, P _h = 0.018, I ² = 48.6%). However, after further statistical assessment by FPRP, BFDP, and Venice criteria, the positive associations reported here could be deemed to be false-positives and present only weak evidence for a causal relationship. In addition, when we performed pooled analysis and sensitivity analysis on MTHFR A1298C; all the results were negative.

CONCLUSION

The positive relationships between MTHFR C677T and A1298C polymorphisms with the susceptibility to present with hypertension were not robust enough to withstand statistical interrogation by FPRP, BFDP, and Venice criteria. Therefore, these SNPs are probably not important in EH etiology.

A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk

In this meta-analysis, we systematically investigated the correlation between single nucleotide polymorphisms (SNPs) and pancreatic cancer (PC) risk. We searched PubMed, Network Science, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Science and Technology Periodical Database (VIP), and Wanfang databases up to January 2020 for studies on PC risk-associated SNPs. We identified 45 case-control studies (36,360 PC patients and 54,752 non-cancer individuals) relating to investigations of 27 genes and 54 SNPs for this meta-analysis. Direct meta-analysis followed by network meta-analysis and Thakkinstian algorithm analysis showed that homozygous genetic models for CTLA-4 rs231775 (OR =0.326; 95% CI: 0.218-0.488) and VDR rs2228570 (OR = 1.976; 95% CI: 1.496-2.611) and additive gene model for TP53 rs9895829 (OR = 1.231; 95% CI: 1.143-1.326) were significantly associated with PC risk. TP53 rs9895829 was the most optimal SNP for diagnosing PC susceptibility with a false positive report probability < 0.2 at a stringent prior probability value of 0.00001. This systematic review and meta-analysis suggest that TP53 rs9895829, VDR rs2228570, and CTLA-4 rs231775 are significantly associated with PC risk. We also demonstrate that TP53 rs9895829 is a potential diagnostic biomarker for estimating PC risk.

Genetic variations in MicroRNA genes and cancer risk: A field synopsis and meta-analysis

BACKGROUND

Cancer risk has been associated with certain gene variations in microRNA (miRNA), but conflicting evidence warrants re-assessing of significant results in meta-analyses. We summarized published meta-analyses that assess the associations between miRNA polymorphism and cancers to show the validity of the findings.

METHOD

We searched PubMed and investigated the results of meta-analyses published through November 2018. We re-assessed the results based on false-positive report probability (FPRP) to test the noteworthiness of the associations.

RESULTS

Sixty-eight miRNA polymorphisms in 45 meta-analyses associated with cancer were included. Four (7.4%) and sixteen (25.0%) single nucleotide polymorphisms (SNPs) were noteworthy (FPRP < 0.2) at a prior probability of 0.001 for interesting candidate genes and a statistical power to detect an odds ratio (OR) of 1.1 and 1.5, respectively. The four miRNA SNPs noteworthy at an OR of 1.1 were as follows: miR-146a/rs2910164 Cvs.G; miR-27a/rs895819 Cvs.T; miR-423/rs6505162 Cvs.A; and miR-605/rs2043556 Cvs.T. The 16 SNPs noteworthy at an OR of 1.5 include the four genotype comparisons at an OR of 1.1, and the additional 12 genotype comparisons were as follows: miR-196a2/rs11614913 Tvs.C; miR-27a/rs895819 GGvs.AA + AG; miR-196a2/rs11614913 C vs.T; miR-146a/rs2910164 Gvs.C; miR-196a2/rs11614913 Tvs.C; miR-146a/rs2910164 Cvs.G; miR-499/rs3746444 homozygous model; miR-146a/rs2910164 CCvs.GG + GC; miR-499/rs3746444 TCvs.TT; miR-499/rs3746444 GAvs.AA; miR-146a/rs2910164 CCvs.GG; and miR-499/rs3746444 Gvs.A. No association was noteworthy at a prior probability of 0.000001.

CONCLUSION

Out of 68 published associations of miRNA polymorphisms with cancer, sixteen have shown noteworthiness in our re-assessing meta-analysis. Our findings summarize the results of meta-analyses on the association of cancer with SNPs and underline the importance of interpreting results with caution.

Genetic variants in migraine: a field synopsis and systematic re-analysis of meta-analyses

Objective

Numerous genetic variants from meta-analyses of observational studies and GWAS were reported to be associated with migraine susceptibility. However, due to the random errors in meta-analyses, the noteworthiness of the results showing statistically significant remains doubtful. Thus, we performed this field synopsis and re-analysis study to evaluate the noteworthiness using a Bayesian approach in hope of finding true associations.

Methods

Relevant meta-analyses from observational studies and GWAS examining correlation between all genetic variants and migraine risk were included in our study by a PubMed search. Identification of noteworthy associations were analyzed by false-positive rate probability (FPRP) and Bayesian false discovery probability (BFDP). Using noteworthy variants, GO enrichment analysis were conducted through DAVID online tool. Then, the PPI network and hub genes were performed using STRING database and CytoHubba software.

Results

As for 8 significant genetic variants from observational studies, none of which showed noteworthy at prior probability of 0.001. Out of 47 significant genetic variants in GWAS, 36 were noteworthy at prior probability of 0.000001 via FPRP or BFDP. We further found the pathways “positive regulation of cytosolic calcium ion concentration” and “inositol phosphate-mediated signaling” and hub genes including MEF2D, TSPAN2, PHACTR1, TRPM8 and PRDM16 related to migraine susceptibility.

Conclusion

Herein, we have identified several noteworthy variants for migraine susceptibility in this field synopsis. We hope these data would help identify novel genetic biomarkers and potential therapeutic target for migraine.

Field Synopsis and Re-analysis of Systematic Meta-analyses of Genetic Association Studies in Multiple Sclerosis: a Bayesian Approach

To provide an up-to-date summary of multiple sclerosis-susceptible gene variants and assess the noteworthiness in hopes of finding true associations, we investigated the results of 44 meta-analyses on gene variants and multiple sclerosis published through December 2016. Out of 70 statistically significant genotype associations, roughly a fifth (21%) of the comparisons showed noteworthy false-positive rate probability (FPRP) at a statistical power to detect an OR of 1.5 and at a prior probability of 10^-6 assumed for a random single nucleotide polymorphism. These associations (IRF8/rs17445836, STAT3/rs744166, HLA/rs4959093, HLA/rs2647046, HLA/rs7382297, HLA/rs17421624, HLA/rs2517646, HLA/rs9261491, HLA/rs2857439, HLA/rs16896944, HLA/rs3132671, HLA/rs2857435, HLA/rs9261471, HLA/rs2523393, HLA-DRB1/rs3135388, RGS1/rs2760524, PTGER4/rs9292777) also showed a noteworthy Bayesian false discovery probability (BFDP) and one additional association (CD24 rs8734/rs52812045) was also noteworthy via BFDP computation. Herein, we have identified several noteworthy biomarkers of multiple sclerosis susceptibility. We hope these data are used to study multiple sclerosis genetics and inform future screening programs.

The MIF -173G/C gene polymorphism increase gastrointestinal cancer and hematological malignancy risk: evidence from a meta-analysis and FPRP test

The macrophage migration inhibitory factor (MIF) -173G/C gene polymorphism has been implicated in the susceptibility to cancer, but the results are not conclusive. So the aim of study to investigate the association between MIF -173G/C gene polymorphism and cancer risk by a comprehensive meta-analysis. We searched the PubMed, Embase, Wanfang and China National Knowledge Internet (CNKI) databases, with the last updated search being performed on May 24, 2015. The odds ratio (OR) and 95% confidence interval (95% CI) were used to assess the association. Statistical analysis was performed by STATA 11.0 software. Finally, 7,253 participants from 15 studies were included in the meta-analysis. The results of meta-analysis indicated the significant association between MIF -173G/C gene polymorphism and cancer susceptibility, especially in Asians (C vs.

G, OR

1.22, 95% CI=1.00-1.50). In addition, the significant relationship between MIF -173G/C gene polymorphism and gastrointestinal tumors (CC+CG vs.

GG, OR

1.25, 95% CI=1.05-1.50), hematological malignancy (CC+CG vs.

GG, OR

1.27, 95% CI=1.03-1.56), gynecolgical tumors (CC vs. CG+

GG, OR

1.51, 95% CI=1.04-2.19) risk was found. However, to avoid the "false positive report", we investigated the significant associations observed in the present meta-analysis by the false positive report probabilities (FPRPs) test. Interestingly, the results of FPRP test indicated the MIF -173G/C gene polymorphism only associated with gastrointestinal cancer and hematological malignancy risk (FPRP=0.132, 0.067 respectively) at the level of a prior probability is 0.1. Therefore, the meta-analysis suggested MIF -173G/C gene polymorphism would be a risk factor for the gastrointestinal cancer and hematological malignancy.