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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.

Background: Fourteen meta-analyses reported the individual effects of the GSTM1 and GSTT1 polymorphisms on leukemia risk. However, over 40 studies were not included in previously published meta-analyses. Moreover, one key aspect was that previous metaanalyses did not conduct the false-positive test on the aforementioned issues. Furthermore, previous meta-analyses did not observe the combined effects of GSTM1 present/null and GSTT1 present/null polymorphism with leukemia risk. Therefore, we conducted the current study to further analyze these associations. Objectives: This study aimed to investigate the association between the individual and combined effects of the GSTM1 present/null and GSTT1 present/null polymorphisms and the risk of leukemia. Methods: A meta-analysis was performed applying Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines. Moreover, false-positive report probability (FPRP) and Bayesian false discovery probability (BFDP) were applied to investigate the false-positive results. Results: The individual GSTM1 and GSTT1 null genotypes and combined effects of the two genes were associated with a significantly increased leukemia risk in overall and several subgroup analyses, such as Asians, Caucasians, and so on. Then, further analysis was conducted using FPRP and BFDP. Significant associations were considered as "positive" results on the GSTM1 null genotypewith leukemia risk in overall populations (FPRP < 0.001 and BFDP = 0.006), Asians (FPRP < 0.001 and BFDP < 0.001), and East Asian population (FPRP < 0.001 and BFDP = 0.002). For the GSTT1 null genotype, significant associations were regarded "positive" results in overall populations, acute myeloid leukemia (AML), Asians, and East Asian population. For the combined effects of the GSTM1 and GSTT1 polymorphisms, significant associations were also considered "positive" results in the overall analysis of Asians, Indians, and East Asian population. Conclusion: This study strongly indicates that the individual GSTM1 and GSTT1 null genotypes and combined effects of the two genes are associated with increased leukemia risk in Asians, especially in the East Asian population; the GSTT1 null genotype is associated with increased AML risk; the combined effects of the two genes are associated with increased leukemia risk in Indians. [ABSTRACT FROM AUTHOR]

Background: Numerous studies reported the associations between endothelial nitric oxide synthase (eNOS) polymorphisms (4b/a VNTR (rs869109213), G894T (rs1799983) and T786C (rs2070744)) and type 2 diabetes mellitus (T2DM) risk. However, the conclusions were incongruent. Moreover, since no published meta-analyses were performed, a key issue regarding false-positive results needs to be addressed. Furthermore, four new articles have been published on these issues. Therefore, an updated meta-analysis was conducted to further explore these associations. Objectives: To investigate the association between eNOS 4b/a, G894T and T786C polymorphisms and T2DM risk. Methods: Studies were searched by using the PubMed, China National Knowledge Infrastructure (CNKI), Medline, Embase, International Statistical Institute (ISI) and the China Wanfang databases. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to evaluate the associations using five genetic models. Furthermore, the false-positive report probability (FPRP), Bayesian false discovery probability (BFDP), and the Venice criteria were employed to assess the credibility of statistically significant associations. Results: Overall, the eNOS 4b/a polymorphism was associated with a significantly decreased T2DM risk in Asians (bb vs. aa: OR = 0.44, 95% CI = 0.23–0.84; ab + bb vs. aa: OR = 0.45, 95% CI = 0.24–0.86; bb vs. aa + ab: OR = 0.73, 95% CI = 0.59–0.91; b vs. a: OR = 0.71, 95% CI = 0.57–0.88); the eNOS G894T polymorphism was associated with a significantly increased T2DM risk in Asians (GT vs. GG: OR = 1.52, 95% CI = 1.15–2.01; GT + TT vs. GG: OR = 1.52, 95% CI = 1.15–2.01; T vs. G: OR = 1.39, 95% CI = 1.09–1.76); the eNOS T786C polymorphism was associated with a significantly increased T2DM risk in Indian (TC vs. TT: OR = 1.93, 95% CI = 1.27–2.94; TC + CC vs. TT: OR = 2.06, 95%CI = 1.26–3.36; C vs. T: OR = 1.90, 95%CI = 1.17–3.08). However, when a sensitivity analysis was performed after excluding low quality and Hardy–Weinberg Disequilibrium (HWD) studies, no significant association was found for the eNOS G894T polymorphism. After credibility assessment, we identified "less-credible positive results" for the statistically significant associations in the current meta-analysis. Conclusion: In conclusion, this article suggests that all substantial relationships between eNOS 4b/a, G894T, and T786C polymorphisms and T2DM risk are most likely due to false positive results rather than real connections or biological variables. [ABSTRACT FROM AUTHOR]

Background: Numerous studies reported the associations between endothelial nitric oxide synthase (eNOS) polymorphisms (4b/a VNTR (rs869109213), G894T (rs1799983) and T786C (rs2070744)) and type 2 diabetes mellitus (T2DM) risk. However, the conclusions were incongruent. Moreover, since no published meta-analyses were performed, a key issue regarding false-positive results needs to be addressed. Furthermore, four new articles have been published on these issues. Therefore, an updated meta-analysis was conducted to further explore these associations.Objectives: To investigate the association between eNOS 4b/a, G894T and T786C polymorphisms and T2DM risk.Methods: Studies were searched by using the PubMed, China National Knowledge Infrastructure (CNKI), Medline, Embase, International Statistical Institute (ISI) and the China Wanfang databases. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to evaluate the associations using five genetic models. Furthermore, the false-positive report probability (FPRP), Bayesian false discovery probability (BFDP), and the Venice criteria were employed to assess the credibility of statistically significant associations.Results: Overall, the eNOS 4b/a polymorphism was associated with a significantly decreased T2DM risk in Asians (bb vs. aa: OR = 0.44, 95% CI = 0.23–0.84; ab + bb vs. aa: OR = 0.45, 95% CI = 0.24–0.86; bb vs. aa + ab: OR = 0.73, 95% CI = 0.59–0.91; b vs. a: OR = 0.71, 95% CI = 0.57–0.88); the eNOS G894T polymorphism was associated with a significantly increased T2DM risk in Asians (GT vs. GG: OR = 1.52, 95% CI = 1.15–2.01; GT + TT vs. GG: OR = 1.52, 95% CI = 1.15–2.01; T vs. G: OR = 1.39, 95% CI = 1.09–1.76); the eNOS T786C polymorphism was associated with a significantly increased T2DM risk in Indian (TC vs. TT: OR = 1.93, 95% CI = 1.27–2.94; TC + CC vs. TT: OR = 2.06, 95%CI = 1.26–3.36; C vs. T: OR = 1.90, 95%CI = 1.17–3.08). However, when a sensitivity analysis was performed after excluding low quality and Hardy–Weinberg Disequilibrium (HWD) studies, no significant association was found for the eNOS G894T polymorphism. After credibility assessment, we identified “less-credible positive results” for the statistically significant associations in the current meta-analysis.Conclusion: In conclusion, this article suggests that all substantial relationships between eNOS 4b/a, G894T, and T786C polymorphisms and T2DM risk are most likely due to false positive results rather than real connections or biological variables.

Abstract 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.

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. [ABSTRACT FROM AUTHOR]

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, Ph = 0.032, I2 = 39.8%; TT + TC vs. CC: OR = 1.15, 95% CI: 1.01–1.29, Ph = 0.040, I2 = 38.1%; T vs. C: OR = 1.14, 95% CI: 1.04–1.25, Ph = 0.005, I2 = 50.2%) and Asian population (TC vs. CC: OR = 1.14, 95% CI: 1.01–1.28, Ph = 0.265, I2 = 16.8%; TT + TC vs. CC: OR = 1.17, 95% CI: 1.04–1.30, Ph = 0.105, I2 = 32.9%; T vs. C: OR = 1.10, 95% CI: 1.02–1.19, Ph = 0.018, I2 = 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.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract A Bayesian statistical method was developed to assess the noteworthiness of a single nucleotide polymorphism (SNP)-phenotype association that shows statistical significance in various observational studies, but it has seldom been applied to GWAS meta-analyses in cancers. Data (i.e. allelic frequency, odds ratio, 95% confidence interval, etc.) on various SNP-cancer associations were extracted from meta-analysis of GWAS and the National Human Genome Research Institute (NHGRI) Catalog of Published GWAS and were used to compute the false positive report probability (FPRP) and Bayesian false discovery probability (BFDP) to evaluate the noteworthiness of SNP-cancer associations. Independent paired t -tests showed a direct relationship between SNP-cancer P -values and both FPRP and BFDP estimates. However, a discrepancy in the number of noteworthy associations between P -value comparison and either FPRP or BFDP was found using data extracted from meta-analyses of GWAS and the GWAS Catalog. Most P -values of associations with nonsignificant P -values but with noteworthy FPRP and BFDP estimates were within the range of 10−6 to 5 × 10−8. A poorly selected genome-wide significance threshold and inclusion of a nonsignificant SNP-phenotype association into the noteworthy test can, with either noteworthy FPRP or BFDP computation, give a false impression of noteworthiness for a nonsignificant association. Highlights • Currently, very few epidemiological studies discuss caveats in determining whether a reported significant genetic association is truly noteworthy. • It is possible to obtain "noteworthy" Bayesian results at higher P -values that are not considered statistically significant in GWAS. • Many of these non-noteworthy GWAS results are found noteworthy due to effects of pooled sample size. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is a multi-systemic severe autoimmune disease which results from the irreversible loss of self-tolerance and impaired molecular responses, especially an altered interferon signature. We synthesized all meta-analyses reporting a genetic association of SLE, and further investigated their validity to discover false positive results under Bayesian methods. We executed a PubMed search to extract the respective results regarding gene polymorphisms of SLE, published until June 30th 2017 and selected a single result per genetic variant among duplicates. Among 133 significant genotype comparisons, 45 (34%) were found noteworthy under both false positive report probability (FPRP) and Bayesian false discovery probability (BFDP). From the meta-analysis of genome-wide association studies (GWAS), we could confirm that all significant comparisons were noteworthy under both Bayesian approaches. Both approaches may be advantageous for determining whether the reported associations are genuine, especially for interpreting results from observational studies instead of GWAS whose significance was determined in a more strict manner. When determining results from GWAS with a p -value ranging between 0.05 and 5 × 10 −8 , other statistical approaches, rather than single standard significance may be beneficial. Taking into account these considerations, a proportion of meta-analyses claimed statistical significance, but these results need to be interpreted with caution. [ABSTRACT FROM AUTHOR]

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Han, Zheng, Mu, Li and He.)

The article presents a study on the comparative statistical properties of genetic marker ranking which include False Positive Report Probability (FPRP), Bayesian False-Discovery Probability (BFDP), q-values, and p-values. The study employs simulation studies for genomic regions as well as the mean square errors in genome-wide association studies. The study showed the precision of BFDP and p-values in the reconstruction of true genetic markers in the region.

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.

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.