Effects of gene–environment and gene–gene interactions in case-control studies: A novel Bayesian semiparametric approach

Objective The methylenetetrahydrofolate reductase gene C677T polymorphism is closely related to the acute lymphoblastic leukemia. Several case–control studies have investigated this association; however, no conclusions could be drawn. A comprehensive updated meta-analysis is established to explain these contradictions and clarify the overall impact of this variant on the susceptibility to acute lymphoblastic leukemia. Methods Electronic searches were conducted to select published studies prior to June 2018. Pooled odds ratios and stratification analysis were performed under different genetic comparison models, age, and ethnicity. Results Totally, 66 case–control studies including 9619 acute lymphoblastic leukemia cases and 17,396 controls were selected. Our analyses showed that methylenetetrahydrofolate reductase C677T polymorphism was protective mainly in Asian and European countries, under all genetic models and regardless of age, but leukemogenic in mixed population. Conclusion Thus, C677T polymorphism may be a promising acute lymphoblastic leukemia biomarker, but they should be interpreted with caution considering other factors such as folic acid intake, gene–gene and gene–environment interactions.

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Association of the MTHFR 677C>T and 1298A>C polymorphisms and male infertility risk: a meta-analysis

Reproductive Biology and Endocrinology ◽

10.1186/s12958-020-00649-1 ◽

2020 ◽

Vol 18 (1) ◽

Author(s):

Fereshteh Aliakbari ◽

Farkhondeh Pouresmaeili ◽

Nahal Eshghifar ◽

Zahra Zolghadr ◽

Faezeh Azizi

Keyword(s):

Male Infertility ◽

Methylenetetrahydrofolate Reductase ◽

Meta Analysis ◽

Case Control ◽

Inclusion Criteria ◽

Case Control Studies ◽

Crude Odds Ratio ◽

Mthfr Polymorphism ◽

Gene Environment ◽

The Relationship

Abstract Background and objectives One of the possible male sterility risk factors are polymorphisms of Methylenetetrahydrofolate reductase (MTHFR). However, the epidemiologic investigations described inconsistent results regarding MTHFR polymorphism and the risk of male infertility. For that reason, we carried out a meta-analysis of published case-control studies to re-examine the controversy. Methods Electronic searches of Cochrane, EMBASE, Google Scholar, and PubMed were conducted to select eligible studies for this meta-analysis (updated to May 2019). According to our exclusion and inclusion criteria, only high-quality studies that remarked the association between MTHFR polymorphisms and male infertility risk were included. The Crude odds ratio (OR) with a confidence interval of 95% (CI) was used to assess the relationship between MTHFR polymorphism and male infertility risk. Results Thirty-four case-control studies with 9662 cases and 9154 controls concerning 677C/T polymorphism and 22 case-control studies with 5893 cases and 6303 controls concerning 1298A/C polymorphism were recruited. Both MTHFR polymorphisms had significant associations with male infertility risk (CT + TT vs. CC: OR = 1.37, 95% CI: 1.21–1.55, P = 0.00, I2 = 41.9%); (CC vs. CA + AA: OR = 0.82, 95% CI: 0.52–1.30, P = 0.04, I2 = 50.1%). Further, when stratified by ethnicity, the significant association results were observed in Asians and Caucasians for 677C/T and just Asians for 1298A/C. Conclusions Some of MTHFR polymorphisms like MTHFR 677C > T are associated with an elevated male infertility risk. To confirm our conclusion and to provide more accurate and complete gene-environment communication with male infertility risk, more analytical studies are needed.

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BOOST: A Fast Approach to Detecting Gene-Gene Interactions in Genome-wide Case-Control Studies

The American Journal of Human Genetics ◽

10.1016/j.ajhg.2010.07.021 ◽

2010 ◽

Vol 87 (3) ◽

pp. 325-340 ◽

Cited By ~ 309

Author(s):

Xiang Wan ◽

Can Yang ◽

Qiang Yang ◽

Hong Xue ◽

Xiaodan Fan ◽

...

Keyword(s):

Case Control ◽

Gene Interactions ◽

Case Control Studies ◽

Fast Approach ◽

Genome Wide

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Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies

Bioinformatics and Biology Insights ◽

10.4137/bbi.s9867 ◽

2012 ◽

Vol 6 ◽

pp. BBI.S9867 ◽

Cited By ~ 1

Author(s):

Guanjie Chen ◽

Ao Yuan ◽

Jie Zhou ◽

Amy R. Bentley ◽

Adebowale Adeyemo ◽

...

Keyword(s):

Complex Disease ◽

Association Studies ◽

Parametric Method ◽

Case Control ◽

Gene Interactions ◽

Ratio Test ◽

Genome Wide Association Studies ◽

Case Control Studies ◽

F Test ◽

Howard University

Missing heritability is still a challenge for Genome Wide Association Studies (GWAS). Gene-gene interactions may partially explain this residual genetic influence and contribute broadly to complex disease. To analyze the gene-gene interactions in case-control studies of complex disease, we propose a simple, non-parametric method that utilizes the F-statistic. This approach consists of three steps. First, we examine the joint distribution of a pair of SNPs in cases and controls separately. Second, an F-test is used to evaluate the ratio of dependence in cases to that of controls. Finally, results are adjusted for multiple tests. This method was used to evaluate gene-gene interactions that are associated with risk of Type 2 Diabetes among African Americans in the Howard University Family Study. We identified 18 gene-gene interactions ( P < 0.0001). Compared with the commonly-used logistical regression method, we demonstrate that the F-ratio test is an efficient approach to measuring gene-gene interactions, especially for studies with limited sample size.

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RE: "ASYMPTOTIC BIAS AND EFFICIENCY IN CASE-CONTROL STUDIES OF CANDIDATE GENES AND GENE-ENVIRONMENT INTERACTIONS: BASIC FAMILY DESIGNS"

American Journal of Epidemiology ◽

10.1093/aje/152.7.689 ◽

2000 ◽

Vol 152 (7) ◽

pp. 689-690 ◽

Cited By ~ 3

Author(s):

C. Weinberg

Keyword(s):

Candidate Genes ◽

Case Control ◽

Asymptotic Bias ◽

Case Control Studies ◽

Basic Family ◽

Gene Environment

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High-temperature requirement factor A1 rs11200638 polymorphism and age-related macular degenerative from a comprehensive analysis about 15316 subjects

10.21203/rs.2.23339/v2 ◽

2020 ◽

Author(s):

Ying Liu ◽

Huipeng Jin ◽

Dong Wei ◽

Wenxiu Li

Keyword(s):

High Temperature ◽

Meta Analysis ◽

Case Control ◽

Dominant Model ◽

Case Control Studies ◽

Temperature Requirement ◽

Age Related ◽

Gene Environment ◽

Increased Risk ◽

Taqman Pcr

Abstract Background The high-temperature requirement factor A1 (HTRA1) gene at the 10q26 locus has been associated with age-related macular degenerative (AMD) risk, with the significantly associated polymorphism being (rs11200638, -625G/A), however, above association is not consistent. We investigated an updated meta-analysis to evaluate the association between rs11200638 polymorphism and AMD risk thoroughly addressing this issue. Methods An identification was covered with the Pubmed and Chinese Wanfang databases through 27th Jan, 2020. Odds ratios (OR) and 95% confidence intervals (CI) were used to assess the strength of associations. After a thorough and meticulous search, 35 different articles (33 case-control studies with HWE, 22 case-control studies about wet/dry AMD) were retrieved. Results Individuals carrying A-allele or AA genotype may have an increased risk to be AMD disease. For example, there has a significantly increased relationship between rs11200638 polymorphism and AMD both for Asians (OR: 2.50, 95%CI: 2.22-2.80 for A-allele vs. G-allele) and Caucasians (OR: 2.11, 95%CI: 1.43-3.13 for A-allele vs. G-allele). Moreover, a similar trend in the source of control subgroup was detected. To classify the type of AMD, increased association was also observed in both wet (OR: 3.40, 95%CI: 2.90-3.99 for dominant model) and dry (OR: 2.08, 95%CI: 1.24-3.48 for dominant model) AMD. Finally, based on the different genotyping methods, increased relationships were identified by sequencing, TaqMan, PCR-RFLP. Conclusions Our present meta-analysis suggests that the HTRA1 rs11200638 polymorphism are potentially associated with the risk of AMD development, especially about individuals carrying A-allele or AA genotype, who may be as identified targets to detect and intervene in advance. Further studies using larger sample sizes and including information about gene-environment interactions should be conducted to elucidate.

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