MTHFR 677C>T Polymorphism Increases the Male Infertility Risk: A Meta-Analysis Involving 26 Studies
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Methylenetetrahydrofolate reductase (MTHFR) polymorphism may be a risk factor for male infertility. However, the epidemiologic studies showed inconsistent results regarding MTHFR polymorphism and the risk of male infertility. Therefore, we performed a meta-analysis of published case-control studies to re-examine the controversy. METHODS: Electronic searches of PubMed, EMBASE, Google Scholar and China National Knowledge Infrastructure (CNKI) were conducted to select eligible literatures for this meta-analysis (updated to June 19, 2014). According to our inclusion criteria and the Newcastle-Ottawa Scale (NOS), only high quality studies that observed the association between MTHFR polymorphism and male infertility risk were included. Crude odds ratio (OR) with 95% confidence interval (CI) was used to assess the strength of association between the MTHFR polymorphism and male infertility risk. RESULTS: Twenty-six studies involving 5,575 cases and 5,447 controls were recruited. Overall, MTHFR 677C>T polymorphism showed significant associations with male infertility risk in both fixed effects (CT+TT vs. CC: OR = 1.34, 95% CI: 1.23-1.46) and random effects models (CT+TT vs. CC: OR = 1.39, 95% CI: 1.19-1.62). Further, when stratified by ethnicity, sperm concentration and control sources, the similar results were observed in Asians, Caucasians, Azoo or OAT subgroup and both in population-based and hospital-based controls. Nevertheless, no significant association was only observed in oligo subgroup. CONCLUSIONS: Our results indicated that the MTHFR polymorphism is associated with an increased risk of male infertility. Further well-designed analytical studies are necessary to confirm our conclusions and evaluate gene-environment interactions with male infertility risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.048 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".