Correlation study and full management of metabolic syndrome and sperm DNA fragmentation index, a regional multicentre prospective long term follow-up study from Anhui, China - Ma, Dongsheng; Xi, Jianhong (Frontiers in Cell and Developmental Biology, 2025)
ObjectiveTo investigate the correlation between Metabolic syndrome (Mets) and Sperm DNA fragmentation index (DFI) in men of reproductive age, and to summarise the Mets and metabolic component health management model in men.MethodsThe Male Reproductive Health Follow-up Database in Bozhou City, Anhui Province, China (2020–2024) included in the study 1,008 outpatient cases of men with reproductive age,in which normal sperm DFI was the Control group (n = 858) and abnormal DFI was the Observation group (n = 150), and the general data, metabolic endocrine related indicators, and indicators related to fertility assessment were analysed in both groups, and fertility and metabolic indicators were followed up. Spearman rank correlation coefficient was used for correlation analysis, segmented package for threshold analysis, Bootstrap sampling method and Bayesian method for mediation effect test analysis. Univariate-multivariate logistic regression analyses were performed to build a predictive model using R Programming Language (4.42), and to plot the Nomogram, Calibration Curve, Decision Curve Analysis (DCA) Curve, and Clinical impact curve (CIC) to assess the consistency between the predicted probability of the model and the actual occurrence probability, as well as to evaluate the practicality and applicability in clinical decision-making.ResultsIntergroup comparison between the observation and control groups in this study showed no statistical difference between the two groups in terms of baseline information and fertility assessment (P > 0.05). However, there was statistical difference between the two groups in MetS and metabolic scores (P < 0.001). One-way ANOVA showed a statistically significant difference between DFI and MetS scores (P = 0.021), and two-way comparisons showed a statistically significant difference between the groups with 0–4 points (P < 0.05). There was a moderate-strength positive correlation between metabolic score and DFI by Spearman’s correlation analysis (r = 0.475, P < 0.001). Overall, DFI and MetS were positively associated [OR (95%CI):1.09 (1.07–1.11)] when DFI< 32.26 [OR (95%CI): 1.15 (1.12–1.19)]. In the overall analysis, the association between MetS and adverse maternity outcomes was statistically significant (OR = 1.50, 95% CI: 1.01–2.22, P = 0.045). In the sperm DFI subgroup, the association of MetS with adverse maternity outcomes was significant in both DFI ≤15 and DFI >30 (15: OR = 2.51, 95%CI: 1.01–6.22, P = 0.047; >30:OR = 2.94, 95%CI: 1.19–7.22, P = 0.019), and subgroup analyses of age showed significant association between MetS and adverse maternity outcomes in age >30 years (OR = 1.94, 95% CI: 1.13–3.33, P = 0.016). The results of the mediated analysis pathway showed that obesity and hyperlipidaemia lead to sperm DFI abnormalities, which indirectly contribute to adverse maternity outcomes, but it has not been proven that sperm DFI abnormalities contribute to the occurrence of adverse maternity outcomes. The results of multifactorial logistic regression analysis showed that varicocele (OR = 1.975), obesity (OR = 2.296), hyperlipidaemia (OR = 2.422), and Low-HDL (OR = 3.654) were the independent risk factors for abnormal sperm DFI. And effective interventions for the group with abnormal sperm DFI could significantly reduce sperm DFI values and metabolic scores (P < 0.001). The predictive model has been validated to show positive predictive efficacy and clinical benefit.ConclusionMetS may lead to abnormal sperm DNA fragmentation indices, which in turn suggests that abnormal sperm DFI due to MetS may be a risk factor for male infertility and spousal adverse maternity, and that effective interventions to reduce sperm DFI values and metabolic scores are necessary and urgent. This study is part of the China Anhui Regional Male Fertility Survey Phase I (2020–2024).