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Many lifestyle factors, such as nutritional imbalance leading to obesity, metabolic disorders, and nutritional deficiency, have been identified as potential risk factors for male infertility. The aim of this study was to evaluate the relationship between semen parameters and anthropometric, metabolic and nutritional parameters. Relationship was first assessed individually, then after the application of a previously constructed and validated machine learning score that allows their combination. Anthropometric, metabolic, antioxidant, micronutrient, and sperm parameters from 75 men suffering from idiopathic infertility from four infertility centers in France (Jean-Verdier ART Center Hospital, Bondy; North Hospital ART Center, Saint-Étienne; Navarre Polyclinic ART Center, Pau; and Cochin Hospital ART Center, Paris) between September 2009 and December 2013 were collected. After assessing standard correlation analysis, a previously built machine learning model, providing a score ranging from 0 (the poorest) to 1 (the most favorable), was calculated for each man in the study cohort. This machine learning model, which separates infertile/fertile men with unexplained infertility on the basis of their bioclinical signature, provides a more holistic evaluation of the influence of the considered markers (anthropometric, metabolic, and oxidative status). We observed a significant correlation of some anthropometric, metabolic, and nutritional disorders with some sperm characteristics. Moreover, an unfavorable machine learning score was associated with a high level of sperm DNA fragmentation. Favorable anthropometric, metabolic, and oxidative patterns, which may reflect an appropriate lifestyle, appear to positively impact overall health, in particular reproductive function. This study, consistent with previous publications, suggests that beyond semen quality parameters, in an essential assessment of male fertility, other key factors should be taken into account. In this regard, the application of emerging artificial intelligence techniques may provide a unique opportunity to integrate all these parameters and deliver personalized care. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate in a case-control study the associations between idiopathic infertility and antioxidant gene polymorphisms. One hundred ten infertile subjects (58 women and 52 men) with a history of idiopathic infertility and 69 fertile subjects (35 women and 34 men) with no history of infertility were included by three hospital departments of reproductive biology in the NCT01093378 French government clinical trial. Genotyping was assessed by real-time polymerase chain reaction with TaqMan assay. We examined genetic polymorphisms affecting five antioxidant enzymes: manganese superoxide dismutase (MnSOD), myeloperoxidase (MPO), glutathione peroxidase 1 (GPx1), catalase (CAT), and endothelial nitric oxide synthase (eNOS). The presence of at least 1 Ala-MnSOD allele (rs4880) increased significantly the risk of infertility (odds ratio [OR] 2.94; 95% confidence interval [CI], 1.14, 7.60; p=0.03) in male subjects. Moreover, the presence of 2 G- eNOS allele (rs1799983) increased significantly the risk of infertility in both men and women (OR 1.91; 95% CI, 1.04, 3.54; p=0.04). Our observations lead to the hypothesis that the genetic susceptibility modulating oxidative stress may represent a risk factor for male idiopathic infertility. Antioxid. Redox Signal. 21, 565-569. [ABSTRACT FROM AUTHOR]