A new clustering model based on the seminal plasma/serum ratios of multiple trace element concentrations in male patients with subfertility

Purpose To investigate whether seminal plasma (SP)/serum ratios of multiple trace elements (TEs) can classify patients with male subfertility. Methods SP/serum ratios of 20 TEs (lithium, sodium, magnesium, phosphorus, sulfur, potassium, calcium, manganese, iron, cobalt, copper, zinc, arsenic, selenium, rubidium, strontium, molybdenum, cesium, barium, and thallium) were calculated for healthy volunteers (n = 4) and those consulting for male subfertility (n = 245). Volunteer semen samples were collected by split ejaculation into early and subsequent fractions, and SP/serum ratio data were compared between fractions. The patients' SP/serum ratio data were used in an unsupervised clustering analysis and qualitatively compared with the data from the fractions of ejaculation from the volunteers. Semen quality parameters and pregnancy outcomes were compared between patient clusters. Results The early fraction of volunteers was characterized by lower phosphorus and arsenic and 18 other higher TEs than the subsequent fraction. Cluster analysis classified patients into four distinct clusters, one sharing characteristics with the early fraction and another with the subsequent fraction. One cluster with the early fraction characteristics had significantly lower semen volume and higher pregnancy rates from spontaneous pregnancies or intrauterine insemination. Conclusions Classification of patients based on SP/serum ratios of multiple TEs represents the dominance of fractions of ejaculation samples. A summary of the research approach for designing and explaining a new clustering model.