Frontiers in endocrinology · 2026
Association of semen leukocytes with sperm DNA fragmentation in a clinical cohort.
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Peng Lijun, Wang Tengfei, Zhu Mengyi, Le Yun, Yang Sheng
Аннотация
BACKGROUND: Sperm DNA fragmentation index (DFI) is increasingly used to characterize male reproductive health, yet its relationships with routinely measured semen parameters, computer-assisted semen analysis (CASA) kinematics, and systemic biomarkers remain incompletely described in clinical practice.
METHODS: A total of 1679 semen examination records were included in the analysis. Correlations between DFI and various biomarkers were assessed using Spearman rank correlations. Nonlinear associations were modeled using natural cubic splines, and predictive modeling was performed using multivariable logistic regression.
RESULTS: DFI was right-skewed and increased with age, while differences across abstinence duration strata were modest. Conventional semen parameters and CASA kinematics were inversely correlated with DFI, including progressive motility (PR) and multiple motion descriptors. Semen leukocytes correlated positively with DFI and showed a nonlinear pattern, while albumin exhibited the strongest inverse systemic signal. In prediction analyses, the model showed good discrimination with an area under the curve (AUC) of 0.783, and favorable calibration with a Brier score of 0.080 and expected calibration error (ECE) of 0.015. The association for semen leukocytes remained consistent across alternative high DFI thresholds.
CONCLUSIONS: DFI increased with age and was inversely related to semen motility and CASA kinematics in routine clinical practice. Semen leukocytes and albumin were consistent biomarkers associated with sperm DNA fragmentation, with evidence of nonlinear exposure-response patterns. An exploratory multivariable model showed good internal cross-validation performance for identifying high DFI. Further external validation is required before clinical application.
METHODS: A total of 1679 semen examination records were included in the analysis. Correlations between DFI and various biomarkers were assessed using Spearman rank correlations. Nonlinear associations were modeled using natural cubic splines, and predictive modeling was performed using multivariable logistic regression.
RESULTS: DFI was right-skewed and increased with age, while differences across abstinence duration strata were modest. Conventional semen parameters and CASA kinematics were inversely correlated with DFI, including progressive motility (PR) and multiple motion descriptors. Semen leukocytes correlated positively with DFI and showed a nonlinear pattern, while albumin exhibited the strongest inverse systemic signal. In prediction analyses, the model showed good discrimination with an area under the curve (AUC) of 0.783, and favorable calibration with a Brier score of 0.080 and expected calibration error (ECE) of 0.015. The association for semen leukocytes remained consistent across alternative high DFI thresholds.
CONCLUSIONS: DFI increased with age and was inversely related to semen motility and CASA kinematics in routine clinical practice. Semen leukocytes and albumin were consistent biomarkers associated with sperm DNA fragmentation, with evidence of nonlinear exposure-response patterns. An exploratory multivariable model showed good internal cross-validation performance for identifying high DFI. Further external validation is required before clinical application.