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Access Type

Open Access Thesis

Document Type


Degree Program

Molecular & Cellular Biology

Degree Type

Master of Science (M.S.)

Year Degree Awarded


Month Degree Awarded



Introduction. Sperm parameter analysis is the standard method of male fecundity testing; however, minimal evidence supports associations between individual sperm parameters and reproductive outcomes. Our previous work shows strong associations between sperm mitochondrial DNA copy number (mtDNAcn) and time-to-pregnancy (TTP) in general populations, and between mtDNAcn and fertilization outcomes in clinical populations. Thus it is possible for sperm mtDNA biomarkers to act as summary measures of semen quality. In this study, we developed a sperm quality index (SQI) from semen parameters and compared its ability to measure fecundity to sperm mtDNAcn.

Methods. We received 384 semen samples from the Longitudinal Investigation of Fertility in the Environment Study. Sperm mtDNAcn and mtDNA deletions (mtDNAdel) were quantified using a triplex probe-based qPCR method. The SQI was developed by ranking and summing select sperm parameters within the study population, including sperm concentration, sperm count, normal morphology, high DNA stainability, and DNA fragmentation to create a cumulative index. Discrete-time proportional hazards models were used to determine fecundability odds ratios (FOR), indicating associations between mtDNAcn, SQI, and TTP. Receiver operating characteristic (ROC) analyses determined the validity of the SQI and mtDNAcn as predictors of pregnancy within 12 months.

Results. The SQI was highly associated with mtDNAcn, both continuously (Spearman Rho: -0.487; p-value: <0.001) and in deciles (ANOVA p-value: <0.001). The SQI (FOR: 1.25; 95% confidence interval (CI): 1.09, 1.43) and mtDNAcn (FOR: 0.754; 95% CI: 0.657, 0.866) performed similarly in discrete-time survival models and indicated a significant decrease and increase in TTP, respectively. MtDNAcn more effectively predicted pregnancy within 12 months (AUC: 0.703; 95% CI: 0.617, 0.789) than the SQI (AUC: 0.642; 95% CI: 0.531, 0.753). With multiple predictors, mtDNAcn outperformed summary models, with addition of the SQI and percent normal morphology minimally increasing model efficacy (AUC: 0.718, 95% CI: 0.617, 0.819).

Conclusion. The association between the SQI and mtDNAcn suggest that mtDNAcn may serve as a summary biomarker for overall sperm quality. Neither individual nor summed sperm parameters are useful indicators of couple fecundity and reproductive outcomes compared to mtDNAcn. These results suggest that mtDNAcn has potential for use as a biomarker of fecundity.


First Advisor

J. Richard Pilsner

Second Advisor

Brian Whitcomb

Third Advisor

Alexander Suvorov