Association of sperm DNA fragmentation with higher miscarriage rates in non-male factor infertility reproductive cycles

Introduction

Recurrent spontaneous abortion (RSA), defined as the occurrence of two or more lost pregnancies in succession with the same partner (including biochemical pregnancy), is considered one of the most common pregnancy complications. RSA affects up to 5% of women of childbearing age (1) and has become a globally significant issue. A combination of thyroid dysfunction, structural and anatomical irregularities, endocrine imbalances, immune-related disruptions, genetic predisposition, coagulation disorders, and infectious agents plays a key role in this multifactorial disease (2). RSA is a pathological pregnancy that can result in infertility, cardiovascular disease, and venous thromboembolism. It has been linked with psychological issues, including anxiety, depression, and posttraumatic stress disorder (3). Women with RSA may have an elevated risk of pregnancy-associated issues, such as preeclampsia, fetal growth restriction, and premature birth as compared to those with normal fertility (4). Effective therapeutic modalities for RSA are currently scarce, highlighting the clinical significance of identifying reliable strategies for early diagnosis and treatment to reduce its incidence.

Concerning the clinical diagnosis of male factors contributing to RSA, routine semen analysis only assesses the parameters of motility, morphology, and sperm concentration. However, these conventional indicators offer only incomplete predictions of semen quality (5). It is important that DNA integrity be maintained in sperm cells to ensure the accuracy of the genetic information transferred. Loss of integrity impairs this process and has been found to adversely influence the formation and division of fertilized eggs and embryonic development, resulting in infertility and habitual abortion (6,7).

Among the various parameters in the sperm chromatin structure assay (SCSA), the sperm DNA fragmentation (SDF) index (DFI) is regarded as the most reliable measure of DNA integrity and potential damage in the sperm. This approach demonstrates superior diagnostic value compared to traditional routine semen analysis (8,9). Moreover, several systematic reviews have established a significant association between elevated sperm DFI and increased risk of pregnancy loss in both spontaneous and assisted conception, suggesting that higher rates of SDF may contribute to miscarriage (10). A meta-analysis further confirmed that couples experiencing RSA exhibit a higher level of SDF than do fertile couples, suggesting that sperm DFI may be an indicator for RSA (11). However, other studies have reported that SDF levels do not significantly differ between couples experiencing RSA and those with normal fertility (12,13). Thus, there is no consensus regarding the value of DNA integrity assessments in RSA diagnosis and outcome prediction. Further research is required to determine whether sperm DNA integrity correlates with RSA.

This study used SCSA to analyze sperm DFI in 438 RSA cases at a single center to assess the potential of DFI in predicting pregnancy outcome in RSA. Furthermore, the significance of other factors with SDF, including lifestyle variables (smoking and drinking), occupation, and routine semen parameters, was examined to assess the value of SDF in evaluating male fertility in RSA and its influencing factors. We present this article in accordance with the STARD reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-322/rc).

Methods

Participants and data

RSA was defined as pregnancy loss before 28 weeks of gestation that occurred at least twice with the same spouse and could include biochemical pregnancies. This study enrolled 438 males (aged 24–50 years) whose spouses had received diagnoses of RSA between January 2022 and October 2023 in the Outpatient Department of Reproductive Medicine at the Second People’s Hospital of Wuhu (the experimental group). The inclusion criteria were (I) healthy married adult males; (II) couples with a regular, healthy sex life; and (III) spouses diagnosed with RSA. The exclusion criterion was males using medications that could affect semen test results within the previous 6 months. In addition, 183 males (aged 24–50 years) whose spouses had normal fertility in the previous year without RSA were enrolled as the controls. This study collected data on lifestyle factors from all participants, including age, occupation, smoking habits, alcohol consumption, sleep duration, abstinence time, and occupational status. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The Institutional Review Board of the Second People’s Hospital of Wuhu (No. SZ2021002) approved the study, and all patients provided informed consent.

Collection and evaluation of semen specimen

The methods for semen collection and analysis were carried out following the World Health Organization’s (WHO) 2010 recommendations, with minor adjustments. In our Andrology Laboratory, patients were instructed to masturbate and collect semen into a preweighed, sterile, wide-mouthed cup that was previously tested for compatibility with the human sperm collection in a container after 3–5 days of abstinence. The patient’s name and time of semen collection were documented using a marker. After color was assessed, the sperm volume was determined by weighing the specimen in the sperm cup with an electronic scale, while the measurement of the pH was conducted on an extensive precision test strip.

The sperm cup was incubated in a thermostatic water bath at 37 ℃, and a wet specimen was prepared after 20 min to determine whether the semen was completely liquefied. Sperm not completely liquefied after 60 min were recorded as abnormally liquefied. In this case, liquefaction was promoted by mechanical mixing or digestion with bromelain. The viscosity of the specimen was measured, and abnormalities were recorded after complete liquefaction.

Moreover, a preliminary microscopic examination was conducted to evaluate the aggregation or agglutination of the sperm. After being mixed, the semen specimens were subjected to auxiliary analysis using an SQA-V automated semen quality analyzer (Medical Electronic Systems, CA, USA) to assess various parameters, including semen concentration and motility. Following transient centrifugation of the semen, the sperm was resuspended and smeared onto a glass slide for optical microscopy (1,000×) to evaluate sperm morphology after Diff-Quik fixation staining. The reference values for semen quality analysis were established with strict adherence to the WHO 2010 guidelines as follows: semen volume ≥1.5 mL, pH 7.2–8.0, sperm concentration ≥15×10⁶/mL, total sperm number ≥39×10⁶, total motility ≥40%, progressive motility ≥32%, and normal form ≥4%. A semen specimen was defined as normal if it satisfied all of the above criteria and abnormal if it did not satisfy any of the criteria.

Measurement of DFI

The DFI was evaluated using SCSA, and semen (10 µL; final concentration 2×10⁶ cells/mL) was added to 90 µL of Tris-NaCl-EDTA buffer (Abcam, Cambridge, UK). Subsequently, 200 µL of a pH 1.2 buffer (NaCl, Triton X-100) was added and mixed gently. Following a precise timing of 30 s, 600 µL of 0.0006% (v/v) acridine orange in phosphate buffer was introduced. The prepared samples were examined within a time frame of 30 min. A flow cytometer (FACSCalibur, BD Biosciences, San Jose, CA, USA) was used to analyze the samples. Two independent measurements were performed for each sample, with at least 10,000 cell particles being analyzed in each instance. Following acid treatment and staining with acridine orange, the sperm samples demonstrated red fluorescence due to single-stranded DNA fragments with irregular chromatin structures. Conversely, a green fluorescence was emitted when intact double-stranded DNA came into contact with acridine orange. The proportion of red-fluorescing sperm relative to the overall sperm count was used to determine the sperm DFI.

Statistical analysis

Data were analyzed with SPSS 26.0 (IBM Corp., Armonk, NY, USA). Normally distributed variables are shown as the mean ± standard deviation. Independent samples t-tests were conducted when data satisfied the assumption of variance homogeneity, whereas nonparametric rank-sum tests were used for nonnormally distributed variables. The Spearman rank correlation coefficient and linear regression analyses were performed to assess relationships among various factors. Moreover, receiver operating characteristic (ROC) curves were used to examine sensitivity, specificity, and the most suitable cutoff value for predicting risk factors associated with abnormal sperm DFI. Statistical significance was defined as a P value <0.05.

Results

Comparison of routine semen parameters and sperm DFI between the two groups

The experimental and control groups were comparable in terms of normal forms, abstinence duration, volume of semen, concentration of sperm, and progressive and total sperm motility. The DFI values were significantly higher in the experimental group than in the control group (Table 1; P=0.002), indicating a significant association between DNA integrity and the RSA.

Correlation analysis of age and sperm quality

The participants were classified into two subgroups based on age (≤30 and >30 years). Sperm DFI in the subgroup ≤30 years old is lower than that in the subgroup >30 years old (Figure 1A; P=0.01). A positive relationship between DFI and age was indicated in the Spearman correlation analysis (Figure 1B; P=0.03), with older males demonstrating a higher sperm DFI. However, no significant differences were observed in sperm concentrations, total sperm numbers, sperm motility, or progressive motility between the two subgroups. The ≤30-year subgroup demonstrated a significantly higher rate of normal form than did the >30-year group (Figure 1C; P=0.02). Moreover, a negative association was observed between age and normal form (Figure 1D; P=0.01). Since some of these clinical variables were potential confounding factors, age was considered the independent variable in the linear regression analysis. The findings revealed a significant association of age with sperm DFI and normal form (P<0.05), indicating that age might influence sperm quality.

Figure 1 Comparisons and correlations of sperm parameters between different age groups. (A) Bar graph showing sperm DFI in males aged ≤30 and >30 years, with a significant increase in DFI observed in the older group (*, P<0.05). (B) Scatter plot showing a positive correlation between age and sperm DFI (P=0.03). (C) Bar graph comparing the percentage of morphologically normal sperm in the two age groups, with significantly lower values in older males (*, P<0.05). (D) Scatter plot showing a negative correlation between age and normal sperm morphology (P=0.01). DFI, DNA fragmentation index.

Analysis of correlation and difference between lifestyle and sperm quality factors

In the Spearman correlation analysis, there were negative correlations between sperm DFI and sperm concentration (P=0.04), total motility (P<0.001), normal form (P<0.001), and progressive motility (P<0.001). However, sperm DFI did not correlate with semen volume (P=0.45) or total sperm count (P=0.07) (Table 2 and Figure 2). These data suggest that sperm DFI correlates to varying degrees with routine semen parameters.

Figure 2 Correlation between semen parameters and sperm DFI. No significant correlation was found between (A) semen volume or (B) total sperm number and DFI. Significant negative correlations (P<0.05) were found between sperm DFI and (C) sperm concentration, (D) total motility, (E) normal sperm morphology, and (F) sperm progressive motility. DFI, DNA fragmentation index.

The analysis revealed no significant differences in sperm concentration, total sperm number, semen volume, progressive motility, normal morphology, or total motility between the subgroups categorized by sleep duration, alcohol consumption, and smoking (P>0.05). Participants were classified into three distinct labor types (mental labor, manual labor, and military work or law enforcement). No significant differences were identified in semen volume, sperm concentration, total motility, total sperm number, or normal sperm form between these groups (P>0.05). However, significant variations in progressive motility were found between participants with different occupation types. Furthermore, occupation was positively linked with progressive motility (r=0.100, P<0.05). Workers in sedentary occupations had significantly lower progressive motility than did those in other occupations (Figure 3; P<0.05).

Figure 3 Occupation and progressive sperm motility trends. Horizontal axis: 0= mental labor, 1= manual labor, and 2= military work/law enforcement and other work; vertical axis: sperm progressive mobility.

ROC curve determinations of the predictive value of risk factors for sperm DFI

To assess the predictive factors for sperm DFI, multivariate logistic regression was applied, with DFI ≤30 being the dependent variable and age, sperm concentration, progressive motility, total motility, and normal form being the predictors. The findings demonstrated that these variables were significantly associated with a DFI diagnosis (P<0.05). However, the diagnostic accuracy was relatively low, with cutoff values for age, sperm concentration, progressive motility, total motility, and normal form being 19.5 years, 42.9×10⁶/mL, 33.5%, 44.5%, and 3.31%, respectively; the corresponding sensitivities were 0.977, 0.708, 0.601, 0.853, and 0.593, respectively, while the specificities were 0.002, 0.414, 0.614, 0.363, and 0.779, respectively. The analysis of the ROC curve indicated that the area under the curve (AUC) values ranged from 0.568 to 0.706, demonstrating the good predictive value of age (P=0.03), sperm concentration (P=0.01), progressive motility (P<0.001), total motility (P<0.001), and normal form (P<0.001) for sperm DFI (Figure 4).

Figure 4 Comparison of ROC curves for the risk factors in predicting sperm DFI. DFI, DNA fragmentation index; ROC, receiver operating characteristic.

Discussion

In-depth research on the etiology and intervention targets of RSA suggests a potential link between male sperm quality and RSA incidence. A comprehensive meta-analysis revealed that the partners of patients with RSA had markedly reduced sperm concentration, vitality, and normal form in comparison to those with normal fertility (7). Another study reported significantly higher progressive motility and sperm abnormalities associated with RSA relative to normal controls (14). However, Eisenberg et al. identified no obvious relationship between RSA and semen parameters in their observational study (15). In our study, a comparison of an RSA group and a healthy control group revealed no significant variations in normal sperm morphology, semen volume, concentration, or progressive or total motility (P>0.05). This implies that routine semen parameters are inadequate for accurately assessing male fertility in the examination of the male pathogenic factors for RSA. Therefore, further research is needed to examine the roles and mechanisms of male factors in embryonic development. This would allow for the identification of more specific sperm detection indicators to clarify the complex relationship between sperm quality and RSA.

It is widely recognized that 50% of the genetic material in progeny originates from the father, emphasizing the importance of sperm DNA, the carrier of human genetic material, in facilitating embryonic development and pregnancy outcomes by ensuring complete transmission of genetic information to the offspring (16). Although protamine encloses most sperm DNA, a portion is located at the periphery and is susceptible to oxidative damage. Notably, a considerable proportion of SDF irreparable by the oocyte can result in anomalous embryonic growth and spontaneous abortion following the activation of the paternal genome. In clinical practice, the sperm DFI serves as a key measure for evaluating sperm DNA quality. According to Bhattacharya, DNA integrity in sperm is not significantly associated with sperm parameters (17).

In contrast, other researchers have reported there to be a negative correlation between SDF and routine semen parameters such as sperm morphology, concentration, and progressive motility (18). In line with this, our study found the same negative correlations between sperm DFI and sperm concentration, total motility, the normal form, and progressive motility. This suggests that a higher probability of SDF is associated with inferior-quality sperm parameters. A study has confirmed there to be a strong correlation between sperm DFI and RSA, indicating higher rates of RSA in the spouses of males with a higher DFI than in those with a lower DFI (19). Aitken proposed high DFI as a potential risk factor for RSA (20). In our study, the DFI values were markedly higher in the RSA group relative to the control group. The sperm DFI can thus be used as an indicator of RSA risk.

Lower semen quality and fertility have been observed in older males. In our study, we found that as age increased, there was a decrease in the proportion of morphologically normal sperm, while the DFI value increased. Previous research suggests that aging in males contributes to a lower proportion of normal sperm, with a sharp reduction observed after 35 years of age (21). This may be explained by the diminishing antioxidant capacity of sperm, overproduction of reactive oxygen species (ROS), and age-related rise in oxidative stress resulting in a decrease in the abundance of normal form (22). A few studies have reported there to be a higher likelihood of DNA damage in older men and that advancing age has an adverse effect on sperm chromatin integrity (23,24).

An increase in age may induce excessive ROS production and decrease antioxidant capacity, leading to oxidative DNA injury (25,26). Markers of oxidative stress, such as malondialdehyde (MDA), 8-hydroxy-2'-deoxyguanosine (8-OHdG), and total antioxidant capacity (TAC), have been closely associated with impaired sperm function and reduced DNA integrity (27). It has been reported that high levels of markers for oxidative stress in men are associated with poor semen quality and high DFI (28). These results hint that oxidative stress biomarkers may contribute to explain the biological mechanism of this association between poor sperm quality and RSA. Moreover, older age may alter the permeability of the mitochondrial membrane in the sperm, reducing the mitochondrial membrane potential, promoting DNA fragmentation, and eventually producing a higher DFI (29). Normal sperm form and DNA integrity are essential for sperm development and have profound implications for fertilization, embryonic development, implantation, and pregnancy outcomes. Overall, age is a critical factor for assessing the risk factors associated with fertility issues and unfavorable pregnancy outcomes in males.

Among various lifestyle and environmental factors, occupational exposure has emerged as a significant contributor to male fertility. Exposure to higher temperatures, toxins, and workplace pollutants can reduce sperm concentration, total motility, and abundance of normal form (30). This study demonstrated that sedentary employees experience a decline in progressive motility. It has been previously hypothesized that the physiological temperature of human testes is crucial for normal sperm production and that sedentary work obstructs blood flow in the groin area, resulting in increased testicular temperature. Heat stress hinders sperm production and decreases inhibin B levels, thereby reducing sperm quality (31,32). In contrast, appropriate exercise to reduce sedentary behavior can enhance antioxidant capacity to mitigate the effect of oxidative stress on sperm quality (33). Therefore, a long-term sedentary occupation represents a potential risk factor for decreased progressive motility, thereby increasing the risk of RSA.

In this study, ROC curve analysis confirmed that male age, sperm concentration, progressive motility, total motility, and normal sperm form were independently associated with sperm DFI. Although statistically significant associations were observed, the AUC values for sperm DFI in this study ranged from 0.568 to 0.706, indicating limited utility as a standalone predictive test. These findings suggest that sperm DFI alone may not serve as a highly reliable independent predictor for RSA (34,35). Instead, it should be considered in combination with other clinical parameters—such as age, sperm morphology, and oxidative stress markers—to improve risk stratification and predictive accuracy. Further large-scale, prospective studies are warranted to validate the incremental predictive value of DFI within an integrated risk assessment model for RSA.

This study still has certain limitations. Since this study mainly focused on the fathers and did not consider the maternal variables, including age, hormonal status, uterine abnormalities, or immune mechanisms. This may limit the full adjustment of all possible confounding factors contributing to RSA. Future studies should collect comprehensive data from both parents and use multivariate models to sort out the relative impacts of fathers and mothers on RSA. Additionally, this was a single-center study conducted in southern Anhui, China, which may limit the generalizability of the findings to broader populations with different ethnic, environmental, or lifestyle characteristics. While oxidative stress is recognized as a key factor contributing to sperm DNA damage, direct measurements of oxidative stress biomarkers were not performed, which limits mechanistic insights.

Conclusions

The established correlation between sperm chromatin structural integrity and RSA suggests that a reduced SDF rate may decrease RSA incidence. In addition, age may affect sperm quality, with normal morphology and compromised DNA integrity intensifying as men age. Given the potential adverse influence of older paternal age on fertility, preventive and treatment strategies for RSA should account for age. Furthermore, occupational exposure was also found to be associated with sperm quality. Therefore, the identified risk factors should be integrated into clinical practice to prevent, diagnose, and treat RSA.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-322/rc

Data Sharing Statement: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-322/dss

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-322/prf

Funding: This study was supported by Wuhu Science and Technology Bureau Project (No. 2023jc34), the Scientific Research Program of Wuhu Municipal Health and Wellness Committee (No. WHWJ2023y035), and the Wuhu “Hua Tuo Plan” High-level Talent Cultivation Project (No. 2021[134]).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-322/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study protocol was reviewed and approved by the Institutional Review Board of the Second People’s Hospital of Wuhu (No. SZ2021002). Informed consent was provided by all participants when they were enrolled.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: J. Gray)