It should be noted that all the publications on this topic investigated only routine semen parameters. Although these parameters have been found to be helpful in diagnosing male infertility, their power to evaluate a man's fertility is limited, as some people who have normal semen parameters can still be infertile (Bonde et al ., 1998 ; Guzick et al ., 2001 ; Van Der Steeg et al ., 2011 ). Sperm chromatin integrity has been documented as an independent predictor of male infertility (Bungum et al ., 2012 ). Recently, certain indirect and direct clues have suggested that sleep duration can affect chromatin integrity, i.e. sleep restriction changed the level of reactive oxygen species which were important interruptors of chromatin structure (Alvarenga et al ., 2015 ; Lobascio et al ., 2015 ; Mathangi et al ., 2012 ; Novotny et al ., 2013 ; Villafuerte et al ., 2015 ). Moreover, a study on 26 human volunteers reported that sleep restriction disrupted the gene expresson of both circadian rhythm and the oxidative stress pathway, and chromatin modification was found to be affected in whole blood (Moller‐Levet et al ., 2013 ). Nevertheless, to our knowledge, the association between sleep duration and sperm chromation integrity has not been reported to date.

Sleep is necessary for health and wellbeing, yet modern industrialized societies have become sleep‐deprived. It is common knowledge that people are getting 1–2 h less sleep per night compared with their ancestors (Roenneberg, 2013 ). According to previous publications, either restricted or excessive sleep duration is associated with increased disease risk, including obesity, diabetes, hypertension, ulcerative colitis and total mortality (Ananthakrishnan et al ., 2014 ; Cappuccio et al ., 2008 ; Lauderdale et al ., 2008 ; Liu et al ., 2013 ). However, research into the relationship between sleep duration and semen quality is just beginning. Recently, studies on animals showed that sleep deprivation will lead to a decrease in the number of live sperm and sperm motility (Alvarenga et al ., 2015 ; Choi et al ., 2016 ). Further, an inverse U‐shaped association between sleep duration and semen parameters was found in 796 young males, thus indicating that sleep duration may play a pivotal role in the regulation of male reproductive health (Chen et al ., 2016 ).

As we had the repeated‐measurement data from three surveys and an additional potential confounder was measured in later surveys, we first analysed the association of sleep duration and chromatin integrity in the baseline data and then in the follow‐up data. Further, concerning the association between total sperm number and sleep duration, the association between sleep duration and sperm count with normal/abnormal chromatin integrity was also analysed separately.

As the sperm chromatin integrity parameters were of skewed distribution, a Jonckheere–Terpstra test was performed as a univariate analysis. The association was analysed using multivariate linear regression, and potential confounders were chosen according to previous publications on sleep and semen quality (Chen et al ., 2016 ; Jensen et al ., 2013 ). Sleep duration may be associated with lifestyle factors such as tobacco smoking, alcohol consumption and the intake of tea, cola and coffee. Some covariates such as age, BMI and abstinence time were also adjusted for. Sleep disturbance (as PSQI scores) was adjusted for in the follow‐up data, as it was suggested to be associated with sleep duration and semen quality (Jensen et al ., 2013 ). To improve the skewed distribution, the chromatin integrity parameters were transformed into a logarithmic scale before analysis and then back‐transformed as the percentage change, which indicated the relative difference of chromatin integrity parameters for the subjects with different sleep duration.

As sleep duration was in inverse U‐shaped association with sperm chromatin integrity, two methods were used to investigate the association. (1) Sleep duration was categorized into an ordinal variable with an 0.5‐h increment, e.g. 6.5–7, 7–7.5, 7.5–8 h day −1 , etc. The data were separated into two parts, i.e. sleep duration ≤ 7.5 and sleep duration > 7 h day −1 . An association analysis was performed respectively. (2) The sleep duration was transformed into a distance from 7 to 7.5 h day −1 (see Supporting information, Fig. S1 ), and the association between the distance and the chromatin integrity was explored. The 7–7.5‐h day −1 sleep duration was used as the reference in the above‐mentioned analyses, because it was reported to be the turning‐point in the inverse U‐shaped association between sleep duration and other semen parameters, and was similar to the turning‐point in the association between sleep duration and many other phenotypes (Ananthakrishnan et al ., 2014 ; Heckman et al ., 2017 ).

The semen sample was diluted with phosphate‐buffered saline to a concentration of 4 × 10 6 /mL and 40 μL diluted semen sample was mixed with 200 μL 0.6% low melting‐point agarose gel (Sigma Aldrich Co., St Louis, MO, USA). The mixture was then added to a slide covered with 1% normal melting‐point agarose gel before assay. The slide was coverslipped and kept at 4 °C for 15 min. The coverslip was removed and the slide was submersed in lysing solution at 4 °C for 1 h. The slide was then treated with enzyme solution at 37 °C for 16 h and the slide was immersed in alkaline electrophoresis solution for 20 min, leading to the unwinding of the double‐strand DNA. The slide was electrophoresed at 4 °C for 8 min, 22 V (0.714 v cm −1 ) and 160 mA. The slide was immersed in neutralizing solution for 10 min and fixed with ethanol for 10 min. The slide was then air‐dried and stained with ethidium bromide (20 mg mL −1 ). An inverted fluorescence microscope (ECLIPSE TE2000‐S; Nikon Corporation, Tokyo, Japan) was used to examine the slide at ×200 magnification. All reagents, such as lysing and enzyme solutions, were prepared according to Han et al . ( 2011 ). Tail length and the percentage of tail DNA were evaluated using casp software ( http://casplab.com/ , version 1.2.2). To ensure the validity of the measurements, a standard sample was tested within each batch of samples. Fig. 1 c shows an example of the Comet assay.

Results of Sperm Chromatin Structure Assay (SCSA) and Comet assay. (a) Scatterplot, x ‐axis (FL4): red fluorescence with a scale from 0 to 1024; y‐ axis (FL1): green fluorescence with a scale from 0 to 1024. The sperm above the horizontal line have high DNA stainability (HDS), which reflects immatureness of sperm chromatin. HDS equals the percentage of sperm above this line. For example, HDS = 7.15%. (b) Histogram of DNA Fragmentation Index (DFI). Total % DFI equals the percentage of sperm outside the main sperm population. For example, total % DFI = 23.7%. (c) The measurement frame of Comet assay. It has two subframes: one for comet and the other for background (b). The frame is drawn on the screen and analysed by CASP software automatically. Tail DNA % equals the intensity ratio between tail and whole comet. Tail length (a) equals the distance between the right‐most point of head and tail.

Fresh semen samples were diluted to a concentration of 2 × 10 6 mL −1 in Tris‐NaCl‐ethylenediamine tetraacetic acid buffer (TNE buffer. Diluted semen samples (50 μL) were thawed at 37 °C and treated with 100 μL acid detergent (vibrated for 30 s), then stained with 300 μL acridine orange (AO; Invitrogen, Carlsbad, CA, USA) staining solution. AO was intercalated into the DNA strand in this process. Subsequently, semen samples were loaded into the flow cytometer (Beckman FC 500 MCL/MPL; Beckman Coulter, Brea, CA, USA) and 10 000 events were tested for each sample. When excited by a blue light, the AO intercalated in double‐strand DNA emits green fluorescence, whereas the AO intercalated with single‐strand DNA emits red fluorescence. DFI was defined as the ratio between red and total (red+green) fluorescence intensity. Total % DFI was defined as the percentage of sperm outside the main sperm population. High DNA stainability (HDS) was the percentage of sperm with high green fluorescence. All reagents, such as the TNE buffer, acid detergent and AO staining solution, were prepared according to Evenson et al . (2013). To ensure the validity of the measurements, a standard sample was tested when every 10–15 samples were measured. SCSA and Comet assay were performed within 3–6 months after storage by the same work‐group according to the same protocol. Each sample underwent one freeze–thaw cycle. Fig. 1 a,b shows an example of SCSA.

We used a modified Munich Chronotype Questionnaire (MCTQ) for the measurement of sleep duration. We calculated sleep duration according to information regarding certain time‐points, including the time needed to get ready for sleep (differentiated from the time to go to bed), the duration from wake to sleep after someone went to bed and the time to wake (differentiated from the time to get out of bed). During the follow‐ups, sleep disturbance was also measured using the Pittsburgh Sleep Quality Index (PSQI). A higher PSQI total score indicated worse sleep quality (Buysse et al ., 1989 ; Liu et al ., 1996 ). Further, information on potential confounders such as age, abstinence time, tobacco smoking, alcohol consumption and intake of coffee, coke and tea was also obtained via the questionnaire.

The male college students were recruited from the Chongqing University town in China. Volunteers with any abnormal situation in their urogenital system and volunteers with abstinence time less than 2 days or longer than 7 days were excluded. In the end, 872 volunteers participated in our survey and 796 of them were eligible from the baseline survey. A total of 656 (82.4%) and 568 (71.4%) of these subjects participated in the follow‐up surveys conducted in 2014 and 2015.

The Male Reproductive Health in the Chongqing College Students (MARHCS) cohort was established to investigate the effect of environmental factors and socio‐psycho‐behavioural factors on male reproductive health. We conducted the baseline survey in June 2013 and the follow‐up surveys (twice) during the same season (May–June) in 2014 and 2015. At each visit, the subjects were asked to provide semen samples, undergo physical examination and complete a composited questionnaire, including responses regarding sleep‐related issues. The study was approved by the Ethics Committees of the Third Military Medical University. We also received signed informed consent from each participant.

HDS was an index that represented the proportion of sperm with abnormal chromatin, and it was reported previously that sleep duration was associated with total sperm numbers, so we analysed further whether the sperm count with abnormal chromatin (Sa) and the count of sperm with normal chromatin (Sn) were associated with sleep duration. Sa was calculated as the total sperm number multiplied by HDS; Sn was calculated as the total sperm number minus Sa. We found that both Sa and Sn were associated with sleep duration in an inverse U‐shaped pattern (Supporting information, Table S1 ). On average, each hour of sleep duration distance was associated with an 18.7% (95% CI: 10.4%, 26.2%, P < 0.0001) decrease of Sa and a 9.6% (95% CI: 3.2%, 15.6%, P = 0.004) decrease of Sn. According to the method described by Zeka et al . ( 2006 ), the decrease in Sa was larger than the decrease in Sn (95% CI: −3.1, 21.1, P = 0.07). This was consistent with the result that sleep duration distance was associated negatively with HDS.

Many people were woken artificially and thus had a sleep duration they did not prefer. We investigated further whether the interruption of sleep duration biased the association between sleep duration and the chromatin integrity of sperm. At baseline, the subjects were asked whether they were awakened by a clock on work days or free days. A total of 496 subjects replied that they used clocks either on work days or free days, and 294 replied that they never used them. HDS, total % DFI and the Comet assay parameters were not significantly different between the two groups (Supporting information, Table S2 ). When clock use was adjusted for, the associations between sleep duration and HDS remained significant in the baseline data ( P = 0.008) and the follow‐up data ( P = 0.036). In the mixed‐model analysis, each hour of sleep duration distance was associated with a 9.3% (95% CI: 0.9%, 17.1%, P = 0.032) decrease of HDS in the clock users and a 9.8% (95% CI: 0.9%, 17.9%, P = 0.038) decrease of HDS in the non‐clock users.

To represent comprehensively the association between sleep duration and HDS, we transformed the sleep duration into the distance from 7.0 to 7.5 h day −1 sleep. After adjusting for potential confounders, a negative association was observed between sleep duration distance and HDS: each hour distance from 7 to 7.5 day −1 sleep duration was associated with a 17.6% decrease of HDS (Table 3 , 95% CI: 4.9%, 28.7%, P = 0.008). We applied the same analysis to the follow‐up data from the 2014 survey, and again observed a significant association between HDS and sleep duration distance ( P = 0.049). Additional adjustment for sleep disturbance (PSQI score) did not influence the results substantially (Table 3 , P = 0.036). Further, we integrated the data of three surveys using a multilevel model; the result was similar with the separate results of each survey: each hour of sleep duration distance was associated with an 8.2% decrease of HDS (95% CI: 2.2%, 13.8%, P = 0.009, Table 3 ).

Association between high DNA stainability (HDS) of sperm and sleep duration: multivariate analysis in the baseline survey. The association between HDS and sleep duration was analysed by linear regression, adjusted for age, body mass index, abstinence time, tobacco smoking, alcohol drinking, intake of tea, coffee and cola. To improve the skewed distribution of HDS, it was transformed into logarithmic scale before analyses and then back‐transformed into percent change. Taking the HDS of the subjects with 7–7.5 h day −1 sleep as the reference (solid triangle), the results indicated the percent change in HDS (solid circle) for the subjects with a certain sleep duration. The error bars indicated the 95% confidential interval. P ‐values were also given, assuming that sleep duration below 7–7.5 h day −1 and sleep duration above 7–7.5 h day −1 were, respectively, in linear association with HDS.

In the baseline data, we found an inverse U‐shaped association between HDS and sleep duration. The peak of HDS was found in the 7–7.5‐h day −1 sleep group (Table 2 ): in subjects with sleep duration ≤ 7.5 h day −1 , the sleep duration was associated positively with HDS ( P = 0.008); in subjects with sleep duration > 7.0 h day −1 , the sleep duration was associated negatively with HDS ( P = 0.008). For the other chromatin integrity parameters, no significant differences were found for those with different sleep duration.

The subjects were all young, with a median age of 20 years. The median BMI in our study was 20.9 kg m −2 . Approximately 2.6% of the subjects were obese in this population (criteria for the Chinese population: BMI ≥ 28). Approximately half the subjects did not consume tobacco, alcohol and tea. The median of the entire sleep duration was 7.8 h (25th and 75th percentiles: 7.3 and 8.3 h, respectively) (Table 1 ). No significant difference in sperm chromatin integrity or sleep duration was found between the follow‐up and lost subjects (data not shown).

Discussion

Based on a population of 796 male college students, for the first time we found an inverse U‐shaped association between sleep duration and HDS. The phenomenon was observed repeatedly in the baseline and follow‐up surveys. Our results reinforced the hypothesis that sleep behaviour is associated with semen quality, emphasizing further the necessity to investigate comprehensively the effect of sleep behaviour on male reproductive health.

Higher HDS means there is a lack of normal exchange from histones to protamines, a process important for chromatin condensation (Evenson, 2013). Studies that focus on the clinical utility of SCSA parameters are growing. Some studies have reported that higher HDS was correlated with lower progressive motility, normal morphology rate of sperm, poorer fertilization rates and pregnancy with assisted reproductive techniques (Nijs et al., 2009; Novotny et al., 2013; Payne et al., 2005; Virro et al., 2004; Zini et al., 2009). It is reported that the HDS > 15% indicates an adverse clinical consequence (Virro et al., 2004). However, the results from different studies have not always been consistent. Buck Louis et al. (2014) did not find an association between HDS and time to pregnancy. It is not completely clear what HDS represents regarding reproductive function, but it can be regarded as a potential marker of sperm chromatin integrity when applied to assisted reproduction. The association between sleep duration and HDS in our study indicates that there could be an alteration in chromatin integrity of sperm when a man's sleep duration changes.

The HDS was relatively low in the young and healthy subjects in the present study, but it varied by one‐third (3.0 versus 4.8%), depending on sleep duration. It is sensible, therefore, to anticipate that this effect could lead to a more substantial change in the sperm of more susceptible individuals, such as elderly or subfertile males. Unlike HDS, total % DFI and the parameters of the Comet assay indicate DNA strand breakage. In the present study, however, no association was found between sleep duration and total % DFI or the Comet assay parameters. The negative results for both assays were mutually supportive, thereby suggesting that unsuitable sleep duration was not associated with DNA breakage.

It is accepted widely that the association of sleep duration and hazardous phenotypes is usually U‐shaped (Ananthakrishnan et al., 2014; Liu et al., 2013). Regarding male reproductive health, a previous paper reported an inverse U‐shaped association between sleep duration and total sperm numbers. However, in the same population, the present study showed that either longer or less sleep duration was associated with lower HDS. The simultaneous associations of sleep duration with HDS and total sperm count are not attributable to the correlation between these two semen parameters (P = 0.732 using Spearman's correlation). These two parameters are thought to represent different aspects of fertility. HDS indicates the proportion of incompletely differentiated sperm in the epididymis. For 7–7.5‐h day−1 sleep this proportion increases, while the normal sperm count also reaches its peak. This phenomenon is somewhat unexpected, but in other sleep‐related studies there is already evidence that the same duration may have distinct effects on different aspects of function (Zohar et al., 2005), revealing a complex association between sleep duration and male reproductive health that should be interpreted with caution. Whether sleep duration modifies the success pregnancy rate and the development of offspring deserves further investigation in future.

Currently, the mechanism of the sleep–semen association is not clear. The role of reproductive hormones may be excluded, because they were not associated with sleep duration in this population. This result was also confirmed by Jensen et al. (2013). The circadian clock may be an important factor that induces the sleep–semen association. The circadian clock exists in both the brain and peripheral tissues, including the testis (Archer et al., 2014). It has been found to be necessary for production of mature spermatozoa and fertility in animal models (Alvarez et al., 2008; Beaver et al., 2002; Tobback et al., 2012). More importantly, the circadian genes could catalyze the chromatin modifications (Doi et al., 2006). As an important regulator of circadian genes, improper sleep behaviour is likely to disrupt the circadian genes, resulting in adverse outcomes in the male reproductive system (Boden et al., 2013; Gamble et al., 2013). Scrotal heating could also be involved. Higher temperature in the scrotal area has been reported to induce an increase of HDS (Ahmad et al., 2012; Rao et al., 2016). The scrotal temperature fluctuates with diurnal variation and becomes higher at night (Lerchl et al., 1993). Hence, sleep behaviour may affect the scrotal temperature by regulating the circadian rhythm or the warm circumstances in bed. These hypotheses need in‐depth validation in future studies.

This study has several strengths. First, we applied MCTQ to measure the subjects' sleep duration. The traditional methods of sleep duration assessment use direct questions requiring the subjects to recall the length of sleep. It is easy to induce a misunderstanding of the correct concept of sleep duration, which can lead to systemic error (Lauderdale et al., 2008). MCTQ avoided this shortcoming by recording the time‐point of sleep behaviours that were defined and differentiated clearly from the incorrect concepts that could lead to misunderstanding. It has also been shown to be an accurate tool to assess sleep duration (Kühnle, 2006). Secondly, we used both SCSA and Comet assays to detect sperm chromatin integrity. The Comet assay is a classical method used to detect DNA breakage. SCSA is a developed method used to detect both DNA damage and chromatin maturation. It can analyse thousands of cells without objective analysis (Tamburrino et al., 2012). It was standardized by Evenson, and its result is reproducible and robust (Evenson, 2013). Thirdly, we used the data from baseline survey and follow‐up surveys to investigate the sleep–HDS association separately and found similar results. This could help us to minimize the possibility of chance error. Further, the subjects in this study had similar demographic characteristics and lived in a similar environment, hence the bias caused by certain important potential confounders, such as age, could be excluded. The three surveys were also completed in the same season, thus avoiding any seasonal influence on the semen parameters.

There were several limitations to this study. First, the present study was a cross‐sectional study. The possibility of reverse causation could not be ruled out, although it seems unlikely that semen quality would affect sleep duration. Alteration in sleep duration may be an indicator of stress or other diseases. However, the subjects were young college students and should have no idea of their personal fertility. It was unlikely that they had suffered psychological stress from infertility. Further, only four and five individuals, respectively, took sleeping pills in the follow‐up surveys of 2014 and 2015, and those doses were extremely low. Thus, sleep‐related medication was not likely to be a bias for our results. Studies with higher strength for causal inference, such as randomized controlled trials, would be necessary to validate such causality in the future. Secondly, no correction for multiple comparisons was performed. In fact, we investigated sleep duration using only four parameters of chromatin integrity. The inverse U‐shaped association with HDS (P < 0.01) would remain significant even if Bonferroni's correction was performed (threshold of significance = 0.05/4 = 0.0125). Thirdly, some potential confounders, such as socioeconomic status, were not included. Further studies are thus warranted to validate our findings. Fourthly, the subjects in the present study were young and healthy. Those individuals with reproductive diseases and other severe diseases were excluded which may, of course, limit the generalizability of our results to other males with different health statuses.

In conclusion, we found an inverse U‐shaped association between sleep duration and sperm HDS. Subjects with sleep duration between 7 and 7.5 h day−1 had the highest proportion of chromatin‐abnormal sperm. This finding, in combination with the inverse U‐shaped association between sleep duration and total sperm number, indicates usefully the complexity of the association between sleep duration and male reproductive health. Further studies are needed to validate our findings and investigate the mechanism underlying this association.