Ziyuan Zhou

Lifestyles Associated With Human Semen Quality: Results From MARHCS Cohort Study in Chongqing, China.

AbstractDecline of semen quality in past decades is suggested to be potentially associated with environmental and sociopsychobehavioral factors, but data from population-based cohort studies is limited.The male reproductive health in Chongqing College students (MARHCS) study was established in June 2013 as a perspective cohort study that recruited voluntary male healthy college students from 3 universities in Chongqing. The primary objectives of the MARHCS study are to investigate the associations of male reproductive health in young adults with sociopsychobehavioral factors, as well as changes of environmental exposure due to the relocation from rural campus (in University Town) to metro-campus (in central downtown). A 93-item questionnaire was used to collect sociopsychobehavioral information in manner of interviewer–interviewing, and blood, urine and semen samples were collected at the same time.The study was initiated with 796 healthy young men screened from 872 participants, with a median age of 20. About 81.8% of this population met the WHO 2010 criteria on semen quality given to the 6 routine parameters. Decreases of 12.7%, 19.8%, and 17.0%, and decreases of 7.7%, 17.6%, and 14.7% in total sperm count and sperm concentration, respectively, were found to be associated with the tertiles of accumulated smoking amount. Fried food consumption (1–2 times/wk or ≥3 times/wk vs nonconsumers) was found to be associated with decreased total sperm count (10.2% or 24.5%) and sperm concentration (13.7% or 17.2%), respectively. Coffee consumption was found to be associated with increased progressive and nonprogressive motility of 8.9% or 15.4% for subjects consuming 1–2 cups/wk or ≥3 cups/wk of coffee, respectively. Cola consumption appeared an association with decreased semen volume at 4.1% or 12.5% for 1–2 bottles/wk or ≥3 bottles/wk.A cohort to investigate the effects of environmental/sociopsychobehavioral factors act on semen quality was successfully set up. We found smoking, coffee/cola/fried foods consumption to be significantly associated with semen quality from the baseline investigation.

Anogenital distance is associated with serum reproductive hormones, but not with semen quality in young men

STUDY QUESTION Is anogenital distance associated with semen parameters and serum reproductive hormone levels in males? SUMMARY ANSWER Anogenital distance is associated with serum reproductive hormones, but not with semen quality. WHAT IS KNOWN ALREADY Epidemiological studies have suggested that anogenital distance (AGD) may be associated with testicular dysfunction in adult men. However, the role of AGD in estimating male reproductive function remains unclear. STUDY DESIGN, SIZE, DURATION We examined the associations between AGD and semen parameters and reproductive hormones levels in 656 young college students in a Male Reproductive Health in Chongqing College Students (MARHCSs) cohort study in June of 2014. PARTICIPANTS/MATERIALS, SETTING, METHODS In this study, two variants of AGD (AGDAP and AGDAS) were measured in 656 university students. Serum levels of testosterone (T), estradiol (E2), progesterone (P), prolactin (PRL), luteinizing hormone (LH), follicle-stimulating hormone (FSH), sex hormone-binding globulin (SHBG) and inhibin-B; and semen quality outcomes, including semen volume, sperm concentration, total sperm number, sperm progressive motility, total motility and morphology, were assessed. The associations between AGD and semen parameters/reproductive hormones levels were analyzed using multiple regression analysis. MAIN RESULTS AND THE ROLE OF CHANCE Both AGDAS and AGDAP were not associated with any semen parameters. In the non-parametric correlation analysis, AGDAP were correlated with sperm progressive motility and reproductive hormones of E2, testosterone, SHBG and the testosterone/LH ratio. However, body mass index (BMI) also significantly correlated with serum testosterone ( ITALIC! r = -0.216, ITALIC! P = <0.0001) and SHBG ( ITALIC! r = -0.229, ITALIC! P = <0.001). In the multiple regression models, AGDAP was negatively associated with the serum E2 level (95% CI, -0.198 to -0.043; ITALIC! P = 0.002) and positively associated with the ratio of T/E2 (95% CI, 0.004-0.011; ITALIC! P = 0.001) after an adjustment for BMI and other confounders. LIMITATIONS, REASONS FOR CAUTION Using only a single semen sample to predict male reproductive function over a longer period is a potential limitation of the present study. The other limitation is the cross-sectional nature of the study design. Longitudinal data from an extended follow-up on a large cohort would be more definitive. WIDER IMPLICATIONS OF THE FINDINGS Our results do not support previous studies where AGD is associated with male semen quality. The utility of AGD in predicting reproductive outcomes in adult males should thus be considered prudently. STUDY FUNDING/COMPETING INTERESTS This study was supported by the Key Program of Natural Science Funding of China (no. 81130051), Young Scientist Program of NSFC (no. 81502788) and the National Scientific and Technological Support Program of China (no. 2013BAI12B02). None of authors had any competing interests to declare.

Phthalate exposure, even below US EPA reference doses, was associated with semen quality and reproductive hormones: Prospective MARHCS study in general population

BACKGROUND Environment-Protection-Agency Reference Doses (EPA RfDs) for phthalate intakes are based on limited evidence, especially regarding low-dose male-reproductive toxicity. This study investigates the association between phthalate exposure and semen parameters and reproductive hormones in a general population with low phthalate exposure compared to the EPA RfDs. METHODS The MARHCS (Male-Reproductive-Health-in-Chongqing-College-Students) cohort recruited 796 male students, who experienced a relocation of campuses and shifting environmental exposure. Urine, semen and blood before and after the relocation was collected and investigated for: (1) the associations between 13 urinary phthalate metabolites and 11 semen/hormone outcomes (five semen parameters including semen volume, sperm concentration, total sperm number, progressive motility, normal morphology) and six serum reproductive hormones including estradiol, follicle-stimulating hormone, luteinizing hormone, prolactin, progesterone, testosterone; (2) re-analysis of the metabolite-outcome associations in the subjects with estimated phthalate intakes below the RfDs; (3) a change in phthalate metabolites and change in semen/hormone outcomes after the relocation; (4) the association between these changes. RESULTS (1) All but two semen/hormone outcomes were associated with at least one phthalate metabolite, e.g., each quartile monoethyl phthalate was associated with a 5.3%, 5.7% and 2.6% decrease of sperm concentration, total sperm number and progressive motility respectively. (2) In the subjects with phthalate intakes below the RfDs, these metabolite-outcome associations remained significant. (3) All metabolites except mono(2-ethylhexyl) phthalate declined after relocation (P<0.001 respectively); at the same time, semen volume, normal morphology, estradiol and luteinizing hormone increased (by 5.9%, 25.0%, 34.2% and 10.0%) and testosterone decreased (by 7.0%). (4) The changes in semen volume, normal morphology, estradiol and testosterone, but not the change in luteinizing hormone after relocation, were associated with the changes in the phthalate metabolites. CONCLUSIONS Phthalate exposure is associated with interrupted semen quality and reproductive hormones in the human population even with a dose given below the RfDs. These effects, however, may only partially revert back when exposure decreases, thus emphasizing the urgency of stricter phthalate administration.

Exposures to Atmospheric PM10 and PM10–2.5 Affect Male Semen Quality: Results of MARHCS Study

Studies have shown that the effects of ambient particulate matter (PM) may be related to particles size. However, results on the relationships between different PM and reproductive health are controversial. To explore the impacts of various PM fractions on male reproductive health, a total of 796 eligible subjects recruited in 2013 baseline investigation. In addition, there were 656 (82.4%) and 568 (71.3%) subjects participated follow-up surveys in 2014 and 2015, respectively. We used multivariable regression analysis and mixed-effect model to investigate the associations between air pollutants PM10, PM10-2.5, and PM2.5 exposures and semen quality, sperm DNA fragmentation and serum reproductive hormones of subjects. In the preliminary regression analysis, PM10, PM10-2.5, and PM2.5 exposure all associated with sperm concentration, morphology, sperm high DNA stainability (HDS), serum estradiol and testosterone levels. However, in mixed models, we only found that PM10 exposure were negatively associated with sperm normal morphology (95% CI: -14.13, -24.47) but positively associated with sperm progressive motility (95% CI: 23.00, 8.49), and PM10-2.5 exposure was inversely associated with sperm concentration (95% CI: -9.06, -27.31) after multiplicity adjustment. Our results provide the evidence that air PM10 and PM10-2.5 exposures, not PM2.5, are risk factors of semen quality.

Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer

Colorectal cancer (CRC), as a result of a multistep process and under multiple factors, is one of the most common life-threatening cancers worldwide. To identify the “high risk” populations is critical for early diagnosis and improvement of overall survival rate. Of the complicated genetic and environmental factors, which group is mostly concerning colorectal carcinogenesis remains contentious. For this reason, this study collects relatively complete information of genetic variations and environmental exposure for both CRC patients and cancer-free controls; a multimethod ensemble model for CRC-risk prediction is developed by employing such big data to train and test the model. Our results demonstrate that (1) the explored genetic and environmental biomarkers are validated to connect to the CRC by biological function- or population-based evidences, (2) the model can efficiently predict the risk of CRC after parameter optimization by the big CRC-related data, and (3) our innovated heterogeneous ensemble learning model (HELM) and generalized kernel recursive maximum correntropy (GKRMC) algorithm have high prediction power. Finally, we discuss why the HELM and GKRMC can outperform the classical regression algorithms and related subjects for future study.

Mitochondrial Biomarkers Reflect Semen Quality: Results from the MARCHS Study in Chongqing, China

Unexplained infertility requires that more sensitive and mechanism-based biomarkers should be developed and used independently of or in addition to conventional semen parameters for an infertility diagnosis. In the present study, semen samples were collected from young men participating in the Male Reproductive Health in Chongqing College students (MARCHS) cohort study in the follow-up stage in 2014. Conventional semen parameters were measured in all 656 participants, whereas sperm mitochondrial membrane potential (MMP), mitochondrial DNA copy number (mtDNAcn), mtDNA integrity and apoptotic parameters were measured among 627, 386, 362, and 628 participants, respectively. We found that sperm MMP was significantly positively correlated with all of conventional semen parameters including semen volume (r = 0.090, p = 0.025), sperm concentration (r = 0.301, p<0.01), total sperm count (r = 0.324, p<0.01), and progressive motility (r = 0.399, p<0.01); sperm MMP was also negatively correlated with Annexin V+ sperm (r = -0.553, p<0.01); mtDNAcn was significantly negatively correlated with sperm concentration (r = -0.214, p<0.01), total sperm count (r = -0.232, p<0.01), and progressive motility (r = -0.164, p = 0.01); mtDNA integrity was also significantly positively correlated with sperm concentration (r = 0.195, p<0.01), total sperm count (r = 0.185, p<0.01), and progressive motility (r = 0.106, p = 0.043). After adjusting for potential confounders, these relationships remained significant. Furthermore, we explored the potential effects of lifestyles on such mitochondrial biomarkers and found that the current drinkers displayed a higher level of sperm MMP; additionally, mt DNAcn was increased with age. The results indicated that certain mitochondrial biomarkers could serve as predictors of semen quality in a general population, and the study provides a baseline for the effects of population characteristics and lifestyles on such mitochondrial markers.

Developing a robust colorectal cancer (CRC) risk predictive model with the big genetic and environment related CRC data

Currently, colorectal cancer (CRC) already becomes one of the most common cancers worldwide. Though the prognosis of CRC patients is dramatically improved due to the new advanced treatments and medical improvements, the 5-year survival rate for the CRC patient is still low. Thus, we hypothesize that CRC may result from the complicated reasons related to both genetic and environmental factors. For this reason, this study collects such big CRC data with information of genetic variations and environmental exposure for the CRC patients and cancer-free controls that are employed to train and test the predictive CRC model. Our results demonstrate that (1) the explored genetic and environmental biomarkers are validated to cause the CRC by the manually reviewed experimental evidences, (2) the model can efficiently predict the risk of CRC after parameter optimization by the big CRC-related data, (3) our innovated generalized kernel recursive maximum correntropy(GKRMC) algorithm has high predictive power. Finally, we discuss why the GKRMC can outperform the classical regression algorithms and the related future study.

Exploring the risk dietary factors for the colorectal cancer

The research target is to explore the key biomarkers of colorectal cancer by studying the impact of dietary factors on colorectal cancer. We first employed statistical methods to preprocess experimental data. Then, relief algorithm is employed to extract key features in the dietary data set. Finally, supporting vector machine (SVM) is used to classify the data set and compute classification accuracy. The results demonstrated that vegetables, seafood, eggs and milk have great impacts on the colorectal cancer. Therefore, we concluded that integrating relief algorithm with SVM model can explore the key biomarkers for colorectal cancer, while the investigation of the interactions among these features needs further research.