Multilevel approach to male fertility by machine learning highlights a hidden link between haematological and spermatogenetic cells.

BACKGROUND: Male infertility represents a complex clinical condition requiring an accurate multilevel assessment, in which machine learning technology, combining large data series in non-linear and highly interactive ways, could be innovatively applied. METHODS: A longitudinal, observational, retrospective, big data study was carried out, applying for the first time the ML in the context of male infertility. A large database including all semen samples collected between 2010 and 2016 was generated, together with blood biochemical examinations, environmental temperature and air pollutants exposure. First, the database was analysed with principal component analysis and multivariable linear regression analyses. Second, classification analyses were performed, in which patients were a priori classified according to semen parameters. Third, machine learning algorithms were applied in a training phase (80% of the entire database) and in a tuning phase (20% of the data set). Finally, conventional statistical analyses were applied considering semen parameters and those other variables extracted during machine learning. RESULTS: The final database included 4239 patients, aggregating semen analyses, blood and environmental parameters. Classification analyses were able to recognize oligozoospermic, teratozoospermic, asthenozoospermic and patients with altered semen parameters (0.58 accuracy, 0.58 sensitivity and 0.57 specificity). Machine learning algorithms detected three haematological variables, that is lymphocytes number, erythrocyte distribution and mean globular volume, significantly related to semen parameters (0.69 accuracy, 0.78 sensitivity and 0.41 specificity). CONCLUSION: This is the first machine learning application to male fertility, detecting potential mathematical algorithms able to describe patients' semen characteristics changes. In this setting, a possible hidden link between testicular and haematopoietic tissues was suggested, according to their similar proliferative properties.

Semi-annual seasonal pattern of serum thyrotropin in adults.

Circannual rhythmicity in thyroid-stimulating hormone (TSH) secretion is proposed, whereas evidences on seasonal peripheral thyroid hormones' fluctuation are contradictory. This study was designed to evaluate hypothalamic-pituitary-thyroid (HPT) seasonal secretion pattern using a big data approach. An observational, retrospective, big data trial was carried out, including all TSH measurements performed in a single laboratory between January 2010 and December 2017. A large dataset was created matching TSH data with patients' age, gender, environmental temperature exposure, and free triiodothyronine (fT3) and free thyroxine (fT4) when available. The trend and seasonal distributions were analysed using autoregressive integrated moving average models. A total of 1,506,495 data were included in the final database with patients mean age of 59.00 ± 18.44 years. The mean TSH serum levels were 2.08 ± 1.57 microIU/mL, showing a seasonal distribution with higher levels in summer and winter seasons, independently from age, gender and environmental temperatures. Neither fT3 nor fT4 showed a seasonal trend. TSH seasonal changes occurred independently from peripheral thyroid hormone variations, gender, age and environmental temperatures. Although seasonal TSH fluctuation could represent a residual ancestral mechanism to maintain HPT homeostasis, the underlying physiological mechanism remains unclear and specific studies are needed to clarify its impacting role in humans.

Seasonal Changes of Serum Gonadotropins and Testosterone in Men Revealed by a Large Data Set of Real-World Observations Over Nine Years.

Environmental rhythmicity is able to affect the hypothalamic-pituitary-gonadal axis in several animals to achieve reproductive advantages. However, conflicting results were obtained when assessing the environmental-dependent rhythmicity on reproductive hormone secretion in humans. This study was designed to evaluate seasonal fluctuations of the main hormones involved in the hypothalamic-pituitary-gonadal axis in men, using a big data approach. An observational, retrospective, big data trial was carried out, including all testosterone, luteinizing hormone (LH) and follicle-stimulating hormone (FSH) measurements performed in a single laboratory between January 2010 and January 2019 using Chemiluminescent Microparticle Immunoassay. Subjects presenting any factor interfering with the hypothalamic-pituitary-gonadal axis were excluded. The trend and seasonal distributions were analyzed using autoregressive integrated moving average (ARIMA) models. A total of 12,033 data, accounting for 7,491 men (mean age 47.46 ± 13.51 years, range 18-91 years) were included. Testosterone serum levels (mean 5.34 ± 2.06 ng/dL, range 1.70-15.80 ng/dL) showed a seasonal distribution with higher levels in summer and a direct correlation to environmental temperatures and daylight duration. LH levels (mean 4.64 ± 2.54 IU/L, range 1.00-15.00 IU/L) presented 2 peaks of secretion in autumn and spring, independently from environmental parameters. FSH levels (mean 5.51 ± 3.24 IU/L) did not show any seasonal distribution. A clear seasonal fluctuation of both LH and testosterone was demonstrated in a large cohort of adult men, although a circannual seasonality of hypothalamic-pituitary-gonadal hormones in humans could be not strictly evolutionarily required. Testosterone seasonality seems independent from LH fluctuations, which could be regulated by cyclic central genes expression, and more sensible to environmental temperatures and daylight duration.

Seasonal variation of semen parameters correlates with environmental temperature and air pollution: A big data analysis over 6 years.

BACKGROUND: Male fertility is progressively declining in many developed countries, but the relationship between male infertility and environmental factors is still unclear. OBJECTIVES: To assess the influence of environmental temperature and air pollution on semen parameters, using a big-data approach. METHODS: A big data analysis of parameters related to 5131 men, living in a province of Northern Italy and undergoing semen analyses between January 2010 and March 2016 was performed. Ambient temperature was recorded on the day of analysis and the 90 days prior to the analysis and the average value of particulate matter (PM) and NO2 in the year of the test. All data were acquired by geocoding patients residential address. A data warehouse containing 990,904,591 data was generated and analysed by multiple regressions. RESULTS: 5573 semen analyses were collected. Both maximum and minimum temperatures registered on the day of collection were inversely related to total sperm number (p < .001), non-progressive motility (NPrM) (p < .005) and normal forms (p < .001). Results were confirmed considering temperature in the 30 and 60 days before collection, but not in the 90 days before collection. Total sperm number was lower in summer/autumn (p < .001) and was inversely related with daylight duration (p < .001). PM10 and PM2.5 were inversely related to PrM (p < .001 and p < .005) and abnormal forms (p < .001). CONCLUSIONS: This is the first evaluation of the relationship between male fertility-related parameters and environment using a big-data approach. A seasonal change in semen parameters was found, with a fluctuation related to both temperature and daylight duration. A negative correlation between air pollution and semen quality is suggested. Such seasonal and environmental associations should be considered when assessing changes of male fertility-related parameters over time.

Universal Screening Program in Pregnant Women and Newborns at-Risk for Sickle Cell Disease: First Report from Northern Italy.

The implementation of screening programs for early detection of patients with sickle cell disease has become necessary in Italy as a result of the high rate of migration from areas with a high prevalence of the disease (Sub-Saharan Africa, Middle East and the Balkans). Following a pilot study performed in the province of Modena, Italy in 2011-2013, an official screening program was established on May 31 2014 for all pregnant women, free-of-charge for the family according to the National Guidelines for Physiological Pregnancy. Hemoglobin (Hb) profiles of pregnant women within 10 weeks of pregnancy, of new mothers at delivery and of the newborns of mothers with variant Hb profiles (newborns at-risk), were evaluated by high performance liquid chromatography (HPLC). Samples from 17,077 new mothers were analyzed and 993 showed alteration of Hb patterns (5.8%) (1.0% Hb AS carriers); of the 1011 at-risk newborns, four (0.4%) carried sickle cell disease and 90 (8.9%) were Hb AS carriers. These data show that early diagnosis of sickle cell disease or carrier status can be obtained in high-risk newborns, providing valuable information on the frequency of these conditions in geographic areas in which the disease is historically rare.

Sperm quality and environment: A retrospective, cohort study in a Northern province of Italy.

BACKGROUND: Several studies proposed a relationship between environmental factors and semen quality, as well as the negative effect of air pollution on spermatogenesis and gonadal function. No specific studies evaluated the environmental influence on semen quality in a specific geographical area. AIM: to evaluate the environmental influence on male sperm parameters in a Northern Italian population referred for semen analysis in the National Health System. The objective of the study is the assessment of the relationship of both air pollution and environmental parameters with quality-related sperm variables, during the coldest months of the year when air is usually most polluted, due to low ventilation and poor rainfall. STUDY DESIGN: A retrospective, observational, cohort study was carried out in the province of Modena, located in the Emilia-Romagna region of Northern Italy. METHODS: Semen analyses (n=406), environmental temperature, air humidity and air particulate matter (PM) measurements from the 1st of November 2014 to the 19th of February 2015 were acquired to the first database. Since spermatogenesis lasts over two months, a second, wider database was arranged, evaluating environmental exposure in the 3 months before semen collection (from August 1st 2014). All data included in the database were registered by geo-coding the residential address of the patients and the site of registration of environmental factors. The geo-codification of parameters was performed using Fusion Tables of Google available at https://www.google.com/fusiontables/data? dsrcid=implicit, considering the exact time of measurement. RESULTS: Average air temperature was inversely related to sperm concentration and to total sperm number (p<0.001). Semen volume was inversely related only to the minimum (p<0.001) and not to maximum recorded temperature (p=0.110). Air humidity was not related to sperm quantity and quality. PM2.5 was directly related to total sperm number (p<0.001). PM10 was directly related to both semen volume (0<0.001), and typical forms (p<0.001), inversely related to atypical forms (p<0.001), but related neither to sperm concentration (p=0.430) nor to sperm motility. The extended analyses considering environmental parameters in the 3 months before semen collection, confirmed the relationship between air temperature and sperm quantity, whereas no influence was found between PM and sperm quality. CONCLUSION: An influence of environmental temperature on semen quantity is suggested, without a clear effect of air pollution, as assessed through PM10 levels, on sperm parameter variations.