What are the primary causes of severe male factor infertility? Although 40% of all patients showed primary causes of infertility, which could be subdivided into three groups based on the severity of their effect, ~75% of oligozoospermia cases remained idiopathic. There are few large-scale epidemiological studies analyzing the causes of male factor infertility. A prospective clinical-epidemiological study was conducted at the Andrology Centre, Tartu University Hospital between 2005 and 2013, recruiting male partners of couples failing to conceive a child for over ≥12 months. Among 8518 patients, 1737 (20.4%) were diagnosed with severe male factor infertility. A reference group of fertile controls was comprised of 325 partners of pregnant women. The mean age of infertility patients and fertile controls was 33.2 ± 7.3 and 31.7 ± 6.3 years, respectively. All participants were examined using a standardized andrology workup, accompanied by a structured medical interview. Hormonal analysis included serum FSH, LH and testosterone. Semen quality was determined in accordance to the World Health Organization recommendations. Cases with spermatozoa concentrations of ≤5 million/ml were screened for chromosomal aberrations and Y-chromosomal microdeletions. The primary cause of infertility was defined for 695 of 1737 patients (~40%). The analyzed causal factors could be divided into absolute (secondary hypogonadism, genetic causes, seminal tract obstruction), severe (oncological diseases, severe sexual dysfunction) and plausible causal factors (congenital anomalies in uro-genital tract, acquired or secondary testicular damage). The latter were also detected for 11 (3.4%) men with proven fertility (diagnoses: unilateral cryptorchidism, testis cancer, orchitis, mumps orchitis). The causal factors behind the most severe forms of impaired spermatogenesis were relatively well understood; causes were assigned: for aspermia in 46/46 cases (100%), for azoospermia in 321/388 cases (82.7%), and for cryptozoospermia in 54/130 cases (41.5%). In contrast, 75% of oligozoospermia cases remained unexplained. The main cause of aspermia was severe sexual dysfunction (71.7% of aspermia patients). Azoospermia patients accounted for 86.4% of all cases diagnosed with secondary hypogonadism and 97.1% of patients with seminal tract obstruction. Of patients with a known genetic factor, 87.4% had extreme infertility (azoo-, crypto- or aspermia). The prevalence of congenital anomalies in the uro-genital tract was not clearly correlated with the severity of impaired sperm production. Previously defined ‘potential contributing factors’ varicocele and leukocytospermia were excluded as the primary causes of male infertility. However, their incidence was >2-fold higher (31.0 vs 13.5% and 16.1 vs 7.4%; P < 0.001) in the idiopathic infertility group compared to controls. In addition, the proportions of overweight (or obese) patients and patients suffering from a chronic disease were significantly increased in almost all of the patient subgroups. The study included only subjects with reduced total spermatozoa counts. Thus, these findings cannot be automatically applied to all male factor infertility cases. The novel insights and improved clarity achieved in the comprehensive analysis regarding the absolute, causative and plausible factors behind male infertility, as well as the ‘potential contributing factors’, will be valuable tools in updating the current clinical guidelines. The study highlights knowledge gaps and reiterates an urgent need to uncover the causes and mechanisms behind, and potential treatments of, oligozoospermic cases, representing the majority of idiopathic infertility patients (86.3%). The project was financed by the EU through the ERDF, project HAPPY PREGNANCY, no. 3.2.0701.12-004 (M.P., M.L.) and the Estonian Research Council: grants PUT181 (M.P.) and IUT34-12 (M.L.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We have no competing interests to declare. Not applicable

Recent prospective studies of male reproductive health have shown differences between several European countries. Our objective was to evaluate the current situation in the two Baltic States Estonia and Lithuania. In 1997–99 we investigated semen parameters, levels of reproductive hormones and general health factors of 196 men from the general population in Lithuania; from Estonia, 79 men from the general population and 118 soldiers were investigated. Adjusted for interlaboratory differences and abstinence period, sperm concentration of Lithuanian and Estonian men from the general populations were shown to be 55 and 67 million/mL, respectively. The Estonian soldiers had the highest sperm concentration, 82 million/mL. The frequencies of morphologically normal spermatozoa were 6.2, 7.7 and 9.6%, respectively. In contrast to the semen qualities, highest Inhibin B levels were detected in the Lithuanians (233 pg/mL) followed by Estonian men from the general population (220 pg/mL) and Estonian soldiers (185 pg/mL). The soldiers had also the lowest level of testosterone and oestradiol. The sperm counts of the Estonian and Lithuanian men investigated here are higher than recently shown for Norwegian, Danish, Estonian and Finnish men. Comparisons should be cautiously drawn as the groups are not completely comparable. Still, even within the Baltic region, geographically close and sharing common recent social history, differences in semen quality and levels of reproductive hormones are apparent.

Male factor infertility concerns 7–10% of men and among these 40–60% remain unexplained. This review is based on recent published literature regarding the genetic causes of male infertility. Screening for karyotype abnormalities, biallelic pathogenic variants in the CFTR gene and Y-chromosomal microdeletions have been routine in andrology practice for >20 years, explaining ~10% of infertility cases. Rare specific conditions, such as congenital hypogonadotropic hypogonadism, disorders of sex development and defects of sperm morphology and motility, are caused by pathogenic variants in recurrently affected genes, which facilitate high diagnostic yield (40–60%) of targeted gene panel-based testing. Progress in mapping monogenic causes of quantitative spermatogenic failure, the major form of male infertility, has been slower. No ‘recurrently’ mutated key gene has been identified and worldwide, a few hundred patients in total have been assigned a possible monogenic cause. Given the high genetic heterogeneity, an optimal approach to screen for heterogenous genetic causes of spermatogenic failure is sequencing exomes or in perspective, genomes. Clinical guidelines developed by multidisciplinary experts are needed for smooth integration of expanded molecular diagnostics in the routine management of infertile men. Di−/oligogenic causes, structural and common variants implicated in multifactorial inheritance may explain the ‘hidden’ genetic factors. It is also critical to understand how the recently identified diverse genetic factors of infertility link to general male health concerns across lifespan and how the clinical assessment could benefit from this knowledge.

Background: Mutations in SCN9A, encoding the alpha subunit of the voltage-gated sodium channel (Na^v1.7), have caused severe pain disorders and congenital insensitivity to pain. The aim of this study was to validate the previously reported association between a common non-synonymous polymorphism (R1150W, rs6746030) in SCN9A and chronic widespread pain (CWP), in independent population-based cohorts. Findings: Genotype data for rs6746030 was available in four population-based cohorts (EPIFUND, the European Male Ageing Study (EMAS), the Framingham study and the Dyne Steel DNA Bank of Ageing and Cognition). Pain was assessed using body manikins and CWP was scored using American College of Rheumatology (ACR) criteria in all cohorts, except the Framingham study which assessed widespread pain (WP) using ACR criteria on a joint pain homunculus. Controls were subjects who reported no pain. Logistic regression (additive genetic model) was used to test for association between rs6746030 and CWP compared to controls, adjusting for study centre in EMAS. Generalised estimating equation regression was used to test for association between rs6746030 and WP, whilst accounting for relatedness between subjects in the Framingham study. Genotype data for rs6746030 was available for 1071 CWP cases and 3212 controls. There was no significant association between CWP and rs6476030 in individual cohorts or when combined in a fixed-effects meta-analysis (Odds Ratio = 0.96 (95% confidence interval 0.82, 1.11) p = 0.567). Conclusions: In contrast to a previous study, no association between a non-synonymous polymorphism in SCN9A and CWP was observed in multiple population-based cohorts.

We sought to determine the influence of single-nucleotide polymorphisms (SNPs) in RANKL, RANK, and OPG on volumetric bone mineral density (vBMD) and bone geometry at the radius in men. Pairwise tag SNPs (r ² ≥ 0.8) for RANKL (n = 8), RANK (n = 44), and OPG (n = 22) and five SNPs near RANKL and OPG strongly associated with areal BMD in genomewide association studies were previously genotyped in men aged 40–79 years in the European Male Ageing Study (EMAS). Here, these SNPs were analyzed in a subsample of men (n = 589) who had peripheral quantitative computed tomography (pQCT) performed at the distal (4%) and mid-shaft (50%) radius. Estimated parameters were total and trabecular vBMD (mg/mm³) and cross-sectional area (mm²) at the 4% site and cortical vBMD (mg/mm³); total, cortical, and medullary area (mm²); cortical thickness (mm); and stress strain index (SSI) (mm³) at the 50% site. We identified 12 OPG SNPs associated with vBMD and/or geometric parameters, including rs10505348 associated with total vBMD (β [95% CI] = 9.35 [2.12–16.58], P = 0.011), cortical vBMD (β [95% CI] = 5.62 [2.10–9.14], P = 0.002), cortical thickness (β [95% CI] = 0.08 [0.03–0.13], P = 0.002), and medullary area (β [95% CI] = −2.90 [−4.94 to −0.86], P = 0.005) and rs2073618 associated with cortical vBMD (β [95% CI] = −4.30 [−7.78 to −0.82], P = 0.015) and cortical thickness (β [95% CI] = −0.08 [−0.13 to −0.03], P = 0.001). Three RANK SNPs were associated with vBMD, including rs12956925 associated with trabecular vBMD (β [95% CI] = −7.58 [−14.01 to −1.15], P = 0.021). There were five RANK SNPs associated with geometric parameters, including rs8083511 associated with distal radius cross-sectional area (β [95% CI] = 8.90 [0.92–16.88], P = 0.029). No significant association was observed between RANKL SNPs and pQCT parameters. Our findings suggest that genetic variation in OPG and RANK influences radius vBMD and geometry in men.