Genetics of Sex Hormone-Binding Globulin and Testosterone Levels in Fertile and Infertile Men of Reproductive Age

Role of sex hormone-binding globulin in the free hormone hypothesis and the relevance of free testosterone in androgen physiology

According to the free hormone hypothesis, biological activity of a certain hormone is best reflected by free rather than total hormone concentrations. A crucial element in this theory is the presence of binding proteins, which function as gatekeepers for steroid action. For testosterone, tissue exposure is governed by a delicate equilibrium between free and total testosterone which is determined through interaction with the binding proteins sex hormone-binding globulin and albumin. Ageing, genetics and various pathological conditions influence this equilibrium, hereby possibly modulating hormonal exposure to the target tissues. Despite ongoing controversy on the subject, strong evidence from recent in vitro, in vivo and human experiments emphasizes the relevance of free testosterone. Currently, however, clinical possibilities for free hormone diagnostics are limited. Direct immunoassays are inaccurate, while gold standard liquid chromatography with tandem mass spectrometry (LC-MS/MS) coupled equilibrium dialysis is not available for clinical routine. Calculation models for free testosterone, despite intrinsic limitations, provide a suitable alternative, of which the Vermeulen calculator is currently the preferred method. Calculated free testosterone is indeed associated with bone health, frailty and other clinical endpoints. Moreover, the added value of free testosterone in the clinical diagnosis of male hypogonadism is clearly evident. In suspected hypogonadal men in whom borderline low total testosterone and/or altered sex hormone-binding globulin levels are detected, the determination of free testosterone avoids under- and overdiagnosis, facilitating adequate prescription of hormonal replacement therapy. As such, free testosterone should be integrated as a standard biochemical parameter, on top of total testosterone, in the diagnostic workflow of male hypogonadism.

A GWAS in Idiopathic/Unexplained Infertile Men Detects a Genomic Region Determining Follicle-Stimulating Hormone Levels

CONTEXT

Approximately 70% of infertile men are diagnosed with idiopathic (abnormal semen parameters) or unexplained (normozoospermia) infertility, with the common feature of lacking etiologic factors. Follicle-stimulating hormone (FSH) is essential for initiation and maintenance of spermatogenesis. Certain single-nucleotide variations (SNVs; formerly single-nucleotide polymorphisms [SNPs]) (ie, FSHB c.-211G > T, FSHR c.2039A > G) are associated with FSH, testicular volume, and spermatogenesis. It is unknown to what extent other variants are associated with FSH levels and therewith resemble causative factors for infertility.

OBJECTIVE

We aimed to identify further genetic determinants modulating FSH levels in a cohort of men presenting with idiopathic or unexplained infertility.

METHODS

We retrospectively (2010-2018) selected 1900 men with idiopathic/unexplained infertility. In the discovery study (n = 760), a genome-wide association study (GWAS) was performed (Infinium PsychArrays) in association with FSH values (Illumina GenomeStudio, v2.0). Minor allele frequencies (MAFs) were analyzed for the discovery and an independent normozoospermic cohort. In the validation study (n = 1140), TaqMan SNV polymerase chain reaction was conducted for rs11031005 and rs10835638 in association with andrological parameters.

RESULTS

Imputation revealed 9 SNVs in high linkage disequilibrium, with genome-wide significance (P < 4.28e-07) at the FSHB locus 11p.14.1 being associated with FSH. The 9 SNVs accounted for up to a 4.65% variance in FSH level. In the oligozoospermic subgroup, this was increased up to 6.95% and the MAF was enhanced compared to an independent cohort of normozoospermic men. By validation, a significant association for rs11031005/rs10835638 with FSH (P = 4.71e-06/5.55e-07) and FSH/luteinizing hormone ratio (P = 2.08e-12/6.4e-12) was evident.

CONCLUSIONS

This GWAS delineates the polymorphic FSHB genomic region as the main determinant of FSH levels in men with unexplained or idiopathic infertility. Given the essential role of FSH, molecular detection of one of the identified SNVs that causes lowered FSH and therewith decreases spermatogenesis could resolve the idiopathic/unexplained origin by this etiologic factor.

Prevalence of SLCO1B1 single nucleotide variations and their association with hypercholesterolaemia in hypercholesterolemic patients in Gauteng, South Africa

Statins, the standard treatment for hypercholesterolaemia, among the most widely prescribed, have been associated with side effects, including statin intolerance. The aim of this study was to determine the background prevalence of SLCO1B1 SNVs in a randomly selected sample and to investigate if there are associations between SLCO1B1 SNVs and hypercholesterolaemia patients on statin therapy.Using Polymerase Chain Reaction - Restriction Fragment Length Polymorphism, the presence of SLCO1B1 SNVs (rs4149056, rs2306283 and rs4363657) was identified, while ELISA was used to quantify serum CK levels. Statin intolerance risk was calculated using a quantitative questionnaire.The risk of developing statin intolerance was found to be low (in 36%), moderate (in 49%), or high (in 15%) in the statin-treated group. The prevalence of the rs4149056 variant was 16% in (controls) and 20% in (statin) group; rs2306283 variant was present in 31.5% (controls), 10.5% in (statin) group; while the prevalence of the rs4363657 variant was similar in each. No association between the presence of any one of the SNVs and the statin intolerance severity risk score or CK elevation was found.These findings will facilitate a more personalized approach to statin therapy, especially relevant within the diverse South African population.

NR5A1 c.991-1G > C splice-site variant causes familial 46,XY partial gonadal dysgenesis with incomplete penetrance

OBJECTIVE

The study aimed to identify the genetic basis of partial gonadal dysgenesis (PGD) in a non-consanguineous family from Estonia.

PATIENTS

Cousins P (proband) 1 (12 years; 46,XY) and P2 (18 years; 46,XY) presented bilateral cryptorchidism, severe penoscrotal hypospadias, low bitesticular volume and azoospermia in P2. Their distant relative, P3 (30 years; 46,XY), presented bilateral cryptorchidism and cryptozoospermia.

DESIGN

Exome sequencing was targeted to P1-P3 and five unaffected family members.

RESULTS

P1-P2 were identified as heterozygous carriers of NR5A1 c.991-1G > C. NR5A1 encodes the steroidogenic factor-1 essential in gonadal development and specifically expressed in adrenal, spleen, pituitary and testes. Together with a previous PGD case from Belgium (Robevska et al 2018), c.991-1G > C represents the first recurrent NR5A1 splice-site mutation identified in patients. The majority of previous reports on NR5A1 mutation carriers have not included phenotype-genotype data of the family members. Segregation analysis across three generations showed incomplete penetrance (<50%) and phenotypic variability among the carriers of NR5A1 c.991-1G > C. The variant pathogenicity was possibly modulated by rare heterozygous variants inherited from the other parent, OTX2 p.P134R (P1) or PROP1 c.301_302delAG (P2). For P3, the pedigree structure supported a distinct genetic cause. He carries a previously undescribed likely pathogenic variant SOS1 p.Y136H. SOS1, critical in Ras/MAPK signalling and foetal development, is a strong novel candidate gene for cryptorchidism.

CONCLUSIONS

Detailed genetic profiling facilitates counselling and clinical management of the probands, and supports unaffected mutation carriers in the family for their reproductive decision making.

GWAS and PheWAS of red blood cell components in a Northern Nevadan cohort

In this study, we perform a full genome-wide association study (GWAS) to identify statistically significantly associated single nucleotide polymorphisms (SNPs) with three red blood cell (RBC) components and follow it with two independent PheWASs to examine associations between phenotypic data (case-control status of diagnoses or disease), significant SNPs, and RBC component levels. We first identified associations between the three RBC components: mean platelet volume (MPV), mean corpuscular volume (MCV), and platelet counts (PC), and the genotypes of approximately 500,000 SNPs on the Illumina Infimum DNA Human OmniExpress-24 BeadChip using a single cohort of 4,673 Northern Nevadans. Twenty-one SNPs in five major genomic regions were found to be statistically significantly associated with MPV, two regions with MCV, and one region with PC, with p<5x10^-8. Twenty-nine SNPs and nine chromosomal regions were identified in 30 previous GWASs, with effect sizes of similar magnitude and direction as found in our cohort. The two strongest associations were SNP rs1354034 with MPV (p = 2.4x10^-13) and rs855791 with MCV (p = 5.2x10^-12). We then examined possible associations between these significant SNPs and incidence of 1,488 phenotype groups mapped from International Classification of Disease version 9 and 10 (ICD9 and ICD10) codes collected in the extensive electronic health record (EHR) database associated with Healthy Nevada Project consented participants. Further leveraging data collected in the EHR, we performed an additional PheWAS to identify associations between continuous red blood cell (RBC) component measures and incidence of specific diagnoses. The first PheWAS illuminated whether SNPs associated with RBC components in our cohort were linked with other hematologic phenotypic diagnoses or diagnoses of other nature. Although no SNPs from our GWAS were identified as strongly associated to other phenotypic components, a number of associations were identified with p-values ranging between 1x10^-3 and 1x10^-4 with traits such as respiratory failure, sleep disorders, hypoglycemia, hyperglyceridemia, GERD and IBS. The second PheWAS examined possible phenotypic predictors of abnormal RBC component measures: a number of hematologic phenotypes such as thrombocytopenia, anemias, hemoglobinopathies and pancytopenia were found to be strongly associated to RBC component measures; additional phenotypes such as (morbid) obesity, malaise and fatigue, alcoholism, and cirrhosis were also identified to be possible predictors of RBC component measures.