TNFSF11 Inhibition and Fertility: a Prospective Study

The receptor activator of NF-kB ligand (RANKL) system is considered important for bone homeostasis . RANKL exist in three isoforms and the effects of all isoforms are mediated through binding to a specific receptor (receptor activator of NF-KB (RANK)). RANKL is predominantly found as a transmembrane protein and signalling is therefore dependent on cell-cell interaction to a neighbouring cell expressing RANK that subsequently activates NFKB and regulates cellular activation through regulation of cell cycle i.e proliferation, differentiation and apoptosis. RANKL-RANK interaction is modified by osteoprotegerin (OPG), which is an endogenous secreted protein that binds RANKL and inhibits its signalling.

RANK/RANKL triggers a network of TRAF-mediated kinase cascades that promote osteoclast differentiation. RANKL is expressed on osteoblast cells and its receptor, Rank, on pre- osteoclastic cells. RANKL expression is stimulated by a number of factors, such as IL-1 , IL-6, IL-11 , IL-17, TNF- α, vitamin D, Ca2+, parathyroid, glucocorticoids, prostaglandin E2, and immunosuppressive drugs, and is down-regulated by TGF-α. The RANK/RANKL interaction induces differentiation and formation of multinucleated mature osteoclasts, causing bone resorption. The third protein agonist, osteoprotegerin (OPG), is also produced by osteoblasts and is known to exert an inhibitory effect on the pre-osteoclastic differentiation process. By binding to RANKL also known as osteoprotegerin binding protein (OPGbp), OPG inhibits the RANK/RANKL interaction and subsequent osteoclastogenesis. OPG is thus a very efficient anti-resorptive agent. It also serves as a decoy receptor for the tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) and increases cell survival by blocking the apoptotic effects of this ligand. The fact that the overexpression of OPG in mice results in severe osteopetrosis and that OPG-null mice are osteoporotic is testimony to the physiological importance of OPG. The lack of RANK or RANKL induces osteopetrosis in mice.

Thus, the RANK/RANKL system is vital for activation of the bone resorping cells (osteoclasts). In the skeleton the bone synthesizing cells (osteoblasts) express RANKL that signals to RANK on the immature osteoclasts. This induces proliferation and activation of the cells they start to proliferate and resorp bone. OPG is produced by somatic cells in the bone and this production is regulated by sex hormones, TGF-B and various other substances. Today a human made recombinant antibody against RANKL, Denosumab is used to treat osteoporosis as it inhibits RANKL signalling and causes less bone resorption in humans. RANKL signalling has only two other known additional functions in healthy humans where it is involved in lactation and the immune response.

The investigators have data showing that RANKL, RANK and OPG are expressed at both RNA and protein level in the human testis. The Sertoli cells express RANKL, while the germ cells express RANK and the peritubular cells express OPG. Normally, RANKL activates NFKB and activation of this pathway in the male gonad appears to regulate whether the testicular cells proliferate or undergo apoptosis in the testis. The investigators' in vitro, ex vivo and in vivo data from functional models support this suggestion and this pathway appears therefore to be a novel regulator of germ cell proliferation.

Decreased semen quality is a major factor of male infertility. Semen quality is an indirect measure of the ability of the sperm to accomplish fertilization. Evaluation of male fertility potential is evaluated by semen analysis. Semen analysis evaluates certain characteristics and the most common variables measured to evaluate sperm quality are: sperm count, motility and morphology.

There is no treatment for men with no spermatozoa in the ejaculate or even a drug that can increase sperm number in infertile men.Therefore, we suggest that antibodies against RANKL such as Denosumab, may be used as a novel treatment option for male infertility , which highlights a new indication for Denosumab treatment.

The investigators will therefore test whether inhibition of RANKL by Denosumab in humans increases sperm production and semen quality in this small prospective intervention study.

We will invite 15 infertile men for detailed screening to secure inclusion and study completion of anticipated 12 infertile men

BIOSTATISTICAL ANALYSIS

All the analyses will be performed according to Good Clinical Practice guidelines and the primary analyses in the intention-to-treat population, which included all patients who received the first dose of medicine on day 1. We will analyze the data in two ways. The primary analysis will proceed according to baseline values compared with outcomes variables after intervention. The secondary analysis will be based on stratifying the men according to subgroup analyses in relation to the predefined primary and secondary endpoints.

Data analysis and quality The primary end points for this protocol will be changes in sperm production evaluated by total sperm number, sperm concentration followed by number of progressive and motile sperm, morphologically normal sperm, sperm motility, progressive motility and morfology which will be compared by paired t-test. Multiple secondary endpoints exist but for the initial investigation focus will be on changes of the following secondary endpoints: Sperm DFI, FSH, Inhibin B, serum OPG, RANKL, OPG, vitamin D and calcium homeostasis. Subjects who terminate participation after visit day 1 but before visit day 180 will be included for data analysis up to the last day they provided semen and bloodsample. Men that only deliver semen samples occasionally or have missing data at any visit will still be included in the analysis. Men that do not meet the criteria in the protocol will be excluded from the analysis. Men with fever above 38.5 degrees Celsius will not be included in the analyses up to 3 months after the fever episode. Semen samples obtained with an abstinence period less than 24 hours or with a semen volume < 1.5 ml will not be included in the analyses. Those values will then be carried forward for analyses. A significance level of 5% is used. For the primary analyses Bonferronu-Holm p-value correction is calculated additionally. For the secondary analysis no multiple test correction are used. Instead results are discussed in view of the multiple testing situations.

1. Analyses between baseline versus different timepoints The first step will be to compare the changes in primary outcomes between baseline versus the different timepoints. Spermatogenesis normally takes up to 70 days in men and we will therefore determine the difference to all the individual timepoints and calculate average for days 80, 120 and 180 and compare with baseline values to determine the effect of RANKL inhibition on the whole length of spermatogenesis. This analysis will show if there is a significant difference between groups. For outcomes measured repeatedly, this will entail comparing the estimated slopes, or rates of change, of each outcome between the groups. Mixed models allow for the correlation between the repeated observations baseline-day 1-day 80- day 180 from each man to be suitably incorporated into parameter estimation. For all endpoints measured at baseline and day 180, paired t-tests will be used to assess there is a significant difference between the groups and determine whether the mean change within each group differs significantly from zero. In both cases, data will be transformed as necessary to meet model assumptions. Afterwards, the same analysis will be conducted by using multiple regression with relevant confounders such as season, BMI, smoking, duration of abstinence, time from ejaculation to motility assessment, fever etc. to see if this changes the results For outcomes measured that cannot be compared with t-test or other parametric tests at day 1, day 80 and day 180, groups will be compared using non-parametric tests such as Wilcoxon Mann-Whitney test. For Binary outcome the data will be compared between the two groups by means of conditional logistic-regression analysis with adjustment for relevant confounders (defined as being significantly p<0.05 associated).

2. Analyses after stratification into subgroups Subjects will be grouped according to their BMI, semen quality, serum RANKL, OPG, calcium, PTH, osteocalcin or other bonefactors evaluated at the day of screening. The subgroup analyses will in accordance with normal clinical practice and stratification in appropriate groups according to the clinical (BMI <25, 25-30, >30 etc.), tertiles or highest/lowest versus remaining at baseline. Analyses will be performed on each timpeoint compared with baseline in addition to mean/median of visit day 80, 120, 180 with baseline and mean/median of all visits after intervention.