Quantifying the variability in the assessment of reproductive hormone levels.

OBJECTIVE: To quantify how representative a single measure of reproductive hormone level is of the daily hormonal profile using data from detailed hormonal sampling in the saline placebo-treated arm conducted over several hours. DESIGN: Retrospective analysis of data from previous interventional research studies evaluating reproductive hormones. SETTING: Clinical Research Facility at a tertiary reproductive endocrinology centre at Imperial College Hospital NHS Foundation Trust. PATIENTS: Overall, 266 individuals, including healthy men and women (n = 142) and those with reproductive disorders and states (n = 124 [11 with functional hypothalamic amenorrhoea, 6 with polycystic ovary syndrome, 62 women and 32 men with hypoactive sexual desire disorder, and 13 postmenopausal women]), were included in the analysis. INTERVENTIONS: Data from 266 individuals who had undergone detailed hormonal sampling in the saline placebo-treated arms of previous research studies was used to quantify the variability in reproductive hormones because of pulsatile secretion, diurnal variation, and feeding using coefficient of variation (CV) and entropy. MAIN OUTCOME MEASURES: The ability of a single measure of reproductive hormone level to quantify the variability in reproductive hormone levels because of pulsatile secretion, diurnal variation, and nutrient intake. RESULTS: The initial morning value of reproductive hormone levels was typically higher than the mean value throughout the day (percentage decrease from initial morning measure to daily mean: luteinizing hormone level 18.4%, follicle-stimulating hormone level 9.7%, testosterone level 9.2%, and estradiol level 2.1%). Luteinizing hormone level was the most variable (CV 28%), followed by sex-steroid hormone levels (testosterone level 12% and estradiol level 13%), whereas follicle-stimulating hormone level was the least variable reproductive hormone (CV 8%). In healthy men, testosterone levels fell between 9:00 am and 5:00 pm by 14.9% (95% confidence interval 4.2, 25.5%), although morning levels correlated with (and could be predicted from) late afternoon levels in the same individual (r2 = 0.53, P<.0001). Testosterone levels were reduced more after a mixed meal (by 34.3%) than during ad libitum feeding (9.5%), after an oral glucose load (6.0%), or an intravenous glucose load (7.4%). CONCLUSION: Quantification of the variability of a single measure of reproductive hormone levels informs the reliability of reproductive hormone assessment.

The prospect of artificial intelligence to personalize assisted reproductive technology.

Infertility affects 1-in-6 couples, with repeated intensive cycles of assisted reproductive technology (ART) required by many to achieve a desired live birth. In ART, typically, clinicians and laboratory staff consider patient characteristics, previous treatment responses, and ongoing monitoring to determine treatment decisions. However, the reproducibility, weighting, and interpretation of these characteristics are contentious, and highly operator-dependent, resulting in considerable reliance on clinical experience. Artificial intelligence (AI) is ideally suited to handle, process, and analyze large, dynamic, temporal datasets with multiple intermediary outcomes that are generated during an ART cycle. Here, we review how AI has demonstrated potential for optimization and personalization of key steps in a reproducible manner, including: drug selection and dosing, cycle monitoring, induction of oocyte maturation, and selection of the most competent gametes and embryos, to improve the overall efficacy and safety of ART.

Quantitative approaches in clinical reproductive endocrinology.

Understanding the human hypothalamic-pituitary-gonadal (HPG) axis presents a major challenge for medical science. Dysregulation of the HPG axis is linked to infertility and a thorough understanding of its dynamic behaviour is necessary to both aid diagnosis and to identify the most appropriate hormonal interventions. Here, we review how quantitative models are being used in the context of clinical reproductive endocrinology to: 1. analyse the secretory patterns of reproductive hormones; 2. evaluate the effect of drugs in fertility treatment; 3. aid in the personalization of assisted reproductive technology (ART). In this review, we demonstrate that quantitative models are indispensable tools enabling us to describe the complex dynamic behaviour of the reproductive axis, refine the treatment of fertility disorders, and predict clinical intervention outcomes.

Insulin-like peptide 3 (INSL3) in congenital hypogonadotrophic hypogonadism (CHH) in boys with delayed puberty and adult men.

Background: Delayed puberty in males is almost invariably associated with constitutional delay of growth and puberty (CDGP) or congenital hypogonadotrophic hypogonadism (CHH). Establishing the cause at presentation is challenging, with "red flag" features of CHH commonly overlooked. Thus, several markers have been evaluated in both the basal state or after stimulation e.g. with gonadotrophin releasing hormone agonist (GnRHa).Insulin-like peptide 3 (INSL3) is a constitutive secretory product of Leydig cells and thus a possible candidate marker, but there have been limited data examining its role in distinguishing CDGP from CHH. In this manuscript, we assess INSL3 and inhibin B (INB) in two cohorts: 1. Adolescent boys with delayed puberty due to CDGP or CHH and 2. Adult men, both eugonadal and having CHH. Materials and methods: Retrospective cohort studies of 60 boys with CDGP or CHH, as well as 44 adult men who were either eugonadal or had CHH, in whom INSL3, INB, testosterone and gonadotrophins were measured. Cohort 1: Boys with delayed puberty aged 13-17 years (51 with CDGP and 9 with CHH) who had GnRHa stimulation (subcutaneous triptorelin 100mcg), previously reported with respect to INB. Cohort 2: Adult cohort of 44 men (22 eugonadal men and 22 men with CHH), previously reported with respect to gonadotrophin responses to kisspeptin-54. Results: Median INSL3 was higher in boys with CDGP than CHH (0.35 vs 0.15 ng/ml; p=0.0002). Similarly, in adult men, median INSL3 was higher in eugonadal men than CHH (1.08 vs 0.05 ng/ml; p<0.0001). However, INSL3 more accurately differentiated CHH in adult men than in boys with delayed puberty (auROC with 95% CI in adult men: 100%, 100-100%; boys with delayed puberty: 86.7%, 77.7-95.7%).Median INB was higher in boys with CDGP than CHH (182 vs 59 pg/ml; p<0.0001). Likewise, in adult men, median INB was higher in eugonadal men than CHH (170 vs 36.5 pg/ml; p<0.0001). INB performed better than INSL3 in differentiating CHH in boys with delayed puberty (auROC 98.5%, 95.9-100%), than in adult men (auROC 93.9%, 87.2-100%). Conclusion: INSL3 better identifies CHH in adult men, whereas INB better identifies CHH in boys with delayed puberty.