AI-driven hormone tracking could help detect infertility early and improve conception

Men and women who appear hormonally 'normal' may still have undetected disruptions in the timing and coordination of their reproductive hormones that could impair fertility, according to research presented at the 28th European Congress of Endocrinology in Prague. Now, a newly developed wearable skin sensor patch, combined with artificial intelligence (AI), not only can measure the quantity of reproductive hormones but also how reproductive hormones fluctuate over time, which could help patients and doctors detect infertility early and improve conception.

Unexplained infertility affects about 15-30% of couples and is diagnosed after standard tests reveal no obvious cause. Standard tests for men who are infertile or have hypogonadism - clinically low testosterone - include single morning serum testosterone measurements, while fertility tests for women include assessing the menstrual cycle and reproductive hormones, such as luteinizing hormone (LH), follicle-stimulating hormone (FSH), estradiol and progesterone. However, hormones are highly dynamic that follow a circadian rhythm, rising and falling in regulated patterns throughout the day.

In one study, Dr Tinatin Kutchukhidze from Oxford University and New Anglia University examined 102 men in Georgia and the UK, between the ages of 22 and 38, who had normal morning total testosterone (12-35 nmol/l), with or without infertility or hypogonadal symptoms. She and her team analysed data on their testosterone levels every 15 minutes over four days, using an AI-enabled wearable skin sensor patch they developed, and found that men with symptoms had significantly disrupted testosterone rhythms, despite having normal testosterone levels in standard laboratory tests. In addition, these unmasked rhythm abnormalities were associated with reduced sperm concentration and symptoms of androgen deficiency.

"For the first time, we have been able to track androgen patterns in real time over several days with a novel, non-invasive continuous AI-driven testosterone monitoring patch, compatible with Android and iPhone mobile devices," said Dr Kutchukhidze. "Previous research suggests that a normal morning testosterone level is sufficient to exclude clinically significant androgen deficiency. However, our findings challenge that assumption by demonstrating that men with normal serum testosterone may still exhibit marked disturbances in hormonal rhythmicity associated with reproductive dysfunction," said Dr Kutchukhidze.

In another study, Dr Kutchukhidze and colleagues developed the AI-driven metric, Endocrine Rhythm Integrity (ERI), to analyse data on key reproductive hormones during the luteal phase, basal body temperature, heart rate and sleep patterns of 312 women, aged 18-22 years, with self-reported regular menstrual cycles, who were fertile or had unexplained infertility. She found that women with unexplained fertility had lower ERI scores, even with normal hormone levels, which predicted infertility. Lower ERI scores were also associated with a higher incidence of implantation failure.

"Our study reveals that a woman may have a seemingly healthy menstrual cycle and normal hormone levels but still experience hidden endocrine dysfunction that affects her ability to conceive," said Dr Kutchukhidze. "Rather than analysing hormone levels as isolated values, ERI evaluates whether reproductive hormones are changing in the correct pattern, at the correct time and in the correct relationship to one another across the menstrual cycle."

"Our AI-driven rhythm analyses were significantly better at identifying subclinical reproductive dysfunction than conventional testing, suggesting that both female and male endocrine disorders may not simply be disorders of hormone quantity, but rather disorders of hormonal timing, synchronisation and biological rhythm," said Dr Kutchukhidze.

Dr Kutchukhidze will next assess whether this new tool can reliably predict fertility outcomes across different reproductive conditions in larger and more diverse populations.

"We aim to move fertility care toward predictive, rhythm-based reproductive medicine, where clinicians can identify dysfunction earlier, personalise interventions and improve outcomes before infertility becomes clinically evident," said Dr Kutchukhidze. "If successful, this research could lead to the first clinically actionable tool for measuring endocrine-rhythm health and redefine how fertility is evaluated worldwide." Dr Kutchukhidze added: "Importantly, this technology could also be widely applied in transgender medicine, where hormone therapy currently relies on intermittent blood tests that may not reflect real-time hormonal dynamics. Our long-term goal is to establish wearable hormonal chronodiagnostics as a new standard not only in reproductive medicine and personalised endocrinology, but also in transgender healthcare, enabling more precise, adaptive and patient-centered management across diverse clinical settings."

Source:

European Society of Endocrinology