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HKU and UK university develop robotic solution to diagnose reproductive disorders

Image Credits: The University of Hong Kong, LKS Facility of Medicine, Press Release
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A press release notes that The LKS Faculty of Medicine of The University of Hong Kong (HKUMed) collaborated with Imperial College London to develop and apply a new robotic platform technology to measure hormone pulse patterns in reproductive disorder patients.

Many reproductive disorders are caused by altered pulse patterns of hormone secretion in the bloodstream, leading to a variety of reproductive disorders such as polycystic ovary syndrome (PCOS) and hypothalamic amenorrhea.

Such disorders are very common with PCOS, which is prevalent in 5-7% of all reproductive-age women. There are a wide variety of complications of such reproductive disorders such as infertility, metabolic syndrome and depression. There is a frequent challenge to the diagnosis of these disorders as single measurements from a blood sample cannot tell a clinician the pulse pattern of hormone secretion over time.

The tech developed through the collaboration between the two academic institutions is the first demonstration of this technology which is expected to be widely applied to a wide range of diagnostic scenarios in the future.

One of the lead researchers of the study, the Associate Professor of the School of Biomedical Sciences, HKUMed, remarked that the diagnosis of reproductive disorders that often cause infertility is a long-standing challenge. This study provides an innovative underlying biomedical technology that has the potential to transform medical diagnostics through enabling repeated or even continuous measurement of hormone and other biomolecule concentrations.

Study Results

The team developed and applied an entirely new approach for measuring the pulse pattern of one of the important hormones to be analysed for diagnosing patients with reproductive disorders – a luteinising hormone. A short piece of DNA, known as an aptamer, which specifically bound to luteinising hormone without binding to other closely related hormones was developed.

The team integrated this aptamer onto an electrochemical detector so that when the aptamer changed shape in the presence of the hormone, the electrical properties of the surface changed, enabling a direct measurement of the concentration of the hormone in a blood sample.

This electrochemical detector was integrated into a wire on a robotic platform so that hundreds of blood samples could be easily measured in parallel.

The team then developed a new mathematical approach termed Bayesian Spectrum Analysis to determine the LH pulsatile pattern in a variety of clinical scenarios.

The significance of this study includes:

  1. Development of a novel molecule (aptamer) for luteinising hormone-sensing;
  2. Development of a low-cost, efficient robotic platform for automated measurement;
  3. Development of a novel mathematical method for characterising luteinising hormone pulsatile information; and,
  4. Validation of the performance of the platform with clinical samples in 3 patient cohorts in different LH pulsatility status (around 441 samples).

This is amongst the first ever studies where aptamers have been used for diagnosis in a clinical setting. Antibodies are the usual approach for specific biomolecule measurements, but they cannot be used continuously so are not ideal for a new wave of biomedical technology in this area.

Aptamers are ideal for continuous sensing technologies such as for biochips that might be embedded or may act via microneedle patches or tattoos in the skin in the future.

Therefore, this research opens up significant possibilities as the underlying technology for continuous biomolecule sensing that could transform molecular diagnostics.

Previous Study Results

Over the last decade, the HKU team has been developing the use of aptamers for new approaches for diagnostics, particularly for the point-of-care diagnosis of malaria.

This is the first study where they have extended the impact of aptamer biomedical technology to diagnosis of reproductive disorders.

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