In recent research, the technical capability of wholly Australian-owned bioinformatics start-up, 23Strands, to decipher big data about genomics is revolutionising scientific research in women’s health. 23Strands’ work in genomics was linked with known molecular pathways for endometriosis to identify key genes associated with the disease. This was articulated by PhD student, Zelia Mei-Ze Soo, who presented research on the identification of genetic markers of endometriosis, a debilitating condition affecting ten percent of women and girls of reproductive age.
The methodology was described at the International Congress of Genetics and Genomics Conference in Melbourne, where the new method of applying artificial intelligence (AI) to investigate whole genome data and integrate it with molecular pathways is furthering the understanding of diseases like endometriosis.
The disease is defined as the presence of endometrium-like tissue outside of the uterus. It can cause severe pain and result in possible fertility complications. Currently, diagnosis is only through an invasive surgical procedure known as laparoscopy. It is estimated that 26 percent of common genetic variants are the cause of endometriosis.
The 23Strands proprietary AI-powered platform is an evidence-based approach to research big data. Using the platform’s algorithm, PubMed papers were searched using the search terms endometriosis and genom*, identifying 235 genes of interest. The gene list was then integrated with other sources of clinical information about phenotypes and endometriosis to refine the gene list to 40, with key proteins identified to be involved in endometriosis.
The knowledge gleaned has the potential to provide insight into endometriosis and to further the analysis, diagnosis, management and clinical recommendation flow to improve personal treatment of endometriosis.
The research is a partnership between 23Strands and the University of Technology Artificial Intelligence Institute and is funded jointly by 23Strands, UTS and an Australian Research Council (ARC Linkage) Grant.
“This new methodology of combining 23Strands’ bioinformatics expertise with known molecular pathways for disease to identify clinically relevant genes is a framework that is applicable to other diseases, and even other species, and would be particularly useful for less common, under-represented diseases,” CEO of 23Strands, Mr Mark Grosser, said.
“At 23Strands we continue to refine the application of artificial intelligence (AI) to genomics, to integrate big data with clinical information to revolutionise healthcare, and in this case women’s health.”
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