Newly identified markers of atherosclerotic coronary artery disease (ASCAD) were pinpointed in a study using digital twins. The work was carried out by multi-omics specialist G3 Therapeutics and AI company Aitia, which has Gemini Digital Twin technology.
These new findings suggest triglyceride-rich LDL particles could be a novel diagnostic marker for ASCAD and could also open up potential novel treatment targets for the condition.
“For decades, we have singularly focused on LDL-cholesterol as the sole treatment target in atherosclerotic coronary artery disease. Now, this new discovery of triglyceride-rich LDL particles opens a previously untapped set of opportunities to bring novel diagnostic and therapeutic approaches to our patients suffering from devastating cardiovascular disease,” said Szilard Voros, MD, CEO, and founder of G3 Therapeutics.
The G3/Aitia team’s results were published in Frontiers in Cardiovascular Medicine.
As AI has advanced, use of this technology in cardiovascular clinical research has greatly expanded. In December last year, a team from Mount Sinai reported discovery of an in silico marker for coronary artery disease. Also that month, researchers at the Massachusetts General hospital released a study that used a deep learning tool with a single X-ray to predict a patient’s 10-year risk of death from heart attack or stroke. Digital twins are virtual models designed to accurately mimic an object or process.
This team analyzed 665 patients from G3 Therapeutics’ GLOBAL clinical study. De novo Bayesian networks built out of 37,000 molecular measurements and 99 conventional biomarkers per patient examined the potential causality of specific biomarkers.
They found the impact of triglyceride-rich LDL particles was independent of the cholesterol content of LDL particles. In the Bayesian analysis, LDL-TG was directly linked to atherosclerosis in over 95% of the ensembles.
These particles’ potential causality was further confirmed by genetic validation, based on the hepatic lipase gene. The team’s analysis revealed that atherogenic lipoproteins, inflammation, and endothelial dysfunction are involved in ASCAD, lending additional credence to the novel findings.
“This landmark result clearly demonstrates the power of causal AI and Digital Twins to reveal the hidden circuitry of cardiovascular disease from large-scale multi-omic data”, said Colin Hill, CEO and co-founder of Aitia.
He added that, “70 years of cardiovascular biology including LDL, PCSK9, and Lp(a) were reconstructed in a hypothesis-free fashion in a few months, which created the opportunity to rapidly discover new drivers of atherosclerotic disease such as triglyceride-rich LDL that has eluded researchers for decades. A new era of AI-driven techbio discovery has begun.”
G3 Therapeutics’ GLOBAL clinical study is an international prospective, multi-center study recruiting up to 10,000 patients to characterize novel disease networks and biomarkers. The company says GLOBAL is the largest and most comprehensive pan-omic study combining whole genome sequencing, whole genome methylation, whole transcriptome sequencing, unbiased proteomics, metabolomics, lipidomics, and lipoprotein proteomics with coronary computed tomographic (CT) angiography—an advanced imaging technology for phenotyping that allows the precise classification of disease in patients.
Aitia says it applies “Causal AI and Digital Twins” to discover breakthrough drugs. The company leverages the convergence of multi-omic patient data, high-performance computing, and causal learning in oncology, neurodegenerative disorders, and immunology.
It also reports that Gemini Digital Twins are being used today to discover novel therapies and accelerate R&D in multiple myeloma, prostate cancer, Alzheimer’s Disease, Parkinson’s Disease, and Huntington’s Disease. Aitia partners include seven of the top ten pharmaceutical companies, leading academic research and medical centers, medical societies, leading multi-omic data companies, and patient advocacy groups globally.
“Our discovery demonstrates the power of the combination of biological big data and causal AI in bringing entirely novel treatments to our patients,” said G3’s Voros.
