Newly identified markers of atherosclerotic coronary artery disease (ASCAD) have been identified in a study using digital twins. The work was performed by multi-specialist G3 Therapeutics and artificial intelligence company Aitia Gemini digital twin Technique.
These new findings indicate that LDL particles rich in triglycerides could be a novel diagnostic marker for ASCAD and could also open up potential new therapeutic targets for this condition.
“For decades, we have uniquely focused on LDL cholesterol as the sole target of treatment in coronary atherosclerosis. Now, this new discovery of triglyceride-rich LDL particles opens up a host of previously untapped opportunities to offer novel diagnostic and therapeutic approaches to our patients with cardiovascular disease. bloody devastating.”
G3 Team / Aitia Results Posted in Frontiers in cardiovascular medicine.
With the advancement of artificial intelligence, the use of this technology in clinical research on cardiovascular diseases has expanded exponentially. In December last year, a team from Mount Sinai mentioned Discovery of a marker in silico for coronary artery disease. Also that month, researchers at Massachusetts General Hospital released a study which uses a deep learning tool with a single x-ray to predict a patient’s 10-year risk of dying from a 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 from 37,000 molecular measurements and 99 conventional biomarkers for each patient examined the potential causality of specific biomarkers.
They found that the effect of the triglyceride-rich LDL particles was independent of the cholesterol content of the LDL particles. In a Bayesian analysis, LDL-TG was directly associated with atherosclerosis in more than 95% of the groups.
The potential causation of these particles was confirmed by genetic verification, based on the hepatic lipase gene. The team’s analysis revealed that atherosclerotic lipoproteins, inflammation and endothelial dysfunction are involved in ASCAD, lending further credence to the new findings.
“This landmark result clearly demonstrates the power of causal AI and digital twins in revealing hidden circuits of cardiovascular disease from large-scale multiscale 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 manner in a few months, creating the opportunity to quickly discover new drivers of atherosclerosis such as rich triglycerides. LDL that has eluded researchers for decades. A new era of technological discoveries based on artificial intelligence has begun.
The G3 Therapeutics Global Clinical Study is an international, multicenter, prospective study recruiting up to 10,000 patients to characterize novel disease networks and biomarkers. The company says GLOBAL is the largest and most comprehensive study combining whole-genome sequencing, whole-genome methylation, whole-copy sequencing, unbiased proteomics, metabolomics, lipidology, and lipoprotein profiling with computerized coronary angiography (CT)—an advanced imaging technique for phenotyping that Allows accurate classification of disease in patients.
Aetia says it applies “artificial intelligence and causal digital twins” to cutting-edge drug discovery. The company leverages the convergence of multi-discipline patient data, high-performance computing, and causal learning in oncology, neurodegenerative disorders, and immunology.
It is also reported that Gemini Digital Twins are being used today to discover new therapies and accelerate research and development in multiple myeloma, prostate cancer, Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease. Aitia partners include seven of the ten largest pharmaceutical companies, leading academic and medical research centers, medical associations, leading multi-system data companies and patient advocacy groups globally.
“Our discovery demonstrates the power of combining big biological data with causal AI to deliver completely new therapies to our patients,” said Voros of G3.