New prevention scenarios: polygenic risk

Abstract

Although coronary heart disease is a highly preventable disease, it is still the leading cause of morbidity and mortality in developed countries. This is also due to the fact that the risk models used in clinical practice have proved ineffective in identifying people at risk: up to 30% of cases of myocardial infarction do not have traditional risk factors used in risk estimation models. Although the genetic component of myocardial infarction has been known for many years, with an inheritance rate of between 40% and 60%, it is not yet used as a risk factor in primary prevention models such as the Heart Card or the European SCORE. Recent advances in genomics and the use of clinical big data have allowed the development of genetic risk scores called Polygenic Risk Score (PRS), capable of identifying populations with average LDL-C levels, but with the same risk of heart attack of carriers of hypercholesterolaemia. The clinical usefulness of the PRS lies precisely in identifying high-risk individuals who are invisible to traditional models. The clinical applications of PRS for coronary artery disease are discussed in this report.

Artificial intelligence in cardiovascular prevention: new ways will open new doors

“…Cardiovascular diseases are part of complex or multifactorial diseases, in which numerous causes converge, not all of which are easily recognizable 1 …”

“…Accordingly, the research on cardiovascular prevention and risk stratification focuses, in addition to large genomic datasets, on biomarkers, 3 metabolic phenotypes, imaging, 4,5 both ultrasound and radiological, and on their integration, favoured by artificial intelligence applications 1,6 …”

“…Cardiovascular diseases are part of complex or multifactorial diseases, in which numerous causes converge, not all of which are easily recognizable. 1 Numerous advances have been made in the last 50 years in cardiovascular disease prevention; however, cardiovascular disease is still a significant cause of morbidity and mortality. 2 Over the past few decades, major cardiovascular disease risk factors have been identified and effective and well tolerated risk factor treatments have been developed.…”

“…Accordingly, the research on cardiovascular prevention and risk stratification focuses, in addition to large genomic datasets, on biomarkers, 3 metabolic phenotypes, imaging, 4,5 both ultrasound and radiological, and on their integration, favoured by artificial intelligence applications. 1,6 Accordingly, a basic knowledge of this science is essential; therefore, in this review, we have reported several applications of artificial intelligence in cardiovascular prevention, without neglecting the limitations of this new scientific approach.…”

Genetic influence on brain volume alterations related to self-reported childhood abuse

“…It is calculated according to the weighted accumulation of thousands of risk mutations carried by individuals, and aims to quantify the cumulative effects of a large number of SNPs or genes (Dudbridge, 2013). With the deepening of GWAS research and application transformation research, the application of the PRS model in risk assessment of common diseases has been verified (Dai et al, 2019;Boccanelli and Botta, 2021;Lu et al, 2021). However, at present, the clinical research of PRS in self-reported childhood maltreatment is still lacking.…”