Search PubMedSearch

Biomedical subjects

George Thanassoulis

Publications and source records attributed to George Thanassoulis.

2 recordsLinked to original sources

Lp(a) testing for the primary prevention of cardiovascular disease in high-income countries: a cost-effectiveness analysis.

BACKGROUND AND AIMS: Cost-effectiveness of Lipoprotein(a) [Lp(a)] testing is not established. We aimed to evaluate the cost-effectiveness of Lp(a) testing in the cardiovascular disease (CVD) primary prevention population from healthcare and societal perspectives. METHODS: We constructed and validated a multi-state microsimulation Markov model for a population of 10,000 individuals aged between 40 and 69 years without CVD, selected randomly from the UK Biobank. The model evaluated Lp(a) testing in individuals not initially classified as high-risk based on age, diabetes status, or the SCORE-2 algorithm. Those with an Lp(a) level ≥105 nmol/L (50 mg/dL) were treated as high risk (initiation of a statin plus blood pressure lowering). The Lp(a) testing intervention was compared to standard of care. The primary analyses were conducted from the Australian and UK healthcare perspectives in 2023AUD/GBP. A cost adaptation method estimated cost-effectiveness in multiple European countries, Canada, and the USA. RESULTS: Among 10,000 individuals, 1,807 had their treatment modified from Lp(a) testing. This led to 217 and 255 quality-adjusted life years gained in Australia and the UK, respectively, with corresponding incremental cost-effectiveness ratios of 12,134 (cost-effective) and -3,491 (cost-saving). From a societal perspective, Lp(a) testing saved $85 and £263 per person in Australia and the UK, respectively. Lp(a) testing was cost-saving among all countries tested in the cost adaptation analysis. CONCLUSIONS: Lp(a) testing in the primary prevention population to reclassify CVD risk and treatment is cost-saving and warranted to prevent CVD.

Humans

Distinct Genetic Risk Profile in Aortic Stenosis Compared With Coronary Artery Disease.

IMPORTANCE: Aortic stenosis (AS) and coronary artery disease (CAD) frequently coexist. However, it is unknown which genetic and cardiovascular risk factors might be AS-specific and which could be shared between AS and CAD. OBJECTIVE: To identify genetic risk loci and cardiovascular risk factors with AS-specific associations. DESIGN, SETTING, AND PARTICIPANTS: This was a genomewide association study (GWAS) of AS adjusted for CAD with participants from the European Consortium for the Genetics of Aortic Stenosis (EGAS) (recruited 2000-2020), UK Biobank (recruited 2006-2010), Estonian Biobank (recruited 1997-2019), and FinnGen (recruited 1964-2019). EGAS participants were collected from 7 sites across Europe. All participants were of European ancestry, and information on comorbid CAD was available for all participants. Follow-up analyses with GWAS data on cardiovascular traits and tissue transcriptome data were also performed. Data were analyzed from October 2022 to July 2023. EXPOSURES: Genetic variants. MAIN OUTCOMES AND MEASURES: Cardiovascular traits associated with AS adjusted for CAD. Replication was performed in 2 independent AS GWAS cohorts. RESULTS: A total of 18 792 participants with AS and 434 249 control participants were included in this GWAS adjusted for CAD. The analysis found 17 AS risk loci, including 5 loci with novel and independently replicated associations (RNF114A, AFAP1, PDGFRA, ADAMTS7, HAO1). Of all 17 associated loci, 11 were associated with risk specifically for AS and were not associated with CAD (ALPL, PALMD, PRRX1, RNF144A, MECOM, AFAP1, PDGFRA, IL6, TPCN2, NLRP6, HAO1). Concordantly, this study revealed only a moderate genetic correlation of 0.15 (SE, 0.05) between AS and CAD (P = 1.60 × 10-3). Mendelian randomization revealed that serum phosphate was an AS-specific risk factor that was absent in CAD (AS: odds ratio [OR], 1.20; 95% CI, 1.11-1.31; P = 1.27 × 10-5; CAD: OR, 0.97; 95% CI 0.94-1.00; P = .04). Mendelian randomization also found that blood pressure, body mass index, and cholesterol metabolism had substantially lesser associations with AS compared with CAD. Pathway and transcriptome enrichment analyses revealed biological processes and tissues relevant for AS development. CONCLUSIONS AND RELEVANCE: This GWAS adjusted for CAD found a distinct genetic risk profile for AS at the single-marker and polygenic level. These findings provide new targets for future AS research.

Humans