Using Genomics to Develop Personalized Cardiovascular Treatments DOI
Mihir M. Sanghvi, William J. Young, Hafiz Naderi

et al.

Arteriosclerosis Thrombosis and Vascular Biology, Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Advances in genomic technologies have significantly enhanced our understanding of both monogenic and polygenic etiologies cardiovascular disease. In this review, we explore how the utilization information is bringing personalized medicine approaches to forefront disease management. We discuss data can resolve diagnostic uncertainty, support cascade screening, inform treatment strategies. The role that genome-wide association studies had identifying thousands risk variants for diseases, these insights, harnessed through development scores, could advance prediction beyond traditional clinical algorithms. detail pharmacogenomics leverage genotype guide drug selection mitigate adverse events. Finally, present paradigm-shifting approach gene therapy, which holds promise being a curative intervention conditions.

Language: Английский

Rolle der Genetik in der Präzisionsmedizin der koronaren Herzkrankheit DOI
Veronika Sanin,

R Schmieder,

Wolfgang Köenig

et al.

Herz, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 28, 2025

Language: Английский

Citations

0
Risk in Repose: Sedentary Behavior and Genetic Susceptibility to Cardiovascular Disease DOI Creative Commons
J. Sawalla Guseh, Ezimamaka Ajufo

Journal of the American Heart Association, Journal Year: 2025, Volume and Issue: unknown

Published: March 14, 2025

Language: Английский

Citations

0
Chronic Inflammatory Diseases and Cardiovascular Risk: Current Insights and Future Strategies for Optimal Management DOI Open Access
Stefano Cacciatore, Silvia Andaloro, Marco Bernardi

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(7), P. 3071 - 3071

Published: March 27, 2025

Chronic inflammation is a pivotal driver in the progression of atherosclerosis, significantly contributing to burden cardiovascular disease (CVD). Patients with chronic inflammatory diseases, such as bowel diseases (IBDs) (e.g., ulcerative colitis and Crohn's disease), rheumatological disorders, well individuals auto-immune (such systemic lupus erythematosus), present higher risk major adverse cardiac events (MACEs). Despite their elevated CVD risk, these populations remain underrepresented research, leading critical underestimation (CVR) clinical practice. Furthermore, even recent CVR scores poorly predict specific populations. This narrative review examines physiopathological mechanisms linking inflammation, immunomodulation, thrombosis events. We data from epidemiological studies trials explore potential benefits anti-inflammatory immunomodulatory therapies. existing evidence, significant gaps knowledge remain. Future research mandatory, focusing on innovative strategies for stratification optimization, including lipidomics, proteomics, advanced markers, microbiota profiling, imaging. Addressing unmet needs will enhance understanding enabling tailored interventions better outcomes.

Language: Английский

Citations

0
Development and validation of a risk prediction algorithm for high-risk populations combining genetic and conventional risk factors of cardiovascular disease DOI Creative Commons
Tuuli Jürgenson, Ave Põld, Lili Milani

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: April 4, 2025

Abstract Aim To develop a model for cardiovascular disease (CVD) risk, combining polygenic risk score (PRS) with traditional factors while assessing the added value of PRS in two cohorts biobank participants. Methods Data 128 209 participants from Estonian Biobank recruited between 2003– 2011 and 2018–2019 without prevalent disease, was included. Hazard ratios (HR) versus conventional were estimated Cox proportional hazards models, cumulative incidence assessed Aalen-Johansen curves. Predictive performance tested using split-sample approach competing modelling. Age at CVD event served as outcome, impact evaluated by age group (25–59 vs. 60+), sex, recruitment period, HRs, Harrell’s C-index, net reclassification indices (NRI). Results The HR per one standard deviation (SD) ranged 1.1, 95% CI 1.06–1.15 (age 60+, earlier cohort) to 1.36, 1.24–1.49 (men 25–59, later cohort). Adding 25–59 increased C-statistic 0.028 (p<0.0001) men. In increase 0.016 (p=0.0002) across all. independent validation set, continuous NRI 19.1% (95% 13.3%–24.9%) 13.9% 8.1%–19.6%) 60+ group. Conclusions high-risk population, is strong factor should be considered routine assessment, starting relatively young age.

Language: Английский

Citations

0
Translation of genomics into routine cardiological practice: from polygenic risk scores to nucleic acid-based treatments DOI
Filippo Crea

European Heart Journal, Journal Year: 2025, Volume and Issue: 46(15), P. 1361 - 1364

Published: April 14, 2025

Language: Английский

Citations

0
Using Genomics to Develop Personalized Cardiovascular Treatments DOI
Mihir M. Sanghvi, William J. Young, Hafiz Naderi

et al.

Arteriosclerosis Thrombosis and Vascular Biology, Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Advances in genomic technologies have significantly enhanced our understanding of both monogenic and polygenic etiologies cardiovascular disease. In this review, we explore how the utilization information is bringing personalized medicine approaches to forefront disease management. We discuss data can resolve diagnostic uncertainty, support cascade screening, inform treatment strategies. The role that genome-wide association studies had identifying thousands risk variants for diseases, these insights, harnessed through development scores, could advance prediction beyond traditional clinical algorithms. detail pharmacogenomics leverage genotype guide drug selection mitigate adverse events. Finally, present paradigm-shifting approach gene therapy, which holds promise being a curative intervention conditions.

Language: Английский

Citations

0