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Shaping the future of Metabolic Syndrome: Genetics, prognosis and individual tailoring
Session:
Painel 12- Prevenção / Reabilitação Cardíaca 2
Speaker:
Joao Adriano Sousa
Congress:
CPC 2020
Topic:
J. Preventive Cardiology
Theme:
28. Risk Factors and Prevention
Subtheme:
28.3 Secondary Prevention
Session Type:
Posters
FP Number:
---
Authors:
Joao Adriano Sousa; Maria Isabel Mendonça; Andreia Pereira; Joel Ponte Monteiro; Margarida Temtem; Marina Santos; Flávio Mendonça; Ana Célia Sousa; Mariana Rodrigues; Eva Henriques; Ilídio Ornelas; Ana Isabel Freitas; A. Drumond de Freitas; Roberto Palma dos Reis
Abstract
<p><strong>Background:</strong> Metabolic Syndrome (MetS), characterized by a cluster of cardiovascular risk factors, is considered to be the major health hazard of modern world and a 21st century epidemic. Recent GWAS have identified several susceptibility regions involved in lipid metabolism and oxidation, also associated with MetS. Genetic risk score (GRS) is an emerging method that attempts to establish correlation between SNPs and clinical phenotypes.</p> <p><strong>Aim:</strong> Evaluate the value of a GRS encompassing SNPs involved in lipidic metabolism and oxidation pathways, in predicting CAD outcome (MACEs and long-term cardiovascular Mortality) in a coronary population with Metabolic Syndrome (MetS).</p> <p><strong>Methods: </strong>1101 coronary patients with MetS, were selected from the GENEMACOR study. Genotyping was performed by TaqMan allelic discrimination assay. A multiplicative score (mGRS) was built according to the multiplicative model with variants belonging to the lipid and oxidative axes (PSRC1, PCSK9, KIF6, ZNF259, LPA, APO E, PON192, PON108, PON55, MTHFR677, MTHFR1298, MTHFD1L). This GRS was categorized using the mean (higher vs lower than mean). Cumulative Mortality Hazards Model (Cox regression) adjusted for - age, gender, smoking, hypertension, dyslipidaemia, diabetes, hsCRP, eGFR, Ejection fraction (EF), and multivessel disease- was used to find independent predictors of cardiovascular outcome. We performed Kaplan-Meier Survival curves for both groups (higher vs lower than mean GRS) and used log-rank test to compare survival distributions in both groups.</p> <p><strong>Results: </strong>The following variables have emerged as independently associated with <u>time to MACE</u> occurrence: <strong>mGRS </strong>(HR=1.31, 95%CI(1.07;1.59); p=0.008), <strong>male gender</strong>, <strong>EF </strong>and <strong>multivessel disease</strong>. Concerning <u>cardiovascular mortality</u>, <strong>mGRS </strong>also remained an independent predictor (HR=1.44, 95%CI(1.04-1.99); p=0.028) alongside <strong>age</strong>, <strong>smoking</strong>, <strong>diabetes </strong>and <strong>EF</strong>. The Log-Rank test showed significant differences between the two curves related to MACE occurrence and cardiovascular mortality (p=0.001 and 0.002, respectively). The Kaplan-Meier survival showed that as <u>mGRS increases</u>, patient <u>survival decreases</u>.</p> <p><strong>Conclusion</strong>: In patients with Metabolic Syndrome, a GRS comprising variants in lipidic and oxidative pathways, proved to be a useful stratification tool, identifying patients likely to have a worst prognosis over time. Our data further underlines the additive potential and clinical utility of genetic information in shaping secondary prevention.</p> <p> </p>
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