Biomarkers for Cardiovascular Risk Prediction in Latino Adults: A Scoping Review

Cardiovascular disease is the leading cause of mortality worldwide, with around 80% of deaths occurring in low- and middle-income countries (1). As it is a process that takes years to develop, research has focused on identifying prevention strategies that detect risk, defined as the likelihood of a person developing an atherosclerotic cardiovascular disease (ASCVD) event over a specified period, and allow for early intervention (2). Stratification has been done traditionally using risk factors such as sex, tobacco use, dyslipidemia and obesity, with prediction models that determine cardiovascular risk estimates; even though these tools are accessible and easy to use, they have limitations in discrimination and calibration (3). In this context, many biomarkers have been proposed. They were defined by the BEST (Biomarkers, Endpoints, and other Tools) Resource in 2016, as “A defined characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or biological responses to an exposure or intervention, including therapeutic interventions. Biomarkers may include molecular, histologic, radiographic, or physiologic characteristics.” (4). Biomarkers provide many advantages: they are precise, introduce less bias than questionnaires, and they can be measured in all patients as surrogate clinical endpoints, in contrast to clinical endpoints which are often rare (5). They also provide early data that can be used to initiate interventions upstream. However, issues regarding standardization, clinical utility, cost-effectiveness, and feasibility of their measurement often persist (6). Proposed biomarkers have two profiles. The first one are biomarkers such as troponin and brain natriuretic peptide (BNP), which are widely used in cardiology for diagnosis, and are now being studied for predicting outcomes (7,8). On the other hand, it has been proposed that circulating levels of novel biomarkers, particularly those derived from multi-omics technologies (genomics, proteomics, metabolomics), could indicate cardiometabolic alterations before clinical manifestations appear (9). These technologies offer a detailed view of the biological pathways involved in atherosclerosis beyond traditional risk factors (10). Not until recently, it was considered that risk factors were similar among all populations (11). However, as knowledge has progressed, it is clear that differences are marked by multiple variables, including people origins, which can be reported as race (not terminologically correct nowadays), ethnicity or ancestry, depending on the measurement (12–14). Summarized evidence has identified potential biomarkers for cardiovascular risk stratification; however, most information comes from Caucasic population (15). Differential factors such as genetics and environmental impact biomarker expression, and the lack of knowledge limits the application of models and scores as they are based on non-Hispanic population (16). Thus, this phenomenon generates a gap in the path to personalized medicine, especially in the omics field. However, there are some examples that include Latino population in biomarker research; for example, a cohort named The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) aimed to determine the distribution of lipoprotein(a) levels among 16.415 Latino adults from different geographic and cultural backgrounds living in the US. Lp(a) is a mainly monogenic determined biomarker and a strong, independent ASCVD risk factor. They divided Lp(a) levels into quintiles and compared them with self-identified geographic and cultural backgrounds and median percentage of genetic ancestry (Amerindian, European, West African). Regarding self-reported background, the highest median (IQR) Lp(a) values were seen in Cuban (30.4 [9.2-78.6] nmol/L), Dominican (41 [13.8-89.7] nmol/L), or Puerto Rican (28 [9.4-73.6] nmol/L) background (Figure 2). Lower median (IQR) Lp(a) values were noted in those self-identifying as Central American (16.5 [6.8-44.5] nmol/L), Mexican (12.4 [5.7-38.2] nmol/L), or South American (15.1 [6.7-59.1] nmol/L) background (P < .001). On the other hand, ancestry analysis reported the lowest West African genetic ancestry in the first quintile of Lp(a) level and the highest in the fifth quintile, (5.5% [3.4%-12.9%] and 12.1% [5.0%-32.5%]; respectively; P < .001); the converse was seen for Amerindian ancestry (32.8% [9.9%-53.2%] and 10.7% [4.9%-30.7%], respectively; P < .001). It concluded that Lp(a) levels varied significantly depending on both self-reported background and ancestry ( 18). Further, models considering biomarkers difference by ethnicity have been proposed; the cohort MESA (Multi-Ethnic Study of Atherosclerosis), composed by subjects without a prior history of clinical CVD, evaluated baseline levels of biomarkers (C-reactive protein (CRP), fibrinogen, interleukin-6 (IL-6), D-dimer, plasmin–antiplasmin complex (PAP) and factor VIII), and traditional risk factors characteristics for 6067 adults from 4 different ethnicities, and compared them compared using chi-square test for categorical variables and one-way ANOVA test for continuous variables. Baseline distributions of both biomarkers and traditional risk factors were heterogeneous among ethnic cohorts. They divided biomarkers distributions by quartiles, finding for Hispanics that IL-6, fibrinogen and CRP tend to be in the higher quartiles. After, they determined as primary end point the first incidence of all CVD events (myocardial infarction (MI), resuscitated cardiac arrest, definite angina, probable angina (if followed by revascularization), stroke, stroke death, coronary heart disease (CHD) death or other atherosclerotic death). Posteriorly, they followed the subjects for 4.6 years and calculated the cumulative incidence for CVD events stratified by each ethnicity. An ethnicity-stratified crude and adjusted multivariate Cox proportional hazard model analysis was performed to characterize the predictive role of novel biomarkers for all CVD events across ethnic sub-cohorts. For all subcohorts, it was found that being in the higher quartile of biomarkers levels was correlated with a higher incidence of CVD events. Additionally, they found differential associations for each biomarker in each sub cohort; for example, for Hispanics, they found an statistically significant HR of 4.16 [1.23–14.1] for fibrinogen in the model that integrated the biomarker with traditional risk factors and Framingham score (17). However, research focusing in Latino population is not synthetized, consequently, the objective of this review is to identify and systematically synthesize potential biomarkers and omics signatures for cardiovascular risk stratification in Latino adults. References 1. Di Cesare M, Perel P, Taylor S, Kabudula C, Bixby H, Gaziano TA, et al. The Heart of the World. Glob Heart. 25 de enero de 2024;19(1):11. 2. Catapano AL. Treatment Guidelines Overview. En: Clinical Lipidology [Internet]. Elsevier; 2024 [citado 16 de diciembre de 2025]. p. 113-121.e2. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/B9780323882866000133 3. 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