---
title: "Genistein modifies the association between EASIX and estimated 10-year ASCVD risk"
id: "plos-one-13-interaction-between-genistein-and-the-endothelial-activation-and-stress-index"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-13-interaction-between-genistein-and-the-endothelial-activation-and-stress-index"
content_type: "clinical_feed_article"
specialty: "Cardiology"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356477"
published_at: "2026-08-19T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Genistein modifies the association between EASIX and estimated 10-year ASCVD risk
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-13-interaction-between-genistein-and-the-endothelial-activation-and-stress-index
- **Specialty:** [Cardiology](https://medichelpline.com/clinical-feed/cardiology.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356477)
- **Published At:** 2026-08-19T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- This cross-sectional analysis used NHANES 1999–2010 data to examine the relationship between the **Endothelial Activation and Stress Index (EASIX)** and estimated 10-year atherosclerotic cardiovascular disease (**ASCVD**) risk, and whether urinary **genistein** modifies that relationship. - The analytic sample included 4,478 participants aged 40–79 after excluding those with prior cardiovascular disease and missing key laboratory or urinary genistein data. - EASIX was calculated as LDH (U/L) × creatinine (mg/dL) / platelet count (10^9/L) and evaluated on the log2-transformed scale. Urinary genistein (μg/g) was creatinine-normalized and dichotomized at the 75th percentile (cutoff 54.105 μg/g) into lower and higher exposure groups. - The outcome was estimated 10-year ASCVD risk classification derived from the 2013 ACC/AHA pooled cohort equation and categorized as <7.5% versus ≥7.5%. - In fully adjusted multivariable logistic regression, higher log2-EASIX was independently associated with increased odds of estimated 10-year ASCVD risk ≥7.5% (OR per unit increase = 1.407; 95% CI 1.208–1.640; P < 0.001). - A significant multiplicative interaction between EASIX and urinary genistein was observed (interaction OR = 1.66; 95% CI 1.17–2.35; P = 0.005), indicating effect modification by genistein strata. - Stratified analyses showed the association remained significant in both groups but was slightly attenuated in the higher-genistein group (OR = 1.360; 95% CI 1.066–1.736; P = 0.015) versus the lower-genistein group (OR = 1.397; 95% CI 1.202–1.624; P < 0.001). - Restricted cubic spline analyses revealed a non-linear S-shaped association in the lower-genistein group (P nonlinear = 0.020) and a predominantly linear relationship in the higher-genistein group (P nonlinear = 0.108). - The authors conclude that higher **EASIX** is associated with elevated estimated 10-year **ASCVD** risk and that urinary **genistein** modifies this association; they frame the results as hypothesis-generating and note the NHANES data and minimal dataset are publicly available (Figshare DOI provided).
## Clinical Analysis & Structured Key Points
Interaction between genistein and the endothelial activation and stress index in relation to estimated 10-year atherosclerotic cardiovascular disease risk classification | PLOS One Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Article Authors Metrics Comments Media Coverage Reader Comments Figures Figures Abstract Background The Endothelial Activation and Stress Index (EASIX) has been proposed as a marker of endothelial stress and may be associated with atherosclerotic cardiovascular disease (ASCVD) risk. Whether urinary genistein modifies this association remains unclear. Methods Multivariable logistic regression examined the association between EASIX and estimated 10-year ASCVD risk classification. Effect modification by urinary genistein (<54.105 vs. ≥ 54.105 μg/g) was assessed using interaction terms and stratified analyses. Restricted cubic splines (RCS) evaluated dose–response relationships. Results In the fully adjusted model, higher EASIX was independently associated with increased ASCVD risk (OR per unit increase = 1.407; 95% CI: 1.208–1.640; P < 0.001). A significant multiplicative interaction between EASIX and genistein was observed (OR = 1.66; 95% CI: 1.17–2.35; P = 0.005). Stratified analysis showed that this adverse association was slightly attenuated in the higher genistein group (OR = 1.360; 95% CI: 1.066–1.736; P = 0.015) compared to the lower group (OR = 1.397; 95% CI: 1.202–1.624; P < 0.001). RCS analyses showed a non-linear S-shaped association in the lower-genistein group ( P nonlinear = 0.020), whereas a predominantly linear relationship was observed in the higher-genistein group ( P nonlinear = 0.108). Conclusions Higher EASIX was associated with elevated estimated 10-year ASCVD risk classification, and this association differed across urinary genistein strata. These findings should be interpreted as hypothesis-generating. Citation: Guo X, Lin Y, Mi S, Yin Y (2026) Interaction between genistein and the endothelial activation and stress index in relation to estimated 10-year atherosclerotic cardiovascular disease risk classification. PLoS One 21(8): e0356477. https://doi.org/10.1371/journal.pone.0356477 Editor: Li Yang, Sichuan University, CHINA Received: August 21, 2025; Accepted: August 1, 2026; Published: August 19, 2026 Copyright: © 2026 Guo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The datasets generated and analysed during the current study are available in the [NHANES] repository, [National Health and Nutrition Examination Survey | National Health and Nutrition Examination Survey | CDC] (accessed on 2 May 2025). We have uploaded the minimal dataset required to replicate the findings of our study to figshare, a stable public repository. The dataset is now publicly available and can be accessed via the following DOI link: https://doi.org/10.6084/m9.figshare.31440001 . This dataset contains the core data supporting the results reported in our paper. We confirm that it is shared under the license terms specified in the repository. Funding: The author(s) received no specific funding for this work. Competing interests: NO authors have competing interests. 1. Introduction With the accelerated aging of the global population, atherosclerotic cardiovascular disease (ASCVD) is placing a substantial burden on public health worldwide [ 1 ]. Endothelial dysfunction is widely recognized as a key pathological mechanism underlying the development of ASCVD [ 2 – 3 ]. However, despite the significance of endothelial function assessment in clinical research, current diagnostic methods, such as flow-mediated vasodilation, still face challenges regarding accuracy, reproducibility, and the lack of reliable biomarkers to effectively reflect endothelial status [ 4 – 6 ]. Recently, the endothelial cell activation and stress index (EASIX) has emerged as a novel biomarker and has been applied in prognostic studies in fields such as cancer, infections, and liver diseases [ 7 – 9 ]. However, its application in ASCVD remains underexplored, particularly concerning its relationship with ASCVD risk. Additionally, genistein, a soy isoflavone, has been implicated in the development of metabolic diseases, neurodegenerative disorders, and cancer, potentially due to its anti-inflammatory properties and effects on apoptosis [ 10 – 12 ]. Evidence suggests that soy isoflavones may help prevent cardiovascular diseases (CVDs) by counteracting endothelial dysfunction [ 13 ]. Experimental studies have shown that genistein can improve the uncoupling of endothelial-type nitric oxide synthase, prevent pro-inflammatory factor-induced vascular endothelial barrier dysfunction, and inhibit the interactions between leukocytes and endothelial cells, thereby modulating vascular inflammation [ 14 – 16 ]. However, no studies have evaluated the association of genistein with ASCVD risk in the setting of endothelial dysfunction. Therefore, this study aimed to examine the association between EASIX and estimated 10-year ASCVD risk classification and to assess the potential interaction between genistein and EASIX with respect to this relationship. 2. Materials and methods 2.1 Study population In this cross-sectional study, data of participants were extracted from the National Health and Nutrition Examination Survey (NHANES) database in 1999–2010. The NHANES aims to evaluate health and nutritional status of representative populations in the United States. It collects information of approximately 5000 individuals regularly that carried out from 15 areas and examines in every two-year period since 1999, and utilizes a complex, multistage stratified probability sample based on selected counties, blocks, households, and persons within households. Well-trained professionals conduct interviews in person at their homes, and extensive physical examinations were conducted at mobile exam centers (MECs). This study was based on NHANES data, which received ethical approval from the National Center for Health Statistics (NCHS) Ethics Review Board. All participants gave written informed consent, and the survey followed the principles of the Declaration of Helsinki. The authors did not have access to any information that could identify individual participants at any point during or following data collection. The core dataset supporting the results reported in this manuscript is publicly available at Figshare via the following DOI: https://doi.org/10.6084/m9.figshare.31440001 . Individuals aged 40–79 years old in the database were included (n = 15994). The exclusion criteria were individuals with a history of cardiovascular disease (CVD) (n = 2246), individuals without information on lactate dehydrogenase (LDH), creatinine (Cr), or platelet count (n = 92), and individuals without a measurement of urine genistein (n = 9178). Finally, 4478 participants were eligible for further analysis ( Fig 1 ). Download: PNG larger image TIFF original image Fig 1. Flowchart of participants screening. https://doi.org/10.1371/journal.pone.0356477.g001 2.2 Outcome indicators ASCVD was defined according to the 2013 Guidelines for Cholesterol-Lowering Therapy to Reduce Atherosclerotic Cardiovascular Risk in Adults, published by the American College of Cardiology (ACC) and the American Heart Association (AHA) [ 17 ]. ASCVD is defined as the presence of at least one of the following conditions: coronary heart disease (CHD), angina pectoris, myocardial infarction, or stroke. The estimated 10-year ASCVD risk was calculated using a pooled cohort equation from the 2013 ACC/AHA guidelines [ 18 ]. This equation predicts the risk of stroke, nonfatal myocardial infarction, or death from coronary heart disease over the next 10 years in individuals aged 40–79 years with low-density lipoprotein cholesterol (LDL-C) levels <190 mg/dL and no history of ASCVD. The equation incorporates the following variables: age, sex, race, high-density lipoprotein cholesterol (HDL-C), total cholesterol, systolic blood pressure (SBP), use of antihypertensive medication, smoking status, and diabetes mellitus (DM). The estimated 10-year ASCVD risk classification was categorized as <7.5% and ≥7.5%, based on previous studies [ 19 – 20 ]. 2.3 Laboratory According to the laboratory guidelines of the NHANES, blood samples from the study subjects were collected by the staff of mobile examination centers (MECs) [ 21 ]. The blood samples were stored at approximately −30°C and transported to the Nutritional Biomarkers Unit of the Laboratory Sciences Division of NHANES for further analysis. EASIX score was calculated by the formula-LDH (U/L) × Cr (mg/dL) / platelet count (10 9 /L) and evaluated based on log2 transformed values. Urinary genistein concentrations (μg/g) were normalized using urinary creatinine (urinary genistein concentration in ng/mL divided by urinary creatinine concentration in mg/dL). In epidemiologic studies, the 75th percentile is typically used as the criterion for the high-exposure group. Based on previous epidemiological studies that categorized urinary genistein concentrations using quartiles, we prespecified the upper quartile as the threshold for defining higher urinary genistein exposure [ 22 – 23 ]. The corresponding cutoff of 54.105 μg/g was determined as the 75th percentile of urinary genistein in the current analytic sample. 2.4 Covariates Variables that could be potential confounding factors were also extracted from the database, including age, gender, race, educational level, marital status, poverty-to-income ratio (PIR), smoking, drinking, physical activity, total energy intake, diabetes mellitus (DM), hypertension, dyslipidemia, body mass index (BMI), antihypertensive medication use, lipid-lowering medication use, C-reactive protein (CRP) and uric acid (UA). In the NHANES, dietary information of participants was collected through two 24-hour dietary recalls, and consists of daily diet and supplements [ 24 ]. Well trained interviewers conducted the first 24-hour recall interview in person in the MEC, and the second interview was performed through telephone or mail 3–10 days later. Dietary variables were calculated as the mean of two 24-hour dietary recalls when both recalls were available and were based on the available single recall when only one recall was available. During the NHANES household interviews, participants who claimed to have smoked fewer than 100 cigarettes in their lives were divided into non-smoking group. The pattern of alcohol consumption was also captured by questionnaires [ 25 ]. Overweight was defined according to WHO criteria as a BMI of ≥25 kg/m 2 . Physical activity was converted into metabolic equivalent (MET), which was calculated according to the information collected by physical activity questionnaire in the NHANES. Energy expenditure (MET·min) = recommended MET × exercise time of corresponding activity (min), with the cutoff value of 450 MET·min/week. Hypertension diagnosis was through self-reported hypertension or systolic blood pressure (SBP) ≥130 mmHg or diastolic blood pressure (DBP) ≥80 mmHg or using antihypertensive agent. Patients with total cholesterol ≥200 mg/dL (5.2 mmol/L) or triglycerides ≥150 mg/dL (1.7 mmol/L) or low-density lipoprotein cholesterol ≥130 mg/dL (3.4 mmol/L) or high-density lipoprotein cholesterol ≤40 mg/dL (1.0 mmol/L) or self-reported hypercholesteremia or receiving lipid-lowering therapy were identified as dyslipidemia [ 26 ]. DM was defined according to a self-reported diagnosis, the use of oral hypoglycemic agents or insulin, HbAlc ≥ 6.5%, a plasma glucose level ≥200 mg/dL at 2 hours after the oral glucose tolerance test, or a fasting glucose level ≥126 mg/dL. 2.5 Statistical analyses Continuous variables were summarized as weighted means with standard errors (SEs) and were compared between the non-elevated and elevated estimated 10-year ASCVD risk classification groups using survey-weighted t tests. Categorical variables were summarized as unweighted numbers with weighted percentages and were compared using survey-weighted chi-square tests. In accordance with NHANES guidelines, appropriate MEC sample weights (WTMEC2YR and WTMEC4YR) were applied because multiple survey cycles were combined. Covariates associated with 10-year ASCVD risk were identified using weighted logistic regression and included in multivariable models when P < 0.05. Weighted univariate and multivariable logistic regression analyses were performed to examine the association between EASIX and estimated 10-year ASCVD risk classification, reported as odds ratios (ORs) with 95% confidence intervals (CIs). Interaction between genistein and EASIX was assessed using a multiplicative interaction term, followed by stratified analyses. Additionally, restricted cubic splines (RCS) were utilized to evaluate the potential non-linear dose-response relationships. Subgroup analyses were conducted by age, BMI, diabetes, hypertension, and dyslipidemia. Missing data for covariates with less than 20% missingness, including educational level, marital status, PIR, drinking status, physical activity, total energy intake, BMI, and CRP, were imputed using a random forest method prior to applying NHANES survey weights. Variables with substantial missingness were categorized as “unknown” when appropriate. Missing values were imputed only for covariates, whereas the main exposure variable, EASIX, and the primary outcome, elevated estimated 10-year ASCVD risk classification, were not imputed. All subsequent analyses incorporated NHANES survey weights. The proportions of missing values for key variables are provided in S1 Table , and the sensitivity analysis of participants’ characteristics before and after imputation of variables with missing values is provided in S2 Table . Statistical analyses were performed using R version 4.2.3. 3. Results 3.1 Characteristics of participants A comparison of the characteristics of participants between the low 10-year ASCVD risk group (n = 2157) and the high 10-year ASCVD risk group (n = 2321) is presented in Table 1 . The average age of total population was 54.26 years, 2185 (47.19%) of them were male. The mean values of EASIX in ASCVD <7.5% group were significantly lower than those in ASCVD ≥7.5% group (0.43 vs. 0.55). The average mean urine genistein concentrations in ASCVD <7.5% group were significantly higher than those in ASCVD ≥7.5% group (184.33 μg/g vs. 138.87 μg/g). In addition, the high-risk group tended to be older, male, hypertensive, diabetic, high cholesterol, and smokers (all P < 0.05). Download: PNG larger image TIFF original image Table 1. Characteristics of participants in low 10-year ASCVD risk group and high 10-year ASCVD risk group. https://doi.org/10.1371/journal.pone.0356477.t001 3.2 Associations of genistein and EASIX with estimated 10-year ASCVD risk classification Before we explored associations of genistein and EASIX with estimated 10-year ASCVD risk classification, covariates associated with 10-year ASCVD risk were screened ( S3 Table ). It was shown that age, educational level, marital status, PIR, physical activity, BMI, hypolipidemic drugs, CRP and UA were significantly associated with 10-year ASCVD risk (all P < 0.05). According to the Table 2 after adjusting for all selected covariates (model 3), continuous EASIX maintained a robust and independent positive association with the odds of 10-year ASCVD risk. Specifically, for every 1-point increase in the EASIX score, the odds ratio for 10-year ASCVD risk increases by 40.7% (OR = 1.407; 95% CI: 1.208–1.640; P < 0.001). Regarding urinary genistein levels, no statistically significant independent association with estimated 10-year ASCVD risk classification was noted in the fully adjusted model, with an OR of 1.22 (95% CI: 0.97–1.55; P = 0.091) for those with genistein < 54.105 μg/g compared to the reference group (≥54.105). Sensitivity analyses based on EASIX tertiles and median dichotomization showed generally consistent associations between higher EASIX levels and elevated estimated 10-year ASCVD risk classification ( S4 Table ). Download: PNG larger image TIFF original image Table 2. Associations of genistein and EASIX with estimated 10-year ASCVD risk classification. https://doi.org/10.1371/journal.pone.0356477.t002 3.3 Potential interaction effect of genistein on association between EASIX and estimated 10-year ASCVD risk classification The multiplicative interaction effect between EASIX and genistein was significant after adjusting for covariates (OR = 1.66, 95% CI: 1.17–2.35, P = 0.005) ( Table 3 ). Stratified analyses by urinary genistein levels revealed that continuous EASIX maintained a persistent positive association with estimated 10-year ASCVD risk classification in both strata, with a slight attenuation in risk magnitude observed in the higher genistein group ( Table 4 and Fig 2 ). In the fully adjusted Model 3 in Table 4 , each 1-unit increase in EASIX was associated with higher odds of being classified as having elevated estimated 10-year ASCVD risk classification among participants with lower creatinine-corrected urinary genistein levels (< 54.105 μg/g) (OR = 1.397; 95% CI: 1.202–1.624; P < 0.001). In comparison, this adverse effect was slightly blunted but remained statistically significant among those with higher genistein levels (≥ 54.105 μg/g), where each 1-unit increase in EASIX was associated with a 36.0% increase in the odds of estimated 10-year ASCVD (OR = 1.360; 95% CI: 1.066–1.736; P = 0.015). However, despite the statistically significant multiplicative interaction, the difference between the stratum-specific estimates was modest (OR = 1.397 vs. 1.360). Sensitivity analyses using tertile-based and median-based categorizations of EASIX showed results that were broadly consistent with those of the continuous EASIX analysis, although the magnitude and statistical significance of the associations varied across urinary genistein strata ( S5 Table ). Download: PNG larger image TIFF original image Table 3. Potential interaction effect of genistein on association between EASIX and estimated 10-year ASCVD risk classification. https://doi.org/10.1371/journal.pone.0356477.t003 Download: PNG larger image TIFF original image Table 4. Associations of EASIX with estimated 10-year ASCVD risk classification stratified by urinary genistein levels. https://doi.org/10.1371/journal.pone.0356477.t004 Download: PNG larger image TIFF original image Fig 2. Dose-response associations of EASIX with estimated 10-year ASCVD risk classification stratified by urinary genistein levels: a restricted cubic spline analysis. Dose-response associations of continuous EASIX with the risk of ASCVD stratified by urinary genistein levels (a: Genistein < 54.105 ug/g; b: Genistein ≥ 54.105 ug/g). Data were fitted using restricted cubic splines in logistic regression models with 4 knots. The solid blue lines represent the multi-variable adjusted Odds Ratios (ORs), and the light blue shaded areas represent the corresponding 95% confidence intervals. The horizontal dashed line indicates the reference line where OR = 1.0. Models were fully adjusted for age, educational level, marital status, PIR, physical activity, hypolipidemic drugs, BMI, CRP and UA.; EASIX, Endothelial Activation Sequential Organ Failure Assessment; PIR, poverty-to-income ratio; CRP, C-reactive protein; UA: uric acid. https://doi.org/10.1371/journal.pone.0356477.g002 Consistently, restricted cubic spline (RCS) curves further illustrated these patterns ( Fig 2 ). In the lower genistein group, EASIX displayed a significant non-linear S-shaped relationship ( P overall &l
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