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. 2025 Nov 26;399(5):6791–6802. doi: 10.1007/s00210-025-04779-4

Regulating effect of genistein on the association of endothelial activation and stress index with atherosclerotic cardiovascular disease risk: a cross-sectional study of the NHANES database

Yongliang Huang 1,✉, Huijuan Lan 2, Hongchuan Yang 3
PMCID: PMC13053385  PMID: 41296032

Abstract

The aim of this study is to assess the associations of urinary genistein and endothelial activation and stress index (EASIX) with 10-year atherosclerotic cardiovascular disease (ASCVD) risk. This cross-sectional analysis employed data obtained from the National Health and Nutrition Examination Survey (NHANES). Weighted univariable and multivariable logistic regression models examined EASIX–ASCVD risk correlations, with odds ratio and 95% confidence interval [OR (95%CI)] as effect measures. The potential interactions were explored between EASIX and genistein on 10-year ASCVD risk using additive and multiplicative interaction analyses. The relationships of EASIX and 10-year ASCVD risk were further assessed at different genistein levels. Subgroup analyses examined age, BMI, diabetes, hypertension, and dyslipidemia categories. Totally, 4478 eligible participants were stratified into low-risk (n = 2157) and high-risk (n = 2321) ASCVD groups. Elevated levels of EASIX (OR = 1.35, 95% CI 1.18–1.54), EASIXmedian ≥ 0.427 (OR = 1.40, 95% CI 1.14–1.73), EASIXRCS ≥ 0.434 (OR = 1.45, 95% CI 1.18–1.77), EASIXquartile (0.325–0.427, OR = 1.48, 95% CI 1.05–2.07; 0.427–0.567, OR = 1.51, 95% CI 1.08–2.10; ≥ 0.567, OR = 2.08, 95% CI 1.57–2.77), and log2(EASIX) (OR = 1.32, 95% CI 1.19–1.46) were associated with higher odds of 10-year ASCVD. Low genistein levels presented no significant correlation with 10-year ASCVD risk. The multiplicative interaction between EASIX and genistein levels was significant. When genistein levels < 54.105 µg/g, the connections between elevated EASIX levels and higher 10-year ASCVD risk were established in subgroups of age < 60 years, BMI ≥ 25 kg/m2, non-diabetes, hypertension, and dyslipidemia. Elevated EASIX levels correlated with a higher 10-year ASCVD risk. Whether genistein modulates this association requires further validation, which may have potential implications for ASCVD prevention strategies in the general population.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00210-025-04779-4.

Keywords: Genistein, EASIX, 10-year ASCVD risk, NHANES, Regulating effect

Introduction

With the acceleration of population aging, atherosclerotic cardiovascular disease (ASCVD) has emerged as a substantial worldwide health burden (Nedkoff et al. 2023). Impaired endothelial function represents a key pathophysiological component in ASCVD development (Gimbrone and Garcia-Cardena 2016; Xu et al. 2021). However, at present, there is no recognized biomarker reflecting endothelial function, and the accuracy of the detection of endothelial function (flow-mediated dilation) is affected by the operator, and the repeatability needs to be improved (Zhang 2022; Leite et al. 2020; Mucka et al. 2022). Recently, the endothelial activation and stress index (EASIX), a newly established endothelial dysfunction marker, has emerged as a prognostic tool for patients with cancer, infection, and liver disorders (Kordelas et al. 2023; Luft et al. 2021; Schult et al. 2023; Estler et al. 2025). Nevertheless, existing studies have not yet addressed the potential link between EASIX and ASCVD.

Genistein, a soybean-derived isoflavone, is associated with metabolic disorders, neurodegenerative conditions, and cancers, potentially through its anti-inflammatory properties and modulation of apoptotic pathways (Mukund et al. 2017; Nicastro et al. 2013; Mas-Bargues et al. 2022). Evidence has shown that soy isoflavones may prevent cardiovascular diseases (CVDs) through inhibiting endothelial dysfunction (Yamagata 2019). Studies reveal genistein’s ability to correct endothelial nitric oxide synthase dysfunction, maintain endothelial integrity during inflammation, and limit leukocyte adhesion, ultimately controlling vascular inflammation (Zhang et al. 2016; Si and Liu 2007; Babu et al. 2012). However, no studies have investigated whether genistein influences the risk of ASCVD associated with endothelial function impairment.

Herein, this investigation intended to examine EASIX-ASCVD risk connections and genistein’s possible regulatory effects, providing preventive implications for ASCVD.

Methods

Study design and participants

Study data were obtained from the 1999–2010 NHANES database for cross-sectional analysis. The NHANES employs a multistage sampling methodology to select representative populations for evaluating the health and nutritional conditions of the US population (https://wwwn.cdc.gov/nchs/nhanes/).

Database records for individuals aged 40 to 79 were analyzed. The exclusion criteria consisted of (1) individuals with CVD history, (2) individuals without information on lactate dehydrogenase (LDH), creatinine (Cr) or platelet, (3) individuals with missing data for calculation of 10-year ASCVD risk, and (4) individuals without measurement of urine genistein. Finally, 4478 participants were eligible for further analysis. The NHANES study protocol received Institutional Review Board (IRB) approval from the National Center for Health Statistics (NCHS). Ethical review was waived by our IRB given the database’s public availability and regulatory provisions.

Examination of urine genistein and calculation of EASIX

Urinary Cr levels were determined in NHANES participants via the Roche/Hitachi Modular P Chemistry Analyzer (Roche Diagnostics, Indianapolis, IN, USA). Human urine samples underwent enzymatic deconjugation of glucuronidated genistein, followed by reversed-phase high-performance liquid chromatography separation, atmospheric pressure photoionization–tandem mass spectrometry detection, and isotope dilution quantification. Genistein levels in urine (μg/g) were creatinine-adjusted by dividing ng/mL genistein concentrations by mg/dL creatinine values (Marcelo et al. 2019). In this study, urinary genistein concentrations were categorized into two levels according to the upper tertile value.

Consistent with NHANES laboratory standards, mobile exam centers (MEC) technicians collected all participant blood samples (Yamazaki et al. 2010). After temporary storage at − 30 °C, all samples were transferred to the biomarker laboratory for comprehensive analysis. EASIX score was computed as [LDH (U/L) × Cr (mg/dL)]/platelets (10⁹/L). In this study, EASIX groups were considered continuous EASIX, median (EASIXmedian), quartile (EASIXquartile), continuous log2(EASIX), and RCS inflection point of EASIX (EASIXRCS).

Assessment of 10-year ASCVD risk

ASCVD was defined as at least one diagnosis of coronary heart disease (CHD), angina, heart attack, or stroke following the ACC/AHA 2013 guidelines (Stone et al. 2013). ASCVD 10-year risk was estimated using the ACC/AHA 2013 pooled cohort equations (Goff et al. 2014), predicting stroke, nonfatal myocardial infarction, and coronary artery disease mortality in adults (40–79 years) with low-density lipoprotein (LDL) < 190 mg/dL and no prior ASCVD. This equation considers age, gender, race, high-density lipoprotein cholesterol (HDL-C), total cholesterol, systolic blood pressure (SBP), the use of hypertension drugs, smoking habits, and diabetes. The 10-year ASCVD risk was categorized as < 7.5% (low-risk) and ≥ 7.5% (high-risk) according to a previous study (Grundy et al. 2019).

Variables selection

Potential confounders retrieved from the dataset comprised age, gender, race, educational level, marital status, poverty-to-income ratio (PIR), smoking, drinking, physical activity, hypertension, anti-hypertension drugs, diabetes, dyslipidemia, anti-dyslipidemia drugs, chronic kidney disease (CKD), estimated glomerular filtration rate (eGFR), colchicine, GLP-1 receptor agonists, C-reactive protein (CRP) and uric acid, body mass index (BMI), dietary live microbe intake, total energy intake, and healthy eating index (HEI)−2015.

In the NHENAS, dietary information of participants was collected through two 24-h dietary recalls and consists of daily diet and supplements (Wang et al. 2021). Well-trained interviewers administered the initial 24-h dietary recall face-to-face at the MEC, with follow-up interviews conducted via telephone or postal mail within 3–10 days. Individuals reporting lifetime cigarette consumption below 100 were classified as non-smokers. Alcohol consumption patterns were examined through survey questionnaires (Niezen et al. 2021). Overweight/obesity classification followed the WHO standards (BMI ≥ 25 kg/m2). Physical activity questionnaire data were used to compute metabolic equivalents (METs). Energy expenditure (MET-min/week) was derived by multiplying activity-specific MET values by duration, with 450 MET-min/week as the threshold. The diagnosis of hypertension, dyslipidemia, and diabetes incorporated self-reported data, lab results, and medication records (Jellinger et al. 2012). Dietary live microbe intake was calculated as the amount of medium- and high-level food consumed per person, in units of 100 g, and was defined as MedHi (Marco et al. 2022; Huo et al. 2024). MedHi was also converted to categorical variables for analysis: low MedHi, people who did not consume any MedHi food; median MedHi, people with a median diet below the median; and high MedHi, individuals whose MedHi intake exceeded the median.

Statistical analyses

The proportion of missing data has been shown in Table S1. The comparison for missing data before and after imputation using a multiple imputation method has been presented in Table S2. Continuous data were summarized as mean ± standard error (mean ± SE) and compared between groups via t-test. Categorical data were presented as frequency with constituent ratio N (%) and compared between groups via chi-square test (χ2). According to the NHANES guidelines, the 2-year MEC sample weights (WTMEC2YR) and 4-year MEC sample weights (WTMEC4YR) should be used for analysis because we combined data from different year cycles in this study.

Covariates connected to 10-year ASCVD risk were screened and selected using a weighted logistic regression model. Significant variables (P < 0.05) were identified as covariates and incorporated into the multivariable models. The connection between EASIX and 10-year ASCVD risk was examined through weighted univariable and multivariate logistic regression, with results summarized as odds ratios and 95% confidence intervals [OR (95% CI)]. The potential interactions were explored between EASIX and genistein on 10-year ASCVD risk using additive [relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI)] and multiplicative interaction analyses. The relationships of EASIX and 10-year ASCVD risk were further assessed at different genistein levels. Additionally, subgroup analyses examined age, BMI, diabetes, hypertension, and dyslipidemia categories. The subgroup analyses have been performed using Bonferroni correction. Statistical analysis was conducted using R version 4.2.3 (Institute for Statistics and Mathematics, Vienna, Austria).

Results

Characteristics of participants

Figure 1 illustrates the participant screening flowchart. The NHANES 1999–2010 included 15,994 participants aged 40–79 years. Those who had a CVD history (n = 2246), without measurements of LDH, Cr, or platelet (n = 92), or without information on urine genistein (n = 9178) were excluded. Finally, 4478 participants were eligible for further analysis.

Fig. 1.

Fig. 1

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Flowchart of participants screening

Characteristic comparisons of low-risk (n = 2157) and high-risk (n = 2321) ASCVD groups appear in Table 1. The study population had a mean age of 54.26 years, with 2185 males (47.19%). Significant differences were observed between groups for age, gender, race, educational level, marital status, PIR, smoking, physical activity, hypertension, anti-hypertension drugs, diabetes, dyslipidemia, anti-dyslipidemia drugs, CKD, eGFR, GLP-1 receptor agonists, uric acid, and BMI (all P < 0.05). The EASIX score and log2(EASIX) value were significantly higher in the high-risk ASCVD group [EASIX = 0.53, log2(EASIX) =  − 1.05] versus the high-risk ASCVD group [EASIX = 0.43, log2(EASIX) =  − 1.35], respectively. The proportions of individuals with EASIXmedian ≥ 0.427, EASIXRCS ≥ 0.434, and EASIXquartile ≥ 0.567 were higher in the high-risk ASCVD group than those in the low-risk ASCVD group. Urinary genistein levels were significantly elevated in the low-risk ASCVD patients versus high-risk ASCVD patients (184.33 µg/g vs. 138.87 µg/g).

Table 1.

Characteristics of participants in the two groups

Variables Total (N = 4478) Low-risk ASCVD (n = 2157) High-risk ASCVD (n = 2321) Statistics P
Age, years, mean (± S.E) 54.26 (± 0.23) 48.55 (± 0.16) 61.85 (± 0.31) t = 41.728  < 0.001
Gender, n (%) χ2 = 280.196  < 0.001
  Male 2185 (47.19) 756 (35.60) 1429 (62.59)
  Female 2293 (52.81) 1401 (64.40) 892 (37.41)
Race, n (%) χ2 = 3.924 0.009
  Non-Hispanic White 2186 (75.08) 1007 (73.75) 1179 (76.84)
  Non-Hispanic Black 884 (9.67) 438 (10.30) 446 (8.83)
  Mexican American 938 (5.88) 484 (6.65) 454 (4.86)
  Other Hispanic 307 (4.70) 137 (4.16) 170 (5.40)
  Other race-including multi-racial 163 (4.68) 91 (5.14) 72 (4.06)
Education level, n (%) χ2 = 66.653  < 0.001
  Above high school 2064 (56.38) 1146 (62.38) 918 (48.41)
  High school and below 2414 (43.62) 1011 (37.62) 1403 (51.59)
Marital status, n (%) χ2 = 2.713 0.103
  Married 2935 (69.91) 1456 (71.16) 1479 (68.26)
  Unmarried 1543 (30.09) 701 (28.84) 842 (31.74)
PIR, n (%) χ2 = 10.590  < 0.001
  < 1.3 1049 (13.94) 443 (12.04) 606 (16.47)
   ≥ 1.3 3074 (78.92) 1566 (81.62) 1508 (75.33)
  Unknown 355 (7.14) 148 (6.34) 207 (8.20)
Smoking, n (%) χ2 = 219.218  < 0.001
  No 2237 (50.32) 1397 (63.75) 840 (32.47)
  Yes 2241 (49.68) 760 (36.25) 1481 (67.53)
Drinking, n (%) χ2 = 0.041 0.954
  Never 1349 (26.46) 679 (26.66) 670 (26.19)
  Occasional 1752 (38.43) 813 (38.32) 939 (38.58)
  Frequent 1377 (35.11) 665 (35.01) 712 (35.23)
Physical activity, n (%) χ2 = 6.922 0.002
  < 600 673 (15.93) 336 (16.69) 337 (14.93)
  ≥ 600 1677 (40.18) 878 (42.64) 799 (36.92)
  Unknown 2128 (43.88) 943 (40.68) 1185 (48.14)
Hypertension, n (%) χ2 = 310.148  < 0.001
  No 1545 (38.99) 1116 (52.79) 429 (20.66)
  Yes 2933 (61.01) 1041 (47.21) 1892 (79.34)
Anti-hypertension drugs, n (%) χ2 = 265.136  < 0.001
  No 2843 (68.33) 1726 (80.76) 1117 (51.81)
  Yes 1635 (31.67) 431 (19.24) 1204 (48.19)
Diabetes, n (%) χ2 = 262.802  < 0.001
  No 3649 (87.14) 2009 (95.21) 1640 (76.42)
  Yes 829 (12.86) 148 (4.79) 681 (23.58)
Dyslipidemia, n (%) χ2 = 125.187  < 0.001
  No 930 (20.77) 620 (28.03) 310 (11.12)
  Yes 3548 (79.23) 1537 (71.97) 2011 (88.88)
Anti-dyslipidemia drugs, n (%) χ2 = 119.525  < 0.001
  No 3417 (78.04) 1859 (85.98) 1558 (67.50)
  Yes 1061 (21.96) 298 (14.02) 763 (32.50)
CKD, n (%) χ2 = 127.693  < 0.001
  No 3742 (87.43) 1963 (92.79) 1779 (80.31)
  Yes 736 (12.57) 194 (7.21) 542 (19.69)
  eGFR, Mean (± S.E) 92.04 (± 0.33) 96.31 (± 0.40) 86.37 (± 0.51) t =  − 14.966  < 0.001
Colchicine, n (%) χ2 = 1.277 0.262
  No 4463 (99.72) 2154 (99.83) 2309 (99.58)
  Yes 15 (0.28) 3 (0.17) 12 (0.42)
GLP-1 receptor agonists, n (%) χ2 = 5.448 0.022
  No 4472 (99.87) 2155 (99.96) 2317 (99.75)
  Yes 6 (0.13) 2 (0.04) 4 (0.25)
CRP, mg/dL, mean (± S.E) 0.42 (± 0.01) 0.39 (± 0.02) 0.46 (± 0.02) t = 2.573 0.012
Uric acid, mg/dL, mean (± S.E) 5.41 (± 0.03) 5.11 (± 0.04) 5.81 (± 0.04) t = 15.008  < 0.001
BMI, n (%) χ2 = 59.591  < 0.001
  < 25 kg/m2 1135 (28.71) 643 (34.21) 492 (21.40)
  ≥ 25 kg/m2 3343 (71.29) 1514 (65.79) 1829 (78.60)
Live microbe intake, n (%) χ2 = 1.611 0.189
  Low MedHi 1167 (24.24) 527 (22.93) 640 (25.99)
  Median MedHi 1048 (23.84) 513 (23.54) 535 (24.23)
  High MedHi 1396 (33.93) 703 (35.54) 693 (31.79)
  Unknown 867 (17.99) 414 (17.99) 453 (17.99)
Total energy intake, kcal, mean (± S.E) 2085.08 (± 15.07) 2107.23 (± 21.97) 2055.65 (± 23.48) t =  − 1.513 0.134
HEI-2015, mean (± S.E) 52.39 (± 0.32) 52.24 (± 0.37) 52.57 (± 0.41) t = 0.739 0.462
EASIX, mean (± S.E) 0.47 (± 0.00) 0.43 (± 0.00) 0.53 (± 0.01) t = 14.365  < 0.001
EASIXmedian, n (%) χ2 = 156.112  < 0.001
  < 0.427 2139 (49.98) 1269 (58.61) 870 (38.50)
  ≥ 0.427 2339 (50.02) 888 (41.39) 1451 (61.50)
EASIXRCS, n (%) χ2 = 166.051  < 0.001
  < 0.434 2188 (51.05) 1292 (59.68) 896 (39.59)
  ≥ 0.434 2290 (48.95) 865 (40.32) 1425 (60.41)
EASIXquartile, n (%) χ2 = 72.264  < 0.001
  < 0.325 1101 (25.00) 721 (32.16) 380 (15.48)
  0.325–0.427 1038 (24.98) 548 (26.45) 490 (23.02)
  0.427–0.567 1107 (25.01) 493 (23.28) 614 (27.32)
   ≥ 0.567 1232 (25.01) 395 (18.11) 837 (34.18)
Log2(EASIX), mean (± S.E)  − 1.22 (± 0.01)  − 1.35 (± 0.01)  − 1.05 (± 0.02) t = 15.773  < 0.001
Genistein, µg/g, mean (± S.E) 164.81 (± 12.67) 184.33 (± 18.38) 138.87 (± 14.55) t =  − 2.023 0.046
Genistein, n (%) χ2 = 1.015 0.316
  ≥ 54.105 1422 (33.32) 691 (34.08) 731 (32.30)
  < 54.105 3056 (66.68) 1466 (65.92) 1590 (67.70)
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t t-test, χ2 chi-square test, SE standard errorASCVD atherosclerotic cardiovascular disease, PIR poverty–income ratio, CKD chronic kidney disease, eGFR estimated glomerular filtration rate, GLP glucagon-like peptide, CRP C-reactive protein, BMI body mass index, HEI healthy eating index, EASIX endothelial activation and stress index

Associations of genistein and EASIX with 10-year ASCVD risk

The non-linear correlation of EASIX with 10-year ASCVD risk is displayed in Fig. 2 (Pnon-linear < 0.001). Covariates associated with 10-year ASCVD risk are presented in Table S3. The associations of genistein and EASIX with 10-year ASCVD risk are shown in Table 2. After adjusting for age, educational level, PIR, physical activity, anti-dyslipidemia drugs, CKD, GLP-1 receptor agonists, CRP, uric acid, BMI, and live microbe intake, elevated levels of EASIX (OR = 1.35, 95% CI 1.18–1.54), EASIXmedian ≥ 0.427 (OR = 1.40, 95% CI 1.14–1.73), EASIXRCS ≥ 0.434 (OR = 1.45, 95% CI 1.18–1.77), EASIXquartile (0.325–0.427, OR = 1.48, 95% CI 1.05–2.07; 0.427–0.567, OR = 1.51, 95% CI 1.08–2.10; ≥ 0.567, OR = 2.08, 95% CI 1.57–2.77), and log2(EASIX) (OR = 1.32, 95% CI 1.19–1.46) were associated with higher odds of 10-year ASCVD. Low genistein levels presented no statistically significant correlation with 10-year ASCVD risk (continuous, OR = 0.96, 95% CI 0.88–1.06; < 54.105, OR = 1.21, 95% CI 0.96–1.52).

Fig. 2.

Fig. 2

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The non-linear correlation of EASIX with 10–year ASCVD risk

Table 2.

Associations of genistein and EASIX with 10-year ASCVD risk

Variables Crude model Adjusted model
OR (95% CI) P OR (95% CI) P
EASIX 1.95 (1.76–2.17)  < 0.001 1.35 (1.18–1.54)  < 0.001
EASIXmedian
  < 0.427 Ref Ref
  ≥ 0.427 2.26 (1.98–2.58)  < 0.001 1.40 (1.14–1.73) 0.002
EASIXRCS
  < 0.434 Ref Ref
  ≥ 0.434 2.26 (1.99–2.56)  < 0.001 1.45 (1.18–1.77) 0.001
EASIXquartile
  < 0.325 Ref Ref
  0.325–0.427 1.81 (1.47–2.23)  < 0.001 1.48 (1.05–2.07) 0.024
  0.427–0.567 2.44 (1.98–3.00)  < 0.001 1.51 (1.08–2.10) 0.015
  ≥ 0.567 3.92 (3.23–4.76)  < 0.001 2.08 (1.57–2.77)  < 0.001
Log2(EASIX) 1.76 (1.63–1.90)  < 0.001 1.32 (1.19–1.46)  < 0.001
Genistein 0.92 (0.85–1.01) 0.071 0.96 (0.88–1.06) 0.431
Genistein
  ≥ 54.105 Ref Ref
  < 54.105 1.08 (0.92–1.27) 0.317 1.21 (0.96–1.52) 0.099
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EASIX endothelial activation and stress index, ASCVD atherosclerotic cardiovascular disease, OR odds ratio, CI confidence interval, Ref referenceCrude model: unadjusted modelAdjusted model: adjusted for age, educational level, PIR, physical activity, anti-dyslipidemia drugs, CKD, GLP-1 receptor agonists, CRP, uric acid, BMI, and live microbe intake

Potential interactions between EASIX and genistein on 10-year ASCVD risk

Table 3 shows the potential interactions between EASIX and genistein on 10-year ASCVD risk. The interaction term between EASIX and urinary genistein levels was significant (OR = 1.60, 95% CI 1.13–2.25), suggesting a multiplicative interaction between them. No additive interaction on 10-year ASCVD risk was found between EASIX and urinary genistein levels [RERI = 0.32 (− 0.07–0.72)]. Then, we compared the association between EASIX and 10-year ASCVD risk under different genistein level groups (Table 4). The results showed that in individuals with genistein level of < 54.105, EASIX ≥ 0.427 had a higher 10-year ASCVD risk (OR = 1.65, 95% CI 1.30–2.10). However, this association between EASIX > 0.427 and 10-year ASCVD risk became insignificant when persons have genistein level of ≥ 54.105 (OR = 0.96, 95% CI 0.68–2.10), indicating a potential regulating effect of high genistein level on relationship between EASIX and 10-year ASCVD risk.

Table 3.

Potential interactions between EASIX and genistein on 10-year ASCVD risk

Variables Model 1 Model 2
OR (95% CI) P OR (95% CI) P
EASIXmedian 1.88 (1.55–2.29)  < 0.001 1.03 (0.77–1.38) 0.843
Genistein 0.93 (0.75–1.16) 0.524 0.95 (0.72–1.24) 0.682
EASIXmedian * Genistein 1.32 (1.04–1.67) 0.023 1.60 (1.13–2.25) 0.008
RERI 0.24 (− 0.19–0.67) 0.32 (− 0.07–0.72)
AP 0.10 (− 0.08–0.28) 0.21 (− 0.05–0.47)
SI 1.22 (0.83–1.78) 2.42 (0.32–18.11)
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EASIX endothelial activation and stress index, ASCVD atherosclerotic cardiovascular disease, OR odds ratio, CI confidence interval, RERI relative excess risk due to interaction, AP attributable proportion, SI synergy indexModel 1: unadjusted modelModel 2: adjusted for age, educational level, PIR, physical activity, anti-dyslipidemia, CKD, GLP-1 receptor agonists, CRP, uric acid, BMI, and live microbe intake

Table 4.

Association between EASIX and 10-year ASCVD risk under different genistein level groups

Variables Model 1 Model 2
OR (95% CI) P OR (95% CI) P
Genistein ≥ 54.105 µg/g (n = 1422)
  EASIX < 0.427 Ref Ref
  EASIX ≥ 0.427 1.88 (1.55–2.29)  < 0.001 0.96 (0.68–1.35) 0.797
Genistein < 54.105 µg/g (n = 3056)
  EASIX < 0.427 Ref Ref
  EASIX ≥ 0.427 2.48 (2.11–2.91)  < 0.001 1.65 (1.30–2.10)  < 0.001
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EASIX endothelial activation and stress index, ASCVD atherosclerotic cardiovascular disease, OR odds ratio, CI confidence intervalModel 1: unadjusted modelModel 2: adjusted for age, educational level, PIR, physical activity, anti-dyslipidemia, CKD, GLP-1 receptor agonists, CRP, uric acid, BMI, and live microbe intake

Potential regulating effect of genistein on association between EASIX and 10-year ASCVD risk in different subgroups

The genistein’s regulatory role in the EASIX–10-year ASCVD risk connection was examined based on subgroups of age, BMI, diabetes, hypertension, and dyslipidemia (Table 5). The multiplicative interaction effect between EASIX and genistein was significant in adults aged < 60 years (OR = 1.79, 95% CI 1.15–2.80), with BMI ≥ 25 kg/m2 (OR = 1.71, 95% CI 1.08–2.69), non-diabetic individuals (OR = 1.51, 95% CI 1.02–2.24), those with hypertension (OR = 1.86, 95% CI 1.17–2.96), and individuals with dyslipidemia (OR = 1.64, 95% CI 1.13–2.37). Additionally, we evaluated the connection of EASIX with ASCVD risk under different genistein levels in the aforementioned subgroups (Fig. 3). The results suggested that when genistein levels < 54.105 µg/g, the connections between elevated EASIX levels and higher 10-year ASCVD risk were established in subgroups of age < 60 years (OR = 1.87, 95% CI 1.40–2.48), BMI ≥ 25 kg/m2 (OR = 1.65, 95% CI 1.27–2.15), non-diabetic individuals (OR = 1.59, 95% CI 1.21–2.08), those with hypertension (OR = 1.90, 95% CI 1.32–2.73), and individuals with dyslipidemia (OR = 1.72, 95% CI 1.33–2.21). However, this association became not significant when genistein levels ≥ 54.105 µg/g (all P > 0.05).

Table 5.

Roles of genistein on the association between EASIX and 10–year ASCVD risk in different subgroups

Subgroup & variable Adjusted model
OR (95% CI) P OR (95% CI) P
Subgroup I: Age  < 60 (n = 2604)  ≥ 60 (n = 1874)
  EASIX 1.03 (0.73–1.45) 0.851 1.44 (0.81–2.57) 0.207
  Genistein 0.85 (0.61–1.19) 0.336 1.09 (0.65–1.82) 0.746
  EASIX * Genistein 1.79 (1.15–2.80) 0.011 0.88 (0.43–1.82) 0.729
Subgroup II: BMI  < 25 kg/m2 (n = 1146)  ≥ 25 kg/m2 (n = 3332)
  EASIX 1.13 (0.55–2.30) 0.742 0.96 (0.65–1.42) 0.844
  Genistein 0.99 (0.50–1.97) 0.977 0.93 (0.63–1.36) 0.693
  EASIX * Genistein 1.44 (0.53–3.92) 0.472 1.71 (1.08–2.69) 0.022
Subgroup III: Diabetes No (n = 3649) Yes (n = 829)
  EASIX 1.04 (0.74–1.46) 0.816 1.41 (0.47–4.27) 0.536
  Genistein 0.87 (0.63–1.20) 0.392 1.45 (0.63–3.32) 0.374
  EASIX * Genistein 1.51 (1.02–2.24) 0.040 1.28 (0.31–5.31) 0.733
Subgroup IV: Hypertension No (n = 2150) Yes (n = 2328)
  EASIX 1.04 (0.57–1.89) 0.909 1.01 (0.71–1.44) 0.939
  Genistein 1.24 (0.72–2.14) 0.443 0.85 (0.60–1.22) 0.377
  EASIX * Genistein 1.21 (0.60–2.43) 0.594 1.86 (1.17–2.96) 0.009
Subgroup V: Dyslipidemia No (n = 930) Yes (n = 3548)
  EASIX 1.45 (0.43–4.96) 0.546 1.06 (0.77–1.46) 0.721
  Genistein 1.63 (0.48–5.49) 0.424 0.91 (0.66–1.25) 0.550
  EASIX * Genistein 1.20 (0.26–5.61) 0.817 1.64 (1.13–2.37) 0.009
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EASIX endothelial activation and stress index, ASCVD atherosclerotic cardiovascular disease, OR odds ratio, CI confidence interval, BMI body mass indexSubgroup I: adjusted for age, educational level, PIR, physical activity, anti-dyslipidemia, CKD, GLP-1 receptor agonist, CRP, uric acid, BMI, and live microbe intakeSubgroup II: adjusted for age, educational level, PIR, physical activity, anti-dyslipidemia, CKD, CRP, uric acid, and live microbe intakeSubgroup III: adjusted for age, educational level, PIR, physical activity, anti-dyslipidemia, CKD, CRP, uric acid, BMI, and live microbe intakeSubgroup IV: adjusted for age, educational level, PIR, physical activity, CKD, GLP-1 receptor agonists, CRP, uric acid, BMI, and live microbe intakeSubgroup V: adjusted for age, educational level, PIR, physical activity, CKD, CRP, uric acid, BMI, and live microbe intake

Fig. 3.

Fig. 3

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Associations between EASIX and 10-year ASCVD risk under different genistein levels in different subgroups

Discussion

Elevated levels of EASIX, EASIXmedian ≥ 0.427, EASIXRCS ≥ 0.434, EASIXquartile, and log2(EASIX) were associated with higher odds of 10-year ASCVD. Low genistein levels presented no statistically significant correlation with 10-year ASCVD risk. The multiplicative interaction between EASIX and genistein levels was significant. When genistein levels < 54.105 µg/g, the connections between elevated EASIX levels and higher 10-year ASCVD risk were established in subgroups of age < 60 years, BMI ≥ 25 kg/m2, non-diabetes, hypertension, and dyslipidemia.

This investigation was the first to examine genistein’s potential modulation of the EASIX–ASCVD risk correlation, offering insights for stratifying and managing high-risk ASCVD populations. Endothelial dysfunction, being both the initial clinical marker of atherosclerosis and a precursor to cardiovascular complications, effectively predicts future adverse cardiovascular outcomes (Daiber et al. 2017). EASIX has gained recognition as a reliable endothelial injury indicator in recent years (Luft et al. 2017). Sang et al. (Sang et al. 2024) revealed that increased EASIX scores strongly predict 30-day mortality risk in acute myocardial infarction cases. Finke et al. (Finke et al. 2024) established EASIX as a viable mortality predictor in coronary artery disease patients. Another study demonstrated strong connections between high EASIX scores and sepsis mortality at both 28-day and 90-day intervals (Xu et al. 2023). Compared to previous research, our results relatively supplemented the link of EASIX with 10-year ASCVD in the general population in the USA, which may provide information on prevention and risk stratification of ASCVD.

Clinical and experimental evidence consistently demonstrates genistein’s cardioprotective effects against cardiovascular events (Si and Liu 2007). Huang et al. (Huang et al. 2008) indicated genistein’s endothelial protection against oxidized LDL-induced atherosclerosis through antioxidant enzyme activation and an anti-apoptotic mechanism. Wei et al. (Wei et al. 2022) additionally confirmed genistein’s effects: inhibiting cannabinoid-induced vascular dysfunction, reducing arterial plaques, and maintaining low cerebrospinal concentrations in mice. Recent studies identify programmed endothelial cell death as atherosclerosis’ primary trigger. Current investigations reveal natural products’ anti-atherosclerotic effects via suppression of programmed endothelial demise (Duan et al. 2021). According to this evidence, the present study set the research hypothesis that genistein may be associated with high EASIX levels related to ASCVD risk. Through evaluating the multiplicative interacting effect between genistein and EASIX, we observed that among the study subjects, when the genistein level was less than the median value (54.105 ug/g), a high EASIX level was significantly linked to an increased odds of 10-year ASCVD risk; however, when the genistein level was ≥ 54.105 µg/g, this relationship became not significant. This indicated that genistein has a potential protective effect on 10-year ASCVD risk associated with high EASIX scores.

The potential regulatory effects of genistein on EASIX-ASCVD connections likely involve multifaceted biological pathways. Previous research has suggested a number of possible pathways that could help explain the current findings. Genistein, a legume-derived phytoestrogen, is classified as an isoflavone within the flavonoid family. The naturally derived compound shares conformational similarity with vertebrate estrogen molecules. Both in vitro and in vivo studies demonstrate genistein’s anti-inflammatory effects through multiple pathways: nuclear factor kappa-B (NF-κB) suppression, prostaglandins (PGs) reduction, cytokine downregulation, inducible nitric oxide synthase (iNOS) inhibition, reactive oxygen species (ROS) attenuation, and radical scavenging (Goh et al. 2022). Systemic inflammation critically contributes to endothelial injury and the subsequent development of atherosclerotic plaques (Krolikoski et al. 2019). Elements utilized for genistein calculation are possibly associated with the inflammation pathway. For example, LDH-derived lactate promotes nasopharyngeal carcinoma development through TGF-β-activated kinase 1 modulation and subsequent NF-κB pathway activation (Li et al. 2024). EASIX-incorporated thrombocytopenia signals platelet consumption/destruction, frequently linked to severe inflammatory states or disseminated coagulation (Liu et al. 2023). Besides, genistein safeguards endothelial cells from oxidized LDL-induced atherogenic stress through antioxidant enzyme upregulation and anti-apoptotic effects (Huang et al. 2008). The NF-κB modulates vascular endothelial inflammation and oxidative balance, contributing significantly to endothelial dysfunction development (Read et al. 1994). Genistein inhibits aldosterone secretion; thereby, it may reduce the risk of CVD (Ajdzanović et al. 2009; Cai et al. 2024).

Furthermore, we examined the potential regulating effect of genistein between EASIX and ASCVD risk in adults with different ages, BMI, and complications. According to the subgroup analysis results, this effect was observed in age < 60 years, BMI ≥ 25 kg/m2, non-DM, hypertension, and dyslipidemia subgroups. The progressive aging of the world population is resulting in a higher prevalence of age-related disorders, including frailty and CVD (Garcia-Garcia et al. 2011). In fact, vascular system dysfunction is one of the main mechanisms leading to frailty (Palomo et al. 2024). Therefore, in elderly adults, prevention of frailty-related factors may be applied more widely. Our findings suggested that among persons aged 40 to 60 years, urine genistein concentrations also need to be focused on, which may regulate potential ASCVD risk associated with EASIX. The connection of obesity (BMI ≥ 25 kg/m2) with endothelial dysfunction involves mechanisms of inflammation and oxidative stress (Schafer et al. 2013). Meanwhile, genistein has presented therapeutic potential for both weight control and insulin resistance amelioration (Gan et al. 2020). Therefore, in the obese population, genistein has the potential to regulate ASCVD risk related to a high EASIX score. In addition, DM (Marx et al. 2022), hypertension (Chang et al. 2023a), and dyslipidemia (Chang et al. 2023b) are common complications in middle-aged and aged people, and are associated with an increased ASCVD risk. Our study identified genistein’s potential to modulate the EASIX-ASCVD connection among patients with DM, hypertension, or dyslipidemia, suggesting its preventive value against 10-year ASCVD risk.

Our novel findings on genistein-mediated EASIX–ASCVD connection in the US population may inform future preventive approaches against ASCVD. This investigation utilized NHANES data with a large, nationally representative sample obtained through multi-stage complex sampling. However, limitations should be considered when making conclusions in the current study. Firstly, this cross-sectional design limits causal interpretation and cannot fully eliminate intrinsic bias. Future studies with longitudinal cohorts need to further validate the impact and independence of EASIX on cardiovascular events. Secondly, although potential confounding factors, including demographics, comorbidities, lifestyle, and medications, were considered, there were still other factors (such as detailed treatment information) that were not included in the analysis because of database limitations. Thirdly, data in this study were extracted from the US population. Whether these findings apply to populations with habitually high soy intake, such as East Asians, needs further confirmation. Fourthly, due to the database limitations, dietary changes for individuals could not be obtained. Changes in diet due to poor health may reduce genistein intake, which in turn may affect urinary genistein concentrations.

Conclusion

Elevated EASIX scores correlated with higher 10-year ASCVD risk in US adults, while increased genistein levels may potentially mitigate this EASIX–ASCVD connection. In clinical practice, attention and management should be paid to urine genistein, which may be beneficial for the prevention of ASCVD risk associated with EASIX. However, these findings still need verification by multiple prospective cohort studies with samples from different races.

Supplementary Information

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Author contribution

Yongliang Huang, conceiving and designing the study; Yongliang Huang, Huijuan Lan, Hongchuan Yang, collecting the data; Yongliang Huang, Huijuan Lan, Hongchuan Yang, analyzing and interpreting the data; Yongliang Huang, writing the manuscript; Yongliang Huang, providing critical revisions that are important for the intellectual content; Yongliang Huang, Huijuan Lan, Hongchuan Yang, approving the final version of the manuscript. The authors declare that all data were generated in-house and that no paper mill was used.

Data Availability

The datasets supporting this study can be retrieved from NHANES public databases: https://wwwn.cdc.gov/Nchs/Nhanes/.

Declarations

Ethics approval and consent to participate

It is not applicable because the NHANES Database belongs to public databases, the patients involved in the database have obtained ethical approval, users can download relevant data for free for research and publish relevant articles, and our study is based on open-source data, and the Zhangzhou People’s Hospital does not require research using publicly available data to be submitted for review to their ethics committee, so there are no ethical issues and other conflicts of interest.

Consent for publication

Not applicable.

Conflict of interest

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Supplementary Materials

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Data Availability Statement

The datasets supporting this study can be retrieved from NHANES public databases: https://wwwn.cdc.gov/Nchs/Nhanes/.

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