Created in BioRender. Deconne, T. (2025) https://BioRender.com/rkk95f3.
Abbreviations: LDL-C, low-density lipoprotein-cholesterol; HDL-C, high-density lipoprotein-cholesterol; TG, triglycerides; NK, natural killer; LDL-P, low-density lipoprotein particles; HDL-P, high-density lipoprotein-particles; and TRL-P, triglyceride-rich lipoprotein-particles.
Table 1
Participant descriptive characteristics.
| MEAN (SD), COUNT (%), OR MEDIAN (IQR) | |
|---|---|
| Total n | 1,735 |
| Age, years | 62 (11) |
| Male, % | 852 (49%) |
| Race/Ethnicity | |
| Black, % | 480 (28%) |
| Chinese, % | 240 (14%) |
| Hispanic, % | 398 (23%) |
| White, % | 621 (36%) |
| CVD Risk Factors | |
| BMI, kg/m2 | 28 (5) |
| SBP, mmHg | 128 (22) |
| Hypertension medications | 616 (35%) |
| Diabetes | 227 (13%) |
| eGFR, mL/min/1.73 m2 | 78 (17) |
| Smoking never, % | 862 (50%) |
| Smoking former, % | 632 (36%) |
| Smoking current, % | 241 (14%) |
| Blood Lipids (Median (IQR)) | |
| Total cholesterol, mg/dL | 193 (172, 216) |
| LDL-C, mg/dL | 118 (99, 138) |
| HDL-C, mg/dL | 48 (40, 58) |
| Triglycerides, mg/dL | 111 (78, 166) |
| Blood Lipoproteins (Median (IQR)) | |
| Total LDL-P, nmol/L | 1642 (1408, 1918) |
| Large LDL-P, nmol/L | 127 (43, 286) |
| Medium LDL-P, nmol/L | 209 (45, 462) |
| Small LDL-P, nmol/L | 1134 (812, 1522) |
| Total HDL-P, μmol/L | 21 (19, 23) |
| Large HDL-P, μmol/L | 2 (2, 4) |
| Medium HDL-P, μmol/L | 3 (1, 5) |
| Small HDL-P, μmol/L | 15 (13, 17) |
| Total TRL-P, nmol/L | 168 (128, 212) |
| Small TRL-P, nmol/L | 0.1 (0.1, 0.2) |
| Very Small TRL-P, nmol/L | 3 (1, 8) |
| Medium TRL-P, nmol/L | 21 (11, 35) |
| Large TRL-P, nmol/L | 86 (49, 123) |
| Very Large TRL-P, nmol/L | 44 (22, 75) |
[i] Participant characteristics at the baseline MESA examination are presented. Data are presented as mean (SD), count (%), or median (interquartile range (IQR)). Abbreviations: CVD, cardiovascular disease; BMI, body mass index; SBP, systolic blood pressure; eGFR, estimated glomerular filtration rate; LDL-C, low-density lipoprotein-cholesterol; HDL-C, high-density lipoprotein-cholesterol; LDL-P, LDL particles; HDL-P, HDL particles; and TRL-P, triglyceride rich lipoprotein particles.
Figure 1
Associations of blood lipids with T-cell subsets: Weighted linear regression models were used with blood lipids as the independent variable and T-cell subsets as the dependent variable. Models were adjusted for age, sex, race/ethnicity, MESA site, cell phenotyping analytical batch, BMI, smoking, hypertensive medications, SBP, diabetes, eGFR, and CMV. Each model represents a single exposure. Results are presented as beta (95% CI), p-value. Abbreviations: Chol, cholesterol; HDL-C, high-density lipoprotein-cholesterol; and LDL-C, low-density lipoprotein-cholesterol.
Figure 2
Associations of low-density lipoprotein particle (LDL-P) fractions and T-cell subsets: Weighted linear regression models were used with LDL-P as the independent variable and T-cell subsets as the dependent variable. Models were adjusted for age, sex, race/ethnicity, MESA site, cell phenotyping analytical batch, BMI, smoking, hypertensive medications, SBP, diabetes, eGFR, and CMV. Each model represents a single exposure. Results are presented as beta (95% CI), p-value.
Figure 3
Associations of high-density lipoprotein particle (HDL-P) fractions with T-cell subsets: Weighted linear regression models were used with HDL-P as the independent variable and T-cell subsets as the dependent variable. Models were adjusted for age, sex, race/ethnicity, MESA site, cell phenotyping analytical batch, BMI, smoking, hypertensive medications, SBP, diabetes, eGFR, and CMV. Results are presented as beta (95% CI), p-value. Each model represents a single exposure.
Figure 4
Associations of triglyceride-rich-lipoprotein-particles (TRL-P) and CD4+ and CD8+ T-cell subsets: Weighted linear regression models were used with TRL-P as the independent variable and T-cell subsets as the dependent variable. Models were adjusted for age, sex, race/ethnicity, MESA site, cell phenotyping analytical batch, BMI, smoking, hypertensive medications, SBP, diabetes, eGFR, and CMV. Each model represents a single exposure. Results are presented as beta (95% CI), p-value.