9 research outputs found

    Decreased Naive and Increased Memory CD4<sup>+</sup> T Cells Are Associated with Subclinical Atherosclerosis: The Multi-Ethnic Study of Atherosclerosis

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    <div><p>Background</p><p>Adaptive immunity has been implicated in atherosclerosis in animal models and small clinical studies. Whether chronic immune activation is associated with atherosclerosis in otherwise healthy individuals remains underexplored. We hypothesized that activation of adaptive immune responses, as reflected by higher proportions of circulating CD4<sup>+</sup> memory cells and lower proportions of naive cells, would be associated with subclinical atherosclerosis.</p><p>Methods and Findings</p><p>We examined cross-sectional relationships of circulating CD4<sup>+</sup> naive and memory T cells with biomarkers of inflammation, serologies, and subclinical atherosclerosis in 912 participants of the Multi-Ethnic Study of Atherosclerosis (MESA). Circulating CD4<sup>+</sup> naive cells were higher in women than men and decreased with age (all p-values <0.0001). European-Americans had higher levels of naive cells and lower levels of memory cells compared with African-Americans and Hispanic-Americans (all p-values ≤0.0005). Lower naive/higher memory cells were associated with interleukin-6 levels. In multivariate models, cytomegalovirus (CMV) and <i>H. Pylori</i> titers were strongly associated with higher memory and lower naive cells (all p-values <0.05). Higher memory cells were associated with coronary artery calcification (CAC) level in the overall population [β-Coefficient (95% confidence interval (CI))  = 0.20 (0.03, 0.37)]. Memory and naive (inversely) cells were associated with common carotid artery intimal media thickness (CC IMT) in European-Americans [memory: β =  0.02 (0.006, 0.04); naive: β = −0.02 (−0.004, −0.03)].</p><p>Conclusions</p><p>These results demonstrate that the degree of chronic adaptive immune activation is associated with both CAC and CC IMT in otherwise healthy individuals, consistent with the known role of CD4<sup>+</sup> T cells, and with innate immunity (inflammation), in atherosclerosis. These data are also consistent with the hypothesis that immunosenescence accelerates chronic diseases by putting a greater burden on the innate immune system, and suggest the importance of prospective studies and research into strategies to modulate adaptive immune activation in chronic disease states such as atherosclerosis.</p></div

    Characteristics of the MESA sample population being studied.

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    <p>Data are from MESA exam 4 (2005–2007) unless otherwise noted. *: Data are from MESA baseline (exam 1; 2000–2002). **: Includes all participants with incident cardiovascular events (myocardial infarction, resuscitated cardiac arrest, definite or probable angina, and stroke) from baseline through the start of exam 4. AU: Agatston units; BMI: Body mass index; CAC: Coronary artery calcification; CMV: Cytomegalovirus; CRP: C-reactive protein; CVD: Cardiovascular disease; HSV: Herpes simplex virus; IL-6: Interleukin-6; IMT: Intimal media thickness.</p

    Final regression model for coronary artery calcification.

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    <p>Backward elimination regression was used to develop multivariate models for coronary artery calcification (CAC) level. CAC was analyzed using the ln-agatston score in individuals with a score >0. Independent variables were divided by their standard deviations (shown in parentheses). The candidate starting variables were: age, gender, race/ethnicity, IL-6, BMI, systolic BP, use of BP lowering medication, smoking status, total-cholesterol, HDL-cholesterol, use of lipid lowering medication, type 2 diabetes status, CMV and <i>H. pylori</i> titers, and CD4<sup>+</sup> memory cell proportions or, in separate analyses, CD4<sup>+</sup> naive cell proportions. Only significant variables (p<0.05) were retained in the final model to obtain the model's R<sup>2</sup>. ns: non-significant.</p

    Regression models for CD4<sup>+</sup> naive and memory cell subpopulations.

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    <p>Backward elimination regression was used to develop multivariate models for CD4<sup>+</sup> T cell subpopulations. Independent variables were divided by their standard deviations (shown in parentheses). Age, gender, race/ethnicity, seasonality, BMI, IL-6, and CMV and <i>H. pylori</i> titers were included as the candidate starting variables. Only significant variables (p<0.05) were retained in the final models. BMI: Body mass index; CMV: Cytomegalovirus; IL-6: Interleukin-6; ns: non-significant.</p

    Typical flow cytometric data for lymphocyte, CD4<sup>+</sup> memory, and CD4<sup>+</sup> naive cell populations.

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    <p>At least 30,000 lymphocytes were evaluated and were gated based on their forward (FCS; X-axis) and side (SCS; Y-axis) scatter (Panels A&B). Memory and naive cell subpopulations were gated by positive surface staining for CD4 (Y-axis, panels C–F); memory cells were gated by positive surface staining for CD45RO (X-axis, panels C&D); naive cells were gated by positive surface staining for CD45RA (X-axis, panels E&F). Typical data from respective isotype controls (Panels A, C, and E) and fluorescently labeled samples (Panels B, D, and F) are shown.</p

    Characteristics of the MESA-Inflammation study population by type 2 diabetes status.

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    <p>Data are from MESA exam 4 (2005–2007) unless otherwise noted.</p><p>*: Data are from MESA exam 5 (2010–2012).</p><p>**: Includes all participants with incident cardiovascular events (myocardial infarction, resuscitated cardiac arrest, definite or probable angina, and stroke) from baseline through the start of MESA exam 4.</p><p>Characteristics of the MESA-Inflammation study population by type 2 diabetes status.</p

    Associations of lymphocyte subpopulations with fasting glucose, HbA1c, and insulin among participants without type 2 diabetes.

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    <p>Analyses excluded participants with pharmacologically-treated type 2 diabetes. Lymphocyte subpopulations were analyzed in separate models per SD increment higher. Model 1: Age, gender, race/ethnicity. Model 2: Age, gender, race/ethnicity, and BMI.</p><p>Associations of lymphocyte subpopulations with fasting glucose, HbA1c, and insulin among participants without type 2 diabetes.</p

    Interleukin-6, diabetes, and metabolic syndrome in a biracial cohort: the Reasons for Geographic and Racial Differences in Stroke cohort

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    Objective: Black Americans have a greater risk of type-2 diabetes than White Americans. The proinflammatory cytokine interleukin-6 (IL-6) is implicated in diabetes pathogenesis and is higher in Black people. This study investigated associations of IL-6 with incident diabetes and metabolic syndrome in a biracial cohort.Research Design and Methods: The REasons for Geographic And Racial Differences in Stroke study enrolled 30,239 Black and White adults age 45+ in 2003-07, with a follow-up ~9.5 years later. Baseline plasma IL-6 was measured in 3,399 at risk for incident diabetes and 1,871 for metabolic syndrome. Modified Poisson regression estimated relative risk (RR) by IL-6 for both.Results: Incident diabetes occurred in 14% and metabolic syndrome in 20%; both rose across IL-6 quartiles. There was a 3-way interaction of IL-6, race, and central adiposity for incident diabetes (p=8 x10-5). In Black participants with and without central adiposity RRs were 2.02 (95% CI 1.00-4.07) and 1.66 (1.00-2.75) for the 4th compared to 1st quartile of IL-6, respectively. The corresponding RRs were 1.73 (0.92-3.26) and 2.34 (1.17-4.66) in White participants. The pattern was similar for IL-6 and metabolic syndrome.Conclusions: While IL-6 was higher in Black than White participants and those with central adiposity, associations of IL-6 with diabetes risk was only statistically significant among White participants without central adiposity. Associations with metabolic syndrome risk were similarly stronger in low-risk groups. Results support the concept of interventions to lower inflammation in diabetes prevention, but to reduce race disparities, better biomarkers are needed.</p

    Associations of lymphocyte subpopulations with prevalent type 2 diabetes.

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    <p>P-values are from continuous models. Model 1: Age, gender, race/ethnicity. Model 2: Age, gender, race/ethnicity, and BMI.</p><p>Associations of lymphocyte subpopulations with prevalent type 2 diabetes.</p
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