In Search of a Salient Marker of Immune Function for Population Health Research

In Search of a Salient Marker of Immune Function for Population Health Research Lydia Lydia Feinstein, Feinstein, ab Elizabeth Elizabeth McClure, McClure, b Jennifer Jennifer B Dowd, B Dowd, c and and Allison Allison E. E Aiello Aiello ab a Carolina Population Center, The University of North Carolina at Chapel Hill b Department of Epidemiology, The University of North Carolina at Chapel Hill c CUNY School of Public Health, Hunter College, City University of New York

Population-based longitudinal cohort study (N=2081) 5 study waves & 4 in-home blood draws (2008-2013) 2

Bio-social Integration in DNHS Psychosocial Socio-demographics Neighborhood Social Support Mental Health Substance Use Trauma Biological Anthropometry Inflammation Epigenetics Infections Immunological 3

Overview Background: Stress, infection, and the aging immune system Detroit Neighborhood Health Study Socioeconomic Status, Cytomegalovirus, and T-Cell Markers of Immunological Aging Characterizing Thymic Function in the Community Setting Future directions and challenges 4

Why the Immune System? Critical to multiple health outcomes Target of public health and medical interventions 5

Immune Function Declines with Age Age and the human T-cell repertoire Understanding immunosenescence to improve responses to vaccines. Goronzy JJ et al. Nature Immunology (2013) 6

Variability in Immunological Aging Pathogen exposure Psychosocial stress 7

Table 5 Characteristics of the Immune Risk Profile Increased CD8+ and CD3+ Decreased CD4+ and CD19+ CD4/CD8 ratio < 1 Increased lately differentiated CD8+CD28-CD27- cells Depletion of naive CD8+CD45RA+CCR7+ cells CMV-seropositivity Clonal expansion of CD8+ cells carrying receptors for CMV High proportion of dysfunctional cells among the CMV-specific CD8+ cells 8

Percent CMV Prevalence Patterned by Sociodemographic Characteristics 80 CMV Prevalence in the United States (1999-2004) 70 60 50 40 30 20 10 0 6-11 12-19 20-29 30-39 40-49 Low Middle High < High School HS or GED > High School Age (years) Household Income Household education Bate SL, Dollard SC, Cannon MJ. Cytomegalovirus seroprevalence in the United States: the national health and nutrition examination surveys, 1988-2004. Clin Infect Dis. 2010;50(11):1439-1447. 9

CMV Reactivation Induced by Psychosocial Stress Mental health variables by tertiles of CMV-IgG levels among CMV+ (N = 329) Rector JL, Dowd JB, Loerbroks A, et al. Consistent associations between measures of psychological stress and CMV antibody levels in a large occupational sample. Brain Behav Immun. 2014;38:133-141. 10

Socioeconomic Status, Cytomegalovirus, and T-Cell Markers of Immunological Aging 11

Pilot Study Aims Aim 1: Examine the associations between socioeconomic status and T-cell markers of aging Aim 2: Assess whether CMV IgG antibody levels mediate the associations between socioeconomic status and T-cell markers of aging 12

T-cell Sub-Sample T-cell phenotypes assessed in Wave 1 (n=85) Median age 45 years (IQR: 35-56 years) 63% female 80% Non-Hispanic Black 48% High school education 13

Ascertainment of T-Cell Phenotypes T-cell subsets analyzed using flow cytometry in cryopreserved peripheral blood mononuclear cell (PBMC) samples 14

Study Measures Outcome: T-cell Markers of Immune Aging CD4:CD8 T-cell ratio CD4 Effector:Naïve T-cell ratio CD8 Effector:Naïve T-cell ratio Exposure: Pre-tax annual household income 15

Mediator CMV IgG Antibody Level Income Immune Aging CMV IgG antibodies quantified by ELISA 16

Statistical Analysis Linear regression Total Effect: Income Immune Aging Mediation Analysis (Preacher and Hayes, 2008) Indirect Effect: Income CMV Immune Aging Direct Effect: Income Immune Aging 17

Income and T-cell Markers of Aging 1.00 0.80 Log CD4 E:N ratio *P value <0.1 **P value <0.05 β (95% Confidence Interval) for each $10K decrease in income 0.60 0.40 0.20 Log CD8 E:N ratio Log CD4:CD8 ratio 0.00-0.20 2** Model 1** Model 2** 2** Model 1* Model 2** 2 Model 1 Model 2** Log CD4 E:N ra o Log CD8 E:N ra o Log CD4:CD8 ra o Model 1: Adjusted for age, gender, and race/ethnicity Model 2: Additionally adjusted for smoking, medication use, and mental health status. AE Aiello et al. Psychosom Med [In Press] 18

Mediation Results Indirect effect 0.22 (0.08, 0.39)** CMV IgG *P value <0.1 **P value <0.05 Income Direct effect 0.19 (-0.09, 0.47) CD4 E:N ratio Adjustments: age, gender, race/ethnicity, smoking, medication use, and mental health status Indirect effect 0.09 (0.02, 0.21)** CMV IgG Income Direct effect 0.11 (-0.07, 0.29) CD8 E:N ratio AE Aiello et al. Psychosom Med [In Press] 19

Characterizing Thymic Function in the Community Setting 20

Thymic Involution Over Life Course Newborn Adult 21

Thymic Function Critical for Immune Response Essential for maintaining supply of naïve T cells Reduced thymic function predictive of poor health outcomes Stress-induced thymic atrophy compromises immune system 22

Aims Aim 1: Characterize thymic function in community setting Aim 2: Examine whether economic stressors are associated with reduced thymic function 23

Thymic Function Sub-Sample Thymic function measured in Wave 4 (n=390) Median age 48 years (IQR: 38-62 years) 49% female 88% Non-Hispanic Black 53% High school education 24

Thymic Function Measurement Signal joint T-cell receptor excision circles (sjtrec) Nonreplicated extrachromosomal DNA byproducts of TCR gene rearrangements evident in recently developed T cells (Douek et al. Nature 1998) Analyzed by PCR in genomic DNA 25

Thymic function in DHNS Mean Thymic Function (sjtrec per Million Whole Blood Cells) by Age and Gender 25000 20000 Women Men 15000 10000 5000 0 18-34 35-44 45-54 55-64 65+ Age in Years L Feinstein, S Ferrando-Martínez, M Leal, GD Sempowski, DE Wildman, and AE Aiello. Population Distributions of Thymic Function in Adults: Variation by Age and Health Status. Biodemography Soc Biol. [In Press] 26

Past-Year Economic Stressors and Thymic function 1 β (95% Confidence Interval) 0.5 0-0.5-1 -1.5 Low Income Income <$75k Job Loss Unemployed >3 months Unemployed >3mo Perceived financial problems Perceived serious financial problems -2 *Linear regression models adjusted for age, gender, race/ethnicity, and education 27

Conclusions Immune signatures provide clues about how social determinants influence biological pathways to health Research gaps remain Smaller-scale, yet still representative, studies offer opportunities more detailed immune phenotyping Ability to measure thymic function in dried blood spots offers potential for larger-scale application 28

Acknowledgements Aiello Research Group Allison Aiello Christian Douglas Anissa Vines Amanda Simanek Rebecca Stebbins Erline Miller Libby McClure Evette Cordoba Julia Ward Graham Pawelec and Evelyna Derhovanessian (University of Tübingen, Germany) Sara Ferrando-Martínez and Manuel Leal (Laboratory of Immunovirology, Institute of Biomedicine of Seville, IBiS, Virgen del Rocío University Hospital, Sevilla, Spain) Gregory Sempowski and Melissa Samo (Duke University) Funding Support NICHD T32 HD007168 (PI: Halpern) NICHD P2C HD050924 (PI: Morgan) NIDA R01 DA022720 (PI: Aiello) NIDA R01 DA022720-S1 (PI: Aiello) NIA AG013283 (PI: Aiello) 29

Questions? Lydia Feinstein, PhD, MSPH Department of Epidemiology & Carolina Population Center The University of North at Chapel Hill lfeinst@email.unc.edu