Cohabitation as a determinant of adaptive and innate immune cell profiles: Findings from the Health and Retirement Study

Introduction

Non-genetic factors are important but poorly understood determinants of immune profiles. Age and Cytomegalovirus (CMV) infection remain two well documented non-genetic determinants of the immune profile. Recently, one study identified cohabitation in the same household as an important determinant of immune profiles.

Methods

We used immunophenotyping data from the Health and Retirement Study (HRS) to evaluate the association between cohabitation and the adaptive (subsets of T-cells, B-cells) and innate immune profiles (subsets of monocytes, natural killer cells and neutrophils). We compared adaptive and innate immune cell profiles using immunophenotyping data from 1184 same-household pairs (cohabitating partners) to 1184 non-household pairs to evaluate the association between cohabitation and adaptive immune cell profiles. We used data from 1737 same-household pairs and 1737 non-household pairs to evaluate the association between cohabitation and innate cell profiles. Household and non-household pairs were matched on age (±2years), educational background and race/ethnicity to minimize confounding due to these factors. The adaptive immune cells and innate immune cell profiles were compressed to two coordinates using multidimensional scaling (MDS). The Euclidean distances between same-household pairs were compared to the distances between non-household pairs for the adaptive and innate cell profiles separately using two sample independent t-tests. We also performed additional adjustment for age and BMI differences, CMV serostatus and smoking concordance/discordance status among household members.

Results

For adaptive immune cell profiles, the mean Euclidean distance between same-household pairs was 4% lower than the non-household pairs (p = 0.03). When stratified by concordance for CMV serostatus among household pairs, the Euclidean distance was significantly lower by 8% in the same-household pairs as compared to non-household pairs among those who were discordant for CMV serostatus (p = 0.01) and among same-household pairs who were CMV seronegative (p = 0.02) after covariate adjustment. The mean Euclidian distance between same-household pairs was also 8% lower than non-household pairs for the innate immune cell profiles (p-value <0.0001) and this difference remained consistent across all strata of CMV infection.

Discussion

This study confirms that cohabitation is associated with similarity in immune cell profiles. The differential effects of cohabitation on the adaptive and innate immune profiles suggest that further studies into the common environmental factors that influence individual immune cell subsets need to be evaluated in greater detail.

Grip strength is inversely associated with DNA methylation age acceleration

BACKGROUND

There is a large body of evidence linking muscular weakness, as determined by low grip strength, to a host of negative ageing-related health outcomes. Given these links, grip strength has been labelled a 'biomarker of aging'; and yet, the pathways connecting grip strength to negative health consequences are unclear. The objective of this study was to determine whether grip strength was associated with measures of DNA methylation (DNAm) age acceleration.

METHODS

Middle age and older adults from the 2006 to 2008 waves of the Health and Retirement Study with 8-10 years of follow-up were included. Cross-sectional and longitudinal regression modelling was performed to examine the association between normalized grip strength (NGS) and three measures of DNAm age acceleration, adjusting for cell composition, sociodemographic variables and smoking. Longitudinal modelling was also completed to examine the association between change in absolute grip strength and DNAm age acceleration. The three DNAm clocks used for estimating age acceleration include the established DunedinPoAm, PhenoAge and GrimAge clocks.

RESULTS

There was a robust and independent cross-sectional association between NGS and DNAm age acceleration for men using the DunedinPoAm (β: -0.36; P < 0.001), PhenoAge (β: -8.27; P = 0.01) and GrimAge (β: -4.56; P = 0.01) clocks and for women using the DunedinPoAm (β: -0.36; P < 0.001) and GrimAge (β: -4.46; P = 0.01) clocks. There was also an independent longitudinal association between baseline NGS and DNAm age acceleration for men (β: -0.26; P < 0.001) and women (β: -0.36; P < 0.001) using the DunedinPoAm clock and for women only using the PhenoAge (β: -8.20; P < 0.001) and GrimAge (β: -5.91; P < 0.001) clocks. Longitudinal modelling revealed a robust association between change in grip strength from wave 1 to wave 3 was independently associated with PhenoAgeAA (β: -0.13; 95% CI: -0.23, -0.03) and GrimAgeAA (β: -0.07; 95% CI: -0.14, -0.01) in men only (both P < 0.05).

CONCLUSIONS

Our findings provide some initial evidence of age acceleration among men and women with lower NGS and loss of strength over time. Future research is needed to understand the extent to which DNAm age mediates the association between grip strength and chronic disease, disability and mortality.

Latent Class Models of Early-life Trauma and Incident Breast Cancer

BACKGROUND

Psychosocial trauma has been hypothesized to influence breast cancer risk, but little is known about how co-occurring traumas-particularly during early life-may impact incidence. We examine the relationship between multiple measures of early-life trauma and incident breast cancer.

METHODS

The Sister Study is a prospective cohort study of US women (n = 50,884; enrollment 2003-2009; ages 35-74). Of 45,961 eligible participants, 3,070 developed invasive breast cancer or ductal carcinoma in situ through 2017. We assessed trauma before age 18 using previously studied measures (cumulative score, individual trauma type, and substantive domain) and a six-class latent variable to evaluate co-occurring traumas. We accounted for missing data using multiple imputation and estimated hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox proportional-hazards models.

RESULTS

Approximately 49% of participants reported early-life trauma. Using the latent class variable approach, breast cancer hazard was higher among participants who had sexual trauma or household dysfunction (HR = 1.1; CI = 0.93, 1.3) or moderate (HR = 1.2; CI = 0.99, 1.4) but not high trauma (HR = 0.66; CI = 0.44, 0.99) compared to low trauma. Breast cancer HRs associated with sexual early-life trauma or household dysfunction were elevated for pre- and postmenopausal breast cancer and by estrogen receptor status. We found no effect modification by race-ethnicity. Estimated effects were attenuated with report of constant childhood social support.

CONCLUSIONS

Breast cancer incidence varied by latent patterns of co-occurring early-life trauma. Models capturing childhood social support and trauma patterning, rather than cumulative or discrete indicators, may be more meaningful in breast cancer risk assessment.