Adverse Childhood Experiences, Institute of Epidemiology and Health Care Adverse Childhood Experiences, Stress Biomarkers, and Depression in Later Life Eleonora Iob, PhD Candidate Department of Behavioural Science and Health Soc-B CDT (ESRC & BBSRC) University College London I’m going to talk about.., which is the main topic of my PhD project. APS 77th Annual Scientific Meeting “BODY to MIND”

Outline Background Study 1: Relationship of C-reactive Protein (CRP) and Cortisol with Depressive Symptoms Study 2: Association of Adverse Childhood Experiences (ACE) with CRP and Cortisol Study 3: Longitudinal mediation analysis of ACE, CRP, and Depressive Symptoms Conclusions This is the outline of what I will discuss today… I will start by providing a brief overview of the background of my research, I will then present the results of three studies that I’ve conducted in this first year of my PhD project using data from ELSA. Finally, I will discuss the main findings of these studies and next steps for my research.

Outline Background Study 1: Relationship of C-reactive Protein (CRP) and Cortisol with Depressive Symptoms Study 2: Association of Adverse Childhood Experiences (ACE) with CRP and Cortisol Study 3: Longitudinal mediation analysis of ACE, CRP, and Depressive Symptoms Conclusions

Adverse Childhood Experiences (ACE) Psychobiological Processes Background Adverse Childhood Experiences (ACE) High prevalence (Bellis et al., 2014) Associated with several health and disease outcomes (Hughes et al., 2017) Depression 50% greater risk of developing depression (McLaughlin et al., 2016) Worse recovery and treatment outcomes (Nanni et al., 2012) Psychobiological Processes Hypothalamic-pituitary-adrenal (HPA)-axis: Cortisol Inflammation: C-reactive protein (Danese & McEwen, 2012; Danese & Lewis, 2017) Adverse childhood experiences (e.g. Abuse, maltreatment, family dysfunction) are extremely prevalent both in the uk and across the world, and have been associated with several health and disease outcomes. Amongst these, depression is one the health outcomes more strongly associated with ACE. Indeed, Ind exposed to ACE are twice more likely to develop depression and also experience worse recovery and treatment outcomes. The ACE and depression is now well-established. However, the specific biopsychosocial mechanisms through which this may occur remain unclear to date. In this context, it has been proposed that maladaptive alterations in the function of the hpa-axis and of the inflammatory response system might explain the long lasting effects of early-life stress on depression. Several studies have investigated the associations of biomarkers of these systems, such as cortisol and c-reactive protein, with both ACE and depression. However, different meta-analyses have provided inconsistent or weak evidence for these associations, possibly due to a considerable variability in the way in which ACE, depression, and the biomarkers have been measured across studies (I will provide more details on this shortly). Moreover, lack of prospective studies and direct evidence for mediation effects. These are all issues that I’ve addressed in the 3 studies I am going to present today.

Adverse Childhood Experiences (ACE) Psychobiological Processes Background Adverse Childhood Experiences (ACE) Depression Psychobiological Processes Cortisol C-reactive protein Limitations Inconsistent or weak evidence Methodological differences in measurement of variables Reverse causality Lack of evidence for mediation effects Several studies have investigated the associations of biomarkers of these systems, such as cortisol and c-reactive protein, with both ACE and depression. However, different meta-analyses have provided inconsistent or weak evidence for these associations, possibly due to a considerable variability in the way in which ACE, depression, and the biomarkers have been measured across studies (I will provide more details on this shortly). Moreover, lack of prospective studies and direct evidence for mediation effects. These are all issues that I’ve addressed in the 3 studies I am going to present today.

Outline Background Study 1: Relationship of C-reactive Protein (CRP) and Cortisol with Depressive Symptoms Study 2: Association of Adverse Childhood Experiences (ACE) with CRP and Cortisol Study 3: Longitudinal mediation analysis of ACE, CRP, and Depressive Symptoms Conclusions

Study 1: Aim and Hypotheses Aim: To investigate the relationship of cortisol (i.e. HPA-axis) and C-reactive protein (CRP) (i.e. inflammation) with: Persistent depressive symptoms 2) Cognitive-affective versus somatic dimensions - Let’s move onto the first study.. - Somatic symptoms: some preliminary evidence indicating that association of these biomarkers with depression might be predominantly driven by its somatic components.

Study 1: Methods Sample English Longitudinal Study of Ageing (ELSA) CRP sample: N = 5,784 Cortisol sample: N = 4,761 Measures Outcome: Depressive symptoms (CES-D 8), w1-8 (14-year period) Independent variables: Hair cortisol & plasma C-reactive Protein, w6 Covariates: Demographic, socioeconomic, lifestyle, chronic disease, and medication data COGNITIVE-AFFECTIVE: ‘‘enjoyed life”, ‘‘depressed”, ‘‘happy”, ‘‘lonely” , ‘sad” SOMATIC: ‘‘everything was an effort”, ‘‘sleep was restless”, ‘‘I could not get going” -data from ELSA -sample of_ for crp and of_ for cortisol

Trait-State Occasion (TSO) model Study 1: Methods Trait-State Occasion (TSO) model Statistical Analyses Trait-State-Occasion (TSO) structural equation modelling TSO model and missing data estimated using WLSMV estimator in Mplus Cortisol and CRP (<=10mg/l) were log-transformed C = cognitive-affective; S = somatic

Overall, cognitive-affective, and somatic factors Study 1: Results Effects of Cortisol (N= 4,761) and CRP (N=5,784) on persistent depressive symptoms: Overall, cognitive-affective, and somatic factors -overall -cognitive-affective versus somatic: this provides evidence that relationship between hpa-axis and inflammation might be driven by somatic symptoms.

Outline Background Study 1: Relationship of C-reactive Protein (CRP) and Cortisol with Depressive Symptoms Study 2: Association of Adverse Childhood Experiences (ACE) with CRP and Cortisol Study 3: Longitudinal mediation analysis of ACE, CRP, and Depressive Symptoms Conclusions After confirming the relationship of cortisol and crp with depression, examined the effect of adverse childhood experience on C-reactive protein and cortisol

Study 2: Aim and Hypotheses Aim: To investigate the effect of exposure to adverse childhood experiences (ACE) on C-reactive protein (CRP) and hair cortisol, distinguishing between: ACE cumulative exposure 2) ACE dimensions ACE - For which I will use the acronym ACE throughout this presentation ACE dimensions –most studies have used cumulative scores, although some evidence indicating that different dimensions may have distinct physiological effects.

Study 2: Methods Sample English Longitudinal Study of Ageing (ELSA) CRP sample: N = 4,198 Cortisol sample: N = 3,357 Measures Independent variable: Adverse childhood experiences (wave 3) Outcomes: (1) CRP, wave 4 (log) (2) High CRP, wave 4+6 (>3mg/l) (3) Hair Cortisol, wave 6 (log) Covariates: Demographic characteristics, childhood and adult socioeconomic factors, BMI, health behaviours, and medications Sample Variables Covariates: all analyses adjusted for relevant confounders.

Study 2: Methods CFA model of ACE Statistical Analyses ACE cumulative exposure: linear and ordered logistic regression (Rstudio) ACE dimensions: Confirmatory factor analysis (CFA) (Mplus) Missing data estimated using multiple imputation (R package ‘mice’) - ACE cumulative exposure - CFA model – different items available in ELSA, all measured retrospectively at wave 3. I grouped them into 4 main dimensions, namely… RMSEA: 0.038; CFI: 0.946; TLI: 0.926

Study 2: CRP(log) w4 ACE Cumulative score ACE Dimensions (model 3) Note. Linear regression model, Ref: ACE(0) Model 1: sex, age, marital status, medications Model 2: Model 1 + childhood and adult socioeconomic factors Model 3: Model 2 + lifestyle indicators -ACE cumulative score: Effects of being exposed to 1,2 and 3 or more adversities on crp at wave 4, compared to reference group = no adversity. I will focus on the fully adjusted models, blue bar. Group of people with 3 or more adversities had sign higher crp. No differences between the other groups. -ACE dimensions: all dimensions positively associated with crp at wave4, but loss dimension had much larger effects. C = cognitive-affective; S = somatic

Study 2: High CRP w4+w6 (>3 mg/l) ACE Cumulative score ACE Dimensions (model 3) Note. Ordered logistic regression, Ref: ACE(0) Model 1: sex, age, marital status, medications Model 2: Model 1 + childhood and adult socioeconomic factors Model 3: Model 2 + lifestyle indicators Ordered logistic regression. The estimates in the output are given in units of ordered logits, or ordered log odds. So for ace3+ we would say that we expect people with ACE3+ to have a value of High CRP on the log odds scale, of almost two units larger, when all other variables are held constant. Risk of having high crp at 0,1,or 2 occasions – very similar pattern of results. Group of people with 3 or more adversities had sign higher crp. Differences between other groups were much smaller. Dimensions- all associated, but stronger effects for loss. C = cognitive-affective; S = somatic

Study 2: Hair Cortisol w6 ACE Cumulative score ACE Dimensions (model 3) Note. Linear regression, Ref: ACE(0) Model 1: sex, age, marital status, hair data, medications Model 2: Model 1 + childhood and adult socioeconomic factors Model 3: Model 2 + lifestyle indicators - Hair cortisol was not associated neither with the ACE cumulative score, nor with the different dimensions of adversity. - After a more careful review of the literature, I found some evidence indicating that age might have moderating effects on cortisol

Study 2: Hair Cortisol w6 Interaction effect: ACE Cumulative score x Age (Model 3) Outcome: Hair cortisol Est. SE p-value ACE(1)*Age 0.003 0.353 ACE(2)*Age 0.000 0.004 0.963 ACE(3+)*Age 0.010 0.005 0.029 Ref: ACE(0)*Age Positive interaction effect between group of people with 3 or more adversities and age. Plot: purple line is for 3 or more adversity group. With increasing age, there was a steeper increase in cortisol for those who had 3 or more adversities compared to those with no or fewer adversities. Model 3: sex, age, marital status, hair characteristics, medications, childhood and adult socioeconomic factors, lifestyle indicators (bmi, smoking, alcohol, physical activity)

Outline Background Study 1: Relationship of C-reactive Protein (CRP) and Cortisol with Depressive Symptoms Study 2: Effect of Adverse Childhood Experiences (ACE) on C-reactive protein and Cortisol Study 3: Longitudinal mediation analysis of ACE, CRP, and Depressive Symptoms Conclusions

Study 3: Aim and Hypotheses Aim: To test the mediational role of C-reactive protein (CRP) in the relationship between childhood adverse experiences (ACE) and depression over time: Direct effects of ACE on depression, CRP, and their trajectories 2) Indirect effects of ACE on depression through CRP For those of you who are not familiar with indirect effects – these are simply the direct effect of the predictor on the mediator multiplied by the direct effect of the mediator on the outcome.

Study 3: Methods Sample English Longitudinal Study of Ageing (ELSA) Sample: N = 4,382 Measures Independent variable: Adverse childhood experiences (wave 3) Mediator: CRP (log) waves 2,4,6 Outcome: Depressive symptoms (CES-D 8) waves 6,7,8 Covariates: Demographic characteristics, childhood and adult socioeconomic factors, lifestyle indicators, and medications

Study 3: Methods Statistical Analyses Parallel process latent growth curve modelling (WLSMV estimator in Mplus) Indirect effects estimated with bias-corrected bootstrap standard errors Missing data estimated using multiple imputation (R package ‘mice’) Longitudinal Mediation Model

Study 3: Methods Statistical Analyses Parallel process latent growth curve model (WLSMV estimator in Mplus) Indirect effects estimated with bias-corrected bootstrap standard errors Missing data estimated using multiple imputation (R package ‘mice’) Longitudinal Mediation Model

Study 3: Methods Statistical Analyses Parallel process latent growth curve model (WLSMV estimator in Mplus) Indirect effects estimated with bias-corrected bootstrap standard errors Missing data estimated using multiple imputation (R package ‘mice’) Longitudinal Mediation Model

Study 3: Results Total Depressive Symptoms Somatic Depressive Symptoms Model 3: Adjusted for sex, age, marital status, childhood and adult socioeconomic factors, lifestyle indicators, and medications

Outline Conclusions Background Study 1: Relationship of C-reactive Protein (CRP) and Cortisol with Depressive Symptoms Study 2: Effect of Adverse Childhood Experiences (ACE) on C-reactive protein and Cortisol Study 3: Longitudinal mediation analysis of ACE, CRP, and Depressive Symptoms Conclusions Both systems activated by stress, and involved in several physical health conditions

Conclusions STUDY 1 STUDY 2 STUDY 3 Higher hair cortisol and CRP levels were associated with more persistent depressive symptoms across a 14-year period These relationships were driven by somatic symptoms STUDY 2 Greater exposure to ACE was associated with elevated CRP levels Adversities related to loss of an attachment figure had the strongest effects Greater exposure to ACE was related to a steeper increase in hair cortisol with age STUDY 3 Greater exposure to ACE was associated with higher CRP and depression at baseline and with their increase over time No evidence for mediation effects of CRP Both systems activated by stress, and involved in several physical health conditions

Conclusions Next steps 1. ELSA 2. ALSPAC 3. TEDS CRP: reverse mediation model Cortisol: Moderated mediation model for the interaction between ACE and age Polygenic scores of depression, cortisol, and CRP: main effects and interaction effects with ACE 2. ALSPAC Associations between ACE, stress biomarkers, and depression Main and interaction effects of polygenic scores DNA methylation 3. TEDS Associations between ACE, salivary cortisol, and depression ALSPAC and TEDS: move onto ALSPAC and TEDS where I conduct similar analyses but with a greater focus on the timing of adversity since both studies have very rich data on adversity collected retrospectively. I might also examine the role of dna methylation of stress-related genes.

Acknowledgments Supervisors & collaborators: Prof Andrew Steptoe, Dr Rebecca Lacey, Dr Panos Demakakos, Prof Clemens Kirschbaum Research funders & ELSA participants Eleonora Iob (PhD Candidate) Soc-B CDT (ESRC & BBSRC) University College London eleonora.iob.17@ucl.ac.uk