Genetic susceptibility, inflammation and specific types of depressive symptoms: evidence from the English Longitudinal Study of Ageing

Measurement invariance of the Center for Epidemiological Studies-Depression scale and associations with genetic risk in older adults

BACKGROUND

As populations are aging, it needs to be ensured that valid depression rating scales are available across old adulthood. Center for Epidemiological Studies-Depression scale (CES-D) is a common depression rating scale, however, few studies have assessed its validity in individuals with age over 90 and/or cognitive impairment. We examined the factor structures of 20-, 15-, and 8-item CES-D scales, their measurement invariance for age and cognition, and associations with genetic risk of depression.

METHODS

Participants were from a population-based older Finnish Twin Cohort study including 71-79-year-olds from the MEMTWIN II (n = 1034 for exploratory and n = 664 for confirmatory factor analyses) and 90+ year-olds from the NONAGINTA (n = 134, confirmatory factor analyses) sub-studies. Associations of polygenic risk score of major depressive disorder (MDD-PRS) with CES-D scales were examined in MEMTWIN II.

RESULTS

Exploratory factor analyses (n = 1034) suggested four- (CES-D 20) and three-factor (CES-D 8) structures and these models fit well in confirmatory analyses (n = 664). Unidimensional models had good (CES-D 15 & 20) or fair fit (CES-D 8). Results supported scalar invariance of all CES-D versions for age and cognitive status. Higher MDD-PRS was associated with more depressive symptoms in different CES-D versions.

CONCLUSIONS

Different CES-D versions are adequate for measuring depressive symptoms across age groups and cognitive spectrum in old age. Genetic risk of depression predicts depressive symptoms even in old age.

Eight-year total, cognitive-affective, and somatic depressive symptoms trajectories and risks of cardiac events

In this study, we analyzed pooled data from two prospective population-based cohorts-the Health Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA)-to explore the association between trajectories of depressive symptoms and the risk of cardiac events. Depressive symptoms were assessed using the 8-item CES-D scale and categorized into somatic and cognitive-affective subtypes. Trajectories were tracked for four surveys from baseline. Heart disease was identified based on self-reported physician-diagnosed conditions. Hazard ratios and 95% confidence intervals were calculated with Cox proportional risk models that adjusted for potential confounders. In total, 17,787 subjects (59.7% female, median age 63 years) were enrolled at baseline. During a 10-year follow-up, 2409 cases of heart disease were identified. Participants with fluctuating (HR = 1.13, 95% CI: 1.06-1.20), increasing (HR = 1.43, 95% CI: 1.25-1.64), and consistently high (HR = 1.64, 95% CI: 1.45-1.84) depressive symptom trajectories exhibited an increased risk of heart disease compared to those with consistently low depressive symptoms, while a decreasing (HR = 1.07, 95% CI: 0.96-1.19) depressive symptom trajectory did not significantly affect the risk of heart disease. Moreover, the association between heart disease and somatic depressive symptoms was found to be stronger than with cognitive-affective symptoms. These findings suggest a significant link between depressive symptom trajectories and heart disease, with particular emphasis on stronger associations with somatic symptoms. It is recommended that the identification and management of depressive symptoms be incorporated into heart disease prevention strategies.

Immune-neuroendocrine patterning and response to stress. A latent profile analysis in the English longitudinal study of ageing

Psychosocial stress exposure can disturb communication signals between the immune, nervous, and endocrine systems that are intended to maintain homeostasis. This dysregulation can provoke a negative feedback loop between each system that has high pathological risk. Here, we explore patterns of immune-neuroendocrine activity and the role of stress. Using data from the English Longitudinal Study of Ageing (ELSA), we first identified the latent structure of immune-neuroendocrine activity (indexed by high sensitivity C-reactive protein [CRP], fibrinogen [Fb], hair cortisol [cortisol], and insulin growth-factor-1 [IGF-1]), within a population-based cohort using latent profile analysis (LPA). Then, we determined whether life stress was associated with membership of different immune-neuroendocrine profiles. We followed 4,934 male and female participants, with a median age of 65 years, over a four-year period (2008-2012). A three-class LPA solution offered the most parsimonious fit to the underlying immune-neuroendocrine structure in the data, with 36 %, 40 %, and 24 % of the population belonging to profiles 1 (low-risk), 2 (moderate-risk), and 3 (high-risk), respectively. After adjustment for genetic predisposition, sociodemographics, lifestyle, and health, higher exposure to stress was associated with a 61 % greater risk of belonging to the high-risk profile (RRR: 1.61; 95 %CI = 1.23-2.12, p = 0.001), but not the moderate-risk profile (RRR = 1.10, 95 %CI = 0.89-1.35, p = 0.401), as compared with the low-risk profile four years later. Our findings extend existing knowledge on psychoneuroimmunological processes, by revealing how inflammation and neuroendocrine activity cluster in a representative sample of older adults, and how stress exposure was associated with immune-neuroendocrine responses over time.

Immune-Neuroendocrine Patterning and Response to Stress. A latent profile analysis in the English Longitudinal Study of Ageing

Psychosocial stress exposure can disturb communication signals between the immune, nervous, and endocrine systems that are intended to maintain homeostasis. This dysregulation can provoke a negative feedback loop between each system that has high pathological risk. Here, we explore patterns of immune-neuroendocrine activity and the role of stress. Using data from the English Longitudinal Study of Ageing (ELSA), we first identified the latent structure of immune-neuroendocrine activity (indexed by high sensitivity C-reactive protein [CRP], fibrinogen [Fb], hair cortisol [cortisol], and insulin growth-factor-1 [IGF-1]), within a population-based cohort using latent profile analysis (LPA). Then, we determined whether life stress was associated with membership of different immune-neuroendocrine profiles. We followed 4,934 male and female participants with a median age of 65 years over a four-year period (2008-2012). A three-class LPA solution offered the most parsimonious fit to the underlying immune-neuroendocrine structure in the data, with 36%, 40%, and 24% of the population belonging to profiles 1 (low-risk), 2 (moderate-risk), and 3 (high-risk), respectively. After adjustment for genetic predisposition, sociodemographics, lifestyle, and health, higher exposure to stress was associated with a 61% greater risk of belonging to the high-risk profile (RRR: 1.61; 95%CI=1.23-2.12, p=0.001), but not the moderate-risk profile (RRR=1.10, 95%CI=0.89-1.35, p=0.401), as compared with the low-risk profile four years later. Our findings extend existing knowledge on psychoneuroimmunological processes, by revealing how inflammation and neuroendocrine activity cluster in a representative sample of older adults, and how stress exposure was associated with immune-neuroendocrine responses over time.

Excess body weight and specific types of depressive symptoms: Is there a mediating role of systemic low-grade inflammation?

OBJECTIVES

Obesity is associated with an increased risk of depression. Systemic low-grade inflammation, a plausible consequence of obesity, has also been linked to depression. However, the potential mediating effects of systemic low-grade inflammation on the association between excess body weight and specific symptom domains of depression remain uncertain. This study examined whether systemic low-grade inflammation mediated the associations of excess body weight (overweight and obesity) with subsequent overall, cognitive-affective, and somatic depressive symptoms.

DESIGN

This study used a prospective cohort design.

METHODS

The final analytical sample included 4,942 adults aged ≥50 years drawn from the English Longitudinal Study of Ageing (ELSA). Body mass index (BMI) and covariates were ascertained at baseline (wave 4, 2008/09). Continuous BMI scores were divided into four categories: 'normal weight' (18.5 ≤ BMI <25 kg/m2); 'overweight' (25 ≤ BMI <30 kg/m2); 'obesity' (BMI ≥30 kg/m2); in addition to 'excess body weight' ('overweight' and 'obesity' combined). Covariates included sociodemographic variables, behavioural factors, and chronic physical conditions. Serum concentrations of CRP were measured at wave 6 (2012/13). Depressive symptoms were assessed at baseline and ten years later (wave 9, 2018/19), using the 8-item Centre for Epidemiological Studies Depression (CES-D) Scale. Two symptom domains were constructed, distinguishing between cognitive-affective (depressed mood, loneliness, sadness, enjoyment in life, and happiness) and somatic (sleep problems, low energy levels, and fatigue) symptoms. Mediation analyses were performed to examine whether CRP statistically mediated the associations between BMI categories and depressive symptoms.

RESULTS

In multivariable-adjusted analyses, excess body weight was associated with elevated somatic (OR = 1.231, 95% CI: 1.029, 1.473), but not cognitive-affective or overall depressive symptoms at follow-up. Higher CRP was associated with elevated somatic (OR = 1.156, 95% CI: 1.061, 1.259), but not cognitive-affective or overall depressive symptoms. CRP acted as a partial mediator (14.92%) of the association between excess body weight and elevated somatic, but not cognitive-affective, or overall depressive symptoms.

CONCLUSION

Systemic low-grade inflammation may partially explain the association of excess body weight with somatic depressive symptoms, but not the associations with cognitive-affective or overall depressive symptoms.

[Genome-wide studies of comorbidity of somatic and mental diseases]

Studies of the genomic architecture of complex phenotypes, which include common somatic and mental diseases, have shown that they are characterized by a high degree of polygenicity, i.e. participation of a large number of genes associated with the risk of developing these diseases. In this regard, it is of interest to establish the genetic overlapping between these two groups of diseases. The aim of the review is to analyze genetic studies of the comorbidity of somatic and mental diseases in terms of the universality and specificity of mental disorders in somatic diseases, the reciprocal relationships of these types of pathologies, and the modulating influence of environmental factors on comorbidity. The results of the analysis indicate the existence of a common genetic predisposition to mental and somatic diseases. At the same time, the presence of common genes does not exclude the specificity of the development of mental disorders depending on a specific somatic pathology. It can be assumed that there are genes that are both unique to a particular somatic and comorbid mental illness, and genes that are common to these diseases. Common genes may have varying degrees of specificity, that is, they may be of a universal nature, which, for example, manifests itself in the development of MDD in various somatic diseases, or be specific only for a couple of individual diseases (schizophrenia - breast cancer). At the same time, common genes can have a multidirectional effect, which also contributes to the specificity of comorbidity. In addition, when searching for common genes for somatic and mental diseases, it is necessary to take into account the modulating influence of such confounders as treatment, unhealthy life style, behavioral characteristics, which can also differ in specificity depending on the diseases under consideration.

Assessing the effect of interaction between gut microbiome and inflammatory bowel disease on the risks of depression

Background

Gut microbiome and inflammatory bowel disease (IBD) are implicated in the development of depression, but the effect of their interactions on the risk of depression remains unclear. We aim to analyze the effect of interactions between gut microbiome and IBD on the risk of depression, and explore candidate genes involving the interactions.

Methods

Using the individual genotype and depression traits data from the UK Biobank, we calculated the polygenetic risk scores (PRS) of 114 gut microbiome, ulcerative colitis (UC), Crohn's disease (CD), and total IBD (CD + UC) respectively. The effects of interactions between gut microbiome and IBD on depression were assessed through a linear regression model. Moreover, for observed significant interactions between gut microbiome PRS and IBD PRS, PLINK software was used to test pair-wise single nucleotide polymorphisms (SNPs) interaction of corresponding gut microbiome PRS and IBD PRS on depression.

Results

We found 64 candidate interactions between gut microbiome and IBD on four phenotypes of depression, such as F_Lachnospiraceae (RNT) × (CD + UC) for patient health questionnaire-9 (PHQ-9) score (P = 1.48 × 10^-3), F_Veillonellaceae (HB) × UC for self-reported depression (P = 2.83 × 10^-3) and P_Firmicutes (RNT) × CD for age at first episode of depression (P = 8.50 × 10^-3). We observed interactions of gut-microbiome-associated SNPs × IBD-associated SNPs, such as G_Alloprevotella (HB)-associated rs147650986 (GPM6A) × IBD-associated rs114471990 (QRICH1) (P = 2.26 × 10^-4).

Conclusion

Our results support the effects of interactions between gut microbiome and IBD on depression risk, and reported several novel candidate genes for depression.

Shared genetic loci between depression and cardiometabolic traits

Epidemiological and clinical studies have found associations between depression and cardiovascular disease risk factors, and coronary artery disease patients with depression have worse prognosis. The genetic relationship between depression and these cardiovascular phenotypes is not known. We here investigated overlap at the genome-wide level and in individual loci between depression, coronary artery disease and cardiovascular risk factors. We used the bivariate causal mixture model (MiXeR) to quantify genome-wide polygenic overlap and the conditional/conjunctional false discovery rate (pleioFDR) method to identify shared loci, based on genome-wide association study summary statistics on depression (n = 450,619), coronary artery disease (n = 502,713) and nine cardiovascular risk factors (n = 204,402–776,078). Genetic loci were functionally annotated using FUnctional Mapping and Annotation (FUMA). Of 13.9K variants influencing depression, 9.5K (SD 1.0K) were shared with body-mass index. Of 4.4K variants influencing systolic blood pressure, 2K were shared with depression. ConjFDR identified 79 unique loci associated with depression and coronary artery disease or cardiovascular risk factors. Six genomic loci were associated jointly with depression and coronary artery disease, 69 with blood pressure, 49 with lipids, 9 with type 2 diabetes and 8 with c-reactive protein at conjFDR < 0.05. Loci associated with increased risk for depression were also associated with increased risk of coronary artery disease and higher total cholesterol, low-density lipoprotein and c-reactive protein levels, while there was a mixed pattern of effect direction for the other risk factors. Functional analyses of the shared loci implicated metabolism of alpha-linolenic acid pathway for type 2 diabetes. Our results showed polygenic overlap between depression, coronary artery disease and several cardiovascular risk factors and suggest molecular mechanisms underlying the association between depression and increased cardiovascular disease risk.

Association Between Systemic Inflammation and Individual Symptoms of Depression: A Pooled Analysis of 15 Population-Based Cohort Studies

OBJECTIVE

Evidence from anti-inflammatory drug trials for the treatment of depression has been inconsistent. This may be ascribed to the differing symptom-specific effects of inflammation. Accordingly, the authors explored the associations between systemic inflammation and an array of individual symptoms of depression across multiple studies.

METHODS

This random-effects pooled analysis included 15 population-based cohorts and 56,351 individuals age 18 years and older. Serum or plasma concentrations of C-reactive protein (CRP) and interleukin-6 (IL-6) were measured at baseline. Using validated self-report measures, 24 depressive symptoms were ascertained in 15 cross-sectional studies, and, in seven cohorts, were also assessed at follow-up (mean follow-up period, 3.2 years).

RESULTS

The prevalence of depressive symptoms ranged from 1.1% (suicidal ideation) to 21.5% (sleep problems). In cross-sectional analyses, higher concentrations of CRP were robustly associated with an increased risk of experiencing four physical symptoms (changes in appetite, felt everything was an effort, loss of energy, sleep problems) and one cognitive symptom (little interest in doing things). These associations remained after adjustment for sociodemographic variables, behavioral factors, and chronic conditions; in sex- and age-stratified analyses; in longitudinal analyses; when using IL-6 as the inflammatory marker of interest; in depressed individuals; and after excluding chronically ill individuals. For four exclusively emotional symptoms (bothered by things, hopelessness about the future, felt fearful, life had been a failure), the overall evidence was strongly against an association with inflammation.

CONCLUSIONS

These findings suggest symptom-specific rather than generalized effects of systemic inflammation on depression. Future trials exploring anti-inflammatory treatment regimens for depression may benefit from targeting individuals presenting with symptom profiles characterized by distinct inflammation-related physical and cognitive symptoms.

Therapy response prediction in major depressive disorder: current and novel genomic markers influencing pharmacokinetics and pharmacodynamics

Major depressive disorder is connected with high rates of functional disability and mortality. About a third of the patients are at risk of therapy failure. Several pharmacogenetic markers especially located in CYP450 genes such as CYP2D6 or CYP2C19 are of relevance for therapy outcome prediction in major depressive disorder but a further optimization of predictive tools is warranted. The article summarizes the current knowledge on pharmacogenetic variants, therapy effects and side effects of important antidepressive therapeutics, and sheds light on new methodological approaches for therapy response estimation based on genetic markers with relevance for pharmacokinetics, pharmacodynamics and disease pathology identified in genome-wide association study analyses, highlighting polygenic risk score analysis as a tool for further optimization of individualized therapy outcome prediction.

Adverse childhood experiences and depressive symptoms in later life: Longitudinal mediation effects of inflammation

BACKGROUND

Adverse childhood experiences (ACEs) have been associated with both inflammation and depression. However, few studies have examined the role of inflammation as a possible biological mechanism underlying the association of ACEs with depression in later life using longitudinal data. This study investigated the longitudinal mediation effects of inflammation in the relationship between ACEs and depressive symptoms in older adults.

METHODS

We utilised data from the English Longitudinal Study of Ageing (N = 4382). ACEs (i.e. threat, family dysfunction, low parental bonding, loss experiences) were assessed retrospectively at wave 3 (2006/07). C-reactive protein (CRP), an inflammatory marker, was measured at waves 2 (2004/05), 4 (2008/09), and 6 (2012/13). Depressive symptoms were ascertained from wave 6 to 8 (2016/17). The mediation analysis was conducted using parallel process latent growth curve modelling.

RESULTS

Greater ACEs cumulative exposure was associated with higher CRP and depressive symptoms at baseline (β_CRPi = 0.066[0.030-0.102]; β_DEPi = 0.149[0.115-0.183]) and with their increase over time (β_CRPs = 0.205[0.095-0.315]; β_DEPs = 0.355[0.184-0.526]). Baseline CRP levels were positively associated with baseline depressive symptoms (β_DEPi = 0.145[0.104-0.186]) and their trajectory (β_DEPs = 0.215[0.124-0.306]). The mediation analysis indicated that higher baseline CRP levels mediated respectively 7% and 5% of the total effect of ACEs cumulative exposure on the baseline value and change in depressive symptoms. These mediation effects were larger for Loss experiences (i.e. 20% and 12% respectively) than for other types of ACEs. In addition, they were independent of possible confounders and additional mediators including adult socioeconomic position and lifestyle factors.

CONCLUSION

ACEs were related to higher depressive symptoms partly via elevated CRP levels. Inflammation might be one of the psychobiological mechanisms underlying the link between ACEs and depression. Psychosocial and behavioural interventions to prevent and reduce the negative impact of ACEs might help to lower the risk of inflammation and depression in the population.