Exploring the potential role of allostatic load biomarkers in risk assessment of patients presenting with depressive symptoms

Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation

Acceptability of mindfulness from the perspective of stroke survivors and caregivers: a qualitative study

Background: Depression is very common among stroke survivors with estimated prevalence rates of approximately 33% among stroke survivors, but treatment options are limited. Mindfulness-Based Stress Reduction (MBSR) is an effective treatment for depression generally, but benefits in stroke patients are unclear. The aim of this study was to determine the feasibility of delivering MBSR to stroke survivors and their caregivers in the community. We conducted a study to gain views of MBSR as a potential treatment option among stroke survivors and their caregivers in the community. Methods: Participants were recruited from an urban community in Scotland (UK) using newspaper adverts, social media and support groups run by health charities. A 2-h MBSR taster session was delivered by two experienced mindfulness instructors, followed by focus group sessions with all participants on their user experience and suggestions for MBSR modifications for stroke survivors. The focus group sessions were audio recorded and transcribed verbatim. Transcript data were analysed thematically using the framework approach. Results: The study sample consisted of 28 participants (16 females); there were 21 stroke survivors (11 females) and 7 caregivers (5 females). The median age for participants was 60 years. Most participants described the MBSR taster session as a positive experience. The main challenge reported was trying to maintain focus and concentration throughout the MBSR session. Some participants expressed reservations about the duration of standard mindfulness course sessions, suggesting a preference for shorter sessions. The potential for achieving better control over negative thoughts and emotions was viewed as a potential facilitator for future MBSR participation. Participants suggested having an orientation session prior to starting an 8-week course as a means of developing familiarity with the MBSR instructor and other participants. Conclusion: It was feasible to recruit 21 stroke survivors and 7 caregivers for MBSR taster sessions in the community. A shorter MBSR session and an orientation session prior to the full course are suggestions for potential MBSR modifications for stroke survivors, which needs further research and evaluation

Relationship of depression screening in cardiometabolic disease with vascular events and mortality: findings from a large primary care cohort with 4 years follow-up

Aims: Benefits of routine depression screening for cardiometabolic disease patients remain unclear. We examined the association between depression screening and all-cause mortality and vascular events in cardiometabolic disease patients. Methods and results: 125 143 patients with cardiometabolic diseases (coronary heart disease, diabetes or previous stroke) in the UK participated in primary care chronic disease management in 2008/09, which included depression screening using the Hospital Anxiety and Depression Score. 10 670 receiving depression treatment exempted, 35 537 screened, while 78 936 not screened. We studied all-cause mortality and vascular events at 4 years, by electronic data linkage of 124 414 patients (99.4%) on primary care registers to hospital discharge and mortality records and used Cox proportional hazards on matched data using propensity score. Mean age for the screened and not screened population was 69 years (standard deviation—SD 11.9) and 67 years (SD 14.3), respectively; 58% (20 658) of the screened population were men and 65.3% (22 726) were socioeconomically deprived, compared with 54.2% (42 727) and 67.4% (51 686), respectively, in the not screened population. The screened population had lower all-cause mortality (Hazard Ratio—HR 0.89) and vascular events (HR 0.85) in the matched data of N = 21 893 patients each in the screened and the unscreened groups. Conclusion: Depression screening was associated with a reduction in all-cause mortality and vascular events in patients with cardiometabolic diseases. The uptake of screening was poor for unknown reasons. Reverse causality and confounding by disease severity and quality of care are important possible limitations. Further research to determine reproducibility and explore underlying mechanisms is merited

Risk factors and mortality associated with multimorbidity in people with stroke or transient ischaemic attack: a study of 8,751 UK Biobank participants

Background: Multimorbidity is common in stroke, but the risk factors and effects on mortality remain poorly understood. Objective: To examine multimorbidity and its associations with sociodemographic/lifestyle risk factors and all-cause mortality in UK Biobank participants with stroke or transient ischaemic attack (TIA). Design: Data were obtained from an anonymized community cohort aged 40–72 years. Overall, 42 comorbidities were self-reported by those with stroke or TIA. Relative risk ratios demonstrated associations between participant characteristics and number of comorbidities. Hazard ratios demonstrated associations between the number and type of comorbidities and all-cause mortality. Results were adjusted for age, sex, socioeconomic status, smoking, and alcohol intake. Data were linked to national mortality data. Median follow-up was 7 years. Results: Of 8,751 participants (mean age 60.9±6.7 years) with stroke or TIA, the all-cause mortality rate over 7 years was 8.4%. Over 85% reported ≥1 comorbidities. Age, socioeconomic deprivation, smoking and less frequent alcohol intake were associated with higher levels of multimorbidity. Increasing multimorbidity was associated with higher all-cause mortality. Mortality risk was double for those with ≥5 comorbidities compared to those with none. Having cancer, coronary heart disease, diabetes, or chronic obstructive pulmonary disease significantly increased mortality risk. Presence of any cardiometabolic comorbidity significantly increased mortality risk, as did any non-cardiometabolic comorbidity. Conclusions: In stroke survivors, the number of comorbidities may be a more helpful predictor of mortality than type of condition. Stroke guidelines should take greater account of comorbidities, and interventions are needed that improve outcomes for people with multimorbidity and stroke

Relationship between blood pressure values, depressive symptoms and cardiovascular outcomes in patients with cardiometabolic disease

We studied joint effect of blood pressure-BP and depression on risk of major adverse cardiovascular outcome in patients with existing cardiometabolic disease. A cohort of 35537 patients with coronary heart disease, diabetes or stroke underwent depression screening and BP was recorded concurrently. We used Cox’s proportional hazards to calculate risk of major adverse cardiovascular event-MACE (myocardial infarction/heart failure/stroke or cardiovascular death) over 4 years associated with baseline BP and depression. 11% (3939) had experienced MACE within 4 years. Patients with very high systolic BP-SBP (160-240) hazard ratio-HR 1.28 and with depression (HR 1.22) at baseline had significantly higher adjusted risk. Depression had significant interaction with SBP in risk prediction (p=0.03). Patients with combination of SBP and depression at baseline had 83% higher adjusted risk of MACE, as compared to patients with reference SBP and without depression. Patients with cardiometabolic disease and comorbid depression may benefit from closer monitoring of SBP

Risk assessment and predicting outcomes in patients with depressive symptoms: a review of potential role of peripheral blood based biomarkers

Depression is one of the major global health challenges and a leading contributor of health related disability and costs. Depression is a heterogeneous disorder and current methods for assessing its severity in clinical practice rely on symptom count, however this approach is unreliable and inconsistent. The clinical evaluation of depressive symptoms is particularly challenging in primary care, where the majority of patients with depression are managed, due to the presence of co-morbidities. Current methods for risk assessment of depression do not accurately predict treatment response or clinical outcomes. Several biological pathways have been implicated in the pathophysiology of depression; however, accurate and predictive biomarkers remain elusive. We conducted a systematic review of the published evidence supporting the use of peripheral biomarkers to predict outcomes in depression, using Medline and Embase. Peripheral biomarkers in depression were found to be statistically significant predictors of mental health outcomes such as treatment response, poor outcome and symptom remission; and physical health outcomes such as increased incidence of cardiovascular events and deaths, and all-cause mortality. However, the available evidence has multiple methodological limitations which must be overcome to make any real clinical progress. Despite extensive research on the relationship of depression with peripheral biomarkers, its translational application in practice remains uncertain. In future, peripheral biomarkers identified with novel techniques and combining multiple biomarkers may have a potential role in depression risk assessment but further research is needed in this area

Multimorbidity and co-morbidity in atrial fibrillation and effects on survival: findings from UK Biobank cohort

Aims: To examine the number and type of co-morbid long-term health conditions (LTCs) and their associations with all-cause mortality in an atrial fibrillation (AF) population. Methods and results: Community cohort participants (UK Biobank n = 502 637) aged 37–73 years were recruited between 2006 and 2010. Self-reported LTCs (n = 42) identified in people with AF at baseline. All-cause mortality was available for a median follow-up of 7 years (interquartile range 76–93 months). Hazard ratios (HRs) examined associations between number and type of co-morbid LTC and all-cause mortality, adjusting for age, sex, socio-economic status, smoking, and anticoagulation status. Three thousand six hundred fifty-one participants (0.7% of the study population) reported AF; mean age was 61.9 years. The all-cause mortality rate was 6.7% (248 participants) at 7 years. Atrial fibrillation participants with ≥4 co-morbidities had a six-fold higher risk of mortality compared to participants without any LTC. Co-morbid heart failure was associated with higher risk of mortality [HR 2.96, 95% confidence interval (CI) 1.83–4.80], whereas the presence of co-morbid stroke did not have a significant association. Among non-cardiometabolic conditions, presence of chronic obstructive pulmonary disease (HR 3.31, 95% CI 2.14–5.11) and osteoporosis (HR 3.13, 95% CI 1.63–6.01) was associated with a higher risk of mortality. Conclusion: Survival in middle-aged to older individuals with self-reported AF is strongly correlated with level of multimorbidity. This group should be targeted for interventions to optimize their management, which in turn may potentially reduce the impact of their co-morbidities on survival. Future AF clinical guidelines need to place greater emphasis on the issue of co-morbidity

Multimorbidity in stroke

No abstract available

Examining the relationship between rheumatoid arthritis, multimorbidity and adverse health-related outcomes: a systematic review protocol

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterised by articular inflammation and systemic complications. Multimorbidity (the presence of two or more long-term health conditions) is highly prevalent in people with RA but the effect of multimorbidity on mortality and other health-related outcomes is poorly understood. Objective: To determine what is known about the effect, if any, of multimorbidity on mortality and health-related outcomes in individuals with RA. Design: Systematic review of the literature. The following electronic medical databases will be searched: MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, The Cochrane Library and Scopus. Included studies will be quality appraised using the Quality in Prognostic Studies tool developed by the Cochrane Prognosis Methods Group. A narrative synthesis of findings will be undertaken and meta-analyses considered, if appropriate. This protocol adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols 2015 guidelines, ensuring the quality of the review. Conclusions: Understanding the influence of multimorbidity on mortality and other health-related outcomes in RA will provide an important basis of knowledge with the potential to improve future clinical management of RA. PROSPERO registration number: CRD42019137756

Risk factors and mortality associated with multimorbidity in people with stroke or transient ischaemic attack: a study of 8,751 UK Biobank participants

Background: Multimorbidity is common in stroke, but the risk factors and effects on mortality remain poorly understood. Objective: To examine multimorbidity and its associations with sociodemographic/lifestyle risk factors and all-cause mortality in UK Biobank participants with stroke or transient ischaemic attack (TIA). Design: Data were obtained from an anonymized community cohort aged 40–72 years. Overall, 42 comorbidities were self-reported by those with stroke or TIA. Relative risk ratios demonstrated associations between participant characteristics and number of comorbidities. Hazard ratios demonstrated associations between the number and type of comorbidities and all-cause mortality. Results were adjusted for age, sex, socioeconomic status, smoking, and alcohol intake. Data were linked to national mortality data. Median follow-up was 7 years. Results: Of 8,751 participants (mean age 60.9±6.7 years) with stroke or TIA, the all-cause mortality rate over 7 years was 8.4%. Over 85% reported ≥1 comorbidities. Age, socioeconomic deprivation, smoking and less frequent alcohol intake were associated with higher levels of multimorbidity. Increasing multimorbidity was associated with higher all-cause mortality. Mortality risk was double for those with ≥5 comorbidities compared to those with none. Having cancer, coronary heart disease, diabetes, or chronic obstructive pulmonary disease significantly increased mortality risk. Presence of any cardiometabolic comorbidity significantly increased mortality risk, as did any non-cardiometabolic comorbidity. Conclusions: In stroke survivors, the number of comorbidities may be a more helpful predictor of mortality than type of condition. Stroke guidelines should take greater account of comorbidities, and interventions are needed that improve outcomes for people with multimorbidity and stroke