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.

Lifestyle factors, adiposity and cardiometabolic risk factors in South Asian women living in Scotland

South Asians migrating to the Western world have a 3 to 5-fold higher risk of developing type 2 diabetes and double the risk of cardiovascular disease (CVD) than the background population of White European descent, without exhibiting a proportional higher prevalence of conventional cardiometabolic risk factors. Notably, women of South Asian descent are more likely to be diagnosed with type 2 diabetes as they grow older compared with South Asian men and, in addition, they have lost the cardio-protective effects of being females. Despite South Asian women in Western countries being a high risk group for developing future type 2 diabetes and CVD, they have been largely overlooked. The aims of this thesis were to compare lifestyle factors, body composition and cardiometabolic risk factors in healthy South Asian and European women who reside in Scotland, to examine whether ethnicity modifies the associations between modifiable environmental factors and cardiometabolic risks and to assess whether vascular reactivity is altered by ethnicity or other conventional and novel CVD risks. I conducted a cross-sectional study and recruited 92 women of South Asian and 87 women of White European descent without diagnosed diabetes or CVD. Women on hormone replacement therapy or hormonal contraceptives were excluded too. Age and body mass index (BMI) did not differ between the two ethnic groups. Physical activity was assessed and with self-reported questionnaires and objectively with the use of accelerometers. Cardiorespiratory fitness was quantified with the predicted maximal oxygen uptake (VO2 max) during a submaximal test (Chester step test). Body composition was assessed with skinfolds measured at seven body sites, five body circumferences, measurement of abdominal subcutaneous (SAT) and visceral adipose tissue (VAT) with the use of magnetic resonance imaging (MRI) and liver fat with the use MR spectroscopy. Dietary density was assessed with food frequency questionnaires. Vascular response was assessed by measuring the response to acetylcholine and sodium nitroprusside with the use of Laser Doppler Imaging with Iontophoresis (LDI-ION) and the response to shear stress with the use of Peripheral Arterial Tonometry (EndoPAT). The South Asian women exhibited a metabolic profile consistent with the insulin resistant phenotype, characterised by greater levels of fasting insulin, lower levels of high density lipoprotein (HDL) and higher levels of triglycerides (TG) compared with their European counterparts. In addition, the South Asians had greater levels of glycated haemoglobin (HbA1c) for any given level of fasting glucose. The South Asian women engaged less time weekly with moderate to vigorous physical activity (MVPA) and had lower levels of cardiorespiratory fitness for any given level of physical activity than the women of White descent. In addition, they accumulated more fat centrally for any given BMI. Notably, the South Asians had equivalent SAT with the European women but greater VAT and hepatic fat for any given BMI. Dietary density did not differ among the groups. Increasing central adiposity had the largest effect on insulin resistance in both ethic groups compared with physical inactivity or decreased cardiorespiratory fitness. Interestingly, ethnicity modified the association between central adiposity and insulin resistance index with a similar increase in central adiposity having a substantially larger effect on insulin resistance index in the South Asian women than in the Europeans. I subsequently examined whether ethnic specific thresholds are required for lifestyle modifications and demonstrated that South Asian women need to engage with MVPA for around 195 min.week-1 in order to equate their cardiometabolic risk with that of the Europeans exercising 150 min.week-1. In addition, lower thresholds of abdominal adiposity and BMI should apply for the South Asians compared with the conventional thresholds. Although the South Asians displayed an adverse metabolic profile, vascular reactivity measured with both methods did not differ among the two groups. An additional finding was that menopausal women with hot flushing of both ethnic groups showed a paradoxical vascular profile with enhanced skin perfusion (measured with LDI-ION) but decreased reactive hyperaemia index (measured with EndoPAT) compared with asymptomatic menopausal women. The latter association was independent of conventional CVD risk factors. To conclude, South Asian women without overt disease who live in Scotland display an adverse metabolic profile with steeper associations between lifestyle risk factors and adverse cardiometabolic outcomes compared with their White counterparts. Further work in exploring ethnic specific thresholds in lifestyle interventions or in disease diagnosis is warranted.