Nicolas J C Stapelberg

A topographical map of the causal network of mechanisms underlying the relationship between major depressive disorder and coronary heart disease

Objective: Major depressive disorder (MDD) and coronary heart disease (CHD) are both clinically important public health problems. Depression is linked with a higher incidence of ischaemic cardiac events and MDD is more prevalent in patients with CHD. No single comprehensive model has yet described the causal mechanisms linking MDD to CHD. Several key mechanisms have been put forward, comprising behavioural mechanisms, genetic mechanisms, dysregulation of immune mechanisms, coagulation abnormalities and vascular endothelial dysfunction, polyunsaturated omega-3 free fatty acid deficiency, and autonomic mechanisms. It has been suggested that these mechanisms form a network, which links MDD and CHD. The aim of this review is to examine the causal mechanisms underlying the relationship between MDD and CHD, with the aim of constructing a topological map of the causal network which describes the relationship between MDD and CHD. Methods: The search term ‘depression and heart disease’ was entered into an electronic multiple database search engine. Abstracts were screened for relevance and individually selected articles were collated. Results: This review introduces the first topological map of the causal network which describes the relationship between MDD and CHD. Conclusions: Viewing the causal pathways as an interdependent network presents a new paradigm in this field and provides fertile ground for further research. The causal network can be studied using the methodology of systems biology, which is briefly introduced. Future research should focus on the creation of a more comprehensive topological map of the causal network and the quantification of the activity between each node of the causal network.

Mind and Heart: Heart Rate Variability in Major Depressive Disorder and Coronary Heart Disease − a Review and Recommendations

Objective: There is a reciprocal association between major depressive disorder (MDD) and coronary heart disease (CHD). These conditions are linked by a causal network of mechanisms. This causal network should be quantitatively studied and it is hypothesised that the investigation of vagal function represents a promising starting point. Heart rate variability (HRV) has been used to investigate cardiac vagal control in the context of MDD and CHD. This review aims to examine the relationship of HRV to both MDD and CHD in the context of vagal function and to make recommendations for clinical practice and research. Methods: The search terms ‘heart rate variability’, ‘depression’ and ‘heart disease’ were entered into an electronic multiple database search engine. Abstracts were screened for their relevance and articles were individually selected and collated. Results: Decreased HRV is found in both MDD and CHD. Both diseases are theorised to disrupt autonomic control feedback loops on the heart and are linked to vagal function. Existing theories link vagal function to both mood and emotion as well as cardiac function. However, several factors can potentially confound HRV measures and would thus impact on a complete understanding of vagal mechanisms in the link between MDD and CHD. Conclusions: The quantitative investigation of vagal function using HRV represents a reasonable starting point in the study of the relationship between MDD and CHD. Many psychotropic and cardiac medications have effects on HRV, which may have clinical importance. Future studies of HRV in MDD and CHD should consider antidepressant medication, as well as anxiety, as potential confounders.

From Physiome to Pathome: A Systems Biology Model of Major Depressive Disorder and the Psycho-Immune-Neuroendocrine Network

This article introduces a systems biology model of the psycho-immune-neuroendocrine (PINE) network. It provides a comprehensive synthesis of the network of biological mechanisms which link major depressive disorder (MDD) with several diseases including hypertension, atherosclerosis, coronary heart disease (CHD), cerebrovascular accident (CVA) and type 2 diabetes. The first part of this article provides an overview of concepts such as the PINE physiome and pathome, as well as the application of a systems biology framework to explain the significant reciprocal associations of MDD with the above named medical illnesses. The second part describes the normal physiological pathways of immune mechanisms, the hypothalamic-pituitary-adrenal (HPA) axis, autonomic pathways and central nervous system function, which form the PINE physiome. The third section describes how homeostasis of the PINE physiome is disrupted by chronic stress, on a background of genetic and developmental diathesis factors, resulting in a network of pathophysiological pathways called the PINE pathome. MDD, CHD, type 2 diabetes, CVA, hypertension and atherosclerosis can act to maintain the PINE network in a stable pathological state. This article presents comprehensive topographical maps of both the PINE physiome and the PINE pathome. Implications of the model and the importance of adopting a systems approach to understanding the relationship between these diseases is discussed in the last section, including the possibility of novel treatments for MDD and areas of future research.

The heartbreak of depression: ‘Psycho-cardiac’ coupling in myocardial infarction

Ample evidence identifies strong links between major depressive disorder (MDD) and both risk of ischemic or coronary heart disease (CHD) and resultant morbidity and mortality. The molecular mechanistic bases of these linkages are poorly defined. Systemic factors linked to MDD, including vascular dysfunction, atherosclerosis, obesity and diabetes, together with associated behavioral changes, all elevate CHD risk. Nonetheless, experimental evidence indicates the myocardium is also directly modified in depression, independently of these factors, impairing infarct tolerance and cardioprotection. It may be that MDD effectively breaks the hearts intrinsic defense mechanisms. Four extrinsic processes are implicated in this psycho-cardiac coupling, presenting potential targets for therapeutic intervention if causally involved: sympathetic over-activity vs. vagal under-activity, together with hypothalamic-pituitary-adrenal (HPA) axis and immuno-inflammatory dysfunctions. However, direct evidence of their involvement remains limited, and whether targeting these upstream mediators is effective (or practical) in limiting the cardiac consequences of MDD is unknown. Detailing myocardial phenotype in MDD can also inform approaches to cardioprotection, yet cardiac molecular changes are similarly ill defined. Studies support myocardial sensitization to ischemic insult in models of MDD, including worsened oxidative and nitrosative damage, apoptosis (with altered Bcl-2 family expression) and infarction. Moreover, depression may de-sensitize hearts to protective conditioning stimuli. The mechanistic underpinnings of these changes await delineation. Such information not only advances our fundamental understanding of psychological determinants of health, but also better informs management of the cardiac consequences of MDD and implementing cardioprotection in this cohort.

A preprocessing tool for removing artifact from cardiac RR interval recordings using three-dimensional spatial distribution mapping

Artifact is common in cardiac RR interval data that is recorded for heart rate variability (HRV) analysis. A novel algorithm for artifact detection and interpolation in RR interval data is described. It is based on spatial distribution mapping of RR interval magnitude and relationships to adjacent values in three dimensions. The characteristics of normal physiological RR intervals and artifact intervals were established using 24-h recordings from 20 technician-assessed human cardiac recordings. The algorithm was incorporated into a preprocessing tool and validated using 30 artificial RR (ARR) interval data files, to which known quantities of artifact (0.5%, 1%, 2%, 3%, 5%, 7%, 10%) were added. The impact of preprocessing ARR files with 1% added artifact was also assessed using 10 time domain and frequency domain HRV metrics. The preprocessing tool was also used to preprocess 69 24-h human cardiac recordings. The tool was able to remove artifact from technician-assessed human cardiac recordings (sensitivity 0.84, SD = 0.09, specificity of 1.00, SD = 0.01) and artificial data files. The removal of artifact had a low impact on time domain and frequency domain HRV metrics (ranging from 0% to 2.5% change in values). This novel preprocessing tool can be used with human 24-h cardiac recordings to remove artifact while minimally affecting physiological data and therefore having a low impact on HRV measures of that data.

From Feedback Loop Transitions to Biomarkers in the Psycho-Immune-Neuroendocrine Network: Detecting the Critical Transition from Health to Major Depression

HighlightsThe psycho‐immune‐neuroendocrine (PINE) network integrates biological pathways of major depressive disorder (MDD).Negative feed‐back loops in the PINE network may undergo feedback loop transitions (FLTs) to positive feedback loops with chronic stress.Putative FLTs are identified within kynurenine, autonomic and endocrine systems, gut permeability and gut microbiome dysbiosis.In progressing from health to disease the PINE network may exhibit early warning signs of critical transition.Early warning signs may be detectable with proposed biomarkers, potentially predicting critical transition to MDD. Background: Biological pathways underlying major depressive disorder (MDD) can be viewed as systems biology networks. The psycho‐immune‐neuroendocrine (PINE) network comprises central nervous, immune, endocrine and autonomic systems, integrating biological mechanisms of MDD. Such networks exhibit recurrent motifs with specific functions, including positive and negative feedback loops, and are subject to critical transitions, influenced by feedback loop transitions (FLTs). Aims: We aim to identify critical feedback loops and their FLTs, as well sentinel network nodes (SNNs), key network nodes that drive FLTs, within the PINE network. Examples of biomarkers are provided which may reflect early warning signs of impending critical transition to MDD. Results: Disruption of homeostatic feedback loops reflects the physiological transition to MDD. Putative FLTs are identified within hypothalamic‐pituitary‐adrenal (HPA) and sympathetic‐parasympathetic axes, the kynurenine pathway, gut function and dysbiosis. Conclusions: Progression from health to disease is driven by FLTs in the PINE network, which is likely to undergo changes characteristic of system instability. Biomarkers of system instability may effectively predict the critical transition to MDD.

Trends and repetition of non-fatal suicidal behaviour: Analyses of the Gold Coast University Hospital’s Emergency Department

Objective The aim of the current paper is to analyse time trends of non-fatal suicidal behaviour (NFSB) and its repetition at the Gold Coast in 2005–2015. Methods Data on presentations for NFSB were obtained from the Emergency Department (ED) Information System. Potential cases were identified through keyword searches, which were further scrutinised and coded. Annual person-based age-standardised rates for NFSB were calculated. Chi-square test, Poisson regression and Cox proportional hazards regression were used. Results: There was a significant increase in the age-standardised rates of NFSB for males (incidence Rate Ratio = 1.05; 95% confidence interval (CI): 1.04–1.07) and females (iRR = 1.06; 95% CI: 1.04–1.07). Age-specific rates showed significant increases for all age groups, except 25–34 and 55+ for females. Different types of poisoning were the predominant method of NFSB (poisoning only – 61.7% of episodes), followed by cutting (23%). Within the first year after the index episode, 13.4% of subjects repeated NFSB. Multivariate Cox regression model showed that sex, age and method predicted repetition. Conclusion: The increasing trends of NFSB and relatively high repetition rates emphasise the need for preventative actions. Monitoring of NFSB at the ED level should be further extended in Australia.

The sensitivity of 38 heart rate variability measures to the addition of artifact in human and artificial 24-hr cardiac recordings

Artifact is common in cardiac RR interval data derived from 24‐hr recordings and has a significant impact on heart rate variability (HRV) measures. However, the relative impact of progressively added artifact on a large group of commonly used HRV measures has not been assessed. This study compared the relative sensitivity of 38 commonly used HRV measures to artifact to determine which measures show the most change with increasing increments of artifact. A secondary aim was to ascertain whether short‐term and long‐term HRV measures, as groups, share similarities in their sensitivity to artifact.

The Impact of Methodology and Confounding Variables on the Association Between Major Depression and Coronary Heart Disease: Review and Recommendations

Background: A reciprocal association exists between Major Depressive Disorder (MDD) and Coronary Heart Disease (CHD). A quantitative evaluation of this association is necessary to identify potential areas of clinical intervention. However, the association is unclear because of methodological differences and confounders across studies. This review examines the impact of methodology and confounding variables on the magnitude of the relationship between MDD and CHD. Methods: The search terms “major depression AND coronary heart disease” were entered into an electronic multiple database search engine. Abstracts were screened for relevance and individually selected articles were collated. Results: Nine methodological issues and three confounders are identified, which have contributed to uncertainty in the quantitative relationship between MDD and CHD. More quantitative, prospective longitudinal studies are needed, which use standard definitions for MDD and CHD and define clear outcomes. Studies should clearly establish the temporal relationship between the onset of depressed mood and one or more adverse cardiac events, should use quantitative measures of depression which are treated as continuous data, and have frequent measures of mental state over time, correlated with measures of cardiac health. Study design should avoid confounding by considering demographic factors, cardiac risk factors and management of MDD in CHD patients. Conclusions: This review raises the need for a standardised methodology in future research, taking into account the biases and confounders listed. Adopting a consensus approach to methodology will facilitate the quantitative exploration of the causal network linking MDD and CHD.

The brain-adipocyte-gut network: Linking obesity and depression subtypes

Major depressive disorder (MDD) and obesity are dominant and inter-related health burdens. Obesity is a risk factor for MDD, and there is evidence MDD increases risk of obesity. However, description of a bidirectional relationship between obesity and MDD is misleading, as closer examination reveals distinct unidirectional relationships in MDD subtypes. MDD is frequently associated with weight loss, although obesity promotes MDD. In contrast, MDD with atypical features (MDD-AF) is characterised by subsequent weight gain and obesity. The bases of these distinct associations remain to be detailed, with conflicting findings clouding interpretation. These associations can be viewed within a systems biology framework—the psycho-immune neuroendocrine (PINE) network shared between MDD and metabolic disorders. Shared PINE subsystem perturbations may underlie increased MDD in overweight and obese people (obesity-associated depression), while obesity in MDD-AF (depression-associated obesity) involves more complex interactions between behavioural and biomolecular changes. In the former, the chronic PINE dysfunction triggering MDD is augmented by obesity-dependent dysregulation in shared networks, including inflammatory, leptin-ghrelin, neuroendocrine, and gut microbiome systems, influenced by chronic image-associated psychological stress (particularly in younger or female patients). In MDD-AF, behavioural dysregulation, including hypersensitivity to interpersonal rejection, fundamentally underpins energy imbalance (involving hyperphagia, lethargy, hypersomnia), with evolving obesity exaggerating these drivers via positive feedback (and potentially augmenting PINE disruption). In both settings, sex and age are important determinants of outcome, associated with differences in emotional versus cognitive dysregulation. A systems biology approach is recommended for further research into the pathophysiological networks underlying MDD and linking depression and obesity.