A Nomothetic Network Model Disclosing the Comorbidity of Depression and Unstable Angina: Effects of Atherogenicity, Insulin Resistance, Immune Activation, Antioxidants, the Endogenous Opioid System, Trace Elements, and Macrominerals

Abstract

Background. There is strong comorbidity between atherosclerosis (ATS) and depression which is attributed to increased atherogenicity, insulin resistance (IR), and immune and oxidative stress.Aim of the study. To examine the role of the above pathways and mu opioid receptor (MOR), β-endorphin, zinc, copper, vitamin D3, calcium, and magnesium in depression due to ATS / unstable angina (UA).Methods. Biomarkers were assayed in 58 controls and 120 ATS patients divided into those with moderate and severe depression according to the Beck Depression Inventory (BDI)-II score > 19 and > 29, respectively. Results. Neural network and logistic regression models showed that severe depression due to ATS/UA was best predicted by IL-6, UA, MOR, zinc, β-endorphin, calcium and magnesium and that moderate depression was associated with IL-6, zinc, MOR, β-endorphin, UA, atherogenicity, IR, and calcium. These neural networks yielded a significant discrimination of severe and moderate depression with an area under the ROC curve of 0.831 and 0.931, respectively. Using Partial Least Squares analysis, 66.2% of the variance in a latent vector extracted from the ATS/UA clinical features, BDI-II scores, atherogenicity, and IR could be explained by the regression on IL-6, IL-10, zinc, copper, calcium, MOR, and age. The BDI-II scores increased from controls to ATS to UA class III to UA class IV.Conclusions. Depression due to ATS/UA is a reflective manifestation of increased atherogenicity and IR, which are modulated by immune activation, aberrations in the endogenous opioid system, antioxidants, trace elements, and macrominerals.

Nomothethic Network Psychiatry: A Bottom-Up Approach to Build Data-Driven Disease Models Based on Risk-Resilience, Adverse Outcome Pathways, and Phenome Scores, and to Discover New Biosignature-Based Classifications

“…These methods [31], however, did not intend to integrate all features of complex psychiatric disorders into a model characterized by causal paths linking causome (all possible causal factors), protectome (all protective factors), adverse output pathways (AOPs, namely biological, molecular, pan-omics, brain imaging features) and phenome (cognitome, symptomatome and phenomenome) feature sets. Figure 1 shows a causal theoretical model applicable to mood and psychotic disorders [3][4][5][6][7]. Causal reasoning based on state-of-the-art knowledge of these mental disorders indicates that causome features including genes and its products including enzymatic activity as well as specific environmentome factors (e.g.…”

“…These R/R feature sets can consequently be used as input variables (predictors) in logistic models, vectors. This parsimonious formal causal framework can then be trained, tested and validated using Partial least Squares (PLS) structural equation modeling [3,4,5,6,7,34].…”

“…Recently, we employed a new approach, namely the nomothetic network psychiatry (NNP) approach, which uses machine learning methods to build new data-driven models of mood disorders and schizophrenia using all features of those disorders including etiological, context centered hermeneutic, biological, molecular, cognitive, descriptive psychopathological, and phenomenological features [3][4][5][6][7]. The aim of this opinion paper is to review how to build nomothetic networks using Partial least Squares (PLS) analysis and how to expose new classifications of these disorders using unsupervised pattern recognition techniques…”

Intersections between Copper, β-Arrestin-1, Calcium, FBXW7, CD17, Insulin Resistance and Atherogenicity Mediate Depression and Anxiety Due to Type 2 Diabetes Mellitus: A Nomothetic Network Approach

“…Magnesium deficiency and/or low magnesium dietary intake may cause IR, glucose tolerance, T2DM and MetS [55,57] and depression [58]. In patients with atherosclerosis and unstable angina, IR is associated with lowered magnesium and zinc and increased copper, whereas comorbid depression is associated with IR coupled with lowered zinc and increased calcium [59]. Nevertheless, no research has delineated the effects of the above-mentioned biomarkers on the severity of affective symptoms including depression and anxiety due to T2DM.…”

Intersections between copper, β-arrestin-1, calcium, FBXW7, CD17, insulin resistance and atherogenicity mediate depression and anxiety due to type 2 diabetes mellitus: a nomothetic network approach

“…Magnesium deficiency and/or low magnesium dietary intake may cause IR, glucose tolerance, T2DM and MetS [55, 57] and depression [58]. In patients with atherosclerosis and unstable angina, IR is associated with lowered magnesium and zinc and increased copper, whereas comorbid depression is associated with IR coupled with lowered zinc and increased calcium [59]. Nevertheless, no research has delineated the effects of the above-mentioned biomarkers on the severity of affective symptoms including depression and anxiety.…”