The top-down Diagnostic and Statistical Manual/International Statistical Classification of Diseases categories of mood disorders are inaccurate, and their dogmatic nature precludes both deductive (as indisputable) and inductive (as top-down) remodelling of case definitions. In trials, psychiatric rating scale scores employed as outcome variables are invalid and rely on folk psychology-like narratives. Using machine learning techniques, we developed a new precision nomothetic model of mood disorders with a recurrence of illness (ROI) index, a new endophenotype class, namely Major Dysmood Disorder (MDMD), characterised by increased ROI, a more severe phenome, and more disabilities. Nonetheless, our previous studies did not compute Research and Diagnostic Algorithmic Rules (RADAR) to diagnose MDMD and score ROI, lifetime (LT), and current suicidal behaviours, as well as the phenome of mood disorders. Here, we provide rules to compute bottom-up RADAR scores for MDMD, ROI, LT and current suicidal ideation and attempts, the phenome of mood disorders, and the lifetime trajectory of mood disorder patients from a family history of mood disorders and substance abuse to adverse childhood experiences, ROI, and the phenome. We also demonstrate how to plot the 12 major scores in a single RADAR graph, which displays all features in a two-dimensional plot. These graphs allow the characteristics of a patient to be displayed as an idiomatic fingerprint, allowing one to estimate the key traits and severity of the illness at a glance. Consequently, biomarker research into mood disorders should use our RADAR scores to examine pan-omics data, which should be used to enlarge our precision models and RADAR graph.
Abstract Background Major depressive disorder (MDD) is accompanied by activated neuro-immune pathways, increased physiosomatic and chronic fatigue-fibromyalgia (FF) symptoms. The most severe MDD phenotype, namely major dysmood disorder (MDMD), is associated with adverse childhood experiences (ACEs) and negative life events (NLEs) which induce cytokines/chemokines/growth factors. Aims To delineate the impact of ACE+NLEs on physiosomatic and FF symptoms in first episode (FE)-MDMD, and examine whether these effects are mediated by immune profiles. Methods ACEs, NLEs, physiosomatic and FF symptoms, and 48 cytokines/chemokines/growth factors were measured in 64 FE-MDMD patients and 32 normal controls. Results Physiosomatic, FF and gastro-intestinal symptoms belong to the same factor as depression, anxiety, melancholia, and insomnia. The first factor extracted from these seven domains is labeled the physio-affective phenome of depression. A part (59.0%) of the variance in physiosomatic symptoms is explained by the independent effects of interleukin (IL)-16 and IL-8 (positively), CCL3 and IL-1 receptor antagonist (inversely correlated). A part (46.5%) of the variance in physiosomatic (59.0%) symptoms is explained by the independent effects of interleukin (IL)-16, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) (positively) and combined activities of negative immunoregulatory cytokines (inversely associated). Partial Least Squares analysis shows that ACE+NLEs exert a substantial influence on the physio-affective phenome which are partly mediated by an immune network composed of IL-16, CCL27, TRAIL, macrophage-colony stimulating factor, and stem cell growth factor. Conclusions The physiosomatic and FF symptoms of FE-MDMD are partly caused by immune-associated neurotoxicity due to T helper (Th)-1 polarization, Th-1, and M1 macrophage activation and relative lowered compensatory immunoregulatory protection.
In the sociological literature, there is an increasing number of contributions with an approach inspired by the field of complexity science. Here, I identify important commonalities between typical sociological research problems and phenomena studied by complexity researchers, arguing that both fields focus on macro-phenomena that emerge from the behavior of micro-entities. Next, I compare the approach of complexity science with prominent methodological approaches to sociology. I argue that complexity research shares core principles with both structural and structural-individualistic approaches to sociology. However, in particular the approach put forward by analytical sociologists overlaps on the crucial dimensions with complexity research.
Immune activation is accompanied by induction of indoleamine (2,3)-dioxygenase (IDO), an enzyme which degrades tryptophan, a phenomenon which plays a role in the pathophysiology of major depression and post-natal depression and anxiety states. TRYCATs - tryptophan catabolites along the IDO pathway - such as kynurenine, kynurenic acid, xanthurenic acid, and quinolinic acid, have multiple effects, e.g. apoptotic, anti- versus pro-oxidant, neurotoxic versus neuroprotective, and anxiolytic versus anxiogenic effects. The aim of the present study was to study the immune effects of the above TRYCATS. Toward this end we examined the effects of the above TRYCATs on the LPS + PHA-induced production of interferon-gamma (IFNgamma), interleukin-10 (IL-10), and tumor necrosis factor-alpha (TNFalpha) in 18 normal volunteers. We found that the production of IFNgamma was significantly decreased by all 4 catabolites. Xanthurenic acid and quinolinic acid decreased the production of IL-10. Kynurenine, kynurenic acid, and xanthurenic acid, decreased the IFNgamma/IL-10 production ratio, whereas quinolinic acid increased this ratio. Kynurenic acid significantly reduced the stimulated production of TNFalpha. It is concluded that kynurenine, kynurenic acid, and xanthurenic acid have anti-inflammatory effects trough a reduction of IFNgamma, whereas quinolinic acid has pro-inflammatory effects in particular via significant decreases in IL-10. Following inflammation-induced IDO activation, some TRYCATs, i.e. kynurenine, kynurenic acid, and xanthurenic acid, exert a negative feedback control over IFNgamma production thus downregulating the initial inflammation, whereas an excess of quinolinic acid further aggravates the initial inflammation.
Abstract Background Early life trauma (ELT) may drive mood disorder phenomenology, neuro-oxidative and neuro-immune pathways and impairments in semantic memory. Nevertheless, there are no data regarding the impact of ELT on affective phenomenology and whether these pathways are mediated by staging or lowered lipid-associated antioxidant defences. Methods This study examined healthy controls (n=54) and patients with affective disorders including major depression, bipolar disorder and anxiety disorders (n=118). ELT was assessed using the Child Trauma Questionnaire. In addition, we measured affective phenomenology and assayed advanced oxidation protein products; malondialdehyde, paraoxonase 1 (CMPAase) activity, high-sensitivity C-reactive protein (hsCRP), and high-density lipoprotein (HDL) cholesterol. Results ELT was associated with increased risk for mood and comorbid anxiety disorders and a more severe phenomenology, including staging characteristics (number of mood episodes), severity of depression and anxiety, suicide attempts, suicidal ideation, type of treatments received, disabilities, body mass index, smoking behaviour and hsCRP, as well as lowered health-related quality of life, socio-economic status, antioxidant defences and semantic memory. The number of mood episodes and CMPAase/HDL-cholesterol levels could be reliably combined into a new vulnerability staging-biomarker index, which mediates in part the effects of ELT on affective phenomenology, while lowered antioxidant defences are associated with increased oxidative stress. Moreover, the effects of female sex on mood disorders and affective phenomenology are mediated by ELT. Discussion The cumulative effects of different types of ELT drive many aspects of affective phenomenology either directly or indirectly through effects of staging and/or lipid–associated antioxidant defences. The results show that children, especially girls, with ELT are at great risk to develop mood disorders and more severe phenotypes of affective disorders.
In insulin-dependent diabetic rats, plasma somatomedin (Sm) levels are low and are not corrected by GH treatment, suggesting GH resistance. To define the mechanism of this GH-resistant state, the number and affinity constant of bovine liver GH-binding sites and the serum Sm-C responses to injections of bovine GH were determined in control (diluentinjected) and diabetic (streptozotocin-injected; 40 mg/kg BW) hypophysectomized rats. The affinity constants (Ka) of the GH-binding sites of control (0.92 ± 0.07 × 109m−1) and diabetic animals (0.68 ± 0.04 × 109m−1) were not significantly different (P < 0.1). Likewise, there were no significant differences in the liver GH-binding capacities between control and diabetic hypophysectomized rats, whether these capacities were expressed as picomoles per liver (26.99 ± 3.43 vs. 22.27 ± 2.55, controls vs. diabetics), picomoles per mg DNA (1.26 ± 0.15 vs. 1.10 ± 0.12), or femtomoles per mg protein (30.95 ± 4.08 vs. 29.98 ± 2.70). Despite the absence of alterations in liver GH-binding sites, the Sm-C responses 24 h after sc injections of graded doses of bovine GH were severely blunted in the diabetic animals. The maximal serum Sm-C response in the controls was 0.81 ± 0.12 U/ml, but was only 0.09 ± 0.01 U/ml in the diabetics (P < 0.01). The dose of GH required to achieve the half-maximal Sm-C response (ED50) was similar in diabetic and nondiabetic rats (700–900 μg). The absence of significant alterations in liver GH binding and the decreased maximal serum Sm-C response without changes in the ED50 suggest that the GH-resistant state in insulin-dependent diabetes is due to a postreceptor defect. (Endocrinology118: 377–382, 1986)
