The new software package OpenMx 2.0 for structural equation and other statistical modeling is introduced and its features are described. OpenMx is evolving in a modular direction and now allows a mix-and-match computational approach that separates model expectations from fit functions and optimizers. Major backend architectural improvements include a move to swappable open-source optimizers such as the newly written CSOLNP. Entire new methodologies such as item factor analysis and state space modeling have been implemented. New model expectation functions including support for the expression of models in LISREL syntax and a simplified multigroup expectation function are available. Ease-of-use improvements include helper functions to standardize model parameters and compute their Jacobian-based standard errors, access to model components through standard R $ mechanisms, and improved tab completion from within the R Graphical User Interface.

OpenMx is free, full-featured, open source, structural equation modeling (SEM) software. OpenMx runs within the R statistical programming environment on Windows, Mac OS–X, and Linux computers. The rationale for developing OpenMx is discussed along with the philosophy behind the user interface. The OpenMx data structures are introduced—these novel structures define the user interface framework and provide new opportunities for model specification. Two short example scripts for the specification and fitting of a confirmatory factor model are next presented. We end with an abbreviated list of modeling applications available in OpenMx 1.0 and a discussion of directions for future development.

This commentary analyzes the extent to which the incommensurability problem can be resolved through the proposed alternative method of integrative experiment design. We suggest that, although one aspect of incommensurability is successfully addressed (dimensional incommensurability), the proposed design space method does not yet alleviate another major source of discontinuity, which we call conceptual incommensurability.

Early flow cytometry studies revealed T cell activation in major depressive disorder (MDD). MDD is characterised by activation of the immune-inflammatory response system (IRS) and the compensatory immunoregulatory system (CIRS), including deficits in T regulatory (Treg) cells. This study examines the number of cannabinoid type 1 (CB1) and type 2 (CB2) receptor-bearing T/B lymphocytes in MDD, and the effects of in vitro cannabidiol (CBD) administration on CB1/CB2-bearing immunocytes. Using flow cytometry, we determined the percentage of CD20+CB2+, CD3+CB2+, CD4+CB2+, CD8+CB2+ and FoxP3+CB1+ cells in 19 healthy controls and 29 MDD patients in 5 conditions: baseline, stimulation with anti-CD3/CD28 with or without 0.1 µg/mL, 1.0 µg/mL, or 10.0 µg/mL CBD. CB2+ was significantly higher in CD20+ than CD3+ and CD4+ and CD 8+ cells. Stimulation with anti-CD3/CD8 increases the number of CB2-bearing CD3+, CD4+ and CD8+ cells, as well as CB1-bearing FoxP3+ cells. There was an inverse association between the number of reduced CD4+ CB2+ and IRS profiles, including M1 macrophage, T helper-(Th)-1 and Th-17 phenotypes. MDD is characterised by lowered basal FoxP3+ CB1+% and higher CD20+ CB2+%. 33.2% of the variance in the depression phenome (including severity of depression, anxiety and current suicidal behaviours) is explained by CD20+ CB2+ % (positively) and CD3+ CB2+% (inversely). All five immune cell populations were significantly increased by 10 µg/mL of CBD administration. Reductions in FoxP3+ CB1+% and CD3+ /CD4+ CB2+% contribute to deficits in immune homoeostasis in MDD, while increased CD20+CB2+% may contribute to the pathophysiology of MDD by activating T-independent humoral immunity.

The first publication demonstrating that major depressive disorder (MDD) is associated with alterations in the gut microbiota appeared in 2008 (Maes et al., 2008). The purpose of the present study is to delineate a) the microbiome signature of the phenome of depression, including suicidal behaviours (SB) and cognitive deficits; the effects of adverse childhood experiences (ACEs) and recurrence of illness index (ROI) on the microbiome; and the microbiome signature of lowered high-density lipoprotein cholesterol (HDLc). We determined isometric log-ratio abundances or prevalences of gut microbiome phyla, genera, and species by analysing stool samples from 37 healthy Thai controls and 32 MDD patients using 16S rDNA sequencing. Six microbiome taxa accounted for 36% of the variance in the depression phenome, namely Hungatella and Fusicatenibacter (positive associations) and Butyricicoccus, Clostridium, Parabacteroides merdae, and Desulfovibrio piger (inverse association). This profile (labelled enterotype 1) indicates compositional dysbiosis, is strongly predicted by ACE and ROI, and is linked to SB. A second enterotype was developed that predicted a decrease in HDLc and an increase in the atherogenic index of plasma (Bifidobacterium, P. merdae, and Romboutsia were positively associated, while Proteobacteria and Clostridium sensu stricto were negatively associated). Together, enterotypes 1 and 2 explained 40.4% of the variance in the depression phenome, and enterotype 1 in conjunction with HDLc explained 39.9% of the variance in current SB. In conclusion, the microimmuneoxysome is a potential new drug target for the treatment of severe depression and SB and possibly for the prevention of future episodes.

Illicit substance use is dangerous in both acute and chronic forms, frequently resulting in lethal poisoning, addiction, and other negative consequences. Similar to research in other psychiatric conditions, whose ultimate goal is to enable effective prevention and treatment, studies in substance use are focused on factors elevating the risk for the disorder. The rapid growth of the substance use problem despite the effort invested in fighting it, however, suggests the need in changing the research approach. Instead of attempting to identify risk factors, whose neutralization is often infeasible if not impossible, it may be more promising to systematically reverse the perspective to the factors enhancing the aspect of liability to disorder that shares the same dimension but is opposite to risk, that is, resistance to substance use. Resistance factors, which enable the majority of the population to remain unaffected despite the ubiquity of psychoactive substances, may be more amenable to translation. While the resistance aspect of liability is symmetric to risk, the resistance approach requires substantial changes in sampling (high-resistance rather than high-risk) and using quantitative indices of liability. This article provides an overview and a practical approach to research in resistance to substance use/addiction, currently implemented in a NIH-funded project. The project benefits from unique opportunities afforded by the data originating from two longitudinal twin studies, the Virginia Twin Study of Adolescent and Behavioral Development and the Minnesota Twin Family Study. The methodology described is also applicable to other psychiatric disorders.

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.

The purpose of this study is to describe how to use the precision nomothetic psychiatry approach to (a) delineate the associations between schizophrenia symptom domains, including negative symptoms, psychosis, hostility, excitation, mannerism, formal thought disorders, psychomotor retardation (PHEMFP), and cognitive dysfunctions and neuroimmunotoxic and neuro-oxidative pathways and (b) create a new endophenotype class based on these features. We show that all symptom domains (negative and PHEMFP) may be used to derive a single latent trait called overall severity of schizophrenia (OSOS). In addition, neurocognitive test results may be used to extract a general cognitive decline (G-CoDe) index, based on executive function, attention, semantic and episodic memory, and delayed recall scores. According to partial least squares analysis, the impacts of adverse outcome pathways (AOPs) on OSOS are partially mediated by increasing G-CoDe severity. The AOPs include neurotoxic cytokines and chemokines, oxidative damage to proteins and lipids, IgA responses to neurotoxic tryptophan catabolites, breakdown of the vascular and paracellular pathways with translocation of Gram-negative bacteria, and insufficient protection through lowered antioxidant levels and impairments in the innate immune system. Unsupervised machine learning identified a new schizophrenia endophenotype class, named major neurocognitive psychosis (MNP), which is characterised by increased negative symptoms and PHEMFP, G-CoDe and the above-mentioned AOPs. Based on these pathways and phenome features, MNP is a distinct endophenotype class which is qualitatively different from simple psychosis (SP). It is impossible to draw any valid conclusions from research on schizophrenia that ignores the MNP and SP distinctions.

This study aimed to explore effects of adjunctive minocycline treatment on inflammatory and neurogenesis markers in major depressive disorder (MDD). Serum samples were collected from a randomised, placebo-controlled 12-week clinical trial of minocycline (200 mg/day, added to treatment as usual) for adults (n = 71) experiencing MDD to determine changes in interleukin-6 (IL-6), lipopolysaccharide binding protein (LBP) and brain derived neurotrophic factor (BDNF). General Estimate Equation modelling explored moderation effects of baseline markers and exploratory analyses investigated associations between markers and clinical outcomes. There was no difference between adjunctive minocycline or placebo groups at baseline or week 12 in the levels of IL-6 (week 12; placebo 2.06 ± 1.35 pg/ml; minocycline 1.77 ± 0.79 pg/ml; p = 0.317), LBP (week 12; placebo 3.74 ± 0.95 µg/ml; minocycline 3.93 ± 1.33 µg/ml; p = 0.525) or BDNF (week 12; placebo 24.28 ± 6.69 ng/ml; minocycline 26.56 ± 5.45 ng/ml; p = 0.161). Higher IL-6 levels at baseline were a predictor of greater clinical improvement. Exploratory analyses suggested that the change in IL-6 levels were significantly associated with anxiety symptoms (HAMA; p = 0.021) and quality of life (Q-LES-Q-SF; p = 0.023) scale scores. No other clinical outcomes were shown to have this mediation effect, nor did the other markers (LBP or BDNF) moderate clinical outcomes. There were no overall changes in IL-6, LBP or BDNF following adjunctive minocycline treatment. Exploratory analyses suggest a potential role of IL-6 on mediating anxiety symptoms with MDD. Future trials may consider enrichment of recruitment by identifying several markers or a panel of factors to better represent an inflammatory phenotype in MDD with larger sample size.

Nutritional ketosis, induced via either the classical ketogenic diet or the use of emulsified medium-chain triglycerides, is an established treatment for pharmaceutical resistant epilepsy in children and more recently in adults. In addition, the use of oral ketogenic compounds, fractionated coconut oil, very low carbohydrate intake, or ketone monoester supplementation has been reported to be potentially helpful in mild cognitive impairment, Parkinson’s disease, schizophrenia, bipolar disorder, and autistic spectrum disorder. In these and other neurodegenerative and neuroprogressive disorders, there are detrimental effects of oxidative stress, mitochondrial dysfunction, and neuroinflammation on neuronal function. However, they also adversely impact on neurone–glia interactions, disrupting the role of microglia and astrocytes in central nervous system (CNS) homeostasis. Astrocytes are the main site of CNS fatty acid oxidation; the resulting ketone bodies constitute an important source of oxidative fuel for neurones in an environment of glucose restriction. Importantly, the lactate shuttle between astrocytes and neurones is dependent on glycogenolysis and glycolysis, resulting from the fact that the astrocytic filopodia responsible for lactate release are too narrow to accommodate mitochondria. The entry into the CNS of ketone bodies and fatty acids, as a result of nutritional ketosis, has effects on the astrocytic glutamate–glutamine cycle, glutamate synthase activity, and on the function of vesicular glutamate transporters, EAAT, Na+, K+-ATPase, Kir4.1, aquaporin-4, Cx34 and KATP channels, as well as on astrogliosis. These mechanisms are detailed and it is suggested that they would tend to mitigate the changes seen in many neurodegenerative and neuroprogressive disorders. Hence, it is hypothesized that nutritional ketosis may have therapeutic applications in such disorders.