How to Construct a Bottom-Up Nomothetic Network Model and Disclose Novel Nosological Classes by Integrating Risk Resilience and Adverse Outcome Pathways with the Phenome of Schizophrenia

Metabolome subtyping reveals multi-omics characteristics and biological heterogeneity in major psychiatric disorders

Growing evidence suggests that major psychiatric disorders (MPDs) share common etiologies and pathological processes. However, the diagnosis is currently based on descriptive symptoms, which ignores the underlying pathogenesis and hinders the development of clinical treatments. This highlights the urgency of characterizing molecular biomarkers and establishing objective diagnoses of MPDs. Here, we collected untargeted metabolomics, proteomics and DNA methylation data of 327 patients with MPDs, 131 individuals with genetic high risk and 146 healthy controls to explore the multi-omics characteristics of MPDs. First, differential metabolites (DMs) were identified and we classified MPD patients into 3 subtypes based on DMs. The subtypes showed distinct metabolomics, proteomics and DNA methylation signatures. Specifically, one subtype showed dysregulation of complement and coagulation proteins, while the DNA methylation showed abnormalities in chemical synapses and autophagy. Integrative analysis in metabolic pathways identified the important roles of the citrate cycle, sphingolipid metabolism and amino acid metabolism. Finally, we constructed prediction models based on the metabolites and proteomics that successfully captured the risks of MPD patients. Our study established molecular subtypes of MPDs and elucidated their biological heterogeneity through a multi-omics investigation. These results facilitate the understanding of pathological mechanisms and promote the diagnosis and prevention of MPDs.

Effects of a six-month yoga intervention on the immune-inflammatory pathway in antipsychotic-stabilized schizophrenia patients: A randomized controlled trial

BACKGROUND

Schizophrenia is a complex neuropsychiatric disorder for which several etiopathological theories have been proposed, one of the prominent ones being immune dysfunction. Recent studies on yoga as an add-on therapy have shown improvement in negative symptoms, cognition, and quality of life in schizophrenia patients. However, the biological mechanism/s of action of yoga in schizophrenia are not clear. The current study was aimed at exploring the effects of long-term (6 months) add-on yoga therapy on the immune inflammatory pathway in schizophrenia patients.

METHODS

Sixty schizophrenia patients were randomized to add-on yoga therapy (YT=30) and treatment-as-usual (TAU=30) groups of which 21 patients in YT and 20 in TAU group completed the study. Blood samples and clinical assessments were obtained at baseline and at the end of 6 months. The plasma levels of nine cytokines (IL-2, IL-4, IL-5, IL-10, IL-12(p70), IL-13, GM-CSF, IFN-γ, and TNF-α) were quantified using multiplex suspension array. The clinical assessments included SAPS, SANS, BPRS, PSS, CGI, SOFS and WHOQUOL-BREF.

RESULTS

Patients in the yoga group showed significant reductions in plasma TNF-α (Z = 2.99, p = 0.003) and IL-5 levels (Z = 2.20, p = 0.03) and greater clinical improvements in SAPS, SANS, PSS, and SOFS scores as compared to TAU group. Further, plasma TNF-α levels exhibited a positive correlation with negative symptoms (r_s =0.45, p = 0.02) and socio-occupational functioning (r_s =0.61, p = 0.002) in the YT group.

CONCLUSIONS

The findings of the study suggest that improvements in schizophrenia psychopathology with yoga interventions are associated with immuno-modulatory effects.

In Schizophrenia, Chronic Fatigue Syndrome- and Fibromyalgia-Like Symptoms are Driven by Breakdown of the Paracellular Pathway with Increased Zonulin and Immune Activation-Associated Neurotoxicity

BACKGROUND

A meaningful part of schizophrenia patients suffer from physiosomatic symptoms (formerly named psychosomatic), which are reminiscent of chronic fatigue syndrome and fibromyalgia (FF) and are associated with signs of immune activation and increased levels of tryptophan catabolites (TRYCATs).

AIMS

The study aims to examine whether FF symptoms in schizophrenia are associated with the breakdown of the paracellular pathway, zonulin, lowered natural IgM responses to oxidative specific epitopes (OSEs); and whether FF symptoms belong to the behavioral-cognitive-physical-psychosocial- (BCPS)-worsening index consisting of indices of a general cognitive decline (G-CoDe), symptomatome of schizophrenia, and quality of life (QoL)-phenomenome.

METHODS

FF symptoms were assessed using the Fibromyalgia and Chronic Fatigue Rating scale in 80 schizophrenia patients and 40 healthy controls and serum cytokines/chemokines, IgA levels to TRYCATs, IgM to OSEs, zonulin and transcellular/paracellular (TRANS/PARA) molecules were assayed using ELISA methods.

RESULTS

A large part (42.3%) of the variance in the total FF score was explained by the regression on the PARA/TRANS ratio, pro-inflammatory cytokines, IgM to zonulin, IgA to TRYCATs (all positively), and IgM to OSEs (inversely). There were highly significant correlations between the total FF score and G-CoDe, symtopmatome, QoL phenomenome, and BCPS-worsening score. FF symptoms belong to a common core shared by G-CoDe, symtopmatome, and QoL phenomenome.

CONCLUSION

The physio-somatic symptoms of schizophrenia are driven by various pathways, including increased zonulin, breakdown of the paracellular tight-junctions pathway, immune activation with induction of the TRYCAT pathway, and consequent neurotoxicity. It is concluded that FF symptoms are part of the phenome of schizophrenia and BCPS-worsening as well.

A pathway phenotype linking metabolic, immune, oxidative, and opioid pathways with comorbid depression, atherosclerosis, and unstable angina

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 levels, 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-II (BDI-II) scores >19 and >29, respectively.

RESULTS

Neural network and logistic regression models showed that severe depression due to ATS/UA was best predicted by interleukin-6 (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. Neural networks yielded a significant discrimination of severe and moderate depression with an area under the receiver operating curves of 0.831 and 0.931, respectively. Using Partial Least Squares path analysis, we found that 66.2% of the variance in a latent vector extracted from ATS/UA clinical features, and the 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

Immune activation, the endogenous opioid system, antioxidants, trace elements, and macrominerals modulate a common core shared by increased depressive symptoms, ATS, UA, atherogenicity, and IR.

Major neurocognitive psychosis: a novel schizophrenia endophenotype class that is based on machine learning and resembles Kraepelin's and Bleuler's conceptions

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.

The interleukin-6/interleukin-23/T helper 17-axis as a driver of neuro-immune toxicity in the major neurocognitive psychosis or deficit schizophrenia: A precision nomothetic psychiatry analysis

BACKGROUND

Schizophrenia and especially deficit schizophrenia (DSCZ) are characterized by increased activity of neuroimmunotoxic pathways and a generalized cognitive decline (G-CoDe). There is no data on whether the interleukin (IL)-6/IL-23/T helper 17 (IL-6/IL-23/Th17)-axis is more associated with DSCZ than with non-deficit schizophrenia (NDSCZ) and whether changes in this axis are associated with the G-CoDe and the phenome (a factor extracted from all symptom domains) of schizophrenia.

METHODS

This study included 45 DSCZ and 45 NDSCZ patients and 40 controls and delineated whether the IL-6/IL-23/Th17 axis, trace elements (copper, zinc) and ions (magnesium, calcium) are associated with DSCZ, the G-CoDe and the schizophrenia phenome.

RESULTS

Increased plasma IL-23 and IL-6 levels were associated with Th17 upregulation, assessed as a latent vector (LV) extracted from IL-17, IL-21, IL-22, and TNF-α. The IL-6/IL-23/Th17-axis score, as assessed by an LV extracted from IL-23, IL-6, and the Th17 LV, was significantly higher in DSCZ than in NDSCZ and controls. We discovered that 70.7% of the variance in the phenome was explained by the IL-6/IL-23/Th17-axis (positively) and the G-CoDe and IL-10 (both inversely); and that 54.6% of the variance in the G-CoDe was explained by the IL-6/IL-23/Th17 scores (inversely) and magnesium, copper, calcium, and zinc (all positively).

CONCLUSION

The pathogenic IL-6/IL-23/Th17-axis contributes to the generalized neurocognitive deficit and the phenome of schizophrenia, especially that of DSCZ, due to its key role in peripheral inflammation and neuroinflammation and its consequent immunotoxic effects on neuronal circuits. These clinical impairments are more prominent in subjects with lowered IL-10, magnesium, calcium, and zinc.

Lowered Quality of Life in Long COVID Is Predicted by Affective Symptoms, Chronic Fatigue Syndrome, Inflammation and Neuroimmunotoxic Pathways

The physio-affective phenome of Long COVID-19 is predicted by (a) immune-inflammatory biomarkers of the acute infectious phase, including peak body temperature (PBT) and oxygen saturation (SpO2), and (b) the subsequent activation of immune and oxidative stress pathways during Long COVID. The purpose of this study was to delineate the effects of PBT and SpO2 during acute infection, as well as the increased neurotoxicity on the physical, psychological, social and environmental domains of health-related quality of life (HR-QoL) in people with Long COVID. We recruited 86 participants with Long COVID and 39 normal controls, assessed the WHO-QoL-BREF (World Health Organization Quality of Life Instrument-Abridged Version, Geneva, Switzerland) and the physio-affective phenome of Long COVID (comprising depression, anxiety and fibromyalgia-fatigue rating scales) and measured PBT and SpO2 during acute infection, and neurotoxicity (NT, comprising serum interleukin (IL)-1β, IL-18 and caspase-1, advanced oxidation protein products and myeloperoxidase, calcium and insulin resistance) in Long COVID. We found that 70.3% of the variance in HR-QoL was explained by the regression on the physio-affective phenome, lowered calcium and increased NT, whilst 61.5% of the variance in the physio-affective phenome was explained by calcium, NT, increased PBT, lowered SpO2, female sex and vaccination with AstraZeneca and Pfizer. The effects of PBT and SpO2 on lowered HR-QoL were mediated by increased NT and lowered calcium yielding increased severity of the physio-affective phenome which largely affects HR-QoL. In conclusion, lowered HR-Qol in Long COVID is largely predicted by the severity of neuro-immune and neuro-oxidative pathways during acute and Long COVID.

Interactions Among Brain-Derived Neurotrophic Factor and Neuroimmune Pathways Are Key Components of the Major Psychiatric Disorders

The purpose of this review is to summarize the current knowledge regarding the reciprocal associations between brain-derived neurotrophic factor (BDNF) and immune-inflammatory pathways and how these links may explain the involvement of this neurotrophin in the immune pathophysiology of mood disorders and schizophrenia. Toward this end, we delineated the protein-protein interaction (PPI) network centered around BDNF and searched PubMed, Scopus, Google Scholar, and Science Direct for papers dealing with the involvement of BDNF in the major psychosis, neurodevelopment, neuronal functions, and immune-inflammatory and related pathways. The PPI network was built based on the significant interactions of BDNF with neurotrophic (NTRK2, NTF4, and NGFR), immune (cytokines, STAT3, TRAF6), and cell-cell junction (CTNNB, CDH1) DEPs (differentially expressed proteins). Enrichment analysis shows that the most significant terms associated with this PPI network are the tyrosine kinase receptor (TRKR) and Src homology region two domain-containing phosphatase-2 (SHP2) pathways, tyrosine kinase receptor signaling pathways, positive regulation of kinase and transferase activity, cytokine signaling, and negative regulation of the immune response. The participation of BDNF in the immune response and its interactions with neuroprotective and cell-cell adhesion DEPs is probably a conserved regulatory process which protects against the many detrimental effects of immune activation and hyperinflammation including neurotoxicity. Lowered BDNF levels in mood disorders and schizophrenia (a) are associated with disruptions in neurotrophic signaling and activated immune-inflammatory pathways leading to neurotoxicity and (b) may interact with the reduced expression of other DEPs (CTNNB1, CDH1, or DISC1) leading to multiple aberrations in synapse and axonal functions.

False dogmas in mood disorders research: Towards a nomothetic network approach

The current understanding of major depressive disorder (MDD) and bipolar disorder (BD) is plagued by a cacophony of controversies as evidenced by competing schools to understand MDD/BD. The DSM/ICD taxonomies have cemented their status as the gold standard for diagnosing MDD/BD. The aim of this review is to discuss the false dogmas that reign in current MDD/BD research with respect to the new, data-driven, machine learning method to model psychiatric illness, namely nomothetic network psychiatry (NNP). This review discusses many false dogmas including: MDD/BD are mind-brain disorders that are best conceptualized using a bio-psycho-social model or mind-brain interactions; mood disorders due to medical disease are attributable to psychosocial stress or chemical imbalances; DSM/ICD are the gold standards to make the MDD/BD diagnosis; severity of illness should be measured using rating scales; clinical remission should be defined using threshold values on rating scale scores; existing diagnostic BD boundaries are too restrictive; and mood disorder spectra are the rule. In contrast, our NNP models show that MDD/BD are not mind-brain or psycho-social but systemic medical disorders; the DSM/ICD taxonomies are counterproductive; a shared core, namely the reoccurrence of illness (ROI), underpins the intertwined recurrence of depressive and manic episodes and suicidal behaviors; mood disorders should be ROI-defined; ROI mediates the effects of nitro-oxidative stress pathways and early lifetime trauma on the phenome of mood disorders; severity of illness and treatment response should be delineated using the NNP-derived causome, pathway, ROI and integrated phenome scores; and MDD and BD are the same illness.

In COVID-19, NLRP3 inflammasome genetic variants are associated with critical disease and these effects are partly mediated by the sickness symptom complex: a nomothetic network approach

In coronavirus disease (COVID-19), the nucleotide-binding domain, leucine-rich repeat and pyrin domain-containing protein 3 (NLRP3) inflammasome is activated in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Acute infections are accompanied by a sickness symptom complex (SSC) which is highly conserved and protects against infections and hyperinflammation. The aim of this study is to delineate the associations of COVID-19, SSC and NLPR3 rs10157379 T > C and NLPR3 rs10754558 C > G variants; and the protective role of SSC in SARS-CoV-2 infection. We recruited COVID-19 patients, 308 with critical, 63 with moderate and 157 with mild disease. Increased SSC protects against SARS, critical disease, and death due to COVID-19. Increasing age, male sex and rs10754558 CG significantly reduce SSC protection. The rs10157379 CT and rs10754558 GG genotypes are positively associated with SARS. Partial Least Squares analysis shows that a) 41.8% of the variance in critical COVID-19 symptoms is explained by SSC and oxygen saturation (inversely associated), inflammation, chest computed tomography abnormalities, increased body mass index, SARS and age (positively associated); and b) the effects of the NLRP3 rs10157379 and rs10754558 variants on critical COVID-19 are mediated via SSC (protective) and SARS (detrimental). SSC includes anosmia and dysgeusia, and maybe gastrointestinal symptoms. In conclusion, intersections among the rs10754558 variant, age, and sex increase risk towards critical COVID-19 by attenuating SSC. NLRP3 variants play an important role in SARS, and severe and critical COVID-19 especially in elderly male individuals with reduced SSC and with increased BMI, hypertension, and diabetes type 2.

First Episode Psychosis and Schizophrenia Are Systemic Neuro-Immune Disorders Triggered by a Biotic Stimulus in Individuals with Reduced Immune Regulation and Neuroprotection

There is evidence that schizophrenia is characterized by activation of the immune-inflammatory response (IRS) and compensatory immune-regulatory systems (CIRS) and lowered neuroprotection. Studies performed on antipsychotic-naïve first episode psychosis (AN-FEP) and schizophrenia (FES) patients are important as they may disclose the pathogenesis of FES. However, the protein–protein interaction (PPI) network of FEP/FES is not established. The aim of the current study was to delineate a) the characteristics of the PPI network of AN-FEP and its transition to FES; and b) the biological functions, pathways, and molecular patterns, which are over-represented in FEP/FES. Toward this end, we used PPI network, enrichment, and annotation analyses. FEP and FEP/FES are strongly associated with a response to a bacterium, alterations in Toll-Like Receptor-4 and nuclear factor-κB signaling, and the Janus kinases/signal transducer and activator of the transcription proteins pathway. Specific molecular complexes of the peripheral immune response are associated with microglial activation, neuroinflammation, and gliogenesis. FEP/FES is accompanied by lowered protection against inflammation, in part attributable to dysfunctional miRNA maturation, deficits in neurotrophin and Wnt/catenin signaling, and adherens junction organization. Multiple interactions between reduced brain derived neurotrophic factor, E-cadherin, and β-catenin and disrupted schizophrenia-1 (DISC1) expression increase the vulnerability to the neurotoxic effects of immune molecules, including cytokines and complement factors. In summary: FEP and FES are systemic neuro-immune disorders that are probably triggered by a bacterial stimulus which induces neuro-immune toxicity cascades that are overexpressed in people with reduced anti-inflammatory and miRNA protections, cell–cell junction organization, and neurotrophin and Wnt/catenin signaling.

Inflammatory and Oxidative Pathways Are New Drug Targets in Multiple Episode Schizophrenia and Leaky Gut, Klebsiella pneumoniae, and C1q Immune Complexes Are Additional Drug Targets in First Episode Schizophrenia

Breakdown of paracellular and vascular pathways and activated neuroimmune and oxidative pathways was established in (deficit) schizophrenia. The aim of this study was to delineate (a) the differences in these pathways between stable-phase, first (FES) and multiple (MES) episode schizophrenia and (b) the pathways that determine the behavioral-cognitive-physical-psychosocial (BCPS) deterioration in FES/MES. This study included 21 FES and 58 FES patients and 40 healthy controls and measured indicants of serum C1q circulating immune complexes (CIC), leaky gut, immune activation, and oxidative stress toxicity (OSTOX). We constructed a BCPS-worsening index by extracting a latent vector from symptomatic, neurocognitive, and quality of life data. FES was associated with higher IgA CIC-C1q, IgA directed to cadherin, catenin, and plasmalemma vesicle-associated protein, and IgA/IgM to Gram-negative bacteria as compared with FES and controls. In FES patients, the BCPS-worsening score was predicted (48.7%) by IgA to Klebsiella pneumoniae and lowered paraoxonase 1 activity. In MES patients, the BCPS-worsening score was explained (42.7%) by increased tumor necrosis factor-α, OSTOX, and number of episodes. In schizophrenia, 34.0% of the variance in the BCPS-worsening score was explained by IgA to K. pneumoniae, OSTOX, and number of episodes. Increased IgA to K. pneumoniae was the single best predictor of residual psychotic symptoms in FES and MES. This study delineated different mechanistic processes in FES, including breakdown of adherens junctions, bacterial translocation, and IgA CIC-C1q formation, and MES, including immune and oxidative neurotoxic pathways. FES and MES comprise different staging subtypes, i.e., FES and MES with and without worsening.

In schizophrenia, immune-inflammatory pathways are strongly associated with depressive and anxiety symptoms, which are part of a latent trait which comprises neurocognitive impairments and schizophrenia symptoms

BACKGROUND

The aim is to examine whether biomarkers of the immune-inflammatory response (IRS) and endogenous opioid (EOS) systems are associated with affective symptoms in schizophrenia.

METHODS

We recruited 115 schizophrenia patients and 43 healthy controls and assessed the Hamilton Depression (HDRS) and Anxiety (HAM-A) rating Scale scores as well as serum levels of interleukin (IL)-6, IL-10, eotaxin (CCL11), high mobility group box 1 (HMGB1), Dickkopf-related protein 1 (DKK1), and mu (MOR) and kappa (KOR) opioid receptors.

RESULTS

The HDRS and HAM-A scores are significantly and positively correlated with a) psychosis, hostility, excitation, mannerism, negative symptoms, psychomotor retardation, and formal thought disorders; and b) lowered scores on semantic and episodic memory, executive functions, and attention tests as measured with the Brief Assessment of Cognition in Psychiatry. Both HDRS and HAM-A are significantly increased in non-responders to treatment as compared with partial responders. Both affective scores are strongly associated with a latent vector extracted from all symptoms, reflecting overall severity of schizophrenia symptoms (OSOS), and neurocognitive test scores, reflecting a generalized cognitive decline (G-CoDe). The HDRS score was strongly and positively associated with IL-6, HMGB1, KOR, and MOR levels, and the HAM-A score with IL-6, IL-10, CCL11, HMGB1, KOR, and MOR levels. A single latent trait may be extracted from OSOS, G-CoDe, and the HDRS and HAMA scores, and this latent vector score is strongly predicted by HMGB1, MOR, and DKK1.

CONCLUSION

Immune-inflammatory and EOS pathways contribute to the phenome of schizophrenia, which comprises OSOS, affective, and physiosomatic symptoms, and G-CoDe.

In (deficit) schizophrenia, a general cognitive decline partly mediates the effects of neuro-immune and neuro-oxidative toxicity on the symptomatome and quality of life

BACKGROUND

Schizophrenia and deficit schizophrenia are accompanied by neurocognitive impairments. The aim of this study was to examine whether a general factor underpins impairments in key Cambridge Neuropsychological Test Automated Battery (CANTAB) probes, verbal fluency test (VFT), world list memory (WLM), True Recall, and mini mental state examination (MMSE).

METHODS

We recruited 80 patients with schizophrenia and 40 healthy controls. All patients were assessed using CANTAB tests, namely paired-association learning, rapid visual information processing, spatial working memory, one touch stockings of Cambridge, intra/extradimensional set-shifting (IED), and emotional recognition test.

RESULTS

We found that a general factor, which is essentially unidimensional, underlies those CANTAB, VFT, WLM, True Recall, and MMSE scores. This common factor shows excellent psychometric properties and fits a reflective model and, therefore, reflects a general cognitive decline (G-CoDe) comprising deficits in semantic and episodic memory, recall, executive functions, strategy use, rule acquisition, visual sustained attention, attentional set-shifting, and emotional recognition. Partial least squares analysis showed that 40.5% of the variance in G-CoDe is explained by C-C motif ligand 11, IgA to tryptophan catabolites, and increased oxidative toxicity, and that G-CoDe explains 44.8% of the variance in a general factor extracted from psychosis, hostility, excitation, mannerism, negative symptoms, formal thought disorders, and psychomotor retardation, and 40.9% in quality-of-life scores. The G-CoDe is significantly greater in deficit than in nondeficit schizophrenia.

CONCLUSIONS

A common core shared by a multitude of neurocognitive impairments (G-CoDe) mediates the effects of neurotoxic pathways on the phenome of (deficit) schizophrenia.

How to construct neuroscience-informed psychiatric classification? Towards nomothetic networks psychiatry

Psychiatry remains in a permanent state of crisis, which fragmented psychiatry from the field of medicine. The crisis in psychiatry is evidenced by the many different competing approaches to psychiatric illness including psychodynamic, biological, molecular, pan-omics, precision, cognitive and phenomenological psychiatry, folk psychology, mind-brain dualism, descriptive psychopathology, and postpsychiatry. The current "gold standard" Diagnostic and Statistical Manual of Mental Disorders/International Classification of Diseases taxonomies of mood disorders and schizophrenia are unreliable and preclude to employ a deductive reasoning approach. Therefore, it is not surprising that mood disorders and schizophrenia research was unable to revise the conventional classifications and did not provide more adequate therapeutic approaches. The aim of this paper is to explain the new nomothetic network psychiatry (NNP) approach, which uses machine learning methods to build data-driven causal models of mental illness by assembling risk-resilience, adverse outcome pathways (AOP), cognitome, brainome, staging, symptomatome, and phenomenome latent scores in a causal model. The latter may be trained, tested and validated with Partial Least Squares analysis. This approach not only allows to compute pathway-phenotypes or biosignatures, but also to construct reliable and replicable nomothetic networks, which are, therefore, generalizable as disease models. After integrating the validated feature vectors into a well-fitting nomothetic network, clustering analysis may be applied on the latent variable scores of the R/R, AOP, cognitome, brainome, and phenome latent vectors. This pattern recognition method may expose new (transdiagnostic) classes of patients which if cross-validated in independent samples may constitute new (transdiagnostic) nosological categories.