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Article ; Online: The Gold Standard Diagnosis of Schizophrenia is Counterproductive: Towards Quantitative Research and Diagnostic Algorithmic Rules (RADAR) and their Derived Qualitative Distinct Classes.

Maes, Michael

2024

Abstract: Recently, we developed Research and Diagnostic Algorithm Rules (RADAR) to assess the clinical and pathway features of mood disorders. The aims of this paper are to review a) the methodology for developing continuous RADAR scores that describe the ... ...

Abstract	Recently, we developed Research and Diagnostic Algorithm Rules (RADAR) to assess the clinical and pathway features of mood disorders. The aims of this paper are to review a) the methodology for developing continuous RADAR scores that describe the clinical and pathway features of schizophrenia, and b) a new method to visualize the clinical status of patients and the pathways implicated in RADAR graphs. We review how to interpret clinical RADAR scores, which serve as valuable tools for monitoring the staging of illness, lifetime suicidal behaviors, overall severity of illness, a general cognitive decline index, and a behavior-cognitive-psychosocial (BCPS) index that represents the "defect"; and b) pathway RADAR scores which reflect various protective (including the compensatory immune- inflammatory system) and adverse (including neuro-immune, neuro-oxidative, and neurotoxic biomarkers) outcome pathways. Using RADAR scores and machine learning, we created new, qualitatively different types of schizophrenia, such as major neurocognitive psychosis and simple psychosis. We also made RADAR graphs, which give us a quick way to compare the patient's clinical condition and pathways to those of healthy controls. We generated a personalized fingerprint for each patient, encompassing various clinical and pathway features of the disorder represented through RADAR graphs. The latter is utilized in clinical practice to assess the clinical condition of patients and identify treatment-required pathways to mitigate the risk of recurrent episodes, worsening BCPS, and increasing staging. The quantitative clinical RADAR scores should be used in schizophrenia research as dependent variables and regressed on the pathway RADAR scores.
Language	English
Publishing date	2024-04-19
Publishing country	United Arab Emirates
Document type	Journal Article
ZDB-ID	2064823-6
ISSN	1873-4294 ; 1568-0266
ISSN (online)	1873-4294
ISSN	1568-0266
DOI	10.2174/0115680266295129240415120646
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Article: Precision Nomothetic Medicine in Depression Research: A New Depression Model, and New Endophenotype Classes and Pathway Phenotypes, and A Digital Self.

Maes, Michael

Journal of personalized medicine

2022 Volume 12, Issue 3

Abstract: Machine learning approaches, such as soft independent modeling of class analogy (SIMCA) and pathway analysis, were introduced in depression research in the 1990s (Maes et al.) to construct neuroimmune endophenotype classes. The goal of this paper is to ... ...

Abstract	Machine learning approaches, such as soft independent modeling of class analogy (SIMCA) and pathway analysis, were introduced in depression research in the 1990s (Maes et al.) to construct neuroimmune endophenotype classes. The goal of this paper is to examine the promise of precision psychiatry to use information about a depressed person's own pan-omics, environmental, and lifestyle data, or to tailor preventative measures and medical treatments to endophenotype subgroups of depressed patients in order to achieve the best clinical outcome for each individual. Three steps are emerging in precision medicine: (1) the optimization and refining of classical models and constructing digital twins; (2) the use of precision medicine to construct endophenotype classes and pathway phenotypes, and (3) constructing a digital self of each patient. The root cause of why precision psychiatry cannot develop into true sciences is that there is no correct (cross-validated and reliable) model of clinical depression as a serious medical disorder discriminating it from a normal emotional distress response including sadness, grief and demoralization. Here, we explain how we used (un)supervised machine learning such as partial least squares path analysis, SIMCA and factor analysis to construct (a) a new precision depression model; (b) a new endophenotype class, namely major dysmood disorder (MDMD), which is a nosological class defined by severe symptoms and neuro-oxidative toxicity; and a new pathway phenotype, namely the reoccurrence of illness (ROI) index, which is a latent vector extracted from staging characteristics (number of depression and manic episodes and suicide attempts), and (c) an ideocratic profile with personalized scores based on all MDMD features.
Language	English
Publishing date	2022-03-05
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662248-8
ISSN	2075-4426
ISSN	2075-4426
DOI	10.3390/jpm12030403
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Article ; Online: Major neurocognitive psychosis: a novel schizophrenia endophenotype class that is based on machine learning and resembles Kraepelin's and Bleuler's conceptions.

Maes, Michael

Acta neuropsychiatrica

2022 Volume 35, Issue 3, Page(s) 123–137

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Humans ; Schizophrenia/complications ; Schizophrenia/diagnosis ; Endophenotypes ; Psychotic Disorders/complications ; Psychotic Disorders/diagnosis ; Machine Learning ; Tryptophan/metabolism
Chemical Substances	Tryptophan (8DUH1N11BX)
Language	English
Publishing date	2022-11-14
Publishing country	England
Document type	Journal Article
ZDB-ID	1154361-9
ISSN	1601-5215 ; 0924-2708
ISSN (online)	1601-5215
ISSN	0924-2708
DOI	10.1017/neu.2022.32
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Article ; Online: Bayesian modelling of antimicrobial resistance in enteric fever in understudied areas.

Bote, Lia / Maes, Mailis

The Lancet. Global health

2024 Volume 12, Issue 3, Page(s) e346–e347

MeSH term(s)	Humans ; Typhoid Fever/drug therapy ; Typhoid Fever/epidemiology ; Anti-Bacterial Agents/pharmacology ; Anti-Bacterial Agents/therapeutic use ; Bayes Theorem ; Drug Resistance, Bacterial ; Salmonella paratyphi A ; Paratyphoid Fever/drug therapy
Chemical Substances	Anti-Bacterial Agents
Language	English
Publishing date	2024-02-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2723488-5
ISSN	2214-109X ; 2214-109X
ISSN (online)	2214-109X
ISSN	2214-109X
DOI	10.1016/S2214-109X(24)00030-5
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Article ; Online: The Role of Choline in Neurodevelopmental Disorders-A Narrative Review Focusing on ASC, ADHD and Dyslexia.

Derbyshire, Emma / Maes, Michael

Nutrients

2023 Volume 15, Issue 13

Abstract: Neurodevelopmental disorders appear to be rising in prevalence, according to the recent Global Burden of Disease Study. This rise is likely to be multi-factorial, but the role of certain nutrients known to facilitate neurodevelopment should be considered. ...

Abstract	Neurodevelopmental disorders appear to be rising in prevalence, according to the recent Global Burden of Disease Study. This rise is likely to be multi-factorial, but the role of certain nutrients known to facilitate neurodevelopment should be considered. One possible contributing factor could be attributed to deficits in choline intake, particularly during key stages of neurodevelopment, which includes the first 1000 days of life and childhood. Choline, a key micronutrient, is crucial for optimal neurodevelopment and brain functioning of offspring. The present narrative review discusses the main research, describing the effect of choline in neurodevelopmental disorders, to better understand its role in the etiology and management of these disorders. In terms of findings, low choline intakes and reduced or altered choline status have been reported in relevant population subgroups: pregnancy (in utero), children with autism spectrum disorders, people with attention deficit hyperactivity disorder and those with dyslexia. In conclusion, an optimal choline provision may offer some neuronal protection in early life and help to mitigate some cognitive effects in later life attributed to neurodevelopmental conditions. Research indicates that choline may act as a modifiable risk factor for certain neurodevelopmental conditions. Ongoing research is needed to unravel the mechanisms and explanations.
MeSH term(s)	Pregnancy ; Child ; Female ; Humans ; Attention Deficit Disorder with Hyperactivity/epidemiology ; Neurodevelopmental Disorders ; Autism Spectrum Disorder/epidemiology ; Dyslexia/complications
Language	English
Publishing date	2023-06-25
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2518386-2
ISSN	2072-6643 ; 2072-6643
ISSN (online)	2072-6643
ISSN	2072-6643
DOI	10.3390/nu15132876
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Article ; Online: Although serotonin is not a major player in depression, its precursor is.

Almulla, Abbas F / Maes, Michael

Molecular psychiatry

2023 Volume 28, Issue 8, Page(s) 3155–3156

MeSH term(s)	Humans ; Depression ; Serotonin ; Depressive Disorder
Chemical Substances	Serotonin (333DO1RDJY)
Language	English
Publishing date	2023-06-16
Publishing country	England
Document type	Letter ; Comment
ZDB-ID	1330655-8
ISSN	1476-5578 ; 1359-4184
ISSN (online)	1476-5578
ISSN	1359-4184
DOI	10.1038/s41380-023-02092-1
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Article: Research and Diagnostic Algorithmic Rules (RADAR) and RADAR Plots for the First Episode of Major Depressive Disorder: Effects of Childhood and Recent Adverse Experiences on Suicidal Behaviors, Neurocognition and Phenome Features.

Maes, Michael / Almulla, Abbas F

Brain sciences

2023 Volume 13, Issue 5

Abstract: Recent studies have proposed valid precision models and valid Research and Diagnostic Algorithmic Rules (RADAR) for recurrent major depressive disorder (MDD). The aim of the current study was to construct precision models and RADAR scores in patients ... ...

Abstract	Recent studies have proposed valid precision models and valid Research and Diagnostic Algorithmic Rules (RADAR) for recurrent major depressive disorder (MDD). The aim of the current study was to construct precision models and RADAR scores in patients experiencing first-episode MDD and to examine whether adverse childhood experiences (ACE) and negative life events (NLE) are associated with suicidal behaviors (SB), cognitive impairment, and phenome RADAR scores. This study recruited 90 patients with major depressive disorder (MDD) in an acute phase, of whom 71 showed a first-episode MDD (FEM), and 40 controls. We constructed RADAR scores for ACE; NLE encountered in the last year; SB; and severity of depression, anxiety, chronic fatigue, and physiosomatic symptoms using the Hamilton Depression and Anxiety Rating Scales and the FibroFatigue scale. The partial least squares analysis showed that in FEM, one latent vector (labeled the phenome of FEM) could be extracted from depressive, anxiety, fatigue, physiosomatic, melancholia, and insomnia symptoms, SB, and cognitive impairments. The latter were conceptualized as a latent vector extracted from the Verbal Fluency Test, the Mini-Mental State Examination, and ratings of memory and judgement, indicating a generalized cognitive decline (G-CoDe). We found that 60.8% of the variance in the FEM phenome was explained by the cumulative effects of NLE and ACE, in particular emotional neglect and, to a lesser extent, physical abuse. In conclusion, the RADAR scores and plots constructed here should be used in research and clinical settings, rather than the binary diagnosis of MDD based on the DSM-5 or ICD.
Language	English
Publishing date	2023-04-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2651993-8
ISSN	2076-3425
ISSN	2076-3425
DOI	10.3390/brainsci13050714
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Article ; Online: Mast Cells in Autism Spectrum Disorder-The Enigma to Be Solved?

Kovacheva, Eleonora / Gevezova, Maria / Maes, Michael / Sarafian, Victoria

International journal of molecular sciences

2024 Volume 25, Issue 5

Abstract: Autism Spectrum Disorder (ASD) is a disturbance of neurodevelopment with a complicated pathogenesis and unidentified etiology. Many children with ASD have a history of "allergic symptoms", often in the absence of mast cell (MC)-positive tests. Activation ...

Abstract	Autism Spectrum Disorder (ASD) is a disturbance of neurodevelopment with a complicated pathogenesis and unidentified etiology. Many children with ASD have a history of "allergic symptoms", often in the absence of mast cell (MC)-positive tests. Activation of MCs by various stimuli may release molecules related to inflammation and neurotoxicity, contributing to the development of ASD. The aim of the present paper is to enrich the current knowledge on the relationship between MCs and ASD by discussing key molecules and immune pathways associated with MCs in the pathogenesis of autism. Cytokines, essential marker molecules for MC degranulation and therapeutic targets, are also highlighted. Understanding the relationship between ASD and the activation of MCs, as well as the involved molecules and interactions, are the main points contributing to solving the enigma. Key molecules, associated with MCs, may provide new insights to the discovery of drug targets for modeling inflammation in ASD.
MeSH term(s)	Child ; Humans ; Mast Cells/metabolism ; Autism Spectrum Disorder/metabolism ; Inflammation/metabolism ; Autistic Disorder/metabolism ; Cytokines/metabolism
Chemical Substances	Cytokines
Language	English
Publishing date	2024-02-24
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2019364-6
ISSN	1422-0067 ; 1422-0067 ; 1661-6596
ISSN (online)	1422-0067
ISSN	1422-0067 ; 1661-6596
DOI	10.3390/ijms25052651
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Article ; Online: The mast cells - Cytokines axis in Autism Spectrum Disorder.

Kovacheva, Eleonora / Gevezova, Maria / Maes, Michael / Sarafian, Victoria

Neuropharmacology

2024 Volume 249, Page(s) 109890

Abstract: Autism Spectrum Disorder (ASD) is a neurodevelopmental disturbance, diagnosed in early childhood. It is associated with varying degrees of dysfunctional communication and social skills, repetitive and stereotypic behaviors. Regardless of the constant ... ...

Abstract	Autism Spectrum Disorder (ASD) is a neurodevelopmental disturbance, diagnosed in early childhood. It is associated with varying degrees of dysfunctional communication and social skills, repetitive and stereotypic behaviors. Regardless of the constant increase in the number of diagnosed patients, there are still no established treatment schemes in global practice. Many children with ASD have allergic symptoms, often in the absence of mast cell (MC) positive tests. Activation of MCs may release molecules related to inflammation and neurotoxicity, which contribute to the pathogenesis of ASD. The aim of the present paper is to enrich the current knowledge regarding the relationship between MCs and ASD by providing PPI network analysis-based data that reveal key molecules and immune pathways associated with MCs in the pathogenesis of autism. Network and enrichment analyzes were performed using receptor information and secreted molecules from activated MCs identified in ASD patients. Our analyses revealed cytokines and key marker molecules for MCs degranulation, molecular pathways of key mediators released during cell degranulation, as well as various receptors. Understanding the relationship between ASD and the activation of MCs, as well as the involved molecules and interactions, is important for elucidating the pathogenesis of ASD and developing effective future treatments for autistic patients by discovering new therapeutic target molecules.
MeSH term(s)	Child ; Humans ; Child, Preschool ; Autism Spectrum Disorder/metabolism ; Mast Cells/metabolism ; Mast Cells/pathology ; Cytokines/metabolism ; Autistic Disorder ; Inflammation/metabolism
Chemical Substances	Cytokines
Language	English
Publishing date	2024-03-01
Publishing country	England
Document type	Journal Article
ZDB-ID	218272-5
ISSN	1873-7064 ; 0028-3908
ISSN (online)	1873-7064
ISSN	0028-3908
DOI	10.1016/j.neuropharm.2024.109890
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Article ; Online: Adverse childhood experiences and recent negative events are associated with activated immune and growth factor pathways, the phenome of first episode major depression and suicidal behaviors.

Almulla, Abbas F / Algon, Ali Abbas Abo / Maes, Michael

Psychiatry research

2024 Volume 334, Page(s) 115812

Abstract: This research assessed the effects of adverse childhood experiences (ACEs) and negative life events (NLEs) on forty-eight cytokines/chemokines/growth factors, in 71 FE-MDMD patients and forty heathy controls. ACEs are highly significantly associated with ...

Abstract	This research assessed the effects of adverse childhood experiences (ACEs) and negative life events (NLEs) on forty-eight cytokines/chemokines/growth factors, in 71 FE-MDMD patients and forty heathy controls. ACEs are highly significantly associated with the classical M1 macrophage, T helper (Th)-1, Th-1 polarization, IRS, and neurotoxicity immune profiles, and not with the alternative M2, and Th-2 immune profiles. There are highly significant correlations between ACEs and NLEs and different cytokines/chemokines/growth factors, especially with interleukin (IL)-16, CCL27, stem cell growth factor, and platelet-derived growth factor. Partial Least Squares analysis showed that 62.3 % of the variance in the depression phenome (based on severity of depression, anxiety and suicidal behaviors) was explained by the regression on IL-4 (p = 0.001, inversely), the sum of ACEs + NLEs (p < 0.0001), and a vector extracted from 10 cytokines/chemokines/growth factors (p < 0.0001; both positively associated). The latter partially mediated (p < 0.0001) the effects of ACE + NLEs on the depression phenome. In conclusion, part of the effects of ACEs and NLEs on the depression phenome is mediated via activation of immune and growth factor networks. These pathways have a stronger impact in subjects with lowered activities of the compensatory immune-regulatory system.
MeSH term(s)	Humans ; Depression ; Suicidal Ideation ; Adverse Childhood Experiences ; Depressive Disorder, Major/genetics ; Cytokines ; Chemokines
Chemical Substances	Cytokines ; Chemokines
Language	English
Publishing date	2024-02-29
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	445361-x
ISSN	1872-7123 ; 1872-7506 ; 0925-4927 ; 0165-1781
ISSN (online)	1872-7123 ; 1872-7506
ISSN	0925-4927 ; 0165-1781
DOI	10.1016/j.psychres.2024.115812
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