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Schizophrenia phenomenology revisited: positive and negative symptoms are strongly related reflective manifestations of an underlying single trait indicating overall severity of schizophrenia

Published online by Cambridge University Press:  20 May 2020

Abbas F. Almulla
Affiliation:
Medical Laboratory Technology Department, College of Medical Technology, The Islamic University, Najaf, Iraq
Hussein K. Al-Hakeim
Affiliation:
Department of Chemistry, College of Science, University of Kufa, Kufa, Iraq
Michael Maes*
Affiliation:
Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand Department of Psychiatry, Medical University of Plovdiv, Plovdiv, Bulgaria Department of Psychiatry, IMPACT Strategic Research Centre, Deakin University, Geelong, Victoria, Australia
*
*Michael Maes, MD, PhD, Email: dr.michaelmaes@hotmail.com

Abstract

Background

To examine whether negative symptoms, psychosis, hostility, excitation, and mannerism (PHEM symptoms), formal thought disorders (FTD) and psychomotor retardation (PMR) are interrelated phenomena in major neurocognitive psychosis (MNP) or deficit schizophrenia and whether those domains belong to an underlying latent vector reflecting general psychopathology.

Methods

In this study, we recruited 120 patients with MNP or deficit schizophrenia and 54 healthy subjects and measured the above-mentioned symptom domains.

Results

In MNP, there were significant associations between negative and PHEM symptoms, FTD and PMR. A single latent trait, which is essentially unidimensional, underlies these key domains of schizophrenia and MNP and additionally shows excellent internal consistency reliability, convergent validity, and predictive relevance. Confirmatory Tedrad Analysis indicates that this latent vector fits a reflective model. The lack of discriminant validity shows that positive (and PHEM or psychotic) and negative symptoms greatly overlap and probably measure the same latent construct. Soft independent modeling of class analogy (SIMCA) shows that MNP (diagnosis based on negative symptoms) is better modeled using PHEM symptoms, FTD, and PMR than negative symptoms.

Conclusions

In stable phase MNP, which is a restricted sample of the schizophrenia population, negative and PHEM symptoms, FTD and PMR belong to one underlying latent vector reflecting overall severity of schizophrenia (OSOS). The bi-dimensional concept of “positive” and “negative” symptoms cannot be validated and, therefore, future research in stable phase schizophrenia should consider that the latent phenomenon OSOS as well as its reflective manifestations are the key factors of schizophrenia phenomenology.

Type
Original Research
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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References

Mellor, CS. Methodological problems in identifying and measuring first-rank symptoms of schizophrenia. In: Marneros, A, Andreasen, NC, Tsuang, MT, eds. Negative Versus Positive Schizophrenia. Berlin, Heidelberg: Springer; 1991.Google Scholar
A, M, Deister, A, Rohde, A. Affective, schizoaffective and schizophrenic psychoses. A comparative long-term study. Monogr Gesamtgeb Psychiatry Ser. 1991;65:1454.Google Scholar
Peralta, V, Cuesta, MJ. Negative symptoms in schizophrenia: a confirmatory factor analysis of competing models. Am J Psychiatry. 1995;152(10):14501457.Google ScholarPubMed
Burton, N. Living with Schizophrenia. 2nd ed.. Oxford, UK: Acheron Press; 2012:3.Google Scholar
Crow, TJ. The two-syndrome concept: origins and current status. Origins. 1985;11:471488.Google ScholarPubMed
Ahmed, AO, Strauss, GP, Buchanan, RW, Kirkpatrick, B, Carpenter, WT. Are negative symptoms dimensional or categorical? Detection and validation of deficit schizophrenia with taxometric and latent variable mixture models. Schizophr Bull. 2015;41:879891.CrossRefGoogle ScholarPubMed
Kirkpatrick, B, Buchanan, RW, McKenney, PD, et al. The schedule for the deficit syndrome: an instrument for research in schizophrenia. Psychiatry Res. 1989;30:119123.CrossRefGoogle Scholar
Bleuler, E. Dementia Praecox, or the Group of Schizophrenias (1911). Zinkin, J, trans-ed. New York, NY: International Universities Press; 1950.Google Scholar
Jablensky, A. The diagnostic concept of schizophrenia: its history, evolution, and future prospects. Dialogues Clin Neurosci. 2010;12:271287.CrossRefGoogle ScholarPubMed
Takahashi, S. Heterogeneity of schizophrenia: genetic and symptomatic factors. Am J Med Genet B Neuropsychiatr Genet. 2013;162B:648652.CrossRefGoogle ScholarPubMed
Kanchanatawan, B, Sriswasdi, S, Thika, S, et al. Deficit schizophrenia is a discrete diagnostic category defined by neuro-immune and neurocognitive features: results of supervised machine learning. Metab Brain Dis. 2018;33(4):10531067.CrossRefGoogle ScholarPubMed
Kanchanatawan, B, Sriswasdi, S, Thika, S, et al. Towards a new classification of stable phase schizophrenia into major and simple neuro-cognitive psychosis: results of unsupervised machine learning analysis. J Eval Clin Pract. 2018;24:879891.CrossRefGoogle ScholarPubMed
Maes, M, Sirivichayakul, S, Kanchanatawan, B, Carvalho, AF. In schizophrenia, psychomotor retardation is associated with executive and memory impairments, negative and psychotic symptoms, neurotoxic immune products and lower natural IgM to malondialdehyde. World J Biol Psychiatry. 2020;7:119.Google Scholar
Sirivichayakul, S, Kanchanatawan, B, Thika, S, Carvalho, AF, Maes, M. Eotaxin, an Endogenous Cognitive Deteriorating Chemokine (ECDC), is a major contributor to cognitive decline in normal people and to executive, memory, and sustained attention deficits, formal thought disorders, and psychopathology in schizophrenia patients. Neurotox Res. 2019;35(1):122138.CrossRefGoogle Scholar
Simpson, DM, Davis, GC. Measuring thought disorder with clinical rating scales in schizophrenic and nonschizophrenic patients. Psychiatry Res. 1985;15:313318.CrossRefGoogle ScholarPubMed
Andreasen, NC, Grove, WM. Thought, language, and communication in schizophrenia: diagnosis and prognosis. Schizophr Bull. 1986;12(3):348359.CrossRefGoogle ScholarPubMed
Bachman, P, Cannon, TD. The cognitive neuroscience of thought disorder in schizophrenia. In: Holyoak, KJ, Morrison, RG. The Oxford Handbook of Thinking and Reasoning; Oxford Handbooks, Oxford, 2012. doi:10.1093/oxfordhb/9780199734689.013.0034.Google Scholar
Kircher, T, Bröhl, H, Meier, F, Engelen, J. Formal thought disorders: from phenomenology to neurobiology. Lancet Psychiatry. 2018;5(6):515526.CrossRefGoogle ScholarPubMed
Kay, SR, Fiszbein, A, Opler, LA. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull. 1987;13:261276.CrossRefGoogle Scholar
Andreasen, NC. The scale for the assessment of negative symptoms (SANS): conceptual and theoretical foundations. Brit J Psychiatry Suppl. 1989;7:4958.CrossRefGoogle Scholar
Overall, JE, Gorham, DR. The brief psychiatric rating scale. Psycholog Rep. 1962;10:799812.CrossRefGoogle Scholar
Hamilton, M. The assessment of anxiety states by rating. Br J Med Psychol. 1959;32:5055.CrossRefGoogle ScholarPubMed
Hamilton, M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:5662.CrossRefGoogle ScholarPubMed
Folstein, MF, Folstein, SE, McHugh, PR. "Mini-mental status." A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189198.CrossRefGoogle Scholar
Sirivichayakul, S, Kanchanatawan, B, Thika, S, Carvalho, AF, Maes, M. A new schizophrenia model: immune activation is associated with the induction of different neurotoxic products which together determine memory impairments and schizophrenia symptom dimensions. CNS Neurol Disord Drug Targets. 2019;18(2):124140.CrossRefGoogle ScholarPubMed
Yoav, B, Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Royal Statist Soc Series B. 1995;57(1):289300.Google Scholar
Tehseen, S, Ramayah, T, Sajilan, S. Testing and controlling for common method variance: a review of available methods. J Manag Sci. 2017;4(2):146175.Google Scholar
Wiberg, M, Sundstrom, A. A comparison of two approaches to correction of restriction of range in correlation analysis. Pract Assess Res Eval. 2009;14(5):19.Google Scholar
Lakes, KD. Restricted sample variance reduces generalizability. Psychol Assess. 2013;25(2):643650.CrossRefGoogle ScholarPubMed
Roy, MA, DeVriendt, X. Positive and negative symptoms in schizophrenia: a current overview. Can J Psychiatry. 1994;39(7):407414.CrossRefGoogle ScholarPubMed
Kanchanatawan, B, Sirivichayakul, S, Thika, S, et al. Physio-somatic symptoms in schizophrenia: association with depression, anxiety, neurocognitive deficits and the tryptophan catabolite pathway. Metab Brain Dis. 2017;32(4):10031016.CrossRefGoogle ScholarPubMed
Kanchanatawan, B, Thika, S, Sirivichayakul, S, Carvalho, AF, Geffard, M, Maes, M. In schizophrenia, depression, anxiety, and physiosomatic symptoms are strongly related to psychotic symptoms and excitation, impairments in episodic memory, and increased production of neurotoxic tryptophan catabolites: a multivariate and machine learning study. Neurotox Res. 2018;33(3):641655.CrossRefGoogle ScholarPubMed
Maes, M, Sirivichayakul, S, Kanchanatawan, B, Vodjani, A. Upregulation of the intestinal paracellular pathway with breakdown of tight and adherens junctions in deficit schizophrenia. Mol Neurobiol. 2019;56(10):70567073.CrossRefGoogle ScholarPubMed
Smith, RS, Maes, M. The macrophage-T-lymphocyte theory of schizophrenia: additional evidence. Med Hypotheses. 1995;45:135141.CrossRefGoogle ScholarPubMed
Anderson, G, Maes, M. Schizophrenia: linking prenatal infection to cytokines, the tryptophan catabolite (TRYCAT) pathway, NMDA receptor hypofunction, neurodevelopment and neuroprogression. Prog Neuropsychopharmacol Biol Psychiatry. 2013;42:519.CrossRefGoogle ScholarPubMed
Davis, J, Moylan, S, Harvey, BH, Maes, M, Berk, M. Neuroprogression in schizophrenia: pathways underpinning clinical staging and therapeutic corollaries. Aust NZ J Psychiatry. 2014;48:512529.CrossRefGoogle ScholarPubMed
Davis, J, Eyre, H, Jacka, FN, et al. A review of vulnerability and risks for schizophrenia: beyond the two-hit hypothesis. Neurosci Biobehav Rev. 2016;65:185194.CrossRefGoogle ScholarPubMed
Al-Hakeim, HK, Almulla, AF, Maes, M. The neuroimmune and neurotoxic fingerprint of major neurocognitive psychosis or deficit schizophrenia: a supervised machine learning study. Neurotox Res. 2020; doi:10.1007/s12640-019-00112-z. [Epub ahead of print] PubMed PMID: 31916129.CrossRefGoogle ScholarPubMed
Maes, M, Sirivichayakul, S, Kanchanatawan, B, Vodjani, A. Breakdown of the paracellular tight and adherens junctions in the gut and blood brain barrier and damage to the vascular barrier in patients with deficit schizophrenia. Neurotox Res. 2019;36(2):306322.CrossRefGoogle Scholar
Kanchanatawan, B, Sirivichayakul, S, Ruxrungtham, K, et al. Deficit but not nondeficit schizophrenia is characterized by mucosa-associated activation of the tryptophan catabolite (TRYCAT) pathway with highly specific increases in IgA responses directed to picolinic, xanthurenic, and quinolinic acid. Mol Neurobiol. 2018;55(2):15241536.CrossRefGoogle Scholar
Kanchanatawan, B, Sirivichayakul, S, Ruxrungtham, K, et al. Deficit schizophrenia is characterized by defects in IgM-mediated responses to tryptophan catabolites (TRYCATs): a paradigm shift towards defects in natural self-regulatory immune responses coupled with mucosa-derived TRYCAT pathway activation. Mol Neurobiol. 2018;55(3):22142226.CrossRefGoogle ScholarPubMed
Maes, M, Nowak, G, Caso, JR, et al. Toward omics-based, systems biomedicine, and path and drug discovery methodologies for depression-inflammation research. Mol Neurobiol. 2016;53(5):29272935.CrossRefGoogle ScholarPubMed
Maes, M, Schotte, C, Maes, L, Cosyns, P. Clinical subtypes of unipolar depression: Part II. Quantitative and qualitative clinical differences between the vital and nonvital depression groups. Psychiatry Res. 1990;34(1):4357.CrossRefGoogle ScholarPubMed
Al-Hakeim, HK, Almulla, AF, Al-Dujaili, AH, Maes, M. Construction of a neuro-immune-cognitive pathway-phenotype underpinning the phenome of deficit schizophrenia. Curr Top Med Chem. 2020; doi:10.2174/1568026620666200128143948. [Epub ahead of print] PubMed PMID: 31994463.CrossRefGoogle ScholarPubMed
Davis, KL, Kahn, RS, Ko, G, Davidson, M. Dopamine in schizophrenia: a review and reconceptualization. Am J Psychiatry. 1991;148:14741486.Google ScholarPubMed
Weinberger, DR. Implications of normal brain development for the pathogenesis of schizophrenia. Arch Gen Psychiatry. 1987;44:660669.CrossRefGoogle ScholarPubMed
Ferrando, PJ, Lorenzo-Seva, U. Program FACTOR at 10: origins, development and future directions. Psicothema. 2017;29:236240.Google ScholarPubMed
Lorenzo-Seva, U, Ferrando, PJ. A general approach for fitting pure exploratory bifactor models. Multivariate Behav Res. 2019;54(1):1530.CrossRefGoogle ScholarPubMed
Ringle, CM, Wende, S, Becker, J-M. SmartPLS 3. Bönningstedt, Germany: SmartPLS; 2015. http://www.smartpls.com.Google Scholar
Fried, EI, van Borkulo, CD, Epskamp, S, Schoevers, RA, Tuerlinckx, F, Borsboom, D. Measuring depression over time … Or not? Lack of unidimensionality and longitudinal measurement invariance in four common rating scales of depression. Psychol Assess. 2016;28(11):13541367.CrossRefGoogle ScholarPubMed
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