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Towards a unified theory of the aetiology of schizophrenia: commentary, Kumari

Published online by Cambridge University Press:  14 October 2024

Veena Kumari*
Affiliation:
Division of Psychology, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, UK
*
Correspondence: Veena Kumari. Email: [email protected]
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Abstract

Type
Commentary
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press on behalf of Royal College of Psychiatrists

Response

Schizophrenia is a complex illness with marked heterogeneity in genetics, environmental risk factors, age at onset, symptoms, neurocognitive profiles, illness progression, treatment outcomes and long-term prognosis. This heterogeneity, which undoubtably has implications for our conceptual understanding of the ‘schizophrenia’ syndrome, as well as for developing effective prevention and treatment approaches, has motivated ‘big data’ studies (e.g.Reference Xiao, Liao, Long, Tao, Zhao and Luo1,Reference Jiang, Wang, Zhou, Palaniyappan, Luo and Ji2 ) to identify patient groups with distinct neurobiological profiles. Recently, Jiang et alReference Jiang, Wang, Zhou, Palaniyappan, Luo and Ji2 employed a pioneering approach, combining phenotypic heterogeneity and illness stage, to identify neuroimaging biomarkers of schizophrenia. Based on the findings of this research, in their editorial in the BJPsych Jiang, Chang & Feng propose two neurophysiological subtypes in schizophrenia, marked by different brain regions of initial grey matter loss (for subtype 1, in Broca's area; for subtype 2, in the hippocampus). Their seemingly uncomplicated yet potentially game-changing model deserves further study taking population-level and individual patient characteristics into account.

The model, in its current form, appears to be based mainly on the findings from a sample of predominantly Asian/Han Chinese patients and therefore needs to be confirmed in other populations. It may or may not be fully applicable, like some genetic findings,Reference Prasad, Bhatia, Kukshal, Nimgaonkar, Deshpande and Thelma3 in certain populations. Concerning patient characteristics, in addition to the positive and negative symptom profiles, illness stage and treatment outcomes that were considered by Jiang and colleagues in their innovative work,Reference Jiang, Wang, Zhou, Palaniyappan, Luo and Ji2 prodromal functioning, duration of untreated psychosis and age at illness onset also need to be carefully considered in further testing of this model, given previous data linking these factors to patterns of brain alteration and/or treatment outcomes. Another important factor to consider in this context is the presence (or absence) of environmental stress and trauma and, where relevant, the age at which individual patients might have been exposed to stress or trauma, given possible differences in developmental trajectories of the brain areasReference Amunts, Schleicher, Ditterich and Zilles4,Reference Lee, Johnson, Ghetti, Hannula and Duff5 implicated in the two schizophrenia subtypes, as well as their differential sensitivity to early environmental stressors such as childhood abuse.Reference Teicher and Samson6 It would be very useful to know, both from prevention and intervention perspectives, why some people with schizophrenia may fall under ‘subtype 1’ or ‘subtype 2’. Are there distinct genetic or environmental risk factors at play and, if so, how?

If the model does survive rigorous empirical scrutiny, to maximise its utility in the context of personalised patient care, especially where routine brain scanning of people with schizophrenia is not a real option, it would be worthwhile to establish any alterations or deficits in ‘specific’ cognitive processes (for example, in language production and comprehension, the primary functions of Broca's area; or in forming and retrieving memories, where the hippocampus plays a key role) which might be present over and above any generalised cognitive impairment in the two schizophrenia subtypes. There will also be a strong case for looking into how to precisely map existing or new animal or experimental models of psychosis onto these two subtypes for a more targeted drug development, the development of other (non-drug) therapy approaches and identification of points of intervention for optimal outcomes.

Data availability

Data availability is not applicable to this article as no new data were created or analysed in this work.

Funding

This work received no specific grant from any funding agency, commercial or not-for-profit sectors.

Declaration of interest

None.

Footnotes

See editorial, pp. 299–301, this issue.

References

Xiao, Y, Liao, W, Long, Z, Tao, B, Zhao, Q, Luo, C, et al. Subtyping schizophrenia patients based on patterns of structural brain alterations. Schizo Bull 2022; 48: 241–50.CrossRefGoogle ScholarPubMed
Jiang, Y, Wang, J, Zhou, E, Palaniyappan, L, Luo, C, Ji, G, et al. Neuroimaging biomarkers define neurophysiological subtypes with distinct trajectories in schizophrenia. Nature Mental Health 2023; 1(3): 186–99.CrossRefGoogle Scholar
Prasad, S, Bhatia, T, Kukshal, P, Nimgaonkar, VL, Deshpande, SN, Thelma, BK. Attempts to replicate genetic associations with schizophrenia in a cohort from north India. NPJ Schizophr 2017; 3(1): 28.CrossRefGoogle Scholar
Amunts, K, Schleicher, A, Ditterich, A, Zilles, K. Broca's region: cytoarchitectonic asymmetry and developmental changes. J Comp Neurol 2003; 465: 7289.CrossRefGoogle ScholarPubMed
Lee, JK, Johnson, EG, Ghetti, S. Hippocampal development: structure, function and implications. In The Hippocampus from Cells to Systems: Structure, Connectivity, and Functional Contributions to Memory and Flexible Cognition (eds Hannula, DE, Duff, MC): 141–66. Springer International Publishing AG, 2017.CrossRefGoogle Scholar
Teicher, MH, Samson, JA. Annual research review: enduring neurobiological effects of childhood abuse and neglect. J Child Psychol Psychiatry 2016; 57: 241–66.CrossRefGoogle ScholarPubMed
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