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Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Naïve Adolescents at High Risk for Psychosis
Published on: November 21, 2013
Predicting clinical and functional trajectories in individuals with first-episode psychosis by baseline deviations in
Manuel Muñoz-Caracuel1,2, Claudio Alemán-Morillo3, Natalia García-San-Martín3
1Mental Health Unit, Virgen del Rocío University Hospital-CIBERSAM, Seville, Spain.
Background:
Predicting long-term outcome trajectories in psychosis remains a crucial and challenging goal in clinical practice. The identification of reliable neuroimaging markers has often been hindered by the clinical and biological heterogeneity of psychotic disorders and the limitations of traditional case-control methodologies, which often mask individual variability. Recently, normative brain charts derived from extensive magnetic resonance imaging (MRI) data-sets covering the human lifespan have emerged as a promising biologically driven solution, offering a more individualised approach.
Aims:
To examine how deviations from normative cortical and subcortical grey matter volume (GMV) at first-episode psychosis (FEP) onset relate to symptom and functional trajectories.
Method:
We leveraged the largest available brain normative model (N > 100 000) to explore normative deviations in a sample of over 240 patients with schizophrenia spectrum disorders who underwent MRI scans at the onset of FEP and received clinical follow-up at 1, 3 and 10 years.
Results:
Our findings reveal that deviations in regional normative GMV at FEP onset are significantly linked to overall long-term clinical trajectories, modulating the effect of time on both symptom and functional outcome. Specifically, negative deviations in the left superior temporal gyrus and Broca’s area at FEP onset were notably associated with a more severe progression of positive and negative symptoms, as well as with functioning trajectories over time.
Conclusions:
These results underscore the potential of brain developmental normative approaches for the early prediction of disorder progression, and provide valuable insights for the development of preventive and personalised therapeutic strategies.
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