Heterogeneous trajectories in schizophrenia: insights from neurodevelopment and neuroprogression models

Abstract

The notion that schizophrenia is a neuroprogressive disorder is based on clinical perception of cumulative impairments over time and is supported by neuroimaging and biomarker research. Nevertheless, increasing evidence has indicated that schizophrenia first emerges as a neurodevelopmental disorder that could follow various pathways, some of them neuroprogressive. The objective of this review is to revisit basic research on cognitive processes and neuroimaging findings in a search for candidate keys to the intricate connections between neurodevelopment and neuroprogression in schizophrenia. In the complete panorama, schizophrenia is a neurodevelopmental disorder, possibly associated with an additional burden over the course of the disease through pathologically accelerated aging, and cognitive heterogeneity may explain the different trajectories of each patient.

Advanced brain ageing in adult psychopathology: A systematic review and meta-analysis of structural MRI studies

“…The sub-analyses indicate that the structural changes associated with advanced ageing begin early in psychosis. Supporting this, research suggests that some of the most severe brain changes occur during the early stages of the disorder (Reckziegel et al, 2021). Our findings suggest an advanced ageing process with increasing illness duration.…”

Effects of socioeconomic status in cognition of people with schizophrenia: results from a Latin American collaboration network with 1175 subjects

“…However, this process is greatly influenced by the fact that individuals who later develop schizophrenia show difficulties in acquisition of cognitive abilities during childhood and adolescence (Bora, 2015), which might also explain the shorter years of study compared to unaffected individuals. The interaction between neurodevelopmental and neuroprogressive processes could elucidate the heterogeneity and distinct cognitive trajectories of the disorder (Reckziegel et al, 2021).…”

Asynchronous neural maturation predicts transition to psychosis

“…Interindividual heterogeneity precludes their use alone to differentiate outcomes 10 . Moreover, it is unclear whether such brain anomalies result from abnormal dysmaturational trajectories that started early on, 11,12 or neuroprogressive processes related to more recent accelerated aging due to biological stress 13,14 . Machine‐learning strategies may provide new means of exploring these questions by leveraging the best combination of features to predict individual outcome 15 .…”