2021
DOI: 10.3389/fpsyt.2021.620401
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Longitudinal Structural MRI Findings in Individuals at Genetic and Clinical High Risk for Psychosis: A Systematic Review

Abstract: Background: Several cross-sectional studies report brain structure differences between healthy volunteers and subjects at genetic or clinical high risk of developing schizophrenia. However, longitudinal studies are important to determine whether altered trajectories of brain development precede psychosis onset.Methods: We conducted a systematic review to determine if brain trajectories differ between (i) those with psychotic experiences (PE), genetic (GHR) or clinical high risk (CHR), compared to healthy volun… Show more

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Cited by 39 publications
(32 citation statements)
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“…Similarly, lower FA in the PCR and corpus callosum (CC) has also been reported in clinical high-risk populations (39, 41, 42). In addition, differences in white matter of the SFO, PCR, and CC have been associated with the transition to psychosis (43). Similar to other major white matter tracts, FA within the SLF increases significantly during adolescence (44).…”
Section: Discussionmentioning
confidence: 99%
“…Similarly, lower FA in the PCR and corpus callosum (CC) has also been reported in clinical high-risk populations (39, 41, 42). In addition, differences in white matter of the SFO, PCR, and CC have been associated with the transition to psychosis (43). Similar to other major white matter tracts, FA within the SLF increases significantly during adolescence (44).…”
Section: Discussionmentioning
confidence: 99%
“…In addition, there are reports of cerebellar abnormalities in idiopathic psychosis (107)(108)(109)(110)(111)(112)(113)(114)(115)(116)(117)(118) and pathology in Purkinje cells, the output neurons of the cerebellar cortex, has been documented in schizophrenia (119)(120)(121). Further, altered functional or structural connectivity and morphology of the cerebellum has been identified in CHR groups (49,(122)(123)(124)(125)(126)(127)(128)(129)(130).…”
Section: Discussionmentioning
confidence: 99%
“…Much of the existing work in the field, as we previously described, analyzes neuroimaging data cross-sectionally, which does not provide information about changes in the structure and functionality of the brain over time. A better understanding of the longitudinal trajectories of brain endophenotypes would improve our knowledge of the underlying biological characterisation of complex neurological diseases [86] , [87] , [88] . For example, application of mixed-effect models to longitudinal brain imaging data has helped to identify a large number of significant genetic-multiphenotype associations [89] , [90] .…”
Section: Discussion and Future Perspectivementioning
confidence: 99%