Evidence of discontinuity between psychosis-risk and non-clinical samples in the neuroanatomical correlates of social function
Haas Shalaila S; Doucet Gaelle E; Antoniades Mathilde; Modabbernia Amirhossein; Corcoran Cheryl M; Kahn René S; Kambeitz Joseph; Kambeitz-Ilankovic Lana; Borgwardt Stefan; Brambilla Paolo; Upthegrove Rachel; Wood Stephen J; Salokangas Raimo K R; Hietala Jarmo; Meisenzahl Eva; Koutsouleris Nikolaos; Frangou Sophia
https://urn.fi/URN:NBN:fi-fe2022081154981
Tiivistelmä
Objective
Social dysfunction is a major feature of clinical-high-risk states for psychosis (CHR-P). Prior research has identified a neuroanatomical pattern associated with impaired social function outcome in CHR-P. The aim of the current study was to test whether social dysfunction in CHR-P is neurobiologically distinct or in a continuum with the lower end of the normal distribution of individual differences in social functioning.
Methods
We used a machine learning classifier to test for the presence of a previously validated brain structural pattern associated with impaired social outcome in CHR-P (CHR-outcome-neurosignature) in the neuroimaging profiles of individuals from two non-clinical samples (total n = 1763) and examined its association with social function, psychopathology and cognition.
Results
Although the CHR-outcome-neurosignature could be detected in a subset of the non-clinical samples, it was not associated was adverse social outcomes or higher psychopathology levels. However, participants whose neuroanatomical profiles were highly aligned with the CHR-outcome-neurosignature manifested subtle disadvantage in fluid (PFDR = 0.004) and crystallized intelligence (PFDR = 0.01), cognitive flexibility (PFDR = 0.02), inhibitory control (PFDR = 0.01), working memory (PFDR = 0.0005), and processing speed (PFDR = 0.04).
Conclusions
We provide evidence of divergence in brain structural underpinnings of social dysfunction derived from a psychosis-risk enriched population when applied to non-clinical samples. This approach appears promising in identifying brain mechanisms bound to psychosis through comparisons of patient populations to non-clinical samples with the same neuroanatomical profiles.
Kokoelmat
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