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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

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
Katso/Avaa
SalokangasEtAl2022EvidenceOfDiscontinuityBetween.pdf (1.317Mb)
Lataukset: 

Elsevier Inc.
doi:10.1016/j.scog.2022.100252
URI
https://doi.org/10.1016/j.scog.2022.100252
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Julkaisun pysyvä osoite on:
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.

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