Brains of people at risk of psychosis show a pattern that can help predict whether they will go on to develop full-fledged schizophrenia, a new Yale-led study indicates. The findings could help doctors begin early intervention therapies for those most likely to develop the disabling disorder.

Using fMRI images of people who exhibit features indicating a high risk for psychosis, the Yale team noted increased functional connectivity in the cerebello-thalamo-cortical circuitry, an extensive network involved in coordination of a host of brain functions, they report. Higher degrees of functional connectivity of this network were found in those who later developed psychosis.

“The hope is that this biomarker can be used in second-stage screening after the identification of other risk factors for schizophrenia,"

said Tyrone Cannon, professor of psychology and psychiatry and senior author of the paper.

Hyperconnectivity Pattern

In a second experiment, the team confirmed the newly found hyperconnectivity pattern was present among those who already have a diagnosis of schizophrenia but not in those with other psychiatric disorders.

A better understanding of the alterations in brain functioning that underlie schizophrenia and pinpointing potential neural markers that predict psychosis in individuals at risk remain major challenges in clinical neuroscience.

[caption id=“attachment_97404” align=“aligncenter” width=“680”]Network alteration observed in the NAPLS-2 data (a) The identified network with higher connectivity in converters and non-converters compared with controls from the NBS analysis. The nodes in the network mapped to seven functional systems (SM sensorimotor, VIS visual, AUD auditory, DMN default-mode, FPN frontoparietal, ATT attentional, SC-CRB subcortical-cerebellar).
(b) Significant linear relationship was shown for the mean cross-paradigm connectivity of the identified network between three groups, with the converter group having the highest value and the control group having the lowest. Note that the cross-paradigm connectivity values were defined at the PCA space, which was rescaled to be mean centered at zero. CHR-C converters, CHR-NC non-converters, HC healthy controls.
(c) The functional connectivity strength of the identified network in the original connectivity matrices for three groups. Significant effects were shown for all five paradigms (RS resting state, WM working memory, EMenc episodic memory encoding, EMret episodic memory retrieval, FM emotional face matching).
(d) The mean cross-paradigm connectivity of the network was significantly correlated with the SOPS disorganization scores in subjects at clinical high risk but not in healthy controls.
(e) The mean cross-paradigm connectivity of the network significantly predicted time to conversion to psychosis among converters.
Credit: Hengyi Cao et al. CC-BY[/caption]

The work used principal component analysis (PCA) combined with connectome-wide network-based statistics (NBS) to analyze data from two independent cohorts. THe data came from a sample of 182 subjects at clinical high risk (CHR) for psychosis (among whom 19 cases later converted to full psychosis during follow-up) and 120 healthy controls, drawn from the second phase of the North American Prodromal Longitudinal Study (NAPLS-2) consortium.

Cognitive Dysmetria Theory

Early intervention in psychosis patients has been linked to better outcomes in schizophrenia, which is marked by hallucinations, delusions, and thought disorder, and generally first strikes people in their late teens and twenties.

The results of this work provide the first empirical evidence that psychosis is associated with an intrinsic “trait-like” abnormality in functional brain architecture, which occurs before the onset of full illness.

[caption id=“attachment_97405” align=“aligncenter” width=“680”]Flowchart of the processing pipeline used in this study Flowchart of the processing pipeline used in this study
Credit: Hengyi Cao et al. CC-BY[/caption]

Cannon said the hyperconnectivity findings suggest that the affected brain network may reflect greater errors in integrative brain functioning, such as the mistiming in the convergence of information from different brain regions. Alternately, he noted, the pattern may reflect compensation for such errors, which are believed to underlie the disorganized thinking that is a hallmark psychosis.

The findings are consistent with the cognitive dysmetria theory of schizophrenia. Initially proposed by Nancy Andreasen and colleagues, this theory holds that patients with schizophrenia are characterized by changes in a key neural circuit, namely, the cerebello–thalamo–cortical circuitry. Dysfunction in this circuitry leads to an impairment in the synchrony or coordination of mental processes. This impaired mental coordination is considered as the fundamental deficit in schizophrenia that further accounts for various clinical symptoms.

The research was supported by the NARSAD Young Investigator Grant, by gifts from the Staglin Music Festival for Mental Health and International Mental Health Research Organization, and by National Institute of Health (NIH) grants.

Hengyi Cao, Oliver Y. Chén, Yoonho Chung, Jennifer K. Forsyth, Sarah C. McEwen, Dylan G. Gee, Carrie E. Bearden, Jean Addington, Bradley Goodyear, Kristin S. Cadenhead, Heline Mirzakhanian, Barbara A. Cornblatt, Ricardo E. Carrión, Daniel H. Mathalon, Thomas H. McGlashan, Diana O. Perkins, Aysenil Belger, Larry J. Seidman, Heidi Thermenos, Ming T. Tsuang, Theo G. M. van Erp, Elaine F. Walker, Stephan Hamann, Alan Anticevic, Scott W. Woods & Tyrone D. Cannon Cerebello-thalamo-cortical hyperconnectivity as a state-independent functional neural signature for psychosis prediction and characterization Nature Communications volume 9, Article number: 3836 (2018)

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