People with psychosis exhibit thalamo-cortical hyperconnectivity and cortico-cortical hypoconnectivity with sensory networks, however, it remains unclear if this applies to all sensory networks, whether it arises from other illness factors, or whether such differences could form the basis of a viable biomarker. To address the foregoing, we harnessed data from the Human Connectome Early Psychosis Project and computed resting-state functional connectivity (RSFC) matrices for 54 healthy controls and 105 psychosis patients. Primary visual, secondary visual ("visual2"), auditory, and somatomotor networks were defined via a recent brain network partition. RSFC was determined for 718 regions via regularized partial correlation. Psychosis patients-both affective and non-affective-exhibited cortico-cortical hypoconnectivity and thalamo-cortical hyperconnectivity in somatomotor and visual2 networks but not in auditory or primary visual networks. When we averaged the visual2 and somatomotor network connections and subtracted the thalamo-cortical and cortico-cortical connectivity values, a robust psychosis biomarker emerged (p=2e-10, Hedges'g=1.05). This "somato-visual" biomarker was present in antipsychotic-naive patients and did not depend on confounds such as psychiatric comorbidities, substance/nicotine use, stress, or anxiety. It had moderate test-retest reliability (ICC=.61) and could be recovered in five-minute scans. The marker could discriminate groups in leave-one-site-out cross-validation (AUC=.79) and improve group classification upon being added to a well-known neurocognition task. Finally, it could differentiate later-stage psychosis patients from healthy or ADHD controls in two independent data sets. These results introduce a simple and robust RSFC biomarker that can distinguish psychosis patients from controls by the early illness stages.

The authors have declared no competing interest.

This work was supported by a K01MH108783 to BPK and a Hendershot pilot grant to BPK through the Psychiatry Department at the University of Rochester.

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The study used ONLY openly available human data that were originally located at HCP dataset and OpenNeuro. The HCP data are public (https://nda.nih.gov/edit_collection.html?id=2914). The UCLA data are located on OpenNeuro.org (accession number: ds000030), and so too are the Rutgers patient and control data (ds005073, ds003404, respectively).

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