34.1 SEPARABLE AND REPLICABLE NEURAL STRATEGIES DURING SOCIAL BRAIN FUNCTION IN PEOPLE WITH AND WITHOUT SEVERE MENTAL ILLNESS. (9th April 2019)

• Record Type: Journal Article
• Authors: Hawco, Colin; Buchanan, Robert; Calarco, Navona; Mulsant, Benoit; Viviano, Joshua; Dickie, Erin; Argyelan, Miklos; Gold, James; Iacoboni, Marco; DeRosse, Pamela; Foussias, George; Malhotra, Anil; Voineskos, Aristotle
• Is Part Of: Schizophrenia bulletin. Volume 45(2019)Supplement 2
• Page Start: S145
• Page End: S145
• Publication Date: 2019-04-09
• Subjects: Schizophrenia -- Periodicals; Schizophrenia -- Research -- Periodicals; 616.898005
• DOI: 10.1093/schbul/sbz022.142
• Languages: English
• ISSNs: 0586-7614

Abstract

Abstract: Background: Case-control study design and disease heterogeneity may be major limiting factors impeding biomarker discovery in brain disorders, including serious mental illnesses. In order to identify biologically/behaviorally driven as opposed to diagnostically driven sub-groups of individuals, we used hierarchical clustering to identify participants with similar patterns of brain activity during a facial Imitate/Observe functional MRI task. Methods: Participants (N=179; 109 with a schizophrenia spectrum disorder and 70 healthy controls) were scanned at three sites during the performance of the imitate/observe task. Hierarchical clustering was performed to identify data-driven groups of participants who shared similar patterns of neural circuit activation. The number of groups was determined using cluster stability analysis, defined as local minimums for instability across a range from 2 to 10 clusters. The new data-driven groups were compared on social and neurocognitive test performance completed out of the scanner. Results: Three clusters with distinct patterns of neural activity were found. Participants showed greater similarity to their cluster than to their diagnostic category (t(178)=14.0, p=1.3x10-30) or site (p > 0.40). The largest cluster represented 'typical activators', with activity in the canonical 'simulation' circuit. The other clusters represented a 'diffuse/inefficient' activating group, and an 'efficient/deactivating' group. The efficient/deactivating group had the highest social cognitive and neurocognitive test scores (F(2, 170)=5.32, p=0.006; post-hoc t tests p<0.05). The hierarchical clustering analysis was repeated on a replication sample (N=108; SSD, euthymic bipolar disorder, or HC), which identified the same three cluster patterns. Conclusions: Our findings demonstrate replicable different patterns of neural activity among individuals during a socio-emotional task independent of DSM-diagnosis or scan site. Our findings may provide objective neuroimaging endpoints (or biomarkers) for subgroups of individuals in target engagement research aimed at enhancing cognitive performance independent of diagnostic category.