Label-based meta-analysis of functional brain dysconnectivity across mood and psychotic disorders

BACKGROUND Psychiatric diseases are increasingly conceptualized as brain network disorders. Hundreds of resting-state functional magnetic resonance imaging (rsfMRI) studies have revealed patterns of functional brain dysconnectivity in disorders such as major depression disorder (MDD), bipolar disorder (BD) and schizophrenia (SZ). Although these disorders have been mostly studied in isolation, there is mounting evidence of shared neurobiological alterations across disorders. METHODS To uncover the nature of the relatedness between these psychiatric disorders, we conducted an innovative meta-analysis of past functional brain dysconnectivity findings obtained separately in MDD, BD and SZ. Rather than relying on a classical coordinate-based approach at the voxel level, our procedure extracted relevant neuroanatomical labels from text data and reported findings at the whole brain network level. Data were drawn from 428 rsfMRI studies investigating MDD (158 studies, 7429 patients / 7414 controls), BD (81 studies, 3330 patients / 4096 patients) and/or SZ (223 studies, 11168 patients / 11754 controls). Permutation testing revealed commonalities and specificities in hypoconnectivity and hyperconnectivity patterns across disorders. RESULTS Among 78 connections within or between 12 cortico-subcortical networks, hypoconnectivity and hyperconnectivity patterns of higher-order cognitive (default-mode, fronto-parietal, cingulo-opercular) networks were similarly observed across the 3 disorders. By contrast, dysconnectivity of lower-order (somatomotor, visual, auditory) networks in some cases differed between disorders, notably dissociating SZ from BD and MDD. CONCLUSIONS Our label-based meta-analytic approach allowed a comprehensive inclusion of prior studies. Findings suggest that functional brain dysconnectivity of higher-order cognitive networks is largely transdiagnostic in nature while that of lower-order networks may best discriminate mood and psychotic disorders, thus emphasizing the relevance of motor and sensory networks to psychiatric neuroscience. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was funded by a salary award chercheur boursier junior 1 of the Fonds de recherche du Quebec Sante [to PO], a Canadian Institutes of Health Research (CIHR) project grant (Grant No. PJT165910 [to PO]), and the Courtois foundation through the Courtois NeuroMod Project () [to PO]. SP is holder of the Eli Lilly Canada Chair on schizophrenia research. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The meta-analysis study used findings from peer-reviewed published studies. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data as well as Python and R scripts necessary to reproduce the findings reported here are available on Github: . The volumetric version of the CAB-NP atlas can be obtained on Figshare: [https://figshare.com/articles/dataset/CAB- NP\_projected\_on\_MNI2009a\_GM\_volumetric\_in\_NIfTI\_format/14200109][1]. [1]: https://figshare.com/articles/dataset/CAB-NP_projected_on_MNI2009a_GM_volumetric_in_NIfTI_format/14200109