Functional Connectomics of Affective and Psychotic Pathology
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Functional connectomics of affective and psychotic pathology Justin T. Bakera,b,1, Daniel G. Dillonb,c, Lauren M. Patrickd, Joshua L. Roffmanb,e,f, Roscoe O. Brady Jr.a,b,g, Diego A. Pizzagallib,c, Dost Öngüra,b, and Avram J. Holmesc,d,h,1 aSchizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA 02478; bDepartment of Psychiatry, Harvard Medical School, Boston, MA 02114; cCenter for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA 02478; dDepartment of Psychology, Yale University, New Haven, CT 06520; eAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129; fDepartment of Psychiatry, Massachusetts General Hospital, Boston, MA 02114; gDepartment of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA 02114; and hDepartment of Psychiatry, Yale University, New Haven, CT 06520 Edited by Marcus E. Raichle, Washington University in St. Louis, St. Louis, MO, and approved March 21, 2019 (received for review December 6, 2018) Converging evidence indicates that groups of patients with nom- advances, we still remain far from a mechanistic understanding of inally distinct psychiatric diagnoses are not separated by sharp or how the functioning of large-scale brain networks might serve to discontinuous neurobiological boundaries. In healthy populations, influence suites of behaviors within, or across, psychiatric illnesses. individual differences in behavior are reflected in variability across Identifying signatures of pathology across the functional con- the collective set of functional brain connections (functional con- nectome could provide a framework for researchers to study neu- nectome). These data suggest that the spectra of transdiagnostic robiological contributions to the onset and maintenance of clinically symptom profiles observed in psychiatric patients may map onto relevant symptoms, informing the development of novel treatments detectable patterns of network function. To examine the manner and future classification schemes. Emerging evidence in healthy through which neurobiological variation might underlie clinical populations suggests that individual differences in behavior may be presentation, we obtained fMRI data from over 1,000 individuals, reflected in variability across the collective set of functional brain including 210 diagnosed with a primary psychotic disorder or connections (11–13) (functional connectome) (14). Work from our affective psychosis (bipolar disorder with psychosis and schizophrenia group and others indicate that the unique connectome architecture or schizoaffective disorder), 192 presenting with a primary affective of an individual’s brain serves as a stable and reliable “fingerprint” NEUROSCIENCE disorder without psychosis (unipolar depression, bipolar disorder (12, 13, 15–17), likely influenced by genetic variation (18–20). The without psychosis), and 608 demographically matched healthy com- parison participants recruited through a large-scale study of brain spectra of symptom profiles observed in patient populations may imaging and genetics. Here, we examine variation in functional con- arise through detectable patterns of network function (1, 21, 22). In nectomes across psychiatric diagnoses, finding striking evidence particular, the disturbance of individual networks might preferen- for disease connectomic “fingerprints” that are commonly disrup- tially contribute to domain-specific (e.g., executive, affective, and ted across distinct forms of pathology and appear to scale as a func- tion of illness severity. The presence of affective and psychotic Significance COGNITIVE SCIENCES illnesses was associated with graded disruptions in frontoparietal PSYCHOLOGICAL AND network connectivity (encompassing aspects of dorsolateral prefron- Historically, most research on the biological origins of psychiatric tal, dorsomedial prefrontal, lateral parietal, and posterior temporal illness has focused on individual diagnostic categories, studied in cortices). Conversely, other properties of network connectivity, in- isolation. Mounting evidence indicates that nominally distinct cluding default network integrity, were preferentially disrupted in psychiatric diagnoses are not separated by clear neurobiological patients with psychotic illness, but not patients without psychotic boundaries. Here, we derive functional connectomic signatures in symptoms. This work allows us to establish key biological and clinical over 1,000 individuals, including patients presenting with differ- features of the functional connectomes of severe mental disease. ent categories of impairment (psychosis), clinical diagnoses, and severity of illness as reflected in treatment seeking. Our analyses functional connectome | schizophrenia | major depressive disorder | reveal features of connectome functioning that are commonly bipolar disorder | resting-state connectivity disrupted across distinct forms of pathology, scaling with clinical severity. Conversely, other aspects of network connectivity were ecent progress in the neurosciences has provided un- preferentially disrupted in patients with psychotic illness. These Rprecedented opportunities for advancing our understanding data have important implications for the establishment of func- of the etiology and pathogenesis of psychiatric illness. At the tional connectome fingerprints of severe mental disease. same time, the gradual reification of diagnostic categories has hampered our ability to take full advantage of these innovations Author contributions: J.T.B., D.G.D., J.L.R., R.O.B., D.A.P., D.Ö., and A.J.H. designed re- – search; J.T.B., D.G.D., and A.J.H. performed research; J.T.B., L.M.P., and A.J.H. analyzed (1 4). To date, the vast majority of research on the biological data; and J.T.B., D.G.D., L.M.P., J.L.R., R.O.B., D.A.P., D.Ö., and A.J.H. wrote the paper. origins of psychopathology has focused on discrete illness cate- Conflict of interest statement: Over the past 3 years, D.A.P. has received consulting fees gories, studied in isolation. Although modern psychiatric diagnoses from Akili Interactive Labs, BlackThorn Therapeutics, Boehringer Ingelheim, Compass, provide advantages to the field in terms of diagnostic reliability, Posit Science, and Takeda Pharmaceuticals and honoraria from Alkermes for activities their construct validity and utility for understanding brain circuit unrelated to the current review. J.T.B. has received consulting fees from Pear Therapeu- tics and Niraxx Therapeutics. J.L.R. has received investigator-initiated funding from Pamlab. dysfunction has been challenged (2, 3). Converging epidemiologic, D.Ö. served on an Advisory Board for Neurocrine Inc. in December 2016, unrelated to the genetic, and neuroscientific research suggests that populations of current work. No funding from these entities was used to support the current work, and all psychiatric patients are not separated by clear neurobiological views expressed are solely those of the authors. borders between diagnostic categories or across health and disease. This article is a PNAS Direct Submission. There is evidence, for example, of substantial overlap in the genetic This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY). – factors that increase risk for both affective and psychotic illness (5 1To whom correspondence may be addressed. Email: [email protected] or avram. 7). Consistent with shared heritability, partially overlapping patterns [email protected]. of brain network dysfunction mark a broad range of mental diseases This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. (8–10), indicating that their breakdown can lead to diverse forms of 1073/pnas.1820780116/-/DCSupplemental. psychopathology. However, despite a flurry of important scientific www.pnas.org/cgi/doi/10.1073/pnas.1820780116 PNAS Latest Articles | 1of10 Downloaded by guest on September 24, 2021 social), but disorder-general, impairments (8, 9, 21). While some seeking patients with unipolar depression, but not within common patterns of network functioning may be shared across nontreatment-seeking individuals who met criteria for unipolar illnesses—for example the hypothesized central role of altered depression but were recruited from the general community. Sec- frontoparietal network connectivity in mental health (8)—other ond, the observed patterns of connectome functioning display network-specific alterations may produce clusters of symptoms that evidence of general as well as specific alterations in network preferentially present in specific illnesses (e.g., psychosis). connectivity across categories of impairment (psychosis) and Despite increasing interest in the study of relationships that link clinical diagnoses. Schizophrenia and psychotic bipolar disorder, connectome functioning with broad diagnostic syndromes, existing for example, associate with a preferential reduction in default work in this domain is often limited in several key respects. First, network integrity that is absent in affective illnesses without psy- most research utilizes case-control designs, examining single psychi- chosis. Taken together, these results suggest that graded impair- atric illnesses in isolation. This approach can potentially mask the ments within key control networks likely represent a common presence of substantial overlap in the distributions of connectome biological substrate central to the pathophysiology of both affec- functioning across populations, giving