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Major depressive disorder (MDD), anxiety disorders (ANX), and chronic pain (CP) are closely-related disorders with both high degrees of comorbidity among them and shared risk factors. Considering this multi-level overlap, but also the distinct phenotypes of the disorders, we hypothesized both common and disorder-specific changes of large-scale brain systems, which mediate neural mechanisms and impaired behavioral traits, in MDD, ANX, and CP. To identify such common and disorder-specific brain changes, we conducted a transdiagnostic, multimodal meta-analysis of structural and functional MRI-studies investigating changes of gray matter volume (GMV) and intrinsic functional connectivity (iFC) of large-scale intrinsic brain networks across MDD, ANX, and CP. The study was preregistered at PROSPERO (CRD42019119709). 320 studies comprising 10,931 patients and 11,135 healthy controls were included. Across disorders, common changes focused on GMV-decrease in insular and medial-prefrontal cortices, located mainly within the so-called default-mode and salience networks. Disorder-specific changes comprised hyperconnectivity between default-mode and frontoparietal networks and hypoconnectivity between limbic and salience networks in MDD; limbic network hyperconnectivity and GMV-decrease in insular and medial-temporal cortices in ANX; and hypoconnectivity between salience and default-mode networks and GMV-increase in medial temporal lobes in CP. Common changes suggested a neural correlate for comorbidity and possibly shared neuro-behavioral chronification mechanisms. Disorder-specific changes might underlie distinct phenotypes and possibly additional disorder-specific mechanisms.

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Introduction: Threat processing, enabled by threat circuits, is supported by a remarkably conserved neural architecture across mammals. Threatening stimuli relevant for most species include the threat of being attacked by a predator or an aggressive conspecific and the threat of pain. Extensive studies in rodents have associated the threats of pain, predator attack and aggressive conspecific attack with distinct neural circuits in subregions of the amygdala, the hypothalamus and the periaqueductal gray. Bearing in mind the considerable conservation of both the anatomy of these regions and defensive behaviors across mammalian species, we hypothesized that distinct brain activity corresponding to the threats of pain, predator attack and aggressive conspecific attack would also exist in human subcortical brain regions. Methods: Forty healthy female subjects underwent fMRI scanning during aversive classical conditioning. In close analogy to rodent studies, threat stimuli consisted of painful electric shocks, a short video clip of an attacking bear and a short video clip of an attacking man. Threat processing was conceptualized as the expectation of the aversive stimulus during the presentation of the conditioned stimulus. Results: Our results demonstrate differential brain activations in the left and right amygdala as well as in the left hypothalamus for the threats of pain, predator attack and aggressive conspecific attack, for the first time showing distinct threat-related brain activity within the human subcortical brain. Specifically, the threat of pain showed an increase of activity in the left and right amygdala and the left hypothalamus compared to the threat of conspecific attack (pain > conspecific), and increased activity in the left amygdala compared to the threat of predator attack (pain > predator). Threat of conspecific attack revealed heightened activity in the right amygdala, both in comparison to threat of pain (conspecific > pain) and threat of predator attack (conspecific > predator). Finally, for the condition threat of predator attack we found increased activity in the bilateral amygdala and the hypothalamus when compared to threat of conspecific attack (predator > conspecific). No significant clusters were found for the contrast predator attack > pain. Conclusion: Results suggest that threat type-specific circuits identified in rodents might be conserved in the human brain.

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BACKGROUND: This study investigated characteristic large-scale brain changes in schizophrenia. Numerous imaging studies have demonstrated brain changes in schizophrenia, particularly aberrant intrinsic functional connectivity (iFC) of ongoing brain activity, measured by resting-state functional magnetic resonance imaging, and aberrant gray matter volume (GMV) of distributed brain regions, measured by structural magnetic resonance imaging. It is unclear, however, which iFC changes are specific to schizophrenia compared with those of other disorders and whether such specific iFC changes converge with GMV changes. To address this question of specific substantial dysconnectivity in schizophrenia, we performed a transdiagnostic multimodal meta-analysis of resting-state functional and structural magnetic resonance imaging studies in schizophrenia and other psychiatric disorders. METHODS: Multiple databases were searched up to June 2017 for whole-brain seed-based iFC studies and voxel-based morphometry studies in schizophrenia, major depressive disorder, bipolar disorder, addiction, and anxiety. Coordinate-based meta-analyses were performed to detect 1) schizophrenia-specific hyperconnectivity or hypoconnectivity of intrinsic brain networks (compared with hyperconnectivity or hypoconnectivity of each other disorder both separately and combined across comparisons) and 2) the overlap between dysconnectivity and GMV changes (via multimodal conjunction analysis). RESULTS: For iFC meta-analysis, 173 publications comprising 4962 patients and 4575 control subjects were included, and for GMV meta-analysis, 127 publications comprising 6311 patients and 6745 control subjects were included. Disorder-specific iFC dysconnectivity in schizophrenia (consistent across comparisons with other disorders) was found for limbic, frontoparietal executive, default mode, and salience networks. Disorder-specific dysconnectivity and GMV reductions converged in insula, lateral postcentral cortex, striatum, and thalamus. CONCLUSIONS: Results demonstrated specific substantial dysconnectivity in schizophrenia in insula, lateral postcentral cortex, striatum, and thalamus. Data suggest that these regions are characteristic targets of schizophrenia.

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