ABSTRACT
A broad range of neuropsychiatric disorders are associated with alterations in macroscale brain circuitry and connectivity. Identifying consistent brain patterns underlying these disorders by means of structural and functional MRI has proven challenging, partly due to the vast number of tests required to examine the entire brain, which can lead to an increase in missed findings. In this study, we propose polyconnectomic score (PCS) as a metric designed to quantify the presence of disease-related brain connectivity signatures in connectomes. PCS summarizes evidence of brain patterns related to a phenotype across the entire landscape of brain connectivity into a subject-level score. We evaluated PCS across four brain disorders (autism spectrum disorder, schizophrenia, attention deficit hyperactivity disorder, and Alzheimer's disease) and 14 studies encompassing ~35,000 individuals. Our findings consistently show that patients exhibit significantly higher PCS compared to controls, with effect sizes that go beyond other single MRI metrics ([min, max]: Cohen's d = [0.30, 0.87], AUC = [0.58, 0.73]). We further demonstrate that PCS serves as a valuable tool for stratifying individuals, for example within the psychosis continuum, distinguishing patients with schizophrenia from their first-degree relatives (d = 0.42, p = 4 × 10-3, FDR-corrected), and first-degree relatives from healthy controls (d = 0.34, p = 0.034, FDR-corrected). We also show that PCS is useful to uncover associations between brain connectivity patterns related to neuropsychiatric disorders and mental health, psychosocial factors, and body measurements.
ABSTRACT
BACKGROUND: Psychiatric conditions show overlap in their symptoms, genetics, and involvement in brain areas and circuits. Structural alterations in the brain have been found to run in parallel with expression profiles of risk genes at the level of the brain transcriptome, which may point toward a potential transdiagnostic vulnerability of the brain to disease processes. METHODS: We characterized the transcriptomic vulnerability of the cortex across 4 major psychiatric disorders based on collated data from patients with psychiatric disorders (n = 390) and matched control participants (n = 293). We compared normative expression profiles of risk genes linked to schizophrenia, bipolar disorder, autism spectrum disorder, and major depressive disorder to examine cross-disorder overlap in spatial expression profiles across the cortex and their concordance with a magnetic resonance imaging-derived cross-disorder profile of structural brain alterations. RESULTS: We showed high expression of psychiatric risk genes converging on multimodal cortical regions of the limbic, ventral attention, and default mode networks versus primary somatosensory networks. Risk genes were found to be enriched among genes associated with the magnetic resonance imaging cross-disorder profile, suggestive of a common link between brain anatomy and the transcriptome in psychiatric conditions. Characterization of this cross-disorder structural alteration map further shows enrichment for gene markers of astrocytes, microglia, and supragranular cortical layers. CONCLUSIONS: Our findings suggest that normative expression profiles of disorder risk genes confer a shared and spatially patterned vulnerability of the cortex across multiple psychiatric conditions. Transdiagnostic overlap in transcriptomic risk suggests a common pathway to brain dysfunction across psychiatric disorders.
Subject(s)
Autism Spectrum Disorder , Bipolar Disorder , Depressive Disorder, Major , Schizophrenia , Humans , Depressive Disorder, Major/genetics , Bipolar Disorder/genetics , Schizophrenia/diagnostic imaging , Schizophrenia/genetics , Schizophrenia/metabolism , Transcriptome , Autism Spectrum Disorder/diagnostic imaging , Autism Spectrum Disorder/genetics , Brain/pathology , NeuroimagingABSTRACT
Network neuroscience has emerged as a leading method to study brain connectivity. The success of these investigations is dependent not only on approaches to accurately map connectivity but also on the ability to detect real effects in the data - that is, statistical power. We review the state of statistical power in the field and discuss sample size, effect size, measurement error, and network topology as key factors that influence the power of brain connectivity investigations. We use the term 'differential power' to describe how power can vary between nodes, edges, and graph metrics, leaving traces in both positive and negative connectome findings. We conclude with strategies for working with, rather than around, power in connectivity studies.
Subject(s)
Brain , Connectome , Humans , Connectome/methods , Magnetic Resonance Imaging/methods , Nerve NetABSTRACT
Background: Temstem is a mobile application developed in cooperation with voice-hearing persons to help them cope with distressing voices. After psychoeducation about voice hearing, Temstem offers two functions: Silencing is a mode designed to inhibit voice activity through the processing of incompatible language; the Challenging mode introduces dual tasking (as used in eye movement desensitisation and reprocessing) designed to reduce the emotionality and vividness of a voice memory. Two different language games, Lingo Tapper and Word Link, are provided, containing both functions. This study aimed to explore the momentary effects of Temstem on voice-hearing distress, emotionality and vividness in a naturalistic sample of voice-hearing app users. Method: Temstem is freely available in the Netherlands. We collected data through the app from 1048 individual users who had given informed consent for the study. We assessed changes in pre- and post-session scores on distress, emotionality and vividness, and we evaluated differences in outcomes between the games and whether effects remained stable over multiple sessions. Results: Users had been hearing voices for an average of 4.95 years; 79 % had been informed about Temstem by a mental health therapist or coach. After a Silencing session, voice-hearing distress was reduced, t(958) = 27.12, p < .001, d = 0.49; the degree of reduction remained stable after repeated use, F(1, 7905.57) = 1.91, p = .167. After a Challenging session, emotionality, t(651) = 23.16, p < .001, d = 0.74, and the vividness of voice memories were reduced, t(651) = 22.20, p < .001, d = 0.71; both diminished slightly with frequent use, F(1, 2222.86) = 7.21, p < .05; F(1, 2289.92) = 4.25, p < .05. In comparison with Lingo Tapper, larger reductions were seen for a Word Link game: emotionality t(226) = 2.88, p < .005, d = 0.21; vividness t(226) = 2.29, p < .05, d = 0.17. Discussion: In this heterogeneous sample of voice-hearing individuals, Temstem appeared to be a promising coping tool; momentary voice-hearing distress and the emotionality and vividness of voice statements were reduced after a Temstem session. Despite important limitations and the need for more research, naturalistic studies of user app data may yield interesting and generalisable findings.