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Kahn, R. S.

Publications and source records attributed to Kahn, R. S..

3 recordsLinked to original sources

Overlapping but asymmetrical relationships between schizophrenia and autism revealed by brain connectivity

(Abstract included 248 words)Although the relationship between schizophrenia spectrum disorder (SSD) and autism spectrum disorder (ASD) has long been debated, it has not yet been fully elucidated. To address this issue, we took advantage of dual (ASD and SSD) classifiers that discriminate patients from their controls based on resting state brain functional connectivity. An SSD classifier using sophisticated machine-learning algorithms that automatically selected SSD- specific functional connections was applied to Japanese datasets including adult patients with SSD in a chronic stage. We demonstrated good performance of the SSD classification for independent validation cohorts. The generalizability was tested by USA and European cohorts in a chronic stage, and one USA cohort including first episode schizophrenia. The specificity was tested by two adult Japanese cohorts of ASD and major depressive disorder, and one European cohort of attention-deficit hyperactivity disorder. The weighted linear summation of the classifiers functional connections constituted the biological dimensions representing neural liability to the disorders. Our previously developed robust ASD classifier constituted the ASD dimension. Distributions of individuals with SSD, ASD and healthy controls were examined on the SSD and ASD biological dimensions. The SSD and ASD populations exhibited overlapping but asymmetrical patterns on the two biological dimensions. That is, the SSD population showed increased liability on the ASD dimension, but not vice versa. Furthermore, the two dimensions were correlated within the ASD population but not the SSD population. Using the two biological dimensions based on resting-state functional connectivity enabled us to quantify and visualize the relationships between SSD and ASD.

neuroscience

Shared vulnerability for connectome alterations across psychiatric and neurological brain disorders

Macroscale white matter pathways form the infrastructure for large-scale communication in the human brain, a prerequisite for healthy brain function. Conversely, disruptions in the brains connectivity architecture are thought to play an important role in a wide range of psychiatric and neurological brain disorders. Here we show that especially connections important for global communication and network integration are involved in a wide range of brain disorders. We report on a meta-analytic connectome study comprising in total 895 patients and 1,016 controls across twelve neurological and psychiatric disorders. We extracted disorder connectome fingerprints for each of these twelve disorders, which were then combined into a cross-disorder disconnectivity involvement map, representing the involvement of each brain pathway across brain disorders. Our findings show connections central to the brains infrastructure are disproportionally involved across a wide range of disorders. Connections critical for global network communication and integration display high disturbance across disorders, suggesting a general cross-disorder involvement and importance of these pathways in normal function. Taken together, our cross-disorder study suggests a convergence of disconnectivity across disorders to a partially shared disconnectivity substrate of central connections.

neuroscience

Comprehensive Pathway Analyses Of Schizophrenia Risk Loci Point To Dysfunctional Postsynaptic Signaling

Large-scale genome-wide association studies (GWAS) have implicated many low-penetrance loci in schizophrenia. However, its pathological mechanisms are poorly understood, which in turn hampers the development of novel pharmacological treatments. Pathway and gene set analyses carry the potential to generate hypotheses about disease mechanisms and have provided biological context to genome-wide data of schizophrenia. We aimed to examine which biological processes are likely candidates to underlie schizophrenia by integrating novel and powerful pathway analysis tools using data from the largest Psychiatric Genomics Consortium schizophrenia GWAS (N = 79 845) and the most recent 2018 schizophrenia GWAS (N = 105 318). By applying a primary unbiased analysis (Multi-marker Analysis of GenoMic Annotation; MAGMA) to weigh the role of biological processes from the MSigDB database, we identified enrichment of common variants in synaptic plasticity and neuron differentiation gene sets. We supported these findings using MAGMA, Meta-Analysis Gene-set Enrichment of variaNT Associations (MAGENTA) and Interval Enrichment Analysis (INRICH) on detailed synaptic signaling pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and found enrichment in mainly the dopaminergic and cholinergic synapses. Moreover, shared genes involved in these neurotransmitter systems had a large contribution to the observed enrichment, protein products of top genes in these pathways showed more direct and indirect interactions than expected by chance, and expression profiles of these genes were largely similar among brain tissues. In conclusion, we provide strong and consistent genetics and protein-interaction informed evidence for the role of postsynaptic signaling processes in schizophrenia, opening avenues for future translational and psychopharmacological studies.

genetics