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      Convergent imaging-transcriptomic evidence for disturbed iron homeostasis in Gilles de la Tourette syndrome

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          Abstract

          Gilles de la Tourette syndrome (GTS) is a neuropsychiatric movement disorder with reported abnormalities in various neurotransmitter systems. Considering the integral role of iron in neurotransmitter synthesis and transport, it is hypothesized that iron exhibits a role in GTS pathophysiology. As a surrogate measure of brain iron, quantitative susceptibility mapping (QSM) was performed in 28 patients with GTS and 26 matched controls. Significant susceptibility reductions in the patient cohort, consistent with reduced local iron content, were obtained in subcortical regions known to be implicated in GTS. Regression analysis revealed a significant negative association of tic scores and striatal susceptibility. To interrogate genetic mechanisms that may drive these reductions, spatially specific relationships between susceptibility and gene-expression patterns extracted from the Allen Human Brain Atlas were assessed. Correlations in the striatum were enriched for excitatory, inhibitory, and modulatory neurochemical signaling mechanisms in the motor regions, mitochondrial processes driving ATP production and iron-sulfur cluster biogenesis in the executive subdivision, and phosphorylation-related mechanisms that affect receptor expression and long-term potentiation. This link between susceptibility reductions and normative transcriptional profiles suggests that disruptions in iron regulatory mechanisms are involved in GTS pathophysiology and may lead to pervasive abnormalities in mechanisms regulated by iron-containing enzymes.

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          STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

          Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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            Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

            Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.
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              A new depression scale designed to be sensitive to change

              The construction of a depression rating scale designed to be particularly sensitive to treatment effects is described. Ratings of 54 English and 52 Swedish patients on a 65 item comprehensive psychopathology scale were used to identify the 17 most commonly occurring symptoms in primary depressive illness in the combined sample. Ratings on these 17 items for 64 patients participating in studies of four different antidepressant drugs were used to create a depression scale consisting of the 10 items which showed the largest changes with treatment and the highest correlation to overall change. The inner-rater reliability of the new depression scale was high. Scores on the scale correlated significantly with scores on a standard rating scale for depression, the Hamilton Rating Scale (HRS), indicating its validity as a general severity estimate. Its capacity to differentiate between responders and non-responders to antidepressant treatment was better than the HRS, indicating greater sensitivity to change. The practical and ethical implications in terms of smaller sample sizes in clinical trials are discussed.
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                Author and article information

                Journal
                medRxiv
                MEDRXIV
                medRxiv
                Cold Spring Harbor Laboratory
                16 May 2023
                : 2023.05.15.23289978
                Affiliations
                [1 ]Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
                [2 ]Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
                [3 ]Center for Human Genetics Research, Massachusetts General Hospital, Boston, MA, USA
                [4 ]Harvard Medical School, Boston, MA, USA
                [5 ]Siemens Healthcare GmbH, Diagnostic Imaging, Magnetic Resonance, Research and Development, Erlangen, Germany
                [6 ]Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
                [7 ]Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
                [8 ]Department of Psychiatry, Center for OCD, Anxiety, and Related Disorders, College of Medicine, University of Florida, Gainesville, FL, USA
                Author notes
                [*]

                These authors contributed equally to this work

                []Corresponding authors: Harald E. Möller, PhD, NMR Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, 04103 Leipzig, Germany; moeller@ 123456cbs.mpg.de ; Ahmad Seif Kanaan, NMR Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, 04103 Leipzig, Germany; amadeus.kanaan@ 123456gmail.com
                Article
                10.1101/2023.05.15.23289978
                10246056
                37292704
                490da5c2-0833-4e8f-9c13-46b93224fe03

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

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                Article

                gene expression,iron,magnetic susceptibility,mri,subcortical brain,tourette syndrome

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