<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Singh K</submitter><funding>British Heart Foundation</funding><funding>Wellcome Trust</funding><pagination>640837</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC7973371</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>12</volume><pubmed_abstract>Inflammatory cardiomyopathy covers a group of diseases characterized by inflammation and dysfunction of the heart muscle. The immunosuppressive agents such as prednisolone, azathioprine and cyclosporine are modestly effective treatments, but a molecular rationale underpinning such therapy or the development of new therapeutic strategies is lacking. We aimed to develop a network-based approach to identify therapeutic targets for inflammatory cardiomyopathy from the evolving myocardial transcriptome in a mouse model of the disease. We performed bulk RNA sequencing of hearts at early, mid and late time points from mice with experimental autoimmune myocarditis. We identified a cascade of pathway-level events involving early activation of cytokine and chemokine-signaling pathways that precede l</pubmed_abstract><journal>Frontiers in immunology</journal><pubmed_title>Transcriptomic Analysis of Inflammatory Cardiomyopathy Identifies Molecular Signatures of Disease and Informs &amp;lt;i&amp;gt;in silico&amp;lt;/i&amp;gt; Prediction of a Network-Based Rationale for Therapy.</pubmed_title><pmcid>PMC7973371</pmcid><funding_grant_id>RG/18/1/33351</funding_grant_id><funding_grant_id>203141/Z/16/Z</funding_grant_id><funding_grant_id>204969/Z/16/Z</funding_grant_id><funding_grant_id>CH/09/003/26631</funding_grant_id><funding_grant_id>PG/16/100/32632</funding_grant_id><funding_grant_id>RE/13/1/30181</funding_grant_id><funding_grant_id>090532/Z/09/Z</funding_grant_id><pubmed_authors>Fang H</pubmed_authors><pubmed_authors>Wright B</pubmed_authors><pubmed_authors>Lockstone H</pubmed_authors><pubmed_authors>Williams RO</pubmed_authors><pubmed_authors>Knight JC</pubmed_authors><pubmed_authors>Singh K</pubmed_authors><pubmed_authors>Bhattacharya S</pubmed_authors><pubmed_authors>Cihakova D</pubmed_authors><pubmed_authors>Davies G</pubmed_authors></additional><is_claimable>false</is_claimable><name>Transcriptomic Analysis of Inflammatory Cardiomyopathy Identifies Molecular Signatures of Disease and Informs &amp;lt;i&amp;gt;in silico&amp;lt;/i&amp;gt; Prediction of a Network-Based Rationale for Therapy.</name><description>Inflammatory cardiomyopathy covers a group of diseases characterized by inflammation and dysfunction of the heart muscle. The immunosuppressive agents such as prednisolone, azathioprine and cyclosporine are modestly effective treatments, but a molecular rationale underpinning such therapy or the development of new therapeutic strategies is lacking. We aimed to develop a network-based approach to identify therapeutic targets for inflammatory cardiomyopathy from the evolving myocardial transcriptome in a mouse model of the disease. We performed bulk RNA sequencing of hearts at early, mid and late time points from mice with experimental autoimmune myocarditis. We identified a cascade of pathway-level events involving early activation of cytokine and chemokine-signaling pathways that precede l</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021</publication><modification>2026-05-01T17:34:55.242Z</modification><creation>2024-11-21T10:23:53.377Z</creation></dates><accession>S-EPMC7973371</accession><cross_references><pubmed>33746983</pubmed><doi>10.3389/fimmu.2021.640837</doi></cross_references></HashMap>