{"database":"biostudies-arrayexpress","file_versions":[],"scores":null,"additional":{"submitter":["Mario Deng"],"organism":["Homo sapiens"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15840"],"description":["Biological Relevance and Intent of the Experiment Statin-associated muscle symptoms (SAMS) are among the most common adverse effects limiting the use of statin therapy, yet their underlying biological mechanisms remain poorly defined. While metabolic and structural causes have been proposed, increasing attention is being given to the possibility of immune system involvement in SAMS pathogenesis. Understanding whether and how immunological pathways contribute to SAMS is essential for improving diagnostic, preventive, and therapeutic strategies.  The present study explores the immunological component of SAMS using a longitudinal, case-based transcriptomic approach. By examining gene expression in peripheral blood mononuclear cells (PBMCs) during controlled exercise challenges before, during, and after the development of SAMS, the study investigates how the immune response to physical stress is altered in the presence of statin-induced myopathy.  The intent of this experiment is to:  Identify immune-related gene expression changes associated with SAMS,  Determine how these changes evolve across disease onset and recovery,  Uncover potential biomarkers or immune pathways involved in the development and resolution of SAMS,  Provide mechanistic insight into the role of the immune system in exercise-induced symptoms exacerbated by statin use.  Experimental Workflow Participant Recruitment and Baseline Testing  At baseline (Visit 1, prior to statin therapy), the participant underwent a standardized cardiopulmonary exercise test (CPX).  Blood samples were collected at three timepoints around exercise:  TP1: Pre-exercise  TP2: Peak exercise  TP3: One hour post-exercise  Statin Therapy and Symptom Development  After Visit 1, while the participant was on Statin medication,  SAMS developed subsequently, marked by muscle discomfort and weakness.  Follow-Up Testing During Symptom Phases  The participant underwent repeat CPX testing and blood sampling:  Visit 2: During active SAMS (symptomatic phase)  Visit 3: After partial symptom resolution (recovery phase)  For the same three timepoints (TP1–TP3) blood samples were collected at each visit.  RNA Isolation and Sequencing  PBMCs were isolated from all blood samples.  RNA was extracted and subjected to next-generation RNA sequencing to profile transcriptomic changes.  Data Analysis  Differential Gene Expression Analysis was used to identify genes with altered expression between visits and timepoints.  Weighted Gene Co-expression Network Analysis (WGCNA) was applied to detect co-regulated gene modules.  Pathway and Gene Ontology Enrichment Analysis (e.g., GO, Reactome) was performed to interpret the biological functions of key modules and differentially expressed genes.  Key Findings  39 co-expression modules were identified from WGCNA analysis.  Several modules that responded to peak exercise in the healthy state (V1) showed blunted responses during SAMS (V2) and partial restoration during recovery (V3).  16 key genes that may contribute to the immune pathways associated with SAMS were identified."],"repository":["biostudies-arrayexpress"],"sample_protocol":["Sample Collection - The blood was collected from the individual for 3 visits and timepoints, PBMC were isolated according to the manufacture's protocol","Sequencing - The cDNA libraries were quantitated using Qubit and size distribution will be checked on Bioanalyzer 2100 (Agilent Technologies, Palo Alto, CA). The library will be sequenced on HiSeq 3000. Each sample will have >15 million reads","Nucleic Acid Extraction - RNA were isolated from the PBMC using RNeasy Mini Kit (Qiagen, Valencia, CA). The quality of the total RNA assessed using NanoDrop® ND-8000 spectrophotometer (NanoDrop Technologies, Wilmington, DE) and Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA) . All RNA samples should display a concentration above 50 ng/µl, purity - 260/280 ~ 2.0., integrity - RIN > 8.0 and average > 8.5","Library Construction - The library prepared with Illumina TruSeq RNA kit according to the manufacturer’s instructions (Illumina, San Diego, CA). Additionally, the KAPA RNA HyperPrep Kit with RiboErase (HMR) (Roche, Pleasanton, CA) will be used in order to provide improved coverage of precursor mRNAs and noncoding RNA"],"figure_sub":["Organization","MINSEQE Score","Assays and Data","MAGE-TAB Files"],"data_protocol":["Data Transformation - The fastq files were aligned and performed quantification with normalization according to StrandNGS protocol in the StrandNGS tool.","Sequence Alignment - Alignment of the samples were done using the StrandNGS tool with transcriptome and genome together with novel splices."],"omics_type":["Unknown","Transcriptomics","Genomics","Proteomics"],"instrument_platform":["Illumina HiSeq 2500"],"study_type":["RNA-seq of total RNA"],"species":["Homo sapiens"],"pubmed_title":["Exercise-Associated Changes of Leukocyte Gene Expression in Statin-Associated Myopathy – A Case Study"],"pubmed_authors":["Mario Deng","Galyna Bondar, Abhinandan Das Mahapatra, Irina Silacheva, Adrian Hairapetian, Thomas Vu, Stephanie Su, Ananya Katappagari, Liana Galan, Joshua Chandran, Ruben Adamov, Alan Yang, Ananya Bukkapatnam, Pejman Mansouri, Mahi Mirchandani, Nathan Dang, Lorenzo Mancusi, Isabel Lai, Tristan Grogan, Jeffrey Hsu, Monica Cappelletti, David Elashoff, Elaine F Reed, Mario Deng"],"additional_accession":[]},"is_claimable":false,"name":"Exercise-associated changes of leukocyte gene expression in Stratin-associated myopathy - A case study","description":"Biological Relevance and Intent of the Experiment Statin-associated muscle symptoms (SAMS) are among the most common adverse effects limiting the use of statin therapy, yet their underlying biological mechanisms remain poorly defined. While metabolic and structural causes have been proposed, increasing attention is being given to the possibility of immune system involvement in SAMS pathogenesis. Understanding whether and how immunological pathways contribute to SAMS is essential for improving diagnostic, preventive, and therapeutic strategies.  The present study explores the immunological component of SAMS using a longitudinal, case-based transcriptomic approach. By examining gene expression in peripheral blood mononuclear cells (PBMCs) during controlled exercise challenges before, during, and after the development of SAMS, the study investigates how the immune response to physical stress is altered in the presence of statin-induced myopathy.  The intent of this experiment is to:  Identify immune-related gene expression changes associated with SAMS,  Determine how these changes evolve across disease onset and recovery,  Uncover potential biomarkers or immune pathways involved in the development and resolution of SAMS,  Provide mechanistic insight into the role of the immune system in exercise-induced symptoms exacerbated by statin use.  Experimental Workflow Participant Recruitment and Baseline Testing  At baseline (Visit 1, prior to statin therapy), the participant underwent a standardized cardiopulmonary exercise test (CPX).  Blood samples were collected at three timepoints around exercise:  TP1: Pre-exercise  TP2: Peak exercise  TP3: One hour post-exercise  Statin Therapy and Symptom Development  After Visit 1, while the participant was on Statin medication,  SAMS developed subsequently, marked by muscle discomfort and weakness.  Follow-Up Testing During Symptom Phases  The participant underwent repeat CPX testing and blood sampling:  Visit 2: During active SAMS (symptomatic phase)  Visit 3: After partial symptom resolution (recovery phase)  For the same three timepoints (TP1–TP3) blood samples were collected at each visit.  RNA Isolation and Sequencing  PBMCs were isolated from all blood samples.  RNA was extracted and subjected to next-generation RNA sequencing to profile transcriptomic changes.  Data Analysis  Differential Gene Expression Analysis was used to identify genes with altered expression between visits and timepoints.  Weighted Gene Co-expression Network Analysis (WGCNA) was applied to detect co-regulated gene modules.  Pathway and Gene Ontology Enrichment Analysis (e.g., GO, Reactome) was performed to interpret the biological functions of key modules and differentially expressed genes.  Key Findings  39 co-expression modules were identified from WGCNA analysis.  Several modules that responded to peak exercise in the healthy state (V1) showed blunted responses during SAMS (V2) and partial restoration during recovery (V3).  16 key genes that may contribute to the immune pathways associated with SAMS were identified.","dates":{"release":"2025-11-13T00:00:00Z","modification":"2025-11-13T19:29:58.606Z","creation":"2025-10-23T17:00:06.634Z"},"accession":"E-MTAB-15840","cross_references":{"ENA":["ERP182842"],"EFO":["EFO_0002944","EFO_0004170","EFO_0009653","EFO_0004917","EFO_0005518","EFO_0003816","EFO_0004184"],"doi":["doi: 10.3389/fphar.2025.1695543"]}}