Inflammation and Postoperative Atrial Fibrillation in Cardiac Surgery
NCT ID: NCT06475547
Last Updated: 2025-08-15
Study Results
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Basic Information
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RECRUITING
100 participants
OBSERVATIONAL
2022-01-01
2027-01-01
Brief Summary
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Detailed Description
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Inflammation and Epicardial Fat Inflammation plays a significant role in the development of POAF. Surgical trauma and cardiopulmonary bypass trigger a systemic inflammatory response, releasing cytokines and other inflammatory mediators. Epicardial fat, the visceral fat depot around the heart, is an active endocrine organ secreting pro-inflammatory cytokines and adipokines. Increased epicardial fat thickness is associated with higher levels of inflammation and has been implicated in the pathogenesis of atrial fibrillation.
RNA isolation and sequencing RNA sequencing (RNA-seq) can be used to investigate gene expression in epicardial fat in several impactful ways. RNA-seq can profile gene expression to identify active genes in epicardial fat and their expression levels, revealing key genes involved in inflammation and metabolism. By comparing gene expression between groups, such as patients with and without POAF, RNA-seq can identify differentially expressed genes associated with atrial fibrillation.
RNA-seq analyses The RNA sequencing data files were aligned to the hg38 reference genome using the Spliced Transcripts Alignment to a Reference (STAR) aligner and read counts in genes were quantified. The resulting data matrix with unnormalized counts was loaded into RStudio together with patient metadata information (e.g., age, gender, BMI, smoking). Differential expression analyses were conducted with DESeq2 using adjustment for different variables, including type of tissue, age of patients, gender, and BMI.
Hypothesis The hypothesis that POAF may be influenced by pre-existing inflammation in epicardial fat, in addition to the inflammation caused by surgical trauma.
Objective:
To compare inflammatory gene expression in epicardial fat between patients who develop POAF and those who do not after elective cardiac surgery.
Study Design:
A prospective cohort study including patients undergoing first-time elective cardiac surgery.
Participants:
Inclusion criteria: Patients undergoing first-time elective cardiac surgery. Exclusion criteria: Patients with previous cardiac surgeries or emergency surgeries.
Groups:
POAF Group: Patients who develop POAF. Non-POAF Group: Patients who do not develop POAF.
Sample Collection:
Epicardial fat samples will be collected during the time of surgery.
RNA Isolation and Sequencing:
Homogenize adipose tissue in TRIzol using ceramic beads (Fastprep 24, MPBio). Purify RNA using EconoSpin columns (Epoch). Prepare RNA libraries with NEBNext Ultra II RNA Library Prep Kit for Illumina. Perform paired-end sequencing on the NovaSeq 6000 platform (Illumina).
Data Analysis:
Align RNA-seq data to the hg38 genome using STAR aligner. Quantify gene counts and perform differential expression analysis using DESeq2. Adjust for variables such as tissue type, age, gender, and BMI.
Outcome Measures:
Compare inflammatory gene expression profiles between POAF and Non-POAF groups at the time of surgery.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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POAF
Patients who develop postoperative atrial fibrillation.
Descriptive
This study is observational and does not involve any clinical intervention. The primary procedure involves the collection of epicardial fat tissue samples. The collected samples are then processed and analyzed to compare inflammatory gene expression between the two groups. The analysis includes RNA sequencing to identify differentially expressed genes associated with atrial fibrillation and inflammation.
Non-POAF
Patients who do not develop postoperative atrial fibrillation.
No interventions assigned to this group
Interventions
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Descriptive
This study is observational and does not involve any clinical intervention. The primary procedure involves the collection of epicardial fat tissue samples. The collected samples are then processed and analyzed to compare inflammatory gene expression between the two groups. The analysis includes RNA sequencing to identify differentially expressed genes associated with atrial fibrillation and inflammation.
Eligibility Criteria
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Inclusion Criteria
* Informed consent
Exclusion Criteria
* General poor health condition at the time of inclusion
* Reoperation
18 Years
99 Years
ALL
No
Sponsors
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Odense University Hospital
OTHER
Responsible Party
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Principal Investigators
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Lytfi Krasniqi, MD
Role: PRINCIPAL_INVESTIGATOR
Odense University Hospital
Locations
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Odense University Hospital, Cardiac Surgery Department
Odense, , Denmark
Countries
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Central Contacts
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Facility Contacts
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References
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Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013 Jan 1;29(1):15-21. doi: 10.1093/bioinformatics/bts635. Epub 2012 Oct 25.
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. doi: 10.1186/s13059-014-0550-8.
Wong CX, Ganesan AN, Selvanayagam JB. Epicardial fat and atrial fibrillation: current evidence, potential mechanisms, clinical implications, and future directions. Eur Heart J. 2017 May 1;38(17):1294-1302. doi: 10.1093/eurheartj/ehw045.
Other Identifiers
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POAF130624
Identifier Type: -
Identifier Source: org_study_id
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