Evidence map›Paper›PMID 35620521›Full record

ArticleFrontiers in cardiovascular medicine2022

DNA Methylation-Based Prediction of Post-operative Atrial Fibrillation.

Matthew A Fischer, Aman Mahajan, Maximilian Cabaj, Todd H Kimball, Marco Morselli, Elizabeth Soehalim, Douglas J Chapski, Dennis Montoya, Colin P Farrell, Jennifer Scovotti and 7 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 2 institutions in 1 country.

Matthew A FischerDepartment of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
Aman MahajanDepartment of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA, United States.
Maximilian CabajDepartment of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
Todd H KimballDepartment of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
Marco MorselliDepartment of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States.
Elizabeth SoehalimDepartment of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
Douglas J ChapskiDepartment of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
Dennis MontoyaDepartment of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States.
Colin P FarrellDepartment of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States.
Jennifer ScovottiDepartment of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
Claudia T BuenoDepartment of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
Naomi A MimilaDepartment of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
Richard J SheminDivision of Cardiac Surgery, Department of Surgery, University of California, Los Angeles, Los Angeles, CA, United States.
David ElashoffDepartment of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.
Matteo PellegriniDepartment of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States.
Emma MonteDepartment of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
Thomas M VondriskaDepartment of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
University of California, Los Angeles · USUniversity of Pittsburgh · US

Funding

Dynamics of Cardiac Nuclei in Heart DiseaseR01HL105699 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI VONDRISKA, THOMAS M. · 2011 to 2025
$5.0M
NHLBI NIH HHS R01 HL105699
6 · The paper itself

Abstract

Background: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and post-operative atrial fibrillation (POAF) is a major healthcare burden, contributing to an increased risk of stroke, kidney failure, heart attack and death. Genetic studies have identified associations with AF, but no molecular diagnostic exists to predict POAF based on pre-operative measurements. Such a tool would be of great value for perioperative planning to improve patient care and reduce healthcare costs. In this pilot study of epigenetic precision medicine in the perioperative period, we carried out bisulfite sequencing to measure DNA methylation status in blood collected from patients prior to cardiac surgery to identify biosignatures of POAF. Methods: We enrolled 221 patients undergoing cardiac surgery in this prospective observational study. DNA methylation measurements were obtained from blood samples drawn from awake patients prior to surgery. After controlling for clinical and methylation covariates, we analyzed DNA methylation loci in the discovery cohort of 110 patients for association with POAF. We also constructed predictive models for POAF using clinical and DNA methylation data. We subsequently performed targeted analyses of a separate cohort of 101 cardiac surgical patients to measure the methylation status solely of significant methylation loci in the discovery cohort. Results: A total of 47 patients in the discovery cohort (42.7%) and 43 patients in the validation cohort (42.6%) developed POAF. We identified 12 CpGs that were statistically significant in the discovery cohort after correcting for multiple hypothesis testing. Of these sites, 6 were amenable to targeted bisulfite sequencing and chr16:24640902 was statistically significant in the validation cohort. In addition, the methylation POAF prediction model had an AUC of 0.79 in the validation cohort. Conclusions: We have identified DNA methylation biomarkers that can predict future occurrence of POAF associated with cardiac surgery. This research demonstrates the use of precision medicine to develop models combining epigenomic and clinical data to predict disease.

Indexed as

cardiac surgeryDNA methylationepigenomicspost-operative atrial fibrillation (POAF)precision medicine

Identifiers

PMID35620521
PMCPMC9127230
OpenAlexW4229445029

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.