JCI InsightGenetic & Genomic MedicinePeer-reviewed journal article
Intraoperative glucocorticoids confound surgical biopsy transcriptomics
Frederik T. LarseniD, Charlotte Wilhelmina WernbergiD, Jyotsna NambiariD, Subhajit DuttaiD, Elise Jonasson NielseniD, Lea Ladegaard GrønkjæriD, Birgitte Gade JacobseniD, Susanne MandrupiD, Anne LoftiD, Soeren Fisker Schmidt, Mette Munk LauridseniD, Kim RavnskjæriD, Lars GrøntvediD
Abstract
Human tissue transcriptomic studies frequently rely on biopsies obtained during surgery under general anesthesia, yet the impact of perioperative medications on gene expression has not been systematically evaluated. Using paired liver biopsies from patients with obesity at risk for metabolic dysfunction-associated steatohepatitis (MASH), we compared RNA sequencing profiles from biopsies collected under local anesthesia months before surgery with matched intraoperative biopsies obtained under general anesthesia. Intraoperative samples exhibited striking transcriptional changes enriched for canonical glucocorticoid receptor target genes, implicating perioperative dexamethasone administration as the principal driver. In a matched cohort in which dexamethasone was administered immediately after biopsy collection, we directly demonstrate that dexamethasone profoundly alters hepatic gene expression during surgery. These findings were independently validated and shown to substantially distort associations between liver fibrosis stage and inflammatory gene expression, obscuring biologically relevant immune signatures. Similar glucocorticoid-responsive transcriptional changes were observed in adipose tissue, indicating a systemic effect. Our findings identify perioperative dexamethasone exposure as a previously unrecognized but readily modifiable confounder in human tissue transcriptomics. As biopsy-based bulk and single-cell transcriptomic studies continue to expand, careful documentation and consideration of perioperative medication exposure will be essential to improve the reproducibility, interpretability, and biological validity of human gene expression studies.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- top 32%
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