Identifying severe COVID-19 risk variants modulating enhancer reporter activity in lung cells
Giovanna Weykopf, Wendy A. Bickmore, Simon C. Biddie, Elias T. Friman
Abstract
Common genetic variants contribute to risk for complex human diseases. However, despite thousands of associations, variants modulating disease risk and their functional impact remain largely unknown. This includes SARS-CoV-2 infection, where outcomes range from asymptomatic to fatal. Most genetic risk variants associated with COVID-19 disease, identified through genome wide association studies, are located in the non-coding genome and may function by altering gene expression in disease-relevant cells and tissues.
Introduction
The heterogeneity in disease outcomes following infection by SARS-CoV-2 virus is influenced by pre-existing health conditions, age, and host genetic risk factors [1]. Genome-wide association studies (GWAS) for severe COVID-19 outcomes (involving intensive care admission), have implicated genes involved in viral host entry, lung inflammation, airway mucus defence, and type I interferon response in COVID-19 susceptibility and severity, with severity being highly heritable [2–5].
Methods
Variant selection and library design
Fine-mapped severe COVID-19 risk variants encompassing causal variants to 95% statistical probability (95% credible set) from the first and second GenOMICC release [2] and a more comprehensive 99% credible set of variants from the third GenOMICC release [3] were included in the STARR-seq library. The fine-mapped 95% credible sets for the first and second release, as well as the GWAS summary statistics and fine-mapping results for the third GenOMICC release [3], were kindly shared by the authors.
Results
COVID-19 variant library design
In the lung, SARS-CoV-2 mainly infects type II alveolar epithelial cells, leading to cell death, barrier disruption, and fibrosis in some individuals [23]. Cell death and the innate immune response of type II alveolar epithelial cells, which also function as progenitors for type I epithelial cells, are the main driver of alveolar damage and acute respiratory distress syndrome in coronavirus infection [24,25].
Discussion
Using STARR-seq to identify functional single and combinatorial variants
In this study, we identify a set of severe COVID-19 associated risk variants which individually, and in some cases in combination, modulate regulatory activity in lung epithelial cells using a massively parallel episomal reporter assay – STARR-seq. Of 4,894 variants tested, only 29 modulated enhancer activity.
Acknowledgments
We thank Erola Pairo-Castineira, Konrad Rawlik, J. Kenneth Baillie for sharing GWAS fine-mapping results and discussion on variant selection for the purpose of library design. We also thank Veronique Vitart for discussion on variant selection and Luciana Gómez-Acuña for advice on experimental techniques.
Citation: Weykopf G, Bickmore WA, Biddie SC, Friman ET (2026) Identifying severe COVID-19 risk variants modulating enhancer reporter activity in lung cells. PLoS Genet 22(7): e1012222. https://doi.org/10.1371/journal.pgen.1012222
Editor: Anne Goriely, University of Oxford, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
Received: May 29, 2026; Accepted: June 20, 2026; Published: July 17, 2026
Copyright: © 2026 Weykopf et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Raw STARR-seq data and processed files generated from this study have been deposited in the Genome expression Omnibus (GEO) repository under the accession number GSE320469. Publicly available A549 datasets were downloaded from ENCODE (https://www.encodeproject.org), including ATAC-seq (ENCFF648AEN), DNase-seq (ENCFF128ZVL), H3K4me1 (ENCFF594YDK), H3K4me3 (ENCFF404REU) and H3K27ac (ENCFF747IZX). The Malinois A549 model was downloaded from https://zenodo.org/records/10698014. Code availability: The SNP2fasta package generated to obtain fasta files for single and combinatorial variant oligonucleotide libraries is available on GitHub: https://github.com/efriman/snp2fasta.
Funding: UKRI | Medical Research Council (MRC): (GW, WAB, ETF) MC_UU_00035/7; Academy of Medical Sciences (The Academy of Medical Sciences):(SCB) SGL028\1022; Chief Scientist Office (CSO): (SCB) PCL/20//02.The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
