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. 2024 Sep;154(3):807-818.
doi: 10.1016/j.jaci.2024.04.032. Epub 2024 Jun 1.

Whole blood transcriptome in long-COVID patients reveals association with lung function and immune response

Jelle M Blankestijn  1 , Nadia Baalbaki  2 , Somayeh Bazdar  2 , Inés Beekers  3 , Rosanne J H C G Beijers  4 , Joop P van den Bergh  5 , Lizan D Bloemsma  2 , Merel E B Cornelissen  2 , Tamara Dekker  6 , Jan Willem Duitman  7 , Laura Houweling  8 , John J L Jacobs  3 , Ivo van der Lee  9 , Paulien M A Linders  10 , Lieke C E Noij  2 , Esther J Nossent  10 , Marianne A van de Pol  10 , Brigitte M Sondermeijer  9 , J J Miranda Geelhoed  11 , Els J M Weersink  10 , Korneliusz Golebski  12 , Mahmoud I Abdel-Aziz  13 , Anke H Maitland-van der Zee  14 ; P4O2 Consortium
Affiliations
Free article

Whole blood transcriptome in long-COVID patients reveals association with lung function and immune response

Jelle M Blankestijn et al. J Allergy Clin Immunol. 2024 Sep.
Free article

Abstract

Background: Months after infection with severe acute respiratory syndrome coronavirus 2, at least 10% of patients still experience complaints. Long-COVID (coronavirus disease 2019) is a heterogeneous disease, and clustering efforts revealed multiple phenotypes on a clinical level. However, the molecular pathways underlying long-COVID phenotypes are still poorly understood.

Objectives: We sought to cluster patients according to their blood transcriptomes and uncover the pathways underlying their disease.

Methods: Blood was collected from 77 patients with long-COVID from the Precision Medicine for more Oxygen (P4O2) COVID-19 study. Unsupervised hierarchical clustering was performed on the whole blood transcriptome. These clusters were analyzed for differences in clinical features, pulmonary function tests, and gene ontology term enrichment.

Results: Clustering revealed 2 distinct clusters on a transcriptome level. Compared with cluster 2 (n = 65), patients in cluster 1 (n = 12) showed a higher rate of preexisting cardiovascular disease (58% vs 22%), higher prevalence of gastrointestinal symptoms (58% vs 29%), shorter hospital duration during severe acute respiratory syndrome coronavirus 2 infection (median, 3 vs 8 days), lower FEV1/forced vital capacity (72% vs 81%), and lower diffusion capacity of the lung for carbon monoxide (68% vs 85% predicted). Gene ontology term enrichment analysis revealed upregulation of genes involved in the antiviral innate immune response in cluster 1, whereas genes involved with the adaptive immune response were upregulated in cluster 2.

Conclusions: This study provides a start in uncovering the pathophysiological mechanisms underlying long-COVID. Further research is required to unravel why the immune response is different in these clusters, and to identify potential therapeutic targets to create an optimized treatment or monitoring strategy for the individual long-COVID patient.

Keywords: DLCO; Long-COVID; lung function; phenotyping; transcriptome.

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Conflict of interest statement

Disclosure statement Disclosure of potential conflict of interest: K. Golebski received funds paid to the institution from the ZonMW grant long COVID; received funds from GlaxoSmithKline (GSK), ALK, and STIMAG; and received consulting fees from GSK. J. W. Duitman has received research funding from Boehringer Ingelheim and Abbvie. M. I. Abdel-Aziz was funded by a full PhD scholarship from the Ministry of Higher Education of the Arab Republic of Egypt during the conduct of the study and received a grant from Stichting Astma Bestrijding. A. H. Maitland-van der Zee received money paid to the institution from the ERANET Systems Medicine and ZonMW grant, another ZonMW grant for COVID-19 research, the Stichting TAAI research grant, the EUROSTARS research grant COPDetect, an unrestricted research grant from Boehringer Ingelheim and GSK, an unrestricted research grant from the Vertex Innovation Award, and the Innovative Health Initiative 3TR research grant; is the (unpaid) chair of the DSMB SOS BPD study; and was the president of the federation of innovative drug research in the Netherlands (FIGON). The rest of the authors declare that they have no relevant conflicts of interest. Data availability: The data are available in the GEO omnibus under accession GSE267625. Also accessible with the link https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE267625.

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