Whole blood transcriptome in long-COVID patients reveals association with lung function and immune response - 27/06/24

Doi : 10.1016/j.jaci.2024.04.032

Jelle M. Blankestijn, MSc ^a,^b,^c,^⁎ , Nadia Baalbaki, MSc ^a,^b,^c, Somayeh Bazdar, MD ^a,^b,^c, Inés Beekers, PhD ^d, Rosanne J.H.C.G. Beijers, PhD ^e, Joop P. van den Bergh, MD, PhD ^f,^g, Lizan D. Bloemsma, PhD ^a,^b,^c, Merel E.B. Cornelissen, MSc ^a,^b,^c, Tamara Dekker, BSc ^h, Jan Willem Duitman, PhD ^a,^h, Laura Houweling, MSc ^a,ⁱ, John J.L. Jacobs, PhD ^d, Ivo van der Lee, MD, PhD ^j, Paulien M.A. Linders, MSc ^a, Lieke C.E. Noij, MSc ^a,^b,^c, Esther J. Nossent, MD ^a, Marianne A. van de Pol, PhD ^a, Brigitte M. Sondermeijer, MD, PhD ^j, J.J. Miranda Geelhoed, MD, PhD ^k, Els J.M. Weersink, MD, PhD ^a, Korneliusz Golebski, PhD ^a,^b, Mahmoud I. Abdel-Aziz, PhD ^a,^b,^c,^l,^{^{∗
These authors contributed equally to this work.}}, Anke H. Maitland-van der Zee, PharmD, PhD ^a,^b,^c,^m,^{^{∗
These authors contributed equally to this work.}}
on behalf of the
P4O2 Consortium
^a Department of Pulmonary Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
^b Amsterdam Institute for Infection and Immunity, Amsterdam, The Netherlands
^c Amsterdam Public Health, Amsterdam, The Netherlands
^d Department of Health, Ortec B.V., Zoetermeer, The Netherlands
^e Department of Respiratory Medicine, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, The Netherlands
^f School of Nutrition and Translational Research in Metabolism, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
^g Department of Internal Medicine, VieCuri Medical Center, Venlo, The Netherlands
^h Experimental Immunology (EXIM), Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
ⁱ Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands
^j Department of Pulmonology, Spaarne Hospital, Hoofddorp, The Netherlands
^k Department of Respiratory Medicine, Leiden University Medical Center (LUMC), Leiden, The Netherlands
^l Department of Clinical Pharmacy, Faculty of Pharmacy, Assiut University, Assiut, Egypt
^m Department of Pediatric Respiratory Medicine, Emma Children’s Hospital, Amsterdam UMC, Amsterdam, The Netherlands

^∗Corresponding author: Jelle M. Blankestijn, MSc, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.Meibergdreef 9Amsterdam1105 AZThe Netherlands

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Graphical abstract

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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.

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Key words : Long-COVID, phenotyping, lung function, DLCO, transcriptome

Abbreviations used : BMI, COPD, COVID-19, CT, DLCO, FEV₁/FVC, FVC, GO, P4O2, SARS-CoV-2