Longitudinal blood transcriptome clustering of post-COVID patients – results from the P4O2 study

Résumé fourni par la source

Introduction Years after the COVID-19 pandemic, post-COVID syndrome still places a large burden on patients lives. However, an effective treatment has yet to be found and the longitudinal molecular patterns underlying this syndrome are still poorly understood. Here we aimed to uncover mechanisms related to recovery of post-COVID syndrome through longitudinal clustering of the blood transcriptome. Methods The blood transcriptome of 54 patients with post-COVID from the P4O2 study was analyzed at 3-6 months and 12-15 months after infection, and compared with the blood transcriptome of 134 healthy controls. Unsupervised clustering of the changes in the transcriptome was used to discover different longitudinal patterns. These clusters were compared for clinical characteristics and functional gene expression. Results Clustering revealed two longitudinal transcriptome clusters with similar age, sex and BMI distributions. Cluster 1 (n=20) showed a significantly lower lung function compared to Cluster 2 (n=34) at baseline, while also showing slightly more improvement in terms of questionnaire scores for post-COVID severity over the study period. Functionally, the clusters differed in pathways related to immunoglobulin response, glucose metabolism and hemoglobin binding. Dysregulated genes at 3-6 months from these pathways in Cluster 1 returned to similar expression patterns compared to healthy controls at 12-15 months. Conclusion Two longitudinal patterns can be distinguished for the post-COVID blood transcriptome with different rates and mechanisms of recovery. This study shed some light into the processes underlying recovery of post-COVID and could aid in identification of therapeutic targets.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.