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.

Abstract

BACKGROUND In the Netherlands, the prevalence of post COVID-19 condition is estimated at 12.7% at 90-150 days after SARS-CoV-2 infection. This study aimed to determine the occurrence of fatigue and other symptoms, to assess how many patients meet the Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) criteria, to identify symptom-based clusters within the P4O2 COVID-19 cohort and to compare these clusters with clusters in a ME/CFS cohort. METHODS In this multicentre, prospective, observational cohort in the Netherlands, 95 post COVID-19 patients aged 40-65 years were included. Data collection at 3-6 months after infection included demographics, medical history, questionnaires, and a medical examination. Follow-up assessments occurred 9-12 months later, where the same data were collected. Fatigue was determined with the Fatigue Severity Scale (FSS), a score of ≥ 4 means moderate to high fatigue. The frequency and severity of other symptoms and the percentage of patients that meet the ME/CFS criteria were assessed using the DePaul Symptom Questionnaire-2 (DSQ-2). A self-organizing map was used to visualize the clustering of patients based on severity and frequency of 79 symptoms. In a previous study, 337 Dutch ME/CFS patients were clustered based on their symptom scores. The symptom scores of post COVID-19 patients were applied to these clusters to examine whether the same or different clusters were found. RESULTS According to the FSS, fatigue was reported by 75.9% of the patients at 3-6 months after infection and by 57.1% of the patients 9-12 months later. Post-exertional malaise, sleep disturbances, pain, and neurocognitive symptoms were also frequently reported, according to the DSQ-2. Over half of the patients (52.7%) met the Fukuda criteria for ME/CFS, while fewer patients met other ME/CFS definitions. Clustering revealed specific symptom patterns and showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort, where 2 clusters had > 10 patients. CONCLUSIONS This study shows persistent fatigue and diverse symptomatology in post COVID-19 patients, up to 12-18 months after SARS-CoV-2 infection. Clustering showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort.