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Abstract Background Identifying symptom clusters in Long COVID is necessary for developing effective therapies for this diverse condition and improving the quality of life of those affected by this heterogeneous condition. In this study, we aimed to identify and compare symptom clusters at 9 and 12 months after a SARS-CoV-2 positive test and describe each cluster regarding factors at infection. Methods This is a cross-sectional study with individuals randomly selected from the Portuguese National System of Epidemiological Surveillance (SINAVE) database. Individuals who had a positive SARS-CoV-2 test in August 2022 were contacted to participate in a telephonic interview approximately 9 and 12 months after the test. A hierarchical clustering analysis was performed, using Euclidean distance and Ward’s linkage. Clustering was performed in the 35 symptoms reported 9 and 12 months after the SARS-CoV-2 positive test and characterised considering age, sex, pre-existing health conditions and symptoms at time of SARS-CoV-2 infection. Results 552 individuals were included at 9 months and 458 at 12 months. The median age was 52 years (IQR: 40–64 years) and 59% were female. Hypertension and high cholesterol were the most frequently reported pre-existing health conditions. Memory loss, fatigue or weakness and joint pain were the most frequent symptoms reported 9 and 12 months after the positive test. Four clusters were identified at both times: no or minor symptoms; multi-symptoms; joint pain; and neurocognitive-related symptoms. Clusters remained similar in both times, but, within the neurocognitive cluster, memory loss and concentration issues increased in frequency at 12 months. Multi-symptoms cluster had older people, more females and more pre-existing health conditions at 9 months. However, at 12 months, older people and those with more pre-existing health conditions were in joint pain cluster. Conclusions Our results suggest that Long COVID is not the same for everyone. In our study, clusters remained similar at 9 and 12 months, except for a slight variation in the frequency of symptoms that composed each cluster. Understanding Long COVID clusters might help identify treatments for this condition. However, further validation of the observed clusters and analysis of its risk factors is needed.

The recurring outbreaks caused by emerging RNA viruses have fostered an increased interest in the research of the mechanisms that regulate viral life cycles and the pathological outcomes associated with infections. Although interactions at the protein level are well-studied, interactions mediated by RNA molecules are less explored. RNA viruses can encode small non-coding RNAs molecules (sncRNAs), including viral miRNAs (v-miRNAs), that play important roles in modulating host immune responses and viral replication by targeting viral or host transcripts. Starting from the analysis of public databases compiling the known repertoire of viral ncRNA molecules and the evolution of publications and research interests on this topic in the wake of the COVID-19 pandemic, we provide an updated view on the current knowledge on viral sncRNAs, with a focus on v-miRNAs encoded by RNA viruses, and their mechanisms of action. We also discuss the potential of these molecules as diagnostic and prognostic biomarkers for viral infections and the development of antiviral therapies targeting v-miRNAs. This review emphasizes the importance of continued research efforts to characterize sncRNAs encoded by RNA viruses, identifies the most relevant pitfalls in the study of these molecules, and highlights the paradigm changes that have occurred in the last few years regarding their biogenesis, prevalence and functional relevance in the context of host-pathogen interactions.