INFEC25NTR02

Duration

2026-2028

Coordinator

Marta Massanella Luna (Main PI) / Gemma Moncunill (ISGlobal PI)

Funded by

CIBERINFEC (Instituto de Salud Carlos III)

Post-COVID-19 condition, also known as persistent COVID or Long COVID (LC), affects more than 10% of people infected with SARS-CoV-2. It is currently estimated that more than 400 million people worldwide live with this condition¹. Its clinical presentation is highly heterogeneous, with more than 200 persistent symptoms that may affect multiple organs and systems. Among the most frequent and disabling manifestations are cognitive dysfunction and dysautonomia, present in over 55% of cases. These alterations have a profound physical, emotional and socioeconomic impact on the lives of patients and their families. According to the SEMG survey (2023), in Spain 46% of patients are on sick leave or work with great difficulty, and only 15.6% are able to perform their work under normal conditions².

Although vaccination against SARS-CoV-2 has reduced the likelihood of developing LC, many new cases continue to be reported. In addition, reinfections may cause LC or worsen existing symptoms. There is currently no specific treatment for this condition, and the symptoms experienced by affected individuals are diverse and overlap with those of other diseases, suggesting the existence of multiple underlying mechanisms. This highlights the urgent need to identify diagnostic and prognostic biomarkers, understand the causes of symptoms and develop effective therapeutic targets for different patient profiles. It is estimated that over the next decade, the number of people with LC could approach that of people with cardiovascular diseases³, making it a serious and unexpected public health problem.

This project aims to identify altered biomarkers and signalling pathways in patients with LC who present dysautonomia and neurocognitive symptoms, with the ultimate goal of identifying therapeutic targets for personalised medicine. Samples will be used from the well-characterised APC-Cog (IrsiCaixa, retrospective) and Long COVID-ISCIII (prospective) cohorts, complemented by the LongCOVICAT (ISGlobal, IDIAPJGol) and COVID-Elx (FISABIO) cohorts as validation cohorts. Multi-omics and single-cell techniques, as well as immunological assays, will be applied. Data will be integrated using machine learning algorithms to generate endophenotypic profiles, identify biomarkers and validate potential therapeutic targets in vitro.

The impact of the study will be threefold:

• Scientific, by providing new insights into the pathological mechanisms of LC.
• Social, by increasing knowledge of this condition and providing new tools for its diagnosis and treatment, contributing to the improvement of clinical guidelines for its management.
• Socioeconomic, by identifying new therapeutic strategies to alleviate the most debilitating persistent symptoms, with a positive impact on the public health system by reducing healthcare pressure and costs associated with sick leave, as well as substantially improving patients’ quality of life.

The project will be carried out within the framework of Open Science, generating bidirectional channels with patient associations. We maintain communication channels through clinical units with the Col·lectiu d’Afectats/es per la COVID-19 Persistent (Catalonia) and the Madrid Association of Persistent COVID (AMACOP, Madrid). Study results will be disseminated through newsletters, seminars and clinical units, and will be published in open access, ensuring public access to information.

Total funding

€100,000

Funded by CIBERINFEC (Instituto de Salud Carlos III)