Epigenetic Changes in Long COVID Patients: Unraveling the Gut-Immune Axis and Therapeutic Targets

The study aims to identify the immunological and molecular mechanisms underlying Long COVID, with particular focus on persistent cardiopulmonary manifestations and the role of gut-resident immunity. The project integrates clinical, immunological, transcriptomic, epigenomic, microbiome and computational analyses to identify biomarkers associated with disease phenotypes and potential therapeutic targets. The study is both retrospective and perspective, providing a significant numerosity. The study is non-profit and its execution does not involve interventions outside of the normal clinical pathway established for the patient.

Three complementary objectives will be addressed. Aim 1 will identify immunological and molecular signatures associated with Long COVID. Approximately 800 participants enrolled in the San Raffaele Hospital Long COVID outpatient cohort (OSR COVID-BIOB Clinical study, NCT04318366), together with recovered COVID-19 subjects and pre-pandemic healthy controls, will be analyzed. Clinical data include acute infection characteristics, disease course, cardiopulmonary manifestations and longitudinal follow-up. Peripheral blood samples already collected will undergo transcriptomic, epigenomic and immunological characterization. Bulk RNA sequencing and DNA methylation profiling will identify differentially expressed genes and epigenetic alterations, which will be validated in independent cohorts. Immunophenotyping will assess T-, B- and NK-cell subsets, regulatory T cells, SARS-CoV-2-specific antibodies, interferon responses, complement activation and memory B cells. Standardized sample processing, technical and biological quality controls, correction for batch effects and adjustment for relevant confounders will ensure data reliability.

Aim 2 will investigate gut-resident immune cells and intestinal alterations in Long COVID using left-over intestinal biopsies collected from patients undergoing clinically indicated colonoscopy within the MedMol Biobank. Multi-omic characterization will evaluate transcriptomic and epigenomic profiles of intestinal immune and epithelial cells through bulk and single-cell RNA sequencing, spatial transcriptomics, whole-genome DNA methylation analysis and chromatin accessibility profiling. Mast-cell activation will be assessed using circulating and tissue biomarkers, while intestinal inflammation, permeability and gut microbiome composition will be evaluated through blood, stool and biopsy analyses. Computational cell-cell interaction analyses and complementary in vitro experiments will investigate communication pathways between gut-resident immune cells and systemic immune responses.

Aim 3 will integrate immunological, intestinal and clinical findings using machine-learning approaches to identify molecular signatures associated with Long COVID phenotypes. Multi-omics datasets and clinical variables will be harmonized and analyzed using supervised and unsupervised learning methods to identify patient subgroups, prioritize biomarkers, predict disease evolution and generate models supporting personalized therapeutic strategies. Model performance will be evaluated using independent validation datasets and cross-validation procedures.

Clinical information will be collected from approximately 800 participants, including demographic characteristics, acute COVID-19 presentation, disease progression, cardiopulmonary function, gastrointestinal manifestations and longitudinal follow-up evaluations. Peripheral blood samples will be processed according to standardized operating procedures for isolation of peripheral blood mononuclear cells, plasma and nucleic acids. Intestinal biopsies will be collected exclusively from residual tissue obtained during clinically indicated colonoscopies.