Tag: erythropoiesis

A multi-omics recovery factor predicts long COVID in the IMPACC study

Abstract:

Background. Following SARS-CoV-2 infection, ~10-35% of COVID-19 patients experience long COVID (LC), in which debilitating symptoms persist for at least three months. Elucidating biologic underpinnings of LC could identify therapeutic opportunities.

Methods. We utilized machine learning methods on biologic analytes provided over 12-months after hospital discharge from >500 COVID-19 patients in the IMPACC cohort to identify a multi-omics “recovery factor”, trained on patient-reported physical function survey scores. Immune profiling data included PBMC transcriptomics, serum O-link and plasma proteomics, plasma metabolomics, and blood CyTOF protein levels. Recovery factor scores were tested for association with LC, disease severity, clinical parameters, and immune subset frequencies. Enrichment analyses identified biologic pathways associated with recovery factor scores.

Results. LC participants had lower recovery factor scores compared to recovered participants. Recovery factor scores predicted LC as early as hospital admission, irrespective of acute COVID-19 severity. Biologic characterization revealed increased inflammatory mediators, elevated signatures of heme metabolism, and decreased androgenic steroids as predictive and ongoing biomarkers of LC. Lower recovery factor scores were associated with reduced lymphocyte and increased myeloid cell frequencies. The observed signatures are consistent with persistent inflammation driving anemia and stress erythropoiesis as major biologic underpinnings of LC.

Conclusion. The multi-omics recovery factor identifies patients at risk of LC early after SARS-CoV-2 infection and reveals LC biomarkers and potential treatment targets.

Trial Registration. ClinicalTrials.gov NCT04378777.

Funding. This study was funded by NIH, NIAID and NSF.

Source: Gisela Gabernet, Leying Guan, Lauren I.R. Ehrlich, et al. A multi-omics recovery factor predicts long COVID in the IMPACC study. J Clin Invest. September 9, 2025. https://doi.org/10.1172/JCI193698. https://www.jci.org/articles/view/193698/ (Full study available as PDF file)

Iron dysregulation and inflammatory stress erythropoiesis associates with long-term outcome of COVID-19

Abstract:

Persistent symptoms following SARS-CoV-2 infection are increasingly reported, although the drivers of post-acute sequelae (PASC) of COVID-19 are unclear. Here we assessed 214 individuals infected with SARS-CoV-2, with varying disease severity, for one year from COVID-19 symptom onset to determine the early correlates of PASC.

A multivariate signature detected beyond two weeks of disease, encompassing unresolving inflammation, anemia, low serum iron, altered iron-homeostasis gene expression and emerging stress erythropoiesis; differentiated those who reported PASC months later, irrespective of COVID-19 severity. A whole-blood heme-metabolism signature, enriched in hospitalized patients at month 1-3 post onset, coincided with pronounced iron-deficient reticulocytosis. Lymphopenia and low numbers of dendritic cells persisted in those with PASC, and single-cell analysis reported iron maldistribution, suggesting monocyte iron loading and increased iron demand in proliferating lymphocytes.

Thus, defects in iron homeostasis, dysregulated erythropoiesis and immune dysfunction due to COVID-19 possibly contribute to inefficient oxygen transport, inflammatory disequilibrium and persisting symptomatology, and may be therapeutically tractable.

Source: Hanson AL, Mulè MP, Ruffieux H, Mescia F, Bergamaschi L, Pelly VS, Turner L, Kotagiri P; Cambridge Institute of Therapeutic Immunology and Infectious Disease–National Institute for Health Research (CITIID–NIHR) COVID BioResource Collaboration; Göttgens B, Hess C, Gleadall N, Bradley JR, Nathan JA, Lyons PA, Drakesmith H, Smith KGC. Iron dysregulation and inflammatory stress erythropoiesis associates with long-term outcome of COVID-19. Nat Immunol. 2024 Mar;25(3):471-482. doi: 10.1038/s41590-024-01754-8. Epub 2024 Mar 1. PMID: 38429458; PMCID: PMC10907301. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10907301/ (Full text)