Unbiased characterization of COVID-19 endotypes leads to prognostication of high-risk individuals using routine blood tests

Abstract Background Only a subset of individuals infected with SARS‑CoV‑2 develop severe COVID‑19. Improved tools for early diagnosis and prognostication are needed. We hypothesized that unsupervised analysis of detailed circulating proteomes could reveal biologically meaningful patient endotypes and help identify individuals at elevated risk of severe outcomes. Methods We performed unsupervised stratification of the circulating proteome in 731 SARS‑CoV‑2 PCR‑positive participants from the Biobanque québécoise de la COVID‑19 (BQC19), representing a range of disease severities. We also developed a prognostic model based solely on clinical laboratory measurements and applied it to 903 patients recruited across early pandemic waves (2020–2022) to generalize identified endotypes. Results Six proteomic endotypes (EPs) emerged. Endotype EP6 showed the highest frequencies of ICU admission, ARDS, and mortality. EP6 was marked by elevated C‑reactive protein, D‑dimer, interleukin‑6, ferritin, soluble fms‑like tyrosine kinase‑1, increased neutrophils, and reduced lymphocyte counts. SHC4 emerged as a protein quantitative trait locus associated with EP6. Among EP6 patients requiring mechanical ventilation, we observed alterations in lipoprotein metabolism, and alpha‑L‑iduronidase levels inversely correlated with duration of ventilation. Conclusions Unsupervised proteomic analysis identified biologically coherent endotypes that advance understanding of acute lung injury in COVID‑19 and support improved diagnostic and prognostic strategies.