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Longitudinal clinical proteomics reveals pneumonia type–specific protein biomarkers and autoantibodies
Anna Semenova, Taylor A. Poor, Johannes B. Müller-Reif, Sai Rama Sridatta Prakki, Phillip Geyer, Martin Mück-Häusl, Rogan A. Grant, Luke Rasmussen, Lesca M. Holdt, Daniel Teupser, Matthias Mann, Ali Ö. Yildirim, Richard G. Wunderink, Alexander V. Misharin, Ben D. Singer, G.R. Scott Budinger, Theodore S. Kapellos, Herbert B. Schiller
Anna Semenova, Taylor A. Poor, Johannes B. Müller-Reif, Sai Rama Sridatta Prakki, Phillip Geyer, Martin Mück-Häusl, Rogan A. Grant, Luke Rasmussen, Lesca M. Holdt, Daniel Teupser, Matthias Mann, Ali Ö. Yildirim, Richard G. Wunderink, Alexander V. Misharin, Ben D. Singer, G.R. Scott Budinger, Theodore S. Kapellos, Herbert B. Schiller
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Research Article Infectious disease Inflammation

Longitudinal clinical proteomics reveals pneumonia type–specific protein biomarkers and autoantibodies

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Abstract

Community-acquired pneumonia is a major cause of morbidity and mortality globally. Specific molecular endotypes are currently not well defined, and different viral or bacterial pathogens may trigger specific host responses and pathogenic mechanisms. We performed longitudinal proteomic profiling of bronchoalveolar lavage fluid and plasma from bacterial, influenza, and SARS-CoV-2–driven pneumonia. Our analysis revealed highly pneumonia type–specific proteomic signatures, including COVID-19–specific antibodies locally produced in the lung. These antibodies showed biased immunoglobulin V–domain usage, linked to a CD69/CD83 plasma cell state associated with disease severity and degree of autoimmunity. Using mass spectrometry–driven autoantibody profiling in 2 independent COVID-19 cohorts, we identified 177 putative autoantibodies targeting extracellular matrix, nuclear, and immune-related proteins. Of note, temporal changes in autoantibody profiles correlated with clinical markers of inflammation, organ dysfunction, and duration of hospitalization. These findings highlight the autoimmune aspects of COVID-19 and provide potential biomarkers and therapeutic targets to help improve patient outcomes.

Authors

Anna Semenova, Taylor A. Poor, Johannes B. Müller-Reif, Sai Rama Sridatta Prakki, Phillip Geyer, Martin Mück-Häusl, Rogan A. Grant, Luke Rasmussen, Lesca M. Holdt, Daniel Teupser, Matthias Mann, Ali Ö. Yildirim, Richard G. Wunderink, Alexander V. Misharin, Ben D. Singer, G.R. Scott Budinger, Theodore S. Kapellos, Herbert B. Schiller

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Figure 1

Pneumonia-specific signatures can be detected in BALF upon intubation in the intensive care unit.

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Pneumonia-specific signatures can be detected in BALF upon intubation in...
(A) Overview of study design. (B) Lollipop chart displaying patient numbers and the longitudinal resolution of sample collection per pneumonia type. (C) Box plots that compare clinical parameters and phenotypical observations across pneumonia types. Data are represented as mean ± SD, and variance was statistically assessed with the non-parametric Kruskal-Wallis test. (D) Principal component analysis of BALF proteomes at the time of intubation based on the 488 most variable proteins. The 20% most variable proteins were calculated by ranking the BALF proteome by decreasing variance across all pneumonia type specimens. (E) Hierarchical clustering of 12 BALF pneumonia-specific protein modules at day 0 of intubation as derived from coexpression network analysis. The color scale denotes the mean fold change of the proteins in each module. (F) Pathway analysis of selected BALF module proteins at intubation induction. The top 5 enriched Reactome terms for each module are displayed. Color code depicts the adjusted P value, and point size refers to the number of proteins detected per term. (G and H) Box plots displaying the longitudinal enrichment of neutrophil degranulation (G) and immunoglobulin (H) Reactome terms in BALF specimens across pneumonia types. Each dot represents the enrichment score for an individual patient. Data are represented as mean ± SD, and the variability between groups was statistically assessed with the nonparametric Kruskal-Wallis test. Proteins involved in the term are displayed on the right side of the plot.

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