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. 2022 Sep 28;19(1):34.
doi: 10.1186/s12014-022-09371-z.

The dynamic changes and sex differences of 147 immune-related proteins during acute COVID-19 in 580 individuals

Guillaume Butler-Laporte  1   2 Edgar Gonzalez-Kozlova  3 Chen-Yang Su  1   4 Sirui Zhou  1   2 Tomoko Nakanishi  1   5   6   7 Elsa Brunet-Ratnasingham  8 David Morrison  1 Laetitia Laurent  1 Jonathan Afilalo  1   2 Marc Afilalo  9 Danielle Henry  1 Yiheng Chen  1   5 Julia Carrasco-Zanini  10 Yossi Farjoun  1 Maik Pietzner  10   11 Nofar Kimchi  1 Zaman Afrasiabi  1 Nardin Rezk  1 Meriem Bouab  1 Louis Petitjean  1 Charlotte Guzman  1 Xiaoqing Xue  1 Chris Tselios  1 Branka Vulesevic  1 Olumide Adeleye  1 Tala Abdullah  1 Noor Almamlouk  1 Yara Moussa  1 Chantal DeLuca  1 Naomi Duggan  1 Erwin Schurr  12 Nathalie Brassard  8 Madeleine Durand  8 Diane Marie Del Valle  13 Ryan Thompson  14 Mario A Cedillo  15 Eric Schadt  14 Kai Nie  16 Nicole W Simons  14 Konstantinos Mouskas  14 Nicolas Zaki  16 Manishkumar Patel  13 Hui Xie  16 Jocelyn Harris  16 Robert Marvin  16 Esther Cheng  14 Kevin Tuballes  13 Kimberly Argueta  16 Ieisha Scott  16 Mount Sinai COVID-19 Biobank TeamCelia M T Greenwood  1   2 Clare Paterson  17 Michael Hinterberg  17 Claudia Langenberg  10   17 Vincenzo Forgetta  1 Vincent Mooser  5 Thomas Marron  3   13   18 Noam Beckmann  14 Ephraim Kenigsberg  14 Alexander W Charney  19 Seunghee Kim-Schulze  16 Miriam Merad  13 Daniel E Kaufmann  8   20 Sacha Gnjatic  16 J Brent Richards  21   22   23   24   25   26
Collaborators, Affiliations

The dynamic changes and sex differences of 147 immune-related proteins during acute COVID-19 in 580 individuals

Guillaume Butler-Laporte et al. Clin Proteomics. .

Erratum in

  • Correction: The dynamic changes and sex differences of 147 immune-related proteins during acute COVID-19 in 580 individuals.
    Butler-Laporte G, Gonzalez-Kozlova E, Su CY, Zhou S, Nakanishi T, Brunet-Ratnasingham E, Morrison D, Laurent L, Aflalo J, Aflalo M, Henry D, Chen Y, Carrasco-Zanini J, Farjoun Y, Pietzner M, Kimchi N, Afrasiabi Z, Rezk N, Bouab M, Petitjean L, Guzman C, Xue X, Tselios C, Vulesevic B, Adeleye O, Abdullah T, Almamlouk N, Moussa Y, DeLuca C, Duggan N, Schurr E, Brassard N, Durand M, Del Valle DM, Thompson R, Cedillo MA, Schadt E, Nie K, Simons NW, Mouskas K, Zaki N, Patel M, Xie H, Harris J, Marvin R, Cheng E, Tuballes K, Argueta K, Scott I; Mount Sinai COVID-19 Biobank Team; Greenwood CMT, Paterson C, Hinterberg M, Langenberg C, Forgetta V, Mooser V, Marron T, Beckmann ND, Kenigsberg E, Charney AW, Kim-Schulze S, Merad M, Kaufmann DE, Gnjatic S, Richards JB. Butler-Laporte G, et al. Clin Proteomics. 2022 Nov 15;19(1):40. doi: 10.1186/s12014-022-09378-6. Clin Proteomics. 2022. PMID: 36376796 Free PMC article. No abstract available.

Abstract

Introduction: Severe COVID-19 leads to important changes in circulating immune-related proteins. To date it has been difficult to understand their temporal relationship and identify cytokines that are drivers of severe COVID-19 outcomes and underlie differences in outcomes between sexes. Here, we measured 147 immune-related proteins during acute COVID-19 to investigate these questions.

Methods: We measured circulating protein abundances using the SOMAscan nucleic acid aptamer panel in two large independent hospital-based COVID-19 cohorts in Canada and the United States. We fit generalized additive models with cubic splines from the start of symptom onset to identify protein levels over the first 14 days of infection which were different between severe cases and controls, adjusting for age and sex. Severe cases were defined as individuals with COVID-19 requiring invasive or non-invasive mechanical respiratory support.

Results: 580 individuals were included in the analysis. Mean subject age was 64.3 (sd 18.1), and 47% were male. Of the 147 proteins, 69 showed a significant difference between cases and controls (p < 3.4 × 10-4). Three clusters were formed by 108 highly correlated proteins that replicated in both cohorts, making it difficult to determine which proteins have a true causal effect on severe COVID-19. Six proteins showed sex differences in levels over time, of which 3 were also associated with severe COVID-19: CCL26, IL1RL2, and IL3RA, providing insights to better understand the marked differences in outcomes by sex.

Conclusions: Severe COVID-19 is associated with large changes in 69 immune-related proteins. Further, five proteins were associated with sex differences in outcomes. These results provide direct insights into immune-related proteins that are strongly influenced by severe COVID-19 infection.

Keywords: COVID-19; Immunity; Proteomics; SOMAscan.

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Conflict of interest statement

J.B.R. has served as an advisor to GlaxoSmithKline and Deerfield Capital and is the Founder of 5 Prime Sciences. The Lady Davis Institute has previously received funding from GlaxoSmithKline, Eli Lilly, and Biogen for research programs at Dr. Richards’ laboratory unrelated to this manuscript. C.P. and M.H. are employees of SomaLogic.

Figures

Fig. 1
Fig. 1
Spearman correlations for three clusters (A, B and C) of proteins in the BQC (left) and the MSB (right). Only correlations with p-values less than 0.05 shown. Proteins with asterisks (***) showed a statistically significant differences between cases and controls (Bonferroni threshold 0.05/147). Full spearman correlation heatmap available in Additional file 3
Fig. 2
Fig. 2
Smoothed curves for cluster-representative immune-related proteins, as a function of days since symptoms onset (x-axis), and separately for severe COVID cases and controls. Estimated curves are shown for 65-year-old. Y-axis is standardized to a mean of 0 and standard deviation of 1. Full results are shown in Additional final 5. Blue: controls. Red: severe COVID-19. Asterisks (***): p < 3.4 × 10–4 for case–control difference in protein levels
Fig. 3
Fig. 3
Smoothed protein level curves showing time-related and sex-related differences as a function of days since symptoms onset (x-axis) in a 65-year-old patient (p < 3.4 × 10–4 for sex differences in cytokine levels). Y-axis is standardized to a mean of 0 and standard deviation of 1 F: female. M: male. Blue: controls. Red: severe COVID-19

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