Identification of biomarkers for COVID-19 associated secondary hemophagocytic lymphohistiocytosis Article Swipe
Susan Canny
,
Ian B. Stanaway
,
Sarah E. Holton
,
Mallorie Mitchem
,
Allison R. O’Rourke
,
Stephan Pribitzer
,
Sarah K. Baxter
,
Mark M. Wurfel
,
Uma Malhotra
,
Jane H. Buckner
,
Pavan K. Bhatraju
,
Eric D. Morrell
,
Cate Speake
,
Carmen Mikacenic
,
Jessica A. Hamerman
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.08.13.607855
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.08.13.607855
OBJECTIVES We aimed to define and validate novel biomarkers that could identify individuals with COVID-19 associated secondary hemophagocytic lymphohistiocytosis (sHLH) and to test whether fatalities due to COVID-19 in the presence of sHLH were associated with specific defects in the immune system. DESIGN In two cohorts of adult patients presenting with COVID-19 in 2020 and 2021, clinical lab values and serum proteomics were assessed. Subjects identified as having sHLH were compared to those with COVID-19 without sHLH. Eight deceased patients defined as COVID-sHLH underwent genomic sequencing in order to identify variants in immune-related genes. SETTING Two tertiary care hospitals in Seattle, Washington (Virginia Mason Medical Center and Harborview Medical Center). PATIENTS 186 patients with COVID-19 INTERVENTIONS None MEASUREMENTS AND MAIN RESULTS Nine percent of enrolled COVID-19 subjects met our defined criteria for sHLH. Using broad serum proteomic approaches (O-link and SomaScan), we identified three biomarkers for COVID-19 associated sHLH (soluble PD-L1, TNF-R1, and IL-18BP), supporting a role for proteins previously associated with other forms of sHLH (IL-18BP and sTNF-R1). We also identified novel biomarkers and pathways of COVID-sHLH, including sPD-L1 and the syntaxin pathway. We detected variants in several genes involved in immune responses in individuals with COVID-sHLH, including in DOCK8 and in TMPRSS15 , suggesting that genetic alterations in immune-related genes may contribute to hyperinflammation and fatal outcomes in COVID-19. CONCLUSIONS Biomarkers of COVID-19 associated sHLH, such as soluble PD-L1, and pathways, such as the syntaxin pathway, and variants in immune genes in these individuals, suggest critical roles for the immune response in driving sHLH in the context of COVID-19. Key Points QUESTION To define biomarkers that could identify individuals with COVID-19 associated secondary hemophagocytic lymphohistiocytosis (sHLH) and to test whether fatalities due to COVID-19 in the presence of sHLH were associated with specific defects in the immune system. FINDINGS In two independent cohorts using two different platforms, we identified sPD-L1, IL-18BP, and sTNF-R1 as COVID-sHLH biomarkers. We identified the syntaxin pathway as important in COVID-sHLH and variants in immune-related genes in a subset of deceased COVID-sHLH subjects. MEANING Immune related proteins and pathways are dysregulated in COVID-sHLH.
Related Topics
Concepts
Immune system
Coronavirus disease 2019 (COVID-19)
Immune dysregulation
Medicine
Immunology
Disease
Internal medicine
Infectious disease (medical specialty)
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2024.08.13.607855
- https://www.biorxiv.org/content/biorxiv/early/2024/08/15/2024.08.13.607855.full.pdf
- OA Status
- green
- Cited By
- 3
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401654454
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4401654454Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2024.08.13.607855Digital Object Identifier
- Title
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Identification of biomarkers for COVID-19 associated secondary hemophagocytic lymphohistiocytosisWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-08-15Full publication date if available
- Authors
-
Susan Canny, Ian B. Stanaway, Sarah E. Holton, Mallorie Mitchem, Allison R. O’Rourke, Stephan Pribitzer, Sarah K. Baxter, Mark M. Wurfel, Uma Malhotra, Jane H. Buckner, Pavan K. Bhatraju, Eric D. Morrell, Cate Speake, Carmen Mikacenic, Jessica A. HamermanList of authors in order
- Landing page
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https://doi.org/10.1101/2024.08.13.607855Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2024/08/15/2024.08.13.607855.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.biorxiv.org/content/biorxiv/early/2024/08/15/2024.08.13.607855.full.pdfDirect OA link when available
- Concepts
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Immune system, Coronavirus disease 2019 (COVID-19), Immune dysregulation, Medicine, Immunology, Disease, Internal medicine, Infectious disease (medical specialty)Top concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2025: 1, 2024: 2Per-year citation counts (last 5 years)
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| abstract_inverted_index.PATIENTS | 111 |
| abstract_inverted_index.QUESTION | 264 |
| abstract_inverted_index.Seattle, | 101 |
| abstract_inverted_index.Subjects | 65 |
| abstract_inverted_index.TMPRSS15 | 204 |
| abstract_inverted_index.clinical | 57 |
| abstract_inverted_index.compared | 71 |
| abstract_inverted_index.criteria | 131 |
| abstract_inverted_index.critical | 248 |
| abstract_inverted_index.deceased | 79, 337 |
| abstract_inverted_index.detected | 186 |
| abstract_inverted_index.enrolled | 125 |
| abstract_inverted_index.identify | 12, 90, 270 |
| abstract_inverted_index.involved | 191 |
| abstract_inverted_index.outcomes | 219 |
| abstract_inverted_index.pathway, | 238 |
| abstract_inverted_index.pathway. | 184 |
| abstract_inverted_index.pathways | 176, 345 |
| abstract_inverted_index.patients | 49, 80, 113 |
| abstract_inverted_index.presence | 31, 289 |
| abstract_inverted_index.proteins | 159, 343 |
| abstract_inverted_index.response | 253 |
| abstract_inverted_index.specific | 37, 295 |
| abstract_inverted_index.subjects | 127 |
| abstract_inverted_index.syntaxin | 183, 237, 322 |
| abstract_inverted_index.tertiary | 97 |
| abstract_inverted_index.validate | 7 |
| abstract_inverted_index.variants | 91, 187, 240, 329 |
| abstract_inverted_index.(Virginia | 103 |
| abstract_inverted_index.COVID-19. | 221, 261 |
| abstract_inverted_index.IL-18BP), | 154 |
| abstract_inverted_index.assessed. | 64 |
| abstract_inverted_index.different | 308 |
| abstract_inverted_index.hospitals | 99 |
| abstract_inverted_index.important | 325 |
| abstract_inverted_index.including | 179, 199 |
| abstract_inverted_index.pathways, | 233 |
| abstract_inverted_index.proteomic | 137 |
| abstract_inverted_index.responses | 194 |
| abstract_inverted_index.sTNF-R1). | 169 |
| abstract_inverted_index.secondary | 17, 275 |
| abstract_inverted_index.subjects. | 339 |
| abstract_inverted_index.underwent | 84 |
| abstract_inverted_index.Biomarkers | 223 |
| abstract_inverted_index.COVID-sHLH | 83, 317, 327, 338 |
| abstract_inverted_index.Harborview | 108 |
| abstract_inverted_index.OBJECTIVES | 1 |
| abstract_inverted_index.SomaScan), | 141 |
| abstract_inverted_index.Washington | 102 |
| abstract_inverted_index.approaches | 138 |
| abstract_inverted_index.associated | 16, 35, 148, 161, 226, 274, 293 |
| abstract_inverted_index.biomarkers | 9, 145, 174, 267 |
| abstract_inverted_index.contribute | 214 |
| abstract_inverted_index.fatalities | 25, 283 |
| abstract_inverted_index.identified | 66, 143, 172, 311, 320 |
| abstract_inverted_index.platforms, | 309 |
| abstract_inverted_index.presenting | 50 |
| abstract_inverted_index.previously | 160 |
| abstract_inverted_index.proteomics | 62 |
| abstract_inverted_index.sequencing | 86 |
| abstract_inverted_index.suggesting | 206 |
| abstract_inverted_index.supporting | 155 |
| abstract_inverted_index.CONCLUSIONS | 222 |
| abstract_inverted_index.COVID-sHLH, | 178, 198 |
| abstract_inverted_index.COVID-sHLH. | 349 |
| abstract_inverted_index.alterations | 209 |
| abstract_inverted_index.biomarkers. | 318 |
| abstract_inverted_index.independent | 304 |
| abstract_inverted_index.individuals | 13, 196, 271 |
| abstract_inverted_index.MEASUREMENTS | 118 |
| abstract_inverted_index.dysregulated | 347 |
| abstract_inverted_index.individuals, | 246 |
| abstract_inverted_index.INTERVENTIONS | 116 |
| abstract_inverted_index.hemophagocytic | 18, 276 |
| abstract_inverted_index.immune-related | 93, 211, 331 |
| abstract_inverted_index.hyperinflammation | 216 |
| abstract_inverted_index.lymphohistiocytosis | 19, 277 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5021144595 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 15 |
| corresponding_institution_ids | https://openalex.org/I201448701, https://openalex.org/I4391012615 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.8299999833106995 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.86672436 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |