Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation

被引:7
作者
An, Andy Yi [1 ]
Baghela, Arjun [1 ]
Zhang, Peter G. Y. [1 ]
Blimkie, Travis M. [1 ]
Gauthier, Jeff [2 ]
Kaufmann, Daniel Elias [3 ,4 ]
Acton, Erica [5 ]
Lee, Amy H. Y. [5 ]
Levesque, Roger C. [2 ]
Hancock, Robert E. W. [1 ]
机构
[1] Univ British Columbia, Ctr Microbial Dis & Immun Res, Vancouver, BC, Canada
[2] Univ Laval, Dept Microbiol Infectiol & Immunol, Laval, PQ, Canada
[3] Univ Montreal, Dept Med, Montreal, PQ, Canada
[4] McGill Genome Ctr, Fonds Rech Quebec FRQ COVID 19 Biobank, Montreal, PQ, Canada
[5] Simon Fraser Univ, Dept Mol Biol & Biochem, Burnaby, BC, Canada
关键词
long COVID; COVID-19; endotypes; gene expression; personalized medicine; LONG; PATHOPHYSIOLOGY; PERSISTENCE;
D O I
10.3389/fimmu.2023.1243689
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
IntroductionPersistent symptoms after COVID-19 infection ("long COVID") negatively affects almost half of COVID-19 survivors. Despite its prevalence, its pathophysiology is poorly understood, with multiple host systems likely affected. Here, we followed patients from hospital to discharge and used a systems-biology approach to identify mechanisms of long COVID.MethodsRNA-seq was performed on whole blood collected early in hospital and 4-12 weeks after discharge from 24 adult COVID-19 patients (10 reported post-COVID symptoms after discharge). Differential gene expression analysis, pathway enrichment, and machine learning methods were used to identify underlying mechanisms for post-COVID symptom development.ResultsCompared to patients with post-COVID symptoms, patients without post-COVID symptoms had larger temporal gene expression changes associated with downregulation of inflammatory and coagulation genes over time. Patients could also be separated into three patient endotypes with differing mechanistic trajectories, which was validated in another published patient cohort. The "Resolved" endotype (lowest rate of post-COVID symptoms) had robust inflammatory and hemostatic responses in hospital that resolved after discharge. Conversely, the inflammatory/hemostatic responses of "Suppressive" and "Unresolved" endotypes (higher rates of patients with post-COVID symptoms) were persistently dampened and activated, respectively. These endotypes were accurately defined by specific blood gene expression signatures (6-7 genes) for potential clinical stratification.DiscussionThis study allowed analysis of long COVID whole blood transcriptomics trajectories while accounting for the issue of patient heterogeneity. Two of the three identified and externally validated endotypes ("Unresolved" and "Suppressive") were associated with higher rates of post-COVID symptoms and either persistently activated or suppressed inflammation and coagulation processes. Gene biomarkers in blood could potentially be used clinically to stratify patients into different endotypes, paving the way for personalized long COVID treatment.
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共 57 条
[1]   Severe COVID-19 and non-COVID-19 severe sepsis converge transcriptionally after a week in the intensive care unit, indicating common disease mechanisms [J].
An, Andy Y. ;
Baghela, Arjun ;
Zhang, Peter ;
Falsafi, Reza ;
Lee, Amy H. ;
Trahtemberg, Uriel ;
Baker, Andrew J. ;
dos Santos, Claudia C. ;
Hancock, Robert E. W. .
FRONTIERS IN IMMUNOLOGY, 2023, 14
[2]   HTSeq-a Python']Python framework to work with high-throughput sequencing data [J].
Anders, Simon ;
Pyl, Paul Theodor ;
Huber, Wolfgang .
BIOINFORMATICS, 2015, 31 (02) :166-169
[3]   Analysis of K-Means and K-Medoids Algorithm For Big Data [J].
Arora, Preeti ;
Deepali ;
Varshney, Shipra .
1ST INTERNATIONAL CONFERENCE ON INFORMATION SECURITY & PRIVACY 2015, 2016, 78 :507-512
[4]   Predicting severity in COVID-19 disease using sepsis blood gene expression signatures [J].
Baghela, Arjun ;
An, Andy ;
Zhang, Peter ;
Acton, Erica ;
Gauthier, Jeff ;
Brunet-Ratnasingham, Elsa ;
Blimkie, Travis ;
Freue, Gabriela Cohen ;
Kaufmann, Daniel ;
Lee, Amy H. Y. ;
Levesque, Roger C. ;
Hancock, Robert E. W. .
SCIENTIFIC REPORTS, 2023, 13 (01)
[5]   Predicting sepsis severity at first clinical presentation: The role of endotypes and mechanistic signatures [J].
Baghela, Arjun ;
Pena, Olga M. ;
Lee, Amy H. ;
Baquir, Beverlie ;
Falsafi, Reza ;
An, Andy ;
Farmer, Susan W. ;
Hurlburt, Andrew ;
Mondragon-Cardona, Alvaro ;
Rivera, Juan Diego ;
Baker, Andrew ;
Trahtemberg, Uriel ;
Shojaei, Maryam ;
Jimenez-Canizales, Carlos Eduardo ;
dos Santos, Claudia C. ;
Tang, Benjamin ;
Bouma, Hjalmar R. ;
Freue, Gabriela V. Cohen ;
Hancock, Robert E. W. .
EBIOMEDICINE, 2022, 75
[6]   Persistence of somatic symptoms after COVID-19 in the Netherlands: an observational cohort study [J].
Ballering, Aranka, V ;
van Zon, Sander K. R. ;
Hartman, Tim Colde ;
Rosmalen, Judith G. M. ;
Lifelines Corona Res Initiative .
LANCET, 2022, 400 (10350) :452-461
[7]   Prevalence of Diabetes and Hypertension and Their Associated Risks for Poor Outcomes in Covid-19 Patients [J].
Barrera, Francisco J. ;
Shekhar, Skand ;
Wurth, Rachel ;
Moreno-Pena, Pablo J. ;
Ponce, Oscar J. ;
Hajdenberg, Michelle ;
Alvarez-Villalobos, Neri A. ;
Hall, Janet E. ;
Schiffrin, Ernesto L. ;
Eisenhofer, Graeme ;
Porter, Forbes ;
Brito, Juan P. ;
Bornstein, Stefan R. ;
Stratakis, Constantine A. ;
Gonzalez-Gonzalez, Jose Gerardo ;
Rodiguez-Gutierrez, Rene ;
Hannah-Shmouni, Fady .
JOURNAL OF THE ENDOCRINE SOCIETY, 2020, 4 (09)
[8]   COVID-Specific Long-term Sequelae in Comparison to Common Viral Respiratory Infections: An Analysis of 17 487 Infected Adult Patients [J].
Baskett, William, I ;
Qureshi, Adnan, I ;
Shyu, Daniel ;
Armer, Jane M. ;
Shyu, Chi-Ren .
OPEN FORUM INFECTIOUS DISEASES, 2023, 10 (01)
[9]   Sample size calculation while controlling false discovery rate for differential expression analysis with RNA-sequencing experiments [J].
Bi, Ran ;
Liu, Peng .
BMC BIOINFORMATICS, 2016, 17
[10]  
bioinformatics.babraham, Babraham Bioinformatics-FastQC A Quality Control tool for High Throughput Sequence Data