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An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression.

ABSTRACT: Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection.

SUBMITTER: Cano-Gamez E

PROVIDER: S-EPMC7613832 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression.

Cano-Gamez Eddie E Burnham Katie L KL Goh Cyndi C Allcock Alice A Malick Zunaira H ZH Overend Lauren L Kwok Andrew A Smith David A DA Peters-Sengers Hessel H Antcliffe David D McKechnie Stuart S Scicluna Brendon P BP van der Poll Tom T Gordon Anthony C AC Hinds Charles J CJ Davenport Emma E EE Knight Julian C JC Webster Nigel N Galley Helen H Taylor Jane J Hall Sally S Addison Jenni J Roughton Sian S Tennant Heather H Guleri Achyut A Waddington Natalia N Arawwawala Dilshan D Durcan John J Short Alasdair A Swan Karen K Williams Sarah S Smolen Susan S Mitchell-Inwang Christine C Gordon Tony T Errington Emily E Templeton Maie M Venatesh Pyda P Ward Geraldine G McCauley Marie M Baudouin Simon S Higham Charley C Soar Jasmeet J Grier Sally S Hall Elaine E Brett Stephen S Kitson David D Wilson Robert R Mountford Laura L Moreno Juan J Hall Peter P Hewlett Jackie J McKechnie Stuart S Garrard Christopher C Millo Julian J Young Duncan D Hutton Paula P Parsons Penny P Smiths Alex A Faras-Arraya Roser R Soar Jasmeet J Raymode Parizade P Thompson Jonathan J Bowrey Sarah S Kazembe Sandra S Rich Natalie N Andreou Prem P Hales Dawn D Roberts Emma E Fletcher Simon S Rosbergen Melissa M Glister Georgina G Cuesta Jeronimo Moreno JM Bion Julian J Millar Joanne J Perry Elsa Jane EJ Willis Heather H Mitchell Natalie N Ruel Sebastian S Carrera Ronald R Wilde Jude J Nilson Annette A Lees Sarah S Kapila Atul A Jacques Nicola N Atkinson Jane J Brown Abby A Prowse Heather H Krige Anton A Bland Martin M Bullock Lynne L Harrison Donna D Mills Gary G Humphreys John J Armitage Kelsey K Laha Shond S Baldwin Jacqueline J Walsh Angela A Doherty Nicola N Drage Stephen S Ortiz-Ruiz de Gordoa Laura L Lowes Sarah S Higham Charley C Walsh Helen H Calder Verity V Swan Catherine C Payne Heather H Higgins David D Andrews Sarah S Mappleback Sarah S Hind Charles C Garrard Chris C Watson D D McLees Eleanor E Purdy Alice A Stotz Martin M Ochelli-Okpue Adaeze A Bonner Stephen S Whitehead Iain I Hugil Keith K Goodridge Victoria V Cawthor Louisa L Kuper Martin M Pahary Sheik S Bellingan Geoffrey G Marshall Richard R Montgomery Hugh H Ryu Jung Hyun JH Bercades Georgia G Boluda Susan S Bentley Andrew A Mccalman Katie K Jefferies Fiona F Knight Julian J Davenport Emma E Burnham Katie K Maugeri Narelle N Radhakrishnan Jayachandran J Mi Yuxin Y Allcock Alice A Goh Cyndi C

Science translational medicine 20221102 669

Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy indiv ...[more]

PMID: 36322631

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Project description:BackgroundAlthough multiple individual immune parameters have been demonstrated to predict the occurrence of secondary infection after critical illness, significant questions remain with regards to the selection, timing and clinical utility of such immune monitoring tests.Research questionAs a sub-study of the REALISM study, the REALIST score was developed as a pragmatic approach to help clinicians better identify and stratify patients at high risk for secondary infection, using a simple set of relatively available and technically robust biomarkers.Study design and methodsThis is a sub-study of a single-centre prospective cohort study of immune profiling in critically ill adults admitted after severe trauma, major surgery or sepsis/septic shock. For the REALIST score, five immune parameters were pre-emptively selected based on their clinical applicability and technical robustness. Predictive power of different parameters and combinations of parameters was assessed. The main outcome of interest was the occurrence of secondary infection within 30 days.ResultsAfter excluding statistically redundant and poorly predictive parameters, three parameters remained in the REALIST score: mHLA-DR, percentage of immature (CD10- CD16-) neutrophils and serum IL-10 level. In the cohort of interest (n = 189), incidence of secondary infection at day 30 increased from 8% for patients with REALIST score of 0 to 46% in patients with a score of 3 abnormal parameters, measured ad D5-7. When adjusted for a priori identified clinical risk factors for secondary infection (SOFA score and invasive mechanical ventilation at D5-7), a higher REALIST score was independently associated with increased risk of secondary infection (42 events (22.2%), adjusted HR 3.22 (1.09-9.50), p = 0.034) and mortality (10 events (5.3%), p = 0.001).InterpretationWe derived and presented the REALIST score, a simple and pragmatic stratification strategy which provides clinicians with a clear assessment of the immune status of their patients. This new tool could help optimize care of these individuals and could contribute in designing future trials of immune stimulation strategies.

Project description:BackgroundImmunoecology aims to explain variation among hosts in the strength and efficacy of immunological defences in natural populations. This requires development of biomarkers of the activation of the immune system so that they can be collected non-lethally and sampled from small amounts of easily obtainable tissue. We used transcriptome profiling in wild greenfinches (Carduelis chloris) to detect whole blood transcripts that most profoundly indicate upregulation of antimicrobial defences during acute phase response. The more general aim of this study was to obtain a functional annotation of a substantial portion of the greenfinch transcriptome that would enable to gain access to more specific genomic tools in subsequent studies. The birds received either bacterial lipopolysaccharide or saline injections and RNA-seq transcriptional profiling was performed 12 h after treatment to provide initial functional annotation of the transcriptome and assess whole blood response to immune stimulation.ResultsA total of 66,084 transcripts were obtained from de novo Trinty assembly, out of which 23,153 could be functionally annotated. Only 1,911 of these were significantly upregulated or downregulated. The manipulation caused marked upregulation of several transcripts related to immune activation. These included avian-specific antimicrobial agents avidin and gallinacin, but also some more general host response genes, such as serum amyloid A protein, lymphocyte antigen 75 and copper-transporting ATPase 1. However, links with avian immunity for most differentially regulated transcripts remained rather hypothetical, as a large set of differentially expressed transcripts lacked functional annotation.ConclusionsThis appears to be the first large scale transcriptional profiling of immune function in passerine birds. The transcriptomic data obtained suggest novel markers for the assessment of the immunological state of wild passerines. Characterizing the function of those possible novel infection markers would assist future vertebrate genome annotation. The extensive sequence information collected enables to identify possible target and housekeeping genes needed to gain access to more specific genomic tools in future studies.

Project description:Background: Multiple myeloma (MM) is characterized by abnormal proliferation of bone marrow clonal plasma cells. Tumor immunotherapy, a new therapy that has emerged in recent years, offers hope to patients, and studying the expression characteristics of immune-related genes (IRGs) based on whole bone marrow gene expression profiling (GEP) in MM patients can help guide personalized immunotherapy. Methods: In this study, we explored the potential prognostic value of IRGs in MM by combining GEP and clinical data from the GEO database. We identified hub IRGs and transcription factors (TFs) associated with disease progression by Weighted Gene Co-expression Network Analysis (WGCNA), and modeled immune-related prognostic signature by univariate and multivariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis. Subsequently, the prognostic ability of signature was verified by multiple statistical methods. Moreover, ssGSEA and GSEA algorithm reveled different immunological characteristics and biological function variation in different risk groups. We mapped the hub IRGs by protein-protein interaction network (PPI) and extracted the top 10 ranked genes. Finally, we conducted vitro assays on two alternative IRGs. Results: Our study identified a total of 14 TFs and 88 IRGs associated with International Staging System (ISS). Ten IRGs were identified by Cox -LASSO regression analysis, and used to develop optimal prognostic signature for overall survival (OS) in MM patients. The 10-IRGs were BDNF, CETP, CD70, LMBR, LTBP1, NENF, NR1D1, NR1H2, PTK2B and SEMA4. In different groups, risk signatures showed excellent survival prediction ability, and MM patients also could be stratified at survival risk. In addition, IRF7 and SHC1 were hub IRGs in PPI network, and the vitro assays proved that they could promote tumor progression. Notably, ssGSEA and GSEA results confirmed that different risk groups could accurately indicate the status of tumor microenvironment (TME) and activation of biological pathways. Conclusion: Our study suggested that immune-related signature could be used as prognostic markers in MM patients.

Dataset Information

An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression.

Publications

An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression.

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