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

Author:

Cano-Gamez Eddie12ORCID,Burnham Katie L.2ORCID,Goh Cyndi13ORCID,Allcock Alice1ORCID,Malick Zunaira H.1,Overend Lauren1ORCID,Kwok Andrew1ORCID,Smith David A.14ORCID,Peters-Sengers Hessel567ORCID,Antcliffe David8ORCID,McKechnie Stuart9,Scicluna Brendon P.51011ORCID,van der Poll Tom5,Gordon Anthony C.8ORCID,Hinds Charles J.12,Davenport Emma E.2ORCID,Knight Julian C.14ORCID,Webster Nigel,Galley Helen,Taylor Jane,Hall Sally,Addison Jenni,Roughton Sian,Tennant Heather,Guleri Achyut,Waddington Natalia,Arawwawala Dilshan,Durcan John,Short Alasdair,Swan Karen,Williams Sarah,Smolen Susan,Mitchell-Inwang Christine,Gordon Tony,Errington Emily,Templeton Maie,Venatesh Pyda,Ward Geraldine,McCauley Marie,Baudouin Simon,Higham Charley,Soar Jasmeet,Grier Sally,Hall Elaine,Brett Stephen,Kitson David,Wilson Robert,Mountford Laura,Moreno Juan,Hall Peter,Hewlett Jackie,McKechnie Stuart,Garrard Christopher,Millo Julian,Young Duncan,Hutton Paula,Parsons Penny,Smiths Alex,Faras-Arraya Roser,Soar Jasmeet,Raymode Parizade,Thompson Jonathan,Bowrey Sarah,Kazembe Sandra,Rich Natalie,Andreou Prem,Hales Dawn,Roberts Emma,Fletcher Simon,Rosbergen Melissa,Glister Georgina,Cuesta Jeronimo Moreno,Bion Julian,Millar Joanne,Perry Elsa Jane,Willis Heather,Mitchell Natalie,Ruel Sebastian,Carrera Ronald,Wilde Jude,Nilson Annette,Lees Sarah,Kapila Atul,Jacques Nicola,Atkinson Jane,Brown Abby,Prowse Heather,Krige Anton,Bland Martin,Bullock Lynne,Harrison Donna,Mills Gary,Humphreys John,Armitage Kelsey,Laha Shond,Baldwin Jacqueline,Walsh Angela,Doherty Nicola,Drage Stephen,Ortiz-Ruiz de Gordoa Laura,Lowes Sarah,Higham Charley,Walsh Helen,Calder Verity,Swan Catherine,Payne Heather,Higgins David,Andrews Sarah,Mappleback Sarah,Hind Charles,Garrard Chris,Watson D,McLees Eleanor,Purdy Alice,Stotz Martin,Ochelli-Okpue Adaeze,Bonner Stephen,Whitehead Iain,Hugil Keith,Goodridge Victoria,Cawthor Louisa,Kuper Martin,Pahary Sheik,Bellingan Geoffrey,Marshall Richard,Montgomery Hugh,Ryu Jung Hyun,Bercades Georgia,Boluda Susan,Bentley Andrew,Mccalman Katie,Jefferies Fiona,Knight Julian,Davenport Emma,Burnham Katie,Maugeri Narelle,Radhakrishnan Jayachandran,Mi Yuxin,Allcock Alice,Goh Cyndi,

Affiliation:

1. Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.

2. Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK.

3. Jenner Institute, University of Oxford, Oxford OX3 7DQ, UK.

4. Chinese Academy of Medical Science Oxford Institute, University of Oxford, Oxford OX3 7BN, UK.

5. Centre for Experimental and Molecular Medicine, Amsterdam University Medical Centers, University of Amsterdam, 1100 DD Amsterdam Southeast, Netherlands.

6. Department of Epidemiology and Data Science, Amsterdam Public Health, Amsterdam University Medical Centers, University of Amsterdam, 1100 DD Amsterdam Southeast, Netherlands.

7. Amsterdam Institute for Infection and Immunity, Amsterdam University Medical Centers, 1100 DD Amsterdam Southeast, Netherlands.

8. Division of Anaesthesia, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK.

9. Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK.

10. Department of Applied Biomedical Science, Faculty of Health Sciences, Materi Dei Hospital, University of Malta, Msida MSD 2080, Malta.

11. Centre for Molecular Medicine and Biobanking, University of Malta, Msida MSD 2080, Malta.

12. William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University, London EC1M 6BQ, UK.

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.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

General Medicine

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