PROFILE The biology of a biomarker Dr Eoin

PROFILE: The biology of a biomarker Dr Eoin Mc. Kinney PROFILE Investigators meeting Moller Centre, Churchill College, Cambridge March 8 th 2018

what does it mean? 4 categories of biomarker interpretation: i. biological interpretation ii. clinician interpretation iii. patient interpretation iv. statistical interpretability

A translational programme in autoimmunity transcriptomics since 2006: 5 cell types from 5 diseases 0 6 12 time / months More cells, more diseases: since 2014 collection expanded to 17 cell types from >12 diseases CD 16+ i. iii. iv. patients with active, untreated disease purified cell subsets source of m. RNA discovery and validation cohorts detailed prospective clinical phenotyping

defining systems biology “The purpose of computing is insight, not numbers” Richard Hamming, Turing Award 1968

Data visualisation: patterns in numbers

scale-free network analysis of the CD 8 T cell transcriptome (after Horvath and Langfelder)

Systemic vasculitis CD 8 T cell network analysis Mc. Kinney et al. Nature 2015; 523: 612 -6

data-driven data interpretation

CD 8 T cell exhaustion and outcome in autoimmunity vasculitis GSEAp < 0. 001 SLE Mc. Kinney et al. Nature 2015; 523: 612 -6 IBD Melanoma TIL

heterogeneity of chronic infection similar at presentation chronic antigen • HCV • HBV • HIV distinct outcomes

CD 8 T cell responses to acute and persistent antigen coinhibitory signaling Wherry et al. Immunity 2007; 27(4): 670 -84 Wherry E J , and Ahmed R J. Virol. 2004; 78: 5535 -5545

Characteristic ‘signature’ of CD 8 T cell exhaustion distinct, specific pattern of gene expression Wherry, Immunity 2007; 27: 670 -84

CD 8 exhaustion signature associated with poor viral clearance but good outcome in multiple immune-mediated diseases AAV SLE IBD Mc. Kinney et al. Nature 2015; 523: 612 -6 early relapse recurrent relapse

CD 8 T Cell independent validation + translation Blood Vasculitis/SLE IBD MS validation Mc. Kinney et al. Nat Med 2010 and Nature 2015; 523: 612 -6

Validation in vaccination, infection and autoimmunity Mc. Kinney et al. Nature 2015; 523: 612 -6

New cell types distinct correlations in different cell types, now collecting up to 17 cell types per disease flare rate auto. Ab titre (anti-PR 3) correlation CD 19 SLE CD 4 Vasculitis Autoantibody titre ds. DNA/ANA/Ig. G auto. Ab titre (anti-MPO) flare-rate +1 T cell % -1 Neutrophils “analysis”

Summary • all forms of biomarker interpretability important • understanding biology increases confidence, may guide new treatment • interpreting biomarkers can inform the underlying biological mechanism of disease relapse

Acknowledgements - Ken Smith Paul Lyons Iona Cuthbertson Chris Connor Daniele Biasci James Lee Holly Davage Giulia Manferrari John Sowerby Laura Bergamaschi Diana Carneiro-Pombal Patients and volunteers David Jayne Miles Parkes Afzal Chaudhry Nuru Noor Jerry Nepom Kristina Harries Fred Gunnar-Karnell Dawn Smilek Carla Greenbaum Kristen Ryker