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IRIS
Complement, a critical defence against pathogens, has been implicated as a driver of pathology in COVID-19. Complement activation products are detected in plasma and tissues and complement blockade considered for therapy. To delineate roles of complement in immunopathogenesis, we undertook the largest comprehensive study of complement in an COVID-19 to date, a comprehensive profiling of 16 complement biomarkers, including key components, regulators and activation products, in 966 plasma samples from 682 hospitalised COVID-19 patients collected across the hospitalisation period as part of the UK ISARIC4C study. Unsupervised clustering of complement biomarkers mapped to disease severity and supervised machine learning identified marker sets in early samples that predicted peak severity. Compared to heathy controls, complement proteins and activation products (Ba, iC3b, terminal complement complex) were significantly altered in COVID-19 admission samples in all severity groups. Elevated alternative pathway activation markers (Ba and iC3b) and decreased alternative pathway regulator (properdin) in admission samples associated with more severe disease and risk of death. Levels of most complement biomarkers were reduced in severe disease, consistent with consumption and tissue deposition. Latent class mixed modelling and cumulative incidence analysis identified the trajectory of increase of Ba to be a strong predictor of peak COVID-19 disease severity and death. The data demonstrate that early-onset, uncontrolled activation of complement, driven by sustained and progressive amplification through the alternative pathway amplification loop is a ubiquitous feature of COVID-19, further exacerbated in severe disease. These findings provide novel insights into COVID-19 immunopathogenesis and inform strategies for therapeutic intervention.
Alternative pathway dysregulation in tissues drives sustained complement activation and predicts outcome across the disease course in COVID-19
Siggins M. K.;Davies K.;Fellows R.;Thwaites R. S.;Baillie J. K.;Semple M. G.;Openshaw P. J. M.;Zelek W. M.;Harris C. L.;Morgan B. P.;Baillie J. K.;Semple M. G.;Openshaw P. J. M.;Carson G.;Alex B.;Bach B.;Barclay W. S.;Bogaert D.;Chand M.;Cooke G. S.;Docherty A. B.;Dunning J.;da Silva Filipe A.;Fletcher T.;Green C. A.;Harrison E. M.;Hiscox J. A.;Ho A. Y. W.;Horby P. W.;Ijaz S.;Khoo S.;Klenerman P.;Law A.;Lim W. S.;Mentzer A. J.;Merson L.;Meynert A. M.;Noursadeghi M.;Moore S. C.;Palmarini M.;Paxton W. A.;Pollakis G.;Price N.;Rambaut A.;Robertson D. L.;Russell C. D.;Sancho-Shimizu V.;Scott J. T.;de Silva T.;Sigfrid L.;Solomon T.;Sriskandan S.;Stuart D.;Summers C.;Tedder R. S.;Thomson E. C.;Thompson A. A. R.;Thwaites R. S.;Turtle L. C. W.;Gupta R. K.;Zambon M.;Hardwick H.;Donohue C.;Lyons R.;Griffiths F.;Oosthuyzen W.;Norman L.;Pius R.;Drake T. M.;Fairfield C. J.;Knight S. R.;Mclean K. A.;Murphy D.;Shaw C. A.;Dalton J.;Girvan M.;Saviciute E.;Roberts S.;Harrison J.;Marsh L.;Connor M.;Halpin S.;Jackson C.;Gamble C.;Leeming G.;Law A.;Wham M.;Clohisey S.;Hendry R.;Scott-Brown J.;Greenhalf W.;Shaw V.;McDonald S.;Keating S.;Ahmed K. A.;Armstrong J. A.;Ashworth M.;Asiimwe I. G.;Bakshi S.;Barlow S. L.;Booth L.;Brennan B.;Bullock K.;Catterall B. W. A.;Clark J. J.;Clarke E. A.;Cole S.;Cooper L.;Cox H.;Davis C.;Dincarslan O.;Dunn C.;Dyer P.;Elliott A.;Evans A.;Finch L.;Fisher L. W. S.;Foster T.;Garcia-Dorival I.;Greenhalf W.;Gunning P.;Hartley C.;Jensen R. L.;Jones C. B.;Jones T. R.;Khandaker S.;King K.;Kiy R. T.;Koukorava C.;Lake A.;Lant S.;Latawiec D.;Lavelle-Langham L.;Lefteri D.;Lett L.;Livoti L. A.;Mancini M.;McDonald S.;McEvoy L.;McLauchlan J.;Metelmann S.;Miah N. S.;Middleton J.;Mitchell J.;Moore S. C.;Murphy E. G.;PenriceRandal R.;Pilgrim J.;Prince T.;Reynolds W.;Ridley P. M.;Sales D.;Shaw V. E.;Shears R. K.;Small B.;Subramaniam K. S.;Szemiel A.;Taggart A.;Tanianis-Hughes J.;Thomas J.;Trochu E.;van Tonder L.;Wilcock E.;Zhang J. E.;Flaherty L.;Maziere N.;Cass E.;Carracedo A. D.;Carlucci N.;Holmes A.;Massey H.;Murphy L.;Wrobel N.;McCafferty S.;Morrice K.;MacLean A.;Adeniji K.;Agranoff D.;Agwuh K.;Ail D.;Aldera E. L.;Alegria A.;Angus B.;Ashish A.;Atkinson D.;Bari S.;Barlow G.;Barnass S.;Barrett N.;Bassford C.;Basude S.;Baxter D.;Beadsworth M.;Bernatoniene J.;Berridge J.;Best N.;Bothma P.;Chadwick D.;Brittain-Long R.;Bulteel N.;Burden T.;Burtenshaw A.;Caruth V.;Chadwick D.;Chambler D.;Chee N.;Child J.;Chukkambotla S.;Clark T.;Collini P.;Cosgrove C.;Cupitt J.;Cutino-Moguel M. -T.;Dark P.;Dawson C.;Dervisevic S.;Donnison P.;Douthwaite S.;DuRand I.;Dushianthan A.;Dyer T.;Evans C.;Eziefula C.;Fegan C.;Finn A.;Fullerton D.;Garg S.;Garg S.;Garg A.;GkraniaKlotsas E.;Godden J.;Goldsmith A.;Graham C.;Hardy E.;Hartshorn S.;Harvey D.;Havalda P.;Hawcutt D. B.;Hobrok M.;Hodgson L.;Hormis A.;Jacobs M.;Jain S.;Jennings P.;Kaliappan A.;Kasipandian V.;Kegg S.;Kelsey M.;Kendall J.;Kerrison C.;Kerslake I.;Koch O.;Koduri G.;Koshy G.;Laha S.;Laird S.;Larkin S.;Leiner T.;Lillie P.;Limb J.;Linnett V.;Little J.;Lyttle M.;MacMahon M.;MacNaughton E.;Mankregod R.;Masson H.;Matovu E.;McCullough K.;McEwen R.;Meda M.;Mills G.;Minton J.;Mirfenderesky M.;Mohandas K.;Mok Q.;Moon J.;Moore E.;Morgan P.;Morris C.;Mortimore K.;Moses S.;Mpenge M.;Mulla R.;Murphy M.;Nagel M.;Nagarajan T.;Nelson M.;O'Shea M. K.;Otahal I.;Ostermann M.;Pais M.;Palmieri C.;Panchatsharam S.;Papakonstantinou D.;Paraiso H.;Patel B.;Pattison N.;Pepperell J.;Peters M.;Phull M.;Pintus S.;Pooni J. S.;Post F.;Price D.;Prout R.;Rae N.;Reschreiter H.;Reynolds T.;Richardson N.;Roberts M.;Roberts D.;Rose A.;Rousseau G.;Ryan B.;Saluja T.;Shah A.;Shanmuga P.;Sharma A.;Shawcross A.;Sizer J.;Shankar-Hari M.;Smith R.;Snelson C.;Spittle N.;Staines N.;Stambach T.;Stewart R.;Subudhi P.;Szakmany T.;Tatham K.;Thomas J.;Thompson C.;Thompson R.;Tridente A.;TupperCarey D.;Twagira M.;Ustianowski A.;Vallotton N.;Vincent-Smith L.;Visuvanathan S.;Vuylsteke A.;Waddy S.;Wake R.;Walden A.;Welters I.;Whitehouse T.;Whittaker P.;Whittington A.;Papineni P.;Wijesinghe M.;Williams M.;Wilson L.;Cole S.;Winchester S.;Wiselka M.;Wolverson A.;Wootton D. G.;Workman A.;Yates B.;Young P.
2022-01-01
Abstract
Complement, a critical defence against pathogens, has been implicated as a driver of pathology in COVID-19. Complement activation products are detected in plasma and tissues and complement blockade considered for therapy. To delineate roles of complement in immunopathogenesis, we undertook the largest comprehensive study of complement in an COVID-19 to date, a comprehensive profiling of 16 complement biomarkers, including key components, regulators and activation products, in 966 plasma samples from 682 hospitalised COVID-19 patients collected across the hospitalisation period as part of the UK ISARIC4C study. Unsupervised clustering of complement biomarkers mapped to disease severity and supervised machine learning identified marker sets in early samples that predicted peak severity. Compared to heathy controls, complement proteins and activation products (Ba, iC3b, terminal complement complex) were significantly altered in COVID-19 admission samples in all severity groups. Elevated alternative pathway activation markers (Ba and iC3b) and decreased alternative pathway regulator (properdin) in admission samples associated with more severe disease and risk of death. Levels of most complement biomarkers were reduced in severe disease, consistent with consumption and tissue deposition. Latent class mixed modelling and cumulative incidence analysis identified the trajectory of increase of Ba to be a strong predictor of peak COVID-19 disease severity and death. The data demonstrate that early-onset, uncontrolled activation of complement, driven by sustained and progressive amplification through the alternative pathway amplification loop is a ubiquitous feature of COVID-19, further exacerbated in severe disease. These findings provide novel insights into COVID-19 immunopathogenesis and inform strategies for therapeutic intervention.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1468775
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.
