Autoantibody discovery across monogenic, acquired, and COVID-19-associated autoimmunity with scalable PhIP-seq
Rattachement africain : us, se, fr, gb, ca, no. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Phage immunoprecipitation sequencing (PhIP-seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-seq for autoantigen discovery, including our previous work (Vazquez et al., 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki disease (KD), multisystem inflammatory syndrome in children (MIS-C), and finally, mild and severe forms of COVID-19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as prodynorphin (PDYN) in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in two patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID-19, including the endosomal protein EEA1. Together, scaled PhIP-seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Autoantibody discovery across monogenic, acquired, and COVID-19-associated autoimmunity with scalable PhIP-seq
- Date Crossref
- 27/10/2022
- Éditeur
- eLife Sciences Publications, Ltd
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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University of California Department of Biochemistry and Biophysics pays non établi dans la noticeUniversité ou école supérieure
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Chan Zuckerberg Initiative (United States) pays non établi dans la noticeEntreprise
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National Institutes of Health pays non établi dans la noticeOrganisme public
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National Institute of Allergy and Infectious Diseases pays non établi dans la noticeStructure de recherche
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Uppsala University Science for life Laboratory pays non établi dans la noticeUniversité ou école supérieure
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Karolinska University Hospital Department of Medicine pays non établi dans la noticeÉtablissement de santé
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Science for Life Laboratory pays non établi dans la noticeStructure de recherche
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Karolinska Institutet Department of Medicine pays non établi dans la noticeUniversité ou école supérieure
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Inserm pays non établi dans la noticeOrganisme public
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Université Paris Cité pays non établi dans la noticeUniversité ou école supérieure
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Great Ormond Street Hospital pays non établi dans la noticeÉtablissement de santé
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Hospital for Sick Children Department of Pediatrics pays non établi dans la noticeÉtablissement de santé
Department of Biochemistry and Biophysics — University of California, Chan Zuckerberg Initiative (United States) et National Institutes of Health, avec 9 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.