WP1: Phenotype Driven Diagnosis. Validation of HPO terms in AID model and optimization of their diagnostic performances (IGG)

Validation with data from real life of the accuracy of HPO terms and hierarchy for the correct identification of IEI (namely autoinflammatory diseases) according to their genotype. SAID will be used as proof of concept.

• Source of clinical and genetic data: Eurofever registry for SAID (>4500 patients). More than 150 clinical terms combined with demographic and genetic data
• Clinical variables will be encoded with the new HPO terms [4]. Clinical terms missing in HPO will be retained for further integration.
• Evaluation of the performance of HPO terms and hierarchy for the proper identification of different IEIs using standard bioinformatic approaches: we’ll first compute the phenotypic similarity using graph-aware distances between the HPO terms assigned to each patient in Eurofever and all the HPO annotated diseases. Leveraging genetic data, we’ll assess the accuracy of bioinformatic tools for phenotype-driven genomic diagnostics [2,3]. The frequency of the HPO terms in the different disease groups from Eurofever will be integrated in the analysis.
• Accuracy of derived HPO terms for clinical characterization: patients will be randomly split into a TRAINING set (70%) and a VALIDATION set (30%). Univariable analyses will be run on the training set to screen clinical variables significantly associated with positivity to that disease and subsequently entered in a multivariable analysis. Then, a linear diagnostic classification score will be calculated. In the Validation set, the performance of the classification score will be assessed by testing its ability in discriminating positive from negative patients.
• The bioinformatic analysis described in C) will be repeated using the HPO terms weighted according to the coefficients obtained in D).
• Implementation of HPO terms with new terms not included in the revision [4].

WP2: Analysis of intra-familial phenotypic heterogeneity and genotype-phenotype correlation discrepancies in informative families derived from registries (UMCG, INSERM)

In SAID identical mutations can give different phenotypes even within families. In common inflammatory diseases GWAS has established polygenic risk score (PRS) as a robust analytic tool (CRP, IBD, RA and coronary heart disease) [11]. We will test the hypothesis that polygenetic (regulatory) factors associated with inflammatory disorders contribute to the different clinical phenotypes in patients from the Eurofever registry with exactly the same disease-causing DNA variant. There are currently 226 of such families. We will perform SNP array (n~100), epigenetic (n~50) and transcriptomic (NEATseq) (n~50) studies on these patients and perform multi layered analysis.

• SNP array (GSA) to study correlation between genetic variation and trait variation in families using PRSs.
• NEAT-seq to investigate the contribution of rare genomic (non-coding) variation and gene regulation to the heterogeneity. We will use a matched control population from Lifelines/EQTL consortium (UMCG) [12,13].
• Methylomics and miRNomics to identify methylation patterns or specific miRNA biomarkers. As a prototype the recently identified biomarker miRNA-326, validated to regulate inflammatory response in healthy subjects by Unit 3 will be explored.

WP3: Functional Characterization of VUS and methodologies for solving cases (WEHI, INSERM, IGG)

Pathogenicity of novel variants in the panels of known SAID-associated gene derived from Infevers database will be assessed by functional strategies. Infevers, created and maintained by Unit 3 (Montpellier), is a freely accessible online registry of curated variants identified to date in the genes responsible for 48 SAID [14]. We intend to validate variants of interest for which there is a broad phenotypic range and clinical impact where pathogenicity can be established. Although it is feasible to validate noncoding variants of interest by CRISPR mediated mutagenesis of the endogenous allele, it is still not possible to do this in a high-throughput fashion for cell lines relevant to the study of SAID. Instead, we propose to focus on gain-of-function non-synonymous coding variants for the autoinflammatory disease genes where there is the broadest spectrum of phenotypic variation, largest number of variants of interest with unknown pathogenicity, and a high-throughput biological assay. The genes that fulfill these criteria are MEFV, PSTPIP1, CDC42, NLRP1, NLRP3 and NLRC4, for which we can establish pathogenicity of VUS by assay of inflammasome activation. Based on the current data on Infevers, there are approximately 625 genetic variants to test, including all known validated mutations as positive controls in each assay. These mutations will be inserted into the plasmids of interest as arrayed in 96 well plates, overexpressed in 293T ASC-GFP reporter cell line using a high-throughput FACS readout. All pathogenic mutants should be spontaneously active due to overexpression, with the exception of FMF mutations which are hyper-responsive to stimuli such as TcdB for example. CDC42 and PSTPIP1 mutations require co-transfection with Pyrin to demonstrate pathogenicity. We propose to optimise our high-throughput processes with NLRP1, NLRC4, PSTPIP1 and CDC42 in year 1 (approximately 75 VUS), then proceed to NLRP3 in year 2 (approx. 200 VUS) and MEFV in year 3 (approx. 350 VUS). We are confident in the feasibility of this approach as we have already validated the assays and confirmed pathogenicity for several VUS in these genes (eg. [7,8]).

WP 4: Ethical, Legal and Social Aspects

WP4 will be devoted to Ethical, Legal and Social Aspects, with an Ethics Advisory Board, including both members of the consortium and external, independent scientific experts managing issues related to re-use and sharing of data from registries, setting up and managing the clinical study for intra-familial segregation analysis and all issues that may arise during the project.

WP 5: Dissemination and, Communication

In WP5, Exploitation, Dissemination and Communication, we will exploit project results by making publicly available for the scientific community the Software for the application of phenotype-based classification. Also, collected clinical data and functional testing results will be shared in Eurofevers and Infevers database. We will implement a project website, with a public area, for dissemination to the general public and a private area and create social media profiles. Partners will participate in congresses and symposia, organize workshop and public on peer review journals, Also PAO will organize events for patients and be active part of the dissemination strategy. A synergic dissemination partnership is envisioned with the International Society of Systemic Autoinflammatory diseases (ISSAID) and the European Network on Rare Primary Immunodeficiency, Autoinflammatory and Autoimmune Diseases (ERN-RITA). A Community engagement forum, to involve relevant stakeholders (medical community, scientific community, patients’ association, policy maker) will be established.

1. Papa R, Picco P, Gattorno M. The expanding pathways of autoinflammation: a lesson from the first 100 genes related to autoinflammatory manifestations. Adv Protein Chem Struct Biol 2020;120:1-44, PMID: 32085880
2. Robinson PN, Köhler S, Oellrich A, Sanger Mouse Genetics Project, Wang K, Mungall CJ, et al. Improved exome prioritization of disease genes through cross-species phenotype comparison. Genome research 2014;24;2;340-8, PMID: 24162188
3. Robinson PN, Ravanmehr V, Jacobsen JOB, Danis D, Aaron Zhang X, Carmody LC, et al. Interpretable Clinical Genomics with a Likelihood Ratio Paradigm. The American Journal of Human Genetics 2020 Sep 3;107(3):403-417, PMID: 32755546
4. Haimel M, Pazmandi J, Jiménez Heredia R, Dmytrus J, Köstel Bal S, Zoghi S, et al. Curation and expansion of Human Phenotype Ontology for defined groups of inborn errors of immunity. J Allergy Clin Immunol. 2021 May 12;149(1):369-378, PMID: 33991581
5. Van Gijn ME, Ceccherini I, Shinar Y, Carbo EC, Slofstra M, Arostegui JI, et al. New workflow for classification of genetic variants' pathogenicity applied to hereditary recurrent fevers by the International Study Group for Systemic Autoinflammatory Diseases (INSAID). J Med Genet. 2018 Mar 29;55(8):530-537, PMID: 29599418
6. Shinar Y, Ceccherini I, Rowczenio D, Aksentijevich I, Arostegui J, Ben-Chétrit E, et al. ISSAID/EMQN Best Practice Guidelines for the Genetic Diagnosis of Monogenic Autoinflammatory Diseases in the Next-Generation Sequencing Era. Clin Chem. 2020 Apr 1;66(4):525-536, PMID: 32176780
7. Masters SL, Lagou V, Jéru I, Baker PJ, Van Eyck L, Parry DA, et al. Familial autoinflammation with neutrophilic dermatosis reveals a regulatory mechanism of pyrin activation. Sci Transl Med. 2016 Mar 30;8(332):332ra45, PMID: 27030597
8. Moghaddas F, Zeng P, Zhang Y, Schützle H, Brenner S, Hofmann SR, et al. Autoinflammatory mutation in NLRC4 reveals a leucine-rich repeat (LRR)-LRR oligomerization interface. J Allergy Clin Immunol. 2018 Dec;142(6):1956-1967.e6, PMID: 29778503
9. Federici S, Sormani MP, Ozen S, Lachmann HJ, Amaryan G, Woo P, et al. Evidence-based provisional clinical classification criteria for autoinflammatory periodic fevers. Ann Rheum Dis. 2015 May;74(5):799-805, PMID: 25637003
10. Gattorno M, Hofer M, Federici S, Vanoni F, Bovis F, Aksentijevich I, et al. Classification criteria for autoinflammatory recurrent fevers. Ann Rheum Dis. 2019 Aug;78(8):1025-1032, PMID: 31018962
11. Hübenthal M, Löscher BS, Erdmann J, Franke A, Gola D, König IR, et al. Current Developments of Clinical Sequencing and the Clinical Utility of Polygenic Risk Scores in Inflammatory Diseases. Front Immunol. 2021 Jan 29;11:577677, PMID: 33633722
12. van der Wijst MGP, de Vries DH, Groot HE, Trynka G, Hon CC, Bonder MJ, et al. The singlecell eQTLGen consortium. Elife. 2020 Mar 9;9:e52155, PMID: 32149610
13. Scholtens S, Smidt N, Swertz MA, Bakker SJ, Dotinga A, Vonk JM, et al. Cohort Profile: Life-Lines, a three-generation cohort study and biobank. Int J Epidemiol. 2015 Aug;44(4):1172-80, PMID: 25502107
14. Sarrauste de Menthière C, Terrière S, Pugnère D, Ruiz M, Demaille J, Touitou I. INFEVERS: the Registry for FMF and hereditary inflammatory disorders mutations. Nucleic Acids Res. 2003 Jan 1;31(1):282-5, PMID: 12520003