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      Pericarditis and Autoinflammation: A Clinical and Genetic Analysis of Patients With Idiopathic Recurrent Pericarditis and Monogenic Autoinflammatory Diseases at a National Referral Center

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          Abstract

          Background

          Idiopathic recurrent pericarditis (IRP) is an orphan disease that carries significant morbidity, partly driven by corticosteroid dependence. Innate immune modulators, colchicine and anti‐interleukin‐1 agents, pioneered in monogenic autoinflammatory diseases, have demonstrated remarkable efficacy in trials, suggesting that autoinflammation may contribute to IRP. This study characterizes the phenotype of patients with IRP and monogenic autoinflammatory diseases, and establishes whether autoinflammatory disease genes are associated with IRP.

          Methods and Results

          We retrospectively analyzed the medical records of patients with IRP (n=136) and monogenic autoinflammatory diseases (n=1910) attending a national center (London, UK) between 2000 and 2021. We examined 4 genes ( MEFV, MVK, NLRP3, TNFRSF1A) by next‐generation sequencing in 128 patients with IRP and compared the frequency of rare deleterious variants to controls obtained from the Genome Aggregation Database. In this cohort of patients with IRP, corticosteroid dependence was common (39/136, 28.7%) and was associated with chronic pain (adjusted odds ratio 2.8 [95% CI, 1.3–6.5], P=0.012). IRP frequently manifested with systemic inflammation (raised C‐reactive protein [121/136, 89.0%] and extrapericardial effusions [68/136, 50.0%]). Pericarditis was observed in all examined monogenic autoinflammatory diseases (0.4%–3.7% of cases). Rare deleterious MEFV variants were more frequent in IRP than in ancestry‐matched controls (allele frequency 9/200 versus 2932/129 200, P=0.040).

          Conclusions

          Pericarditis is a feature of interleukin‐1 driven monogenic autoinflammatory diseases and IRP is associated with variants in MEFV, a gene involved in interleukin‐1β processing. We also found that corticosteroid dependence in IRP is associated with chronic noninflammatory pain. Together these data implicate autoinflammation in IRP and support reducing reliance on corticosteroids in its management.

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          Most cited references35

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          The mutational constraint spectrum quantified from variation in 141,456 humans

          Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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            ClinVar: improving access to variant interpretations and supporting evidence

            Abstract ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease, maintained at the National Institutes of Health. Interpretations of the clinical significance of variants are submitted by clinical testing laboratories, research laboratories, expert panels and other groups. ClinVar aggregates data by variant-disease pairs, and by variant (or set of variants). Data aggregated by variant are accessible on the website, in an improved set of variant call format files and as a new comprehensive XML report. ClinVar recently started accepting submissions that are focused primarily on providing phenotypic information for individuals who have had genetic testing. Submissions may come from clinical providers providing their own interpretation of the variant (‘provider interpretation’) or from groups such as patient registries that primarily provide phenotypic information from patients (‘phenotyping only’). ClinVar continues to make improvements to its search and retrieval functions. Several new fields are now indexed for more precise searching, and filters allow the user to narrow down a large set of search results.
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              CADD: predicting the deleteriousness of variants throughout the human genome

              Abstract Combined Annotation-Dependent Depletion (CADD) is a widely used measure of variant deleteriousness that can effectively prioritize causal variants in genetic analyses, particularly highly penetrant contributors to severe Mendelian disorders. CADD is an integrative annotation built from more than 60 genomic features, and can score human single nucleotide variants and short insertion and deletions anywhere in the reference assembly. CADD uses a machine learning model trained on a binary distinction between simulated de novo variants and variants that have arisen and become fixed in human populations since the split between humans and chimpanzees; the former are free of selective pressure and may thus include both neutral and deleterious alleles, while the latter are overwhelmingly neutral (or, at most, weakly deleterious) by virtue of having survived millions of years of purifying selection. Here we review the latest updates to CADD, including the most recent version, 1.4, which supports the human genome build GRCh38. We also present updates to our website that include simplified variant lookup, extended documentation, an Application Program Interface and improved mechanisms for integrating CADD scores into other tools or applications. CADD scores, software and documentation are available at https://cadd.gs.washington.edu.
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                Author and article information

                Contributors
                claire.peet@nhs.net
                Journal
                J Am Heart Assoc
                J Am Heart Assoc
                10.1002/(ISSN)2047-9980
                JAH3
                ahaoa
                Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
                John Wiley and Sons Inc. (Hoboken )
                2047-9980
                06 June 2022
                07 June 2022
                : 11
                : 11 ( doiID: 10.1002/jah3.v11.11 )
                : e024931
                Affiliations
                [ 1 ] National Amyloidosis Centre Royal Free London NHS Foundation Trust & Division of Medicine University, College London London United Kingdom
                [ 2 ] Department of Medical and Molecular Genetics King’s College London London United Kingdom
                Author notes
                [*] [* ] Correspondence to: Claire J. Peet, National Amyloidosis Centre, Royal Free London NHS Foundation Trust & Division of Medicine, University College London, Rowland Hill Street, London NW3 2PF, UK. Email: claire.peet@ 123456nhs.net

                Author information
                https://orcid.org/0000-0002-9682-8683
                https://orcid.org/0000-0002-3511-6789
                https://orcid.org/0000-0002-3042-3827
                https://orcid.org/0000-0002-1237-0557
                https://orcid.org/0000-0003-2432-5793
                https://orcid.org/0000-0001-8378-2498
                Article
                JAH37388
                10.1161/JAHA.121.024931
                9238712
                35658515
                a31dfc31-5ff9-47fb-9c93-e1b21d03c559
                © 2022 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 10 December 2021
                : 17 March 2022
                Page count
                Figures: 2, Tables: 6, Pages: 12, Words: 8391
                Funding
                Funded by: British Heart Foundation Clinical Research Training Fellowship
                Award ID: FS/19/67/34697
                Categories
                Original Research
                Original Research
                Pericardial Disease
                Custom metadata
                2.0
                June 7, 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.7 mode:remove_FC converted:14.06.2022

                Cardiovascular Medicine
                autoinflammation,inflammation,pericarditis,pericardial disease,genetic, association studies

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