Dynamic disequilibrium-based pathogenicity model in mutated pyrin’s B30.2 domain—Casp1/p20 complex

Fayez, Alaaeldin; Eldeen, Ghada Nour; Zarouk, Waheba A.; Hamed, Khaled H.; Ramadan, Abeer; Foda, Bardees M.; Kobesiy, Maha M.; Zekrie, Mai E; Lotfy, Randa; Sokkar, Mona F; El-Bassyouni, Hala T.

doi:10.1186/s43141-022-00300-z

Cited by 6 publications

(4 citation statements)

References 26 publications

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“…The B30.2 domain has been shown to interact with caspase-1 leading to the hypothesis that the B30.2 domain could regulate pyrin inflammasome through caspase-1 inhibition [ 25 – 27 ]. Yet, the above results demonstrate that the B30.2 domain regulates pyrin activation upstream of ASC speck formation suggesting that it may act independently of caspase-1.…”

Section: Resultsmentioning

confidence: 99%

Mutations in the B30.2 and the central helical scaffold domains of pyrin differentially affect inflammasome activation

et al. 2023

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Familial Mediterranean Fever (FMF) is the most common monogenic autoinflammatory disorder. FMF is caused by mutations in the MEFV gene, encoding pyrin, an inflammasome sensor. The best characterized pathogenic mutations associated with FMF cluster in exon 10. Yet, mutations have been described along the whole MEFV coding sequence. Exon 10 encodes the B30.2 domain of the pyrin protein, but the function of this human-specific domain remains unclear. Pyrin is an inflammasome sensor detecting RhoA GTPase inhibition following exposure to bacterial toxins such as TcdA. Here, we demonstrate that the B30.2 domain is dispensable for pyrin inflammasome activation in response to this toxin. Deletion of the B30.2 domain mimics the most typical FMF-associated mutation and confers spontaneous inflammasome activation in response to pyrin dephosphorylation. Our results indicate that the B30.2 domain is a negative regulator of the pyrin inflammasome that acts independently from and downstream of pyrin dephosphorylation. In addition, we identify the central helical scaffold (CHS) domain of pyrin, which lies immediately upstream of the B30.2 domain as a second regulatory domain. Mutations affecting the CHS domain mimic pathogenic mutations in the B30.2 domain and render the pyrin inflammasome activation under the sole control of the dephosphorylation. In addition, specific mutations in the CHS domain strongly increase the cell susceptibility to steroid catabolites, recently described to activate pyrin, in both a cell line model and in monocytes from genotype-selected FMF patients. Taken together, our work reveals the existence of two distinct regulatory regions at the C-terminus of the pyrin protein, that act in a distinct manner to regulate positively or negatively inflammasome activation. Furthermore, our results indicate that different mutations in pyrin regulatory domains have different functional impacts on the pyrin inflammasome which could contribute to the diversity of pyrin-associated autoinflammatory diseases.

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Section: Resultsmentioning

confidence: 99%

Mutations in the B30.2 and the central helical scaffold domains of pyrin differentially affect inflammasome activation

et al. 2023

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“…According to our model outcomes, LP variants are 2.5 times more likely to be located in domains than LB variants, which contradicts the findings of Accetturo et al 9 , who discovered random distribution of LB and LP mutations. Recent studies, however, indicate distributions of pathogenic variants compatible with particular domains, such as the majority of exon 10 pathogenic variants being in SPRY domains 7,45 . In our study, SPRY domain mutations were 2.5 times more likely to be pathogenic than benign.…”

Section: Implemented 5 ML Methods On 216mentioning

confidence: 99%

THREE STEPS NOVEL HARD MARGIN ENSEMBLE MACHINE LEARNING METHOD CLASSIFIES UNCERTAINMEFVGENE VARIANTS

Alay

Demir²,

Kirişçi

2023

Preprint

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Introduction: The International Study Group for Systemic Autoinflammatory Diseases (INSAID) consensus criteria revealed that the clinical outcomes of more than half of the MEFV gene variants are uncertain. We aimed to detect more accurate classifications of MEFV variants while simultaneously reducing MEFV variant uncertainty. Material-Methods: We extracted variants of the MEFV gene from the infevers database. We then determined the optimal number of in silico instruments for our model. On the training dataset, we implemented seven machine learning algorithms on MEFV gene variants with known clinical effects. We evaluated the effectiveness of our model in three steps: First, we performed machine-learning algorithms on the training dataset and implemented those with a prediction accuracy of greater than 90 percent. Second, we compared our gene-level and protein-level prediction results. Finally, we compared our prediction results to clinical outcomes. Results: Our analysis included 266 of 381 MEFV gene variants and four computational tools (Revel, SIFT, MetaLR, and FATHMM). In our training dataset, the accuracy of three machine learning algorithms (RF: 100%, CRAT: 100%, and KNN: 91%) exceeded the threshold value. Thus, the dataset contained 134 likely pathogenic (LP) variants and 132 likely benign (LB) variants. We found that B30.2 domain variants were 2.5 times more likely to be LP than LB (χ2:12.693, p < 0.001, OR: 2.595 [1.532-4.132]. Discussion: Considering that the clinical effects of 60% of MEFV gene variants have not yet been determined, a combined evaluation of our methods and patients' clinical manifestations significantly simplifies the interpretation of unknown variants.

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“…A recent meta-analysis of Turkish and Iranian GWAS [ 57 ] found strong association of MEFV in AS patients, particularly in B27 negative cases, which may point to a compensatory role of MEFV in the absence of B27. The MEFV gene product, pyrin, has a variety of important functions potentially relevant to inflammatory disease causation, including in innate immunity, inflammatory responses (particularly to the interferon gamma pathway) and autophagy [ 58 , 59 ].…”

Section: Genetic Commonality With Extra-articular Manifestationsmentioning

confidence: 99%

The genetic backbone of ankylosing spondylitis: how knowledge of genetic susceptibility informs our understanding and management of disease

et al. 2022

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Ankylosing spondylitis (AS) is a seronegative, chronic inflammatory arthritis with high genetic burden. A strong association with HLA-B27 has long been established, but to date its contribution to disease aetiology remains unresolved. Recent insights through genome wide studies reveal an increasing array of immunogenetic risk variants extraneous to the HLA complex in AS cohorts. These genetic traits build a complex profile of disease causality, highlighting several molecular pathways associated with the condition. This and other evidence strongly implicates T-cell-driven pathology, revolving around the T helper 17 cell subset as an important contributor to disease. This prominence of the T helper 17 cell subset has presented the opportunity for therapeutic intervention through inhibition of interleukins 17 and 23 which drive T helper 17 activity. While targeting of interleukin 17 has proven effective, this success has not been replicated with interleukin 23 inhibition in AS patients. Evidence points to significant genetic diversity between AS patients which may, in part, explain the observed refractoriness among a proportion of patients. In this review we discuss the impact of genetics on our understanding of AS and its relationship with closely linked pathologies. We further explore how genetics can be used in the development of therapeutics and as a tool to assist in the diagnosis and management of patients. This evidence indicates that genetic profiling should play a role in the clinician’s choice of therapy as part of a precision medicine strategy towards disease management.

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Dynamic disequilibrium-based pathogenicity model in mutated pyrin’s B30.2 domain—Casp1/p20 complex

Cited by 6 publications

References 26 publications

Mutations in the B30.2 and the central helical scaffold domains of pyrin differentially affect inflammasome activation

Mutations in the B30.2 and the central helical scaffold domains of pyrin differentially affect inflammasome activation

THREE STEPS NOVEL HARD MARGIN ENSEMBLE MACHINE LEARNING METHOD CLASSIFIES UNCERTAINMEFVGENE VARIANTS

The genetic backbone of ankylosing spondylitis: how knowledge of genetic susceptibility informs our understanding and management of disease

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