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Record W4286559764 · doi:10.3389/fimmu.2022.926175

TRAPS mutations in Tnfrsf1a decrease the responsiveness to TNFα via reduced cell surface expression of TNFR1

2022· article· en· W4286559764 on OpenAlexaff
Takahiko Akagi, Sumie Hiramatsu, Kenta Ikeda, Hiroyasu Hirano, Shoko Tsuji, Ayano Yahagi, Masanori Iseki, Makoto Matsuyama, Tak W. Mak, Nakano Kazuhisa, Katsuhiko Ishihara, Yoshitaka Morita, Tomoyuki Mukai

Bibliographic record

VenueFrontiers in Immunology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsUniversity of Toronto
FundersJapan Society for the Promotion of ScienceMishima Kaiun Memorial FoundationKawasaki Medical SchoolEli Lilly JapanEli Lilly and Company
KeywordsTumor necrosis factor alphaMutantProinflammatory cytokineMutationLipopolysaccharideBiologyWild typeIn vivoIn vitroReceptorImmunologyMolecular biologyInflammationGeneticsGene

Abstract

fetched live from OpenAlex

Tumor necrosis factor (TNF) receptor-associated periodic syndrome (TRAPS) is an autoinflammatory periodic fever syndrome associated with heterozygous mutations in TNFRSF1A, which encodes TNF receptor type I (TNFR1). Although possible proinflammatory mechanisms have been proposed, most previous studies were performed using in vitro overexpression models, which could lead to undesirable inflammatory responses due to artificial overexpression. It is crucial to reproduce heterozygous mutations at physiological expression levels; however, such studies remain limited. In this study, we generated TRAPS mutant mice and analyzed their phenotypes. Three Tnfrsf1a mutant strains were generated by introducing T79M, G87V, or T90I mutation. T79M is a known mutation responsible for TRAPS, whereas G87V is a TRAPS mutation that we have reported, and T90I is a variant of unknown significance. Using these murine models, we investigated whether TRAPS mutations could affect the inflammatory responses in vivo and in vitro. We found that none of the mutant mice exhibited detectable inflammatory phenotypes under standard housing conditions for 1 year. Interestingly, TRAPS mutant (T79M and G87V) mice had reduced mortality rates after the administration of lipopolysaccharide (LPS) and D-galactosamine, which induce TNFα-dependent lethal hepatitis. Moreover, TRAPS mutations strongly suppressed the development of TNFα-mediated arthritis when crossed with human TNFα transgenic mice. In in vitro primary bone marrow-derived macrophage cultures, the T79M and G87V mutations attenuated the inflammatory responses to TNFα compared with the wild-type, whereas these mutations did not alter the responsiveness of these cells to LPS. The T90I mutant macrophages behaved similarly to wild type in response to LPS and TNFα. The TNFR1 levels were increased in whole-cell lysates of TRAPS mutant macrophages, whereas the cell surface expression of TNFR1 was significantly decreased in TRAPS mutant macrophages. Taken together, TRAPS mutations did not augment the inflammatory responses to TNFα and LPS; instead, they suppressed the response to TNFα via decreased cell surface expression of TNFR1. The stimulation of lymphotoxin-α, adenosine triphosphate, and norepinephrine in primary macrophages or various stimuli in murine splenocytes did not induce detectable inflammatory responses. In conclusion, TRAPS mutations suppressed responsiveness to TNFα, and TRAPS-associated inflammation is likely induced by unconfirmed disease-specific proinflammatory factors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.218
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2022
Admission routes1
Has abstractyes

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