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Enregistrement W4389937002 · doi:10.1101/2023.12.18.23300119

Type 1 reaction leprosy patients display distinct immune-regulatory capacity before onset of symptoms

2023· preprint· en· W4389937002 sur OpenAlexafffund
Wilian Correa-Macedo, Monica Dallmann-Sauer, Marianna Orlova, Jérémy Manry, Vinicius M. Fava, Nguyễn Thu Hương, Nguyen Ngoc Ba, Nguyen Van Thuc, Vu Hong Thai, Erwin Schurr

Notice bibliographique

RevuemedRxiv · 2023
Typepreprint
Langueen
DomaineMedicine
ThématiqueLeprosy Research and Treatment
Établissements canadiensMcGill UniversityMcGill University Health Centre
Organismes subventionnairesMcGill University
Mots-clésMycobacterium lepraeLeprosyImmune systemTranscriptomeBiologyImmunologyMacrophageIn vitroGeneticsGene expressionGene

Résumé

récupéré en direct d'OpenAlex

Abstract Leprosy is a chronic disease of the skin and peripheral nerves caused by Mycobacterium leprae . A major public health and clinical problem are leprosy reactions, which are inflammatory episodes that often contribute to nerve damage and disability. Type I reversal reactions (T1R) can occur after microbiological cure of leprosy and affect up to 50% of leprosy patients. Early intervention to prevent T1R and, hence, nerve damage, is a major focus of current leprosy control efforts. In a prospective study, we enrolled and collected samples from 32 leprosy patients before the onset of T1R. Whole blood aliquots were challenged with M. leprae sonicate or media and total RNA was extracted. After a three-year follow-up, the transcriptomic response was compared between cells from 22 patients who remained T1R-free and 10 patients who developed T1R during that period. Our analysis focused on differential transcript (i.e. isoform) expression and usage. Results showed that, at baseline, cells from T1R-destined and T1R-free subjects had no main difference in their transcripts expression and usage. However, the cells of T1R patients displayed a transcriptomic immune response to M. leprae antigens that was significantly different from the one of cells from leprosy patients who remained T1R-free. Transcripts with significantly higher upregulation in the T1R-destined group, compared to the cells from T1R-free patients, were enriched for pathways and GO terms involved in response to intracellular pathogens, apoptosis regulation and inflammatory processes. Similarly, transcript usage analysis pinpointed different transcript proportions in response to the in-vitro challenge of cells from T1R-destined patients. Hence, transcript usage in concert with transcript expression suggested a dysregulated inflammatory response including increased apoptosis regulation in the peripheral blood cells of T1R-destined patients before the onset of T1R symptoms. Combined, these results provided detailed insight into the pathogenesis of T1R. Author Summary The prevention and clinical management of type 1 reactions (T1R) remain an important unmet need to reduce nerve damage in leprosy patients. It is not known why 30-50% of leprosy patients will develop T1R. This knowledge gap underlies the need for a better mechanistic understanding of T1R that could lead to biomarker candidates to identify leprosy patients who are at high risk of developing T1R. Here, we used a prospective design in which leprosy patients were enrolled before the onset of T1R.Whole blood samples were obtained at enrollment, aliquots were left unstimulated or were stimulated M. leprae antigens and total RNA was extracted. Patients were followed for three years at which time 10 out of 32 participants had developed T1R. Subsequent transcript expression and usage analyses revealed that groups differed little in their isoform landscape at baseline. Following stimulation, transcriptomic response differences became pronounced. Transcripts with higher response in T1R group preferentially involved genes of intracellular defense and inflammatory pathways. Among these transcripts, non-coding ones had higher frequency in T1R. Our study provided new insights into the T1R pathogenesis by suggesting a role for non-coding transcripts into the immune dysregulations of T1R and providing additional candidate genes and their isoforms to be further investigated.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,034
Tête enseignante GPT0,299
Écart entre enseignants0,265 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2023
Routes d'admission2
Résumé présentoui

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