Bridging Pleiotropic Mechanisms in Leprosy Type-1 Reactions and Neurodegenerative diseases
Notice bibliographique
Résumé
ABSTRACT Leprosy is an infectious disease that affects predominantly the skin and peripheral nervous system. Sudden episodes of hyperinflammation, known as Type 1 Reactions (T1R), are a main contributor to permanent nerve damage in leprosy. The genetic component associated with the neuro-inflammatory phenotype of T1R displays pleiotropic effects with Parkinson’s disease (PD) risk genes. In this study, we further explored the genetic overlap between PD and T1R and expanded the evaluation of pleiotropic effects between T1R and other neurodegenerative disorders. We first replicated the association of PD-risk rare variants in PRKN with T1R in Vietnamese leprosy patients ( P = 0.04; OR = 3.1). Additionally, we discovered large PRKN structural variants only in T1R-affected participants when compared to T1R-free leprosy patients. Analysis of 24 PD associated genes revealed compound effects between rare protein-altering variants and T1R in the interacting genes PRKN/PINK1 ( P = 2.7 −05 ; OR = 4.0) and a combination of rare/low frequency variants in the LRRK2/GAK pair ( P = 6.7 −05 ; OR = 0.54). These findings validated a genetic overlap between T1R and PD with two distinct axes, one of shared risk via PRKN/PINK1 and a second of antagonistic pleiotropic effects via LRRK2/GAK . When testing an additional 94 genes associated with neurodegenerative diseases other than PD, we identified variants in the amyotrophic lateral sclerosis (ALS) disease-risk gene TBK1 associated with T1R ( P = 0.004; OR = 12.9). All TBK1 mutations in T1R-affected participants located to the ubiquitin-like TBK1 domain. PRKN , PINK1 and TBK1 play a critical role in autophagy and in the host immune response to Mycobacteria . Our results highlight shared biological processes between leprosy and neurodegenerative diseases, which may indicate candidate drugs for repurposing for a more favorable T1R management. AUTHORS SUMMARY In this study, we investigated the shared genetic component between hyperinflammatory processes in leprosy and neurodegenerative diseases. A subset of leprosy patients develop sudden episodes of severe inflammation, known as type-1 reactions (T1R), which frequently lead to permanent nerve injury. Here, we aimed to identify key genetic mediators of nerve damage shared with diseases of the central nervous system and T1R, which affects the peripheral nervous system. Previous studies showed Parkinson’s disease (PD) risk genes associated with T1R. To explore this further, we analyzed 24 well-established PD-risk genes in over 800 Vietnamese leprosy patients. We found that rare mutations in PRKN and PINK1 were more frequent in individuals experiencing T1R. These genes are involved in mitochondrial quality control and responses to intracellular pathogens. Inversely, the LRRK2 and GAK PD-risk genes were associated with protection from T1R. This pattern suggested two independent biological processes influencing T1R susceptibility. Our findings highlight a shared genetic component between PD and T1R and suggest that therapies developed for PD may be repurposed for T1R management. Our results underscore the value of cross-disease research to uncover new therapeutic strategies, particularly for neglected diseases with limited treatments or therapies with frequent adverse effects.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».