RNA aptamer reveals nuclear TDP-43 pathology is an early aggregation event that coincides withSTMN-2cryptic splicing and precedes clinical manifestation in ALS
Notice bibliographique
Résumé
Abstract TDP-43 is an aggregation-prone protein which accumulates in the hallmark pathological inclusions of amyotrophic lateral sclerosis (ALS). However, analysis of deeply-phenotyped human post-mortem samples has shown that TDP-43 aggregation, revealed by standard antibody methods, correlates poorly with symptom manifestation. Recent identification of cryptic-splicing events, such as the detection of Stathmin-2 ( STMN-2 ) cryptic exons, are providing evidence implicating TDP-43 loss-of-function as a potential driving pathomechanism, but the temporal nature of TDP-43 loss and its relation to the disease process and clinical phenotype is not known. To address these outstanding questions, we used a novel RNA aptamer, TDP-43 APT , to detect TDP-43 aggregation and used single molecule in situ hybridization to sensitively reveal TDP-43 loss-of-function and applied these in a deeply-phenotyped human post-mortem tissue cohort. We demonstrate that TDP-43 APT identifies pathological TDP-43, detecting aggregation events that cannot be detected by classical antibody stains. We show that nuclear TDP-43 pathology is an early event, occurring prior to cytoplasmic aggregation and is associated with loss-of-function measured by coincident STMN-2 cryptic splicing pathology. Crucially, we show that these pathological features of TDP-43 loss-of-function precede the clinical inflection point and are not required for region specific clinical manifestation. Furthermore, we demonstrate that gain-of-function in the form of extensive cytoplasmic aggregation, but not loss-of-function, is the primary molecular correlate of clinical manifestation. Taken together, our findings demonstrate implications for early diagnostics as the presence of STMN-2 cryptic exons and early TDP-43 aggregation events could be detected prior to symptom onset, holding promise for early intervention in ALS. Short Abstract Recent identification of cryptic-splicing events such as the detection of Stathmin-2 ( STMN-2 ) cryptic exons, are providing evidence implicating TDP-43 loss-of-function as a potential driving pathomechanism in amyotrophic lateral sclerosis (ALS). However, the temporal nature of TDP-43 loss and its relation to clinical phenotype is not known. Here, we used a novel RNA aptamer to detect TDP-43 aggregation and used single molecule ISH to sensitively reveal TDP-43 loss-of-function, applying these methods in a deeply-phenotyped human post-mortem tissue cohort. We show that nuclear TDP-43 pathology is an early event, that coincides with STMN-2 cryptic splicing. Crucially, we show that these pathological features of TDP-43 loss-of-function precede the clinical inflection point and are not required for region specific clinical manifestation. Furthermore, we demonstrate that gain-of-function, but not loss-of-function, is the primary molecular correlate of clinical manifestation. Taken together, our findings demonstrate implications for early diagnostics and intervention prior to symptom onset in ALS. Graphical Abstract
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».