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Enregistrement W2116854643 · doi:10.1093/brain/awu018

Lafora’s odyssey reaches a mysterious port of call

2014· letter· en· W2116854643 sur OpenAlexaff
Berge A. Minassian

Notice bibliographique

RevueBrain · 2014
Typeletter
Langueen
DomaineMedicine
ThématiqueGlycogen Storage Diseases and Myoclonus
Établissements canadiensSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésLafora diseaseProgressive myoclonus epilepsyMyoclonusPathologyNeuroscienceMedicineBiologyGenetics

Résumé

récupéré en direct d'OpenAlex

In 1911, the Spanish neurologist-pathologist Gonzalo Lafora, working at the then Government Hospital for the Insane in Washington DC, first described the progressive myoclonus epilepsy that would later bear his name (Lafora, 1911). The journey to understand this disease started with Lafora’s detailed neuropathological description of the large and profuse inclusions (Fig. 1) that would come to be known as Lafora bodies. The odyssey has visited many a shore, and the latest and most mysterious is revealed by Javier Gayarre et al. (2014) in this issue of Brain. Lafora bodies as drawn by Lafora in his original manuscript (Lafora, 1911). Whereas the ‘amyloid’ plaques of Alzheimer’s disease are not in fact amyloid (starch), Lafora bodies, by contrast, are. Lafora bodies are composed of hyperphosphorylated and malformed glycogen molecules. These abnormal starch-like polyglucosans aggregate to form insoluble masses, which over time accumulate inside neuronal somata and dendrites. Lafora disease is caused by loss-of-function mutations in the EPM2A (laforin) or EPM2B (malin) genes (Minassian et al., 1998; Chan et al., 2003). Laforin is the only known glycogen phosphatase. Its absence leads to hyperphosphorylation of glycogen, which correlates with a gradual accumulation of polyglucosans, strongly suggesting that glycogen hyperphosphorylation underlies polyglucosan formation (Tagliabracci et al., 2008). Laforin’s structure resembles that of the plant starch phosphatase SEX4, which is crucial to starch metabolism; its absence leading to a pathological excess of starch. Laforin complements SEX4 and rescues the starch-excess phenotype of SEX4-deficient plants (Gentry et al., 2007). The phosphatase activity of laforin is its only known enzymatic function. Together, these findings suggest a central role for impaired glycogen dephosphorylation by laforin in Lafora disease pathogenesis. As for the enzyme behind glycogen phosphorylation, despite many efforts to identify it, that shore remains unattained. Malin, meanwhile, has been shown to be a ubiquitin E3 ligase. Paradoxically, malin’s only unequivocal target for proteasomal degradation turns out to be none other than laforin (Gentry et al., 2005). How can the absence of malin lead to the same disease as does absence of the protein, laforin, that malin destroys? A solution to this conundrum was suggested by recent work which revealed that, in the absence of malin, laforin accumulates in glycogen and may thus disturb the spherical architecture that is essential for glycogen’s solubility (Tiberia et al., 2012). As such, excess phosphate in glycogen (as a result of laforin deficiency) or excess laforin in glycogen (due to malin deficiency) would have the same effect on glycogen, reducing its solubility and leading it to precipitate and form Lafora bodies. In the current issue of Brain, Gayarre et al. (2014) guide the ship into a new night. They overexpress, in laforin-deficient mice, a form of laforin mutated to lack phosphatase activity, and show that this rescues murine Lafora disease. The inescapable conclusion is that the phosphatase function of laforin is dispensable, and that it is some other function of the laforin-malin complex that is relevant to the disease. The function that Gayarre et al. (2014) highlight, namely autophagy, has been of late a frequent stop in the Lafora voyage, and indeed in the exploration of many other neurodegenerative diseases. Autophagy is disturbed in Lafora disease (Criado et al., 2012), and it has been suggested that defective autophagy impairs the ability of cells to rid themselves of abnormal aggregates, such as malformed glycogen. Gayarre et al. (2014) advance the tantalizing idea that glycogen, in common with proteins, can sometimes be naturally misshapen. This would lead it to precipitate and aggregate, and indeed to accumulate were it not for mechanisms involving laforin and malin that act to clear such deposits. Before accepting autophagy as a port of call of the Lafora saga, one must however keep an open mind. Is it possible that laforin’s sole enzymatic activity is unnecessary? The vicissitudes of the Lafora epic will certainly continue to lead us to exciting lands of milk and honey most relevant to the understanding of neuronal function. But what of the patients who suffer the intractable and continuous seizures, hallucinations and dementia of Lafora disease? The polyglucosans that cause havoc in Lafora disease, irrespective of their shape or origins, are in the end nothing more than chains of glucose. One and only one enzyme, glycogen synthase, manufactures chains of glucose, and recent studies have shown that downregulation of glycogen synthesis prevents Lafora disease in mice (Pederson et al., 2014). While the Lafora pathogenesis ship feels its way through the unknown, a shortcut to safe harbour, namely glycogen synthesis downregulation, may well be open for patients with the disease. Gonzalo Lafora would have appreciated the progress made by the explorers so far.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Étude de cas · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil0,022

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0040,002
Communication savante0,0020,004
Science ouverte0,0010,001
Intégrité de la recherche0,0160,017
Charge utile insuffisante (le modèle a refusé de juger)0,0070,002

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 Opus0,023
Tête enseignante GPT0,268
Écart entre enseignants0,245 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeÉtude de cas
Domainenon disponible
GenreCommentaire

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

En bref

Citations1
Publié2014
Routes d'admission1
Résumé présentoui

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