Genetics and Genomics of Late‐Onset Alzheimer′s Disease and Its Endophenotypes
Notice bibliographique
Résumé
Late-onset Alzheimer's disease is the most common cause of dementia in western societies. Despite remarkable achievements in human genetics over the years, in particular, technological advances in gene mapping and in statistical methods, to date only a small proportion of the genetic contribution to Alzheimer's disease can be explained. One reason for the difficulty in gene identification is that Alzheimer's disease is a complex disorder in which multiple genes with small individual effects as well as environmental factors are likely to contribute to disease risk as well as the various quantitative traits associated with the disease such as age-of-onset, cognition, neuropsychiatric symptoms, amyloid/tau pathology, or structural brain changes. Identifying the genetic factors modulating changes in these individual endophenotypes would help elucidate disease pathogenesis. In this special issue on genetics and genomics of Alzheimer's disease and its endophenotypes, we have invited a few papers that address this issue. The first two articles address the impact of APOE genotype, the best established Alzheimer's disease susceptibility gene, on neuropsychiatric endophenotypes associated with Alzheimer's disease including psychosis, late-life depression, anxiety, apathy, hallucinations, agitation, and aggressiveness. The third paper examines the effect of an intron 7 polymorphism in the amyloid precursor protein (APP) on the age of onset of Alzheimer's disease in persons with Down syndrome. The fourth and fifth papers explore mechanisms modulating components of the amyloid cascade pathway, focusing, in particular, on the APP intracellular domain (AICD), which is an end product of the proteolytic cleavage of APP by β- and γ-secretase. In the first of these two papers, Ansaloni et al. evaluated the effect of NTRK2 which encodes the TrkB receptor on APP metabolism and AICD levels. TrkB is a member of the tyrosine kinase receptor family and binds specifically to brain-derived neurotrophic factor (BDNF). The paper reports on the effects of different TrkB isoforms on APP metabolism in the human neuroblastoma cell line. In the other paper, Raychaudhuri et al. examined the impact of overexpression of AICD on expression of proteins that are part of pathways involved in neurodegeneration and neuroregeneration. Finally, the sixth paper reviews the findings of genome-wide association studies (GWAS) that tested whether SNPs in the top-ranked Alzheimer's disease-related candidate genes were associated with various brain imaging endophenotypes including the volumes of the temporal lobe, hippocampus, amygdale, and frontal lobe, as well as grey matter density, entorhinal cortex thickness, and white matter integrity. In addition, this article discusses multigene and more complex genetic models as a means to identify genetic contributions to Alzheimer's disease. Christiane Reitz Ekaterina Rogaeva Tatiana Foroud Lindsay A. Farrer
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 | 0,000 |
| 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 ».