Sex‐specific relationships among risk factors in those with Mild Cognitive Impairment or Alzheimer’s disease and healthy controls
Notice bibliographique
Résumé
Abstract Background Dementia incidence is projected to significantly increase, posing unique challenges to healthcare systems. Identifying non‐modifiable and modifiable risk factors (RF) is crucial, including sex‐specific factors, given the higher prevalence among females (60%). Here, we employed a network analysis to examine prominent RF in healthy controls compared to those with cognitive decline (CD), as well as the interrelationships and interactions of RF on CD. Additionally, sex‐specific networks were compared to identify unique RF and interactions present among sex. Method Healthy controls and CD individuals (mild cognitive impairment and Alzheimer’s dementia) were included from the Ontario Neurodegenerative Initiative and Canadian Consortium for Neurodegeneration in Aging (n = 339 total; 52% female; 72% CD). Non modifiable RF (e.g., age), modifiable RF (e.g., Framingham RF) and cognitive outcomes (e.g., executive functioning) were included in network modeling. Sex‐specific networks were created within the CD group and compared, as was between CD and healthy controls. Relationships among RF present in CD were identified and the strength. Nodes represented RF and edges are the pairwise dependency between RF, node centrality was investigated for the relative importance of each RF in the network. Result Healthy controls and CD had statistically different networks (M = 0.536; p = 0.02), and the CD network had greater connectivity (S = 2.69; p = 0.005)[Figure 1]. Male and female networks were statistically different within CD (M = 0.432; p = 0.027), and the male’s network had statistically greater connectivity than the females with CD (S = 1.24; p = 0.049)[Figure 2]. Within females, the CD had significantly greater connectivity (S = 0.90; p = 0.03)[Figure 3] than healthy controls and no difference in males (p > 0.05). Conclusion Our findings reveal unique sex‐specific network patterns of RF for CD, which further underscores the need for sex‐disaggregated analyses. The observed differences in heightened connectivity of typically studied RF in males, highlights a potential gap in the understanding of sex‐specific RF for Alzheimer’s. Future work should incorporate biomarkers, such as neuroimaging, to further comprehend sex‐specific RF for CD and to create the framework for precision medicine in targeting sex‐specific RF for CD.
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 | 0,001 | 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 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 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 ».