Precision Medicine Approach to Alzheimer’s Disease: Successful Proof-of-Concept Trial
Notice bibliographique
Résumé
Abstract Importance Effective therapeutics for Alzheimer’s disease and mild cognitive impairment are needed. Objective To determine whether a precision medicine approach to Alzheimer’s disease and mild cognitive impairment, in which potential contributors to cognitive decline are identified and targeted therapeutically, is effective enough in a proof-of-concept trial to warrant a larger, randomized, controlled clinical trial. Rationale Previous clinical trials for Alzheimer’s disease have pre-determined a single treatment modality, such as a drug candidate or therapeutic procedure, that may be unrelated to the primary drivers of the neurodegenerative process. Therefore, increasing data set size to include the potential contributors to cognitive decline for each patient, and addressing the identified potential contributors, may represent a more effective therapeutic strategy. Hypothesis Alzheimer’s disease is a multi-factorial network dysfunction that results from a chronic or repeated insufficiency of support for a neuroplasticity network; thus factors that increase demand—such as infections or toxin exposure—or reduce support—such as reduced energetics or trophic support—may contribute to the neurodegenerative process. Rectifying this hypothesized network dysfunction represents a rational approach to the treatment of the cognitive decline associated with Alzheimer’s disease and mild cognitive impairment. Design Twenty-five patients with Alzheimer’s disease or mild cognitive impairment, with Montreal Cognitive Assessment (MoCA) scores of 19 or higher, were evaluated for markers of inflammation, chronic infection, dysbiosis, insulin resistance, protein glycation, vascular disease, nocturnal hypoxemia, hormone insufficiency or dysregulation, nutrient deficiency, toxin or toxicant exposure (metals, organic toxicants, and biotoxins), genetic predisposition to cognitive decline, and other biochemical parameters associated with cognitive decline. Brain magnetic resonance imaging with volumetrics was performed at baseline and study conclusion. Patients were treated for nine months with a personalized, precision medicine protocol that addressed each patient’s identified potentially contributory factors, and cognition was assessed at t = 0, 3, 6, and 9 months. Trial registration and IRB approval The clinical trial was registered at clinicaltrials.gov ( NCT03883633 ), 1 and approved by the Advarra IRB. Support for the trial The trial was supported by a grant from the Four Winds Foundation via Evanthea, LLC, and we are grateful to Diana Merriam and Gayle Brown for their interest, discussions, and support. Main Outcome Measures Trained external raters evaluated the study subjects with the Montreal Cognitive Assessment (MoCA), CNS Vital Signs (a computerized cognitive assessment battery), AQ-21 (a subjective scale completed by the significant other or study partner), and AQ-C change scale (a subjective scale of cognitive improvement or decline, completed by the significant other or study partner). Follow-up brain MRI with volumetrics was carried out at the completion of the trial. Results All outcome measures revealed improvement: statistically highly significant improvement in MoCA scores, CNS Vital Signs Neurocognitive Index, and AQ-C were documented. No serious adverse events were recorded. Conclusions and Relevance Based on the cognitive improvements observed in this study of patients with Alzheimer’s disease or mild cognitive impairment, a larger, randomized, controlled trial of the precision medicine therapeutic approach described herein is warranted.
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 | 0,015 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».