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Enregistrement W4324146571 · doi:10.3389/fnagi.2023.1168062

Editorial: Additive or synergistic impacts of sleep, circadian rhythm disturbances and other modifiable risk factors on established and novel plasma biomarkers of Alzheimer's disease pathology

2023· editorial· en· W4324146571 sur OpenAlexaboutno aff
Omonigho M. Bubu, Korey Kam, Ankit Parekh, Indu Ayappa

Notice bibliographique

RevueFrontiers in Aging Neuroscience · 2023
Typeeditorial
Langueen
DomaineMedicine
ThématiqueAlzheimer's disease research and treatments
Établissements canadiensnon disponible
Organismes subventionnairesNational Heart, Lung, and Blood InstituteNational Institute on AgingAmerican Academy of Sleep Medicine FoundationAmerican Academy of Sleep MedicineBrightFocus FoundationNational Institutes of HealthCentre de Coopération Internationale en Recherche Agronomique pour le DéveloppementNational Institute for Occupational Safety and HealthAlzheimer's Association
Mots-clésCircadian rhythmDiseaseAlzheimer's diseaseMedicineNeuroscienceInternal medicineGerontologyPsychology

Résumé

récupéré en direct d'OpenAlex

What remains unexamined are the combined effects of sleep disturbances/disorders, circadian rhythm abnormalities and other commonly co-occurring modifiable risk factors on biomarkers of AD pathology. 10,[13][14][15][16] Further, methods to examine the confluence of these exposures have been limited, with potential causal mechanisms linking these synergistic exposures to AD progression yet to be fully understood. This research topic aimed to more deeply examine and understand interactions between sleep, circadian rhythm abnormalities and modifiable risk factors on both established and more importantly, novel plasma AD markers including markers of inflammation and axonal integrity.In our first paper, Carvalho and colleagues https://www.frontiersin.org/articles/10.3389/fnagi.2022.930315/full examined whether sleepiness as measured by the Epworth Sleepiness Scale (ESS) is associated with other biomarkers of Alzheimer's disease (AD), axonal integrity, and inflammation, which may also contribute to neurodegeneration and cognitive decline. This was a cross-sectional analysis of data from 260 cognitively unimpaired adults (>60 years) from the Mayo Clinic Study of Aging.Participants had CSF quantification of AD biomarkers (Aβ42, p-tau, p-tau/Aβ42) in addition to at least one of the following biomarkers [neurofilament light chain (NfL) interleukin-6 (IL-6), IL-10, and tumor necrosis factor-α (TNF-α)]. Adjusting for age, sex, APOε4 status, body mass index, hypertension, dyslipidemia, and prior diagnosis of obstructive sleep apnea. Higher ESS scores were associated with higher CSF IL-6 and NfL, but not with the other CSF biomarkers. A sensitivity analyses however showed ESS scores associated with CSF p-tau/Aβ42 in amyloid positive participants. The findings suggest synergistic associations possibly exist between sleepiness and amyloid levels on p-tau/Aβ42 and this in turn may contribute to vulnerability to sleep disturbance, which may further amyloid accumulation in a feed-forward loop process.Recently, others and we respectively showed vascular risk factors and disturbed sleep each act synergistically with Aβ burden to promote cognitive decline. [17][18][19][20] In addition, Aβ burden and neuroimaging evidence of CVD pathology show additive effects on cognition. [21][22][23][24][25] Xiong and Lei https://www.frontiersin.org/articles/10.3389/fnagi.2022.944283/full provide a timely review on recent advances in our understanding of how sleep and circadian disorders can influence Alzheimer's disease pathology. Firstly, this review covers basic science investigations of how sleep and circadian disturbance can alter both well-known pathological hallmarks of AD: amyloid beta and tau, as well as lesser-known contributions from oxidative stress, blood-brain barrier leakage and brain region susceptibility to sleep fragmentation. Secondly, Xiong and Lei highlight the potential of both non-drug interventions of sleep and circadian disorders such as bright light/physical exercise as well as the effect of more common sleep drug interventions such as melatonin, benzodiazepines and DORAs. Importantly, the review notes that we have made substantial progress in our understanding of the basic mechanisms that control the biological clock and the neural circuits involved in sleep. However, we know very little about how these systems are affected in the brain in neurodegenerative diseases, especially as it relates to with other AD modifiable risk factors including sex, APOE4 status, depression and drug use.We are delighted to publish a report by Nick and colleagues https://www.frontiersin.org/articles/10.3389/fnagi.2022.1025402/full who add to our field the finding of an important neuronal susceptibility to chronic sleep fragmentation. In this paper, the authors examined the role of hypocretin/orexin (HCRT) in hippocampal and locus coeruleus neuronal injury in response to chronic fragmentation of sleep in mice with and without HCRT.Nick et al show that with sleep fragmentation, the presence of HCRT increases amyloid beta while decreasing cholinergic axon projections to the hippocampus, while not influencing sleep disruption effects on locus coeruleus neurons. Their report identifies a molecular mechanism into sleep loss induced neural injury in the hippocampus and provides a rationale to assess the role of HCRT antagonists to prevent such sleep loss induced hippocampal injury.Our final paper in this topic by Turner and colleagues https://www.frontiersin.org/articles/10.3389/fnagi.2022.1017521/full determined the interactive associations of apolipoprotein e4 (APOE-e4), and obstructive sleep apnea (OSA) on biomarkers of Alzheimer's disease and examined for racial/ethnic differences of this association. This study utilized baseline data from 1,387 participants (mean age = 69.73 ± 8.32; 58.6% female; 13.7% Black/African American), 18.4% of the sample had sleep apnea, and 37.9% were APOE-e4 carriers) in the National Alzheimer's Coordinating Center Uniform Dataset (NACC UDS).Biomarkers of AD assessed included CSF Aβ42, hippocampal volume, and white matter hyper intensities (WMH). Performance on the Montreal Cognitive Assessment (MOCA) was used as a surrogate for cognition. Findings showed independent associations of OSA and APOE-e4 with CSF Aβ42, WMH volume and MOCA scores. OSA and APOE-e4 did not interact to affect amyloid pathology; however, in Black/African American subjects, OSA and APOE-e4 interacted with significant associations with WMH and hippocampal volumes. These findings bolster the need for further research exploring the combined effects of modifiable and fixed risk factors for AD, especially in Black/African American populations, where this interaction may partially mediate increased levels of risk.Overall, this special topic section presents evidence-showing associations between sleepiness and neuronal injury markers with sleepiness and amyloid levels showing possible synergistic effects on p-tau/Aβ42. It presents evidence demonstrating that under conditions of sleep fragmentation, hypocretin/orexin is essential for the accumulation of amyloid-β, using WT mice models induced with chronic fragmentation. It presents evidence showing that OSA and APOE-e4 are interactively associated with WHM in Black/African Americans. More importantly, the review highlights the need for more studies that provide a more comprehensive understanding of the mechanisms by which specific neurodegenerative diseases and pathogenic proteins affect the circadian rhythm and sleep system, as well as the interactions linking sleep, and the circadian rhythm system with potential causal mechanisms resulting in synergistic exposure effects on AD progression. This topic remains an open and active area of research because of the continued need to both understand how and when to modify identifiable risk factors; not only across the general population but also with appropriate care and precision among minoritized populations whom may suffer from a combination of under-characterization and under-appreciation in terms of AD risk.

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)0,005
score de la tête « metaresearch » (Gemma)0,016
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,017
Score d'incertitude au seuil0,055

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,016
Méta-épidémiologie (sens strict)0,0040,001
Méta-épidémiologie (sens large)0,0040,003
Bibliométrie0,0020,001
Études des sciences et des technologies0,0020,002
Communication savante0,0040,003
Science ouverte0,0040,001
Intégrité de la recherche0,0110,013
Charge utile insuffisante (le modèle a refusé de juger)0,0170,010

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 Opus0,021
Tête enseignante GPT0,294
Écart entre enseignants0,272 · 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'étudeSans objet
Domainenon disponible
GenreÉditorial

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

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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