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Enregistrement W2562565866 · doi:10.1093/brain/aww312

Increased heart rate and energy expenditure in frontotemporal dementia

2016· letter· en· W2562565866 sur OpenAlexaff
Elizabeth Finger

Notice bibliographique

RevueBrain · 2016
Typeletter
Langueen
DomaineMedicine
ThématiqueAlzheimer's disease research and treatments
Établissements canadiensWestern University
Organismes subventionnairesnon disponible
Mots-clésFrontotemporal dementiaAmyotrophic lateral sclerosisDementiaPsychologyOverweightDiseaseBody mass indexBasal metabolic rateMedicineInternal medicinePsychiatry

Résumé

récupéré en direct d'OpenAlex

This scientific commentary refers to ‘Energy expenditure in frontotemporal dementia: a behavioural and imaging study’ by Ahmed et al. (doi:10.1093/aww263). The obesity paradox, whereby being overweight or obese during mid-life is associated with higher rates of dementia in later life, while low body mass index (BMI) in older populations is associated with a higher risk of dementia, has been demonstrated in multiple studies of patients with Alzheimer’s disease (Fitzpatrick et al., 2009). In another neurodegenerative disorder, frontotemporal dementia (FTD), classic descriptions suggest a different pattern, specifically weight gain with disease onset due to hyperphagia and increased sweet intake. However, BMI has not been found to correlate with food intake in FTD, raising the possibility of altered metabolism in patients with FTD (Ahmed et al., 2016). In this issue of Brain, Ahmed et al. test this hypothesis by measuring activity levels and heart rate to characterize energy expenditure in patients with FTD (Ahmed et al., 2016). They conclude that resting and total energy expenditure are increased in FTD, suggesting that the basal metabolic rate in patients with FTD may be altered as a part of the disease. A relationship between BMI, metabolism and several neurodegenerative disorders including Alzheimer’s disease, Parkinson’s disease and amyotrophic lateral sclerosis is now generally established, though the complex pathways mediating these associations across and within different disorders remain under investigation. In healthy adults and patients with mild cognitive impairment, a precursor state to Alzheimer’s disease, lower BMI is associated with higher levels of cerebral amyloid and tau, the hallmark pathological aggregates in Alzheimer’s disease. Alterations in insulin metabolism and leptin levels, a protein known to regulate appetite, can modify amyloid-β and phosphorylation of tau and are associated with cognitive decline (Procaccini et al., 2016). In FTD, levels of agouti-related peptide (AgRP), which stimulates appetite, were found to be elevated in two studies, while leptin levels appear to be elevated secondary to higher BMI (Hu et al., 2010; Ahmed et al., 2015). These findings in humans are supported by the finding of hypermetabolism in animal models of TDP-43 pathology associated with FTD. To address whether patients with FTD have an altered metabolic state, Ahmed et al. assessed energy expenditure using ‘Actiheart’ devices to measure activity levels and heart rate in standardized experimental and home environments in patients with behavioural variant FTD, Alzheimer’s disease and age-matched controls. Energy expenditure based on heart rate, activity, age and gender has been shown to predict basal metabolic rate measured by indirect calorimetry in normal and obese healthy subjects (Crouter et al., 2008). Stressed heart rate was obtained from the first 30 min of a 2-h cognitive testing session which followed an overnight fast and standardized breakfast. Patients wore the Actiheart monitor at home for 1 week. Twenty-four hour activity levels were recorded from Day 2, and resting heart rate was measured during sleep. Resting, active and total energy expenditures were calculated using activity levels and heart rate indices, while adjusting for bodyweight. The authors found that resting heart rate was increased in patients with FTD compared to those with Alzheimer’s disease or controls (∼8–10 beats per minute higher). Stressed and sleeping heart rate were also increased in FTD relative to controls (again ∼8–10 beats per minute higher). Higher resting heart rate correlated with poorer performance on cognitive tests and poorer behavioural ratings in patients with FTD. While increased energy expenditure in FTD might have been predicted based on symptoms of restlessness and hyperactivity common in many patients, instead the authors found that patients with FTD and Alzheimer’s disease were less active than controls, possibly due to apathy, another hallmark symptom of FTD and Alzheimer’s disease. From these inputs, total and resting energy expenditure were found to be elevated in patients with behavioural variant FTD. Ahmed et al. then examined associations between resting heart rate and cortical thickness measures to test the hypothesis that correlations would be observed in brain regions regulating autonomic responses. Region of interest analysis in the anterior insula and anterior cingulate cortex (averaged across both hemispheres) demonstrated correlations between resting heart rate and atrophy (higher heart rate, greater atrophy), with similar relationships observed in subcortical structures including the hippocampus and amygdala (Fig. 1). Though not measured in the current study, Ahmed et al. previously demonstrated atrophy of the posterior hypothalamus, another structure central to appetite and feeding behaviour as well as homeostatic regulation and autonomic control, in patients with behavioural variant FTD (Ahmed et al., 2015). The findings of increased heart rate are consistent with a recent study reporting reduced vagal tone and increased resting heart rate in patients with behavioural variant FTD (Guo et al., 2016). While the present study found that the averages of bilateral anterior insula and bilateral anterior cingulate atrophy each correlated with resting heart rate, Guo et al. (2016) found that asymmetry of atrophy in these areas, specifically greater left hemisphere atrophy, was associated with reduced parasympathetic outflow and elevated heart rate in behavioural variant FTD. Atrophy in multiple brain regions contributes to altered total energy expenditure in FTD. AgRP = agouti-related peptide; bvFTD = behavioural variant FTD. Glossary Body mass index (BMI): Ratio used to measure body shape. Body mass in kg divided by square of height in metres. BMI > 25 has been categorized as overweight, and BMI of >30 as obese. Frontotemporal dementia (FTD): A neurodegenerative dementia presenting with behaviour and/or language impairments, predominantly affecting the frontal and/or anterior temporal lobe, featuring pathological inclusions most commonly of tau or TDP-43. Subtypes of frontotemporal dementia include behavioural variant FTD, semantic variant FTD, and agrammatic non-fluent FTD. Total energy expenditure: Metabolic unit for the sum of energy used by an organism during activity, rest and feeding (Segen, 2002).

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)0,003
score de la tête « metaresearch » (Gemma)0,015
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,037

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,015
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,002
Communication savante0,0030,002
Science ouverte0,0020,001
Intégrité de la recherche0,0100,011
Charge utile insuffisante (le modèle a refusé de juger)0,0110,006

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 Opus0,019
Tête enseignante GPT0,286
Écart entre enseignants0,267 · 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'étudeObservationnel
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

Citations4
Publié2016
Routes d'admission1
Résumé présentoui

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