Increased heart rate and energy expenditure in frontotemporal dementia
Bibliographic record
Abstract
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).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".