Plasma metabolomic profiling of frailty in older adults at risk of dementia
- 1University of Technology Sydney
Abstract
BackgroundFrailty is a prominent risk factor for dementia. Early detection of at-risk individuals may enable intervention to prevent or slow dementia pathology. Blood-based biomarker discovery could offer a path for early detection of frailty and cognitive decline.
MethodsOlder adults at risk of dementia underwent comprehensive multi-disciplinary assessment at the Healthy Brain Ageing (HBA) clinic, including geriatric, neurophysiological and mood evaluations, in addition to providing a fasted blood sample. Clinical data were used to calculate a deficit accumulation frailty index (FI) score. Additional cohorts attended either one (n=118) or two (n=73) subsequent visits over an average period of 4 years. Untargeted metabolomics was performed on plasma samples, and metabolites were clustered by similarity. Linear regression was used to assess association of clusters with FI. Finally, change in plasma abundance over time was assessed.
ResultsAt assessment, participants had a mean (SD) age of 68.10 (8.07) years; 72.2% were female. Hierarchical clustering identified 10 clusters of metabolites, of which 6 were significantly associated with FI (p<0.05) at baseline and contained similar classes of metabolite. Differential abundance analysis found unique temporal regulation of metabolite abundance in each cluster, but across clusters severity of frailty impacted direction of change in plasma abundance over time.
ConclusionsFrailty index was associated with carboxylic acids and derivatives, fatty acyls and organooxygen compounds across multiple clusters, and a large number of lipids were linked to frailty score, potentially implicating dysregulation of energy metabolism in the pathophysiology of frailty and forming a panel of predictive biomarkers of at risk patients.
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BibTeX
@misc{alldritt2026plasma,
title = {{Plasma metabolomic profiling of frailty in older adults at risk of dementia}},
author = {I. Alldritt and J. C. Michaelian and R. Yu and S. E. Deemer and R. J. Mills and S. L. Naismith and A. Philp},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.06.26364906},
url = {https://www.medrxiv.org/content/10.64898/2026.10.06.26364906v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Plasma metabolomic profiling of frailty in older adults at risk of dementia
AU - I. Alldritt
AU - J. C. Michaelian
AU - R. Yu
AU - S. E. Deemer
AU - R. J. Mills
AU - S. L. Naismith
AU - A. Philp
PY - 2026
DA - 2026/10/06
PB - medRxiv
DO - 10.64898/2026.10.06.26364906
UR - https://www.medrxiv.org/content/10.64898/2026.10.06.26364906v1
AB - BackgroundFrailty is a prominent risk factor for dementia. Early detection of at-risk individuals may enable intervention to prevent or slow dementia pathology. Blood-based biomarker discovery could offer a path for early detection of frailty and cognitive decline. MethodsOlder adults at risk of dementia underwent comprehensive multi-disciplinary assessment at the Healthy Brain Ageing (HBA) clinic, including geriatric, neurophysiological and mood evaluations, in addition to providing a fasted blood sample. Clinical data were used to calculate a deficit accumulation frailty index (FI) score. Additional cohorts attended either one (n=118) or two (n=73) subsequent visits over an average period of 4 years. Untargeted metabolomics was performed on plasma samples, and metabolites were clustered by similarity. Linear regression was used to assess association of clusters with FI. Finally, change in plasma abundance over time was assessed. ResultsAt assessment, participants had a mean (SD) age of 68.10 (8.07) years; 72.2% were female. Hierarchical clustering identified 10 clusters of metabolites, of which 6 were significantly associated with FI (p<0.05) at baseline and contained similar classes of metabolite. Differential abundance analysis found unique temporal regulation of metabolite abundance in each cluster, but across clusters severity of frailty impacted direction of change in plasma abundance over time. ConclusionsFrailty index was associated with carboxylic acids and derivatives, fatty acyls and organooxygen compounds across multiple clusters, and a large number of lipids were linked to frailty score, potentially implicating dysregulation of energy metabolism in the pathophysiology of frailty and forming a panel of predictive biomarkers of at risk patients.
ER -