Given access to a large body of biological data from people of various ages, creating an aging clock from that data is fairly straightforward and costs relatively little in time and funding. Thus clocks are proliferating, a new one published by an academic research group every few months. Most will vanish into obscurity. The problem is not the lack of a perfect clock for any given situation, but the lack of understanding as to how any given clock will react to a novel potential approach to slowing or reversing aging. The real potential value of clocks is not risk estimation for patients, but rather the rapid assessment of potential therapies to treat aging. But that latter use is challenging when one can't trust that a clock will in fact react appropriately and correctly judge the degree to which aging has been slowed or reversed.
Identifying individuals at risk of dementia is essential for prevention and targeted disease-modifying strategies. We investigated whether mid-life metabolomic ageing is associated with incident dementia and its age of onset and assessed joint associations and interactions with APOE genotype and dementia polygenic scores. In the UK Biobank, plasma metabolites were quantified at baseline. Metabolomic age (MileAge) delta reflects the difference between metabolite-predicted and chronological age. Dementia was identified via health records.
Amongst 223,496 participants, 3,976 developed dementia. A higher MileAge delta was associated with higher hazards of all-cause, unspecified and vascular dementia (hazard ratio, HR = 1.61) and earlier onset. Key metabolites were lipids, lipoproteins, and amino acids. MileAge delta and genetic risk were jointly associated with dementia. Individuals with a high MileAge delta and two APOE ε4 alleles had a 10.30-fold higher all-cause dementia risk. Thus metabolomic ageing and genetic risk likely represent independent biological pathways contributing to dementia risk.
Link: https://doi.org/10.1002/alz.71280
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