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Background Metabolomic scores based on age (MetaboAge) and mortality (MetaboHealth) are considered indicators of overall health, but their association with cognition in the general population is unknown. Therefore, the association between MetaboAge/MetaboHealth and level and decline in cognition was studied, as were differences between men and women. Methods Data of 2821 participants (50% women, age range 45–75) from the Doetinchem Cohort Study was used. MetaboAge and MetaboHealth were calculated from 1H-NMR metabolomics data at baseline. Cognitive domain scores (memory, flexibility and processing speed) and global cognitive functioning were available over a 10-year period. The association between MetaboAge/MetaboHealth and level of cognitive functioning was studied using linear regressions while for the association between MetaboAge/MetaboHealth and cognitive decline longitudinal linear mixed models were used. Analyses were adjusted for demographics and lifestyle factors. Results Higher MetaboAge, indicating poorer metabolomic ageing, was only associated with lower levels of processing speed in men. Higher MetaboHealth, indicating poorer immune-metabolic health, was associated with lower levels of cognitive functioning for all three domains and global cognitive functioning in both men and women. Only in men, MetaboHealth was also associated with 10-year decline in flexibility, processing speed and global cognition. Metabolites that contributed to the observed associations were in men mainly markers of protein metabolism, and in women mainly markers of lipid metabolism and inflammatory metabolites. Conclusions MetaboHealth, not MetaboAge, was associated with cognitive functioning independent of conventional risk factors. Individual metabolites affect cognitive functioning differently in men and women, suggesting sex-specific pathophysiological pathways underlying cognitive functioning. [ABSTRACT FROM AUTHOR]

People age differently. Differences in aging might be reflected by metabolites, also known as metabolomic aging. Predicting metabolomic aging is of interest in public health research. However, the added value of longitudinal over cross-sectional predictors of metabolomic aging is unknown. We studied exposome-related exposures as potential predictors of metabolomic aging, both cross-sectionally and longitudinally in men and women. We used data from 4 459 participants, aged 36–75 of Round 4 (2003–2008) of the long-running Doetinchem Cohort Study (DCS). Metabolomic age was calculated with the MetaboHealth algorithm. Cross-sectional exposures were demographic, biological, lifestyle, and environmental at Round 4. Longitudinal exposures were based on the average exposure over 15 years (Round 1 [1987–1991] to 4), and trend in these exposure over time. Random Forest was performed to identify model performance and important predictors. Prediction performances were similar for cross-sectional and longitudinal exposures in both men (R 2 6.8 and 5.8, respectively) and women (R 2 14.8 and 14.4, respectively). Biological and diet exposures were most predictive for metabolomic aging in both men and women. Other important predictors were smoking behavior for men and contraceptive use and menopausal status for women. Taking into account history of exposure levels (longitudinal) had no added value over cross-sectionally measured exposures in predicting metabolomic aging in the current study. However, the prediction performances of both models were rather low. The most important predictors for metabolomic aging were from the biological and lifestyle domain and differed slightly between men and women. [ABSTRACT FROM AUTHOR]

Objective: To summarise available evidence on time to nursing home admission and death among people with dementia, and to explore prognostic indicators., Design: Systematic review and meta-analysis., Data Sources: Medline, Embase, Web of Science, Cochrane, and Google Scholar from inception to 4 July 2024., Eligibility Criteria for Selecting Studies: Longitudinal studies on survival or nursing home admission in people with dementia. Studies with fewer than 150 participants, recruitment during acute hospital admission, or less than one year of follow-up were excluded., Results: 19 307 articles were identified and 261 eligible studies included. 235 reported on survival among 5 553 960 participants and 79 reported on nursing home admission among 352 990 participants. Median survival from diagnosis appeared to be strongly dependent on age, ranging from 8.9 years at mean age 60 for women to 2.2 years at mean age 85 for men. Women overall had shorter survival than men (mean difference 4.1 years (95% confidence interval 2.1 to 6.1)), which was attributable to later age at diagnosis in women. Median survival was 1.2 to 1.4 years longer in Asia than in the US and Europe, and 1.4 years longer for Alzheimer's disease compared with other types of dementia. Compared with studies before 2000, survival was longer in contemporary clinic based studies (P trend =0.02), but not in community based studies. Taken together, variation in reported clinical characteristics and study methodology explained 51% of heterogeneity in survival. Median time to nursing home admission was 3.3 years (interquartile range 1.9 to 4.0). 13% of people were admitted in the first year after diagnosis, increasing to 57% at five years, but few studies appropriately accounted for competing mortality risk when assessing admission rates., Conclusions: The average life expectancy of people with dementia at time of diagnosis ranged from 5.7 years at age 65 to 2.2 at age 85 in men and from 8.0 to 4.5, respectively, in women. About one third of remaining life expectancy was lived in nursing homes, with more than half of people moving to a nursing home within five years after a dementia diagnosis. Prognosis after a dementia diagnosis is highly dependent on personal and clinical characteristics, offering potential for individualised prognostic information and care planning., Systematic Review Registration: PROSPERO CRD42022341507., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: FJW was supported by a research fellowship from the Alzheimer’s Association; no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Skin autofluorescence (SAF), reflecting advanced glycation end-products' accumulation in tissue, has been proposed as a non-invasive aging biomarker. Yet, SAF has not been compared to well-established blood-based aging biomarkers such as MetaboHealth in association with frailty. Furthermore, no previous study determined the longitudinal association of SAF with frailty. We used 2382 Doetinchem Cohort Study participants' (aged 46.0 to 85.4) cross-sectional data, of whom 1654 had longitudinal SAF measurements. SAF was measured using the AGE reader™. MetaboHealth was calculated on 1H-NMR-metabolomics. Linear regressions were used for the associations of SAF and MetaboHealth on the 36-deficit frailty index and logistic regressions for being pre-frail or frail as determined by the frailty phenotype. Longitudinal associations were determined by an interaction term between age and SAF in a linear mixed model. SAF and MetaboHealth were associated with higher odds of pre-frailty (odd ratios per standard deviation SAF: 1.21(1.10;1.32), MetaboHealth: 1.35(1.24;1.49)) and frailty (SAF: 1.70(1.41;2.06), MetaboHealth: 1.90(1.57;2.32)). When mutually adjusted, both aging biomarkers remained associated with pre-frailty (SAF: 1.16(1.05;1.27), MetaboHealth 1.33(1.21;1.46)) and frailty (SAF: 1.52(1.25;1.85), MetaboHealth: 1.75(1.43;2.14)). Additionally, SAF and MetaboHealth were associated with higher frailty index scores (percentage increase per standard deviation SAF:1.35(1.00;1.70), MetaboHealth: 1.87(1.54;2.20)), also after mutual adjustment (SAF: 1.02(0.68;1.37), MetaboHealth: 1.69(1.35;2.02)). SAF was also longitudinally associated with the frailty index (percentage per unit/year increase 0.12(0.07;0.16)). The mutual independence of SAF and MetaboHealth implies they capture distinct aspects of the aging process. Altogether, these findings emphasize SAF's clinical potential as an age-related decline biomarker, which could be further enhanced when combined with MetaboHealth., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America.)

A common feature of human aging is the acquisition of somatic mutations, and mitochondria are particularly prone to mutation due to their inefficient DNA repair and close proximity to reactive oxygen species, leading to a state of mitochondrial DNA heteroplasmy 1,2 . Cross-sectional studies have demonstrated that detection of heteroplasmy increases with participant age 3 , a phenomenon that has been attributed to genetic drift 4-7 . In this first large-scale longitudinal study, we measured heteroplasmy in two prospective cohorts (combined n=1405) at two timepoints (mean time between visits, 8.6 years), demonstrating that deleterious heteroplasmies were more likely to increase in variant allele fraction (VAF). We further demonstrated that increase in VAF was associated with increased risk of overall mortality. These results challenge the claim that somatic mtDNA mutations arise mainly due to genetic drift, instead demonstrating positive selection for predicted deleterious mutations at the cellular level, despite an negative impact on overall mortality.