Abstract INTRODUCTION Proteomic aging clocks detect disease‐related systemic and organ‐specific changes and are easily accessible by minimally invasive blood draws. However, their potential in Alzheimer's disease (AD) assessment remains unestablished. METHODS We investigated associations of proteomic and epigenetic clocks with AD‐related blood‐based biomarkers and cognitive tests. Omics were generated from blood samples of 153 cognitively unimpaired individuals (average age 62 years); blood biomarkers and cognition were measured approximately nine years after. RESULTS Proteomic clocks explained up to 23% of variance in cognitive and biomarker measures not explained by epigenetics. Accelerated systemic and brain‐specific proteomic aging were linked to poorer cognition and higher levels of plasma neurofilament light chain. Exploratory interaction analyses suggested weaker proteomic aging‐cognition associations in individuals with higher genetic liability for diabetes. DISCUSSION Our study illustrates the potential of plasma proteomic clocks in detecting AD‐related phenotypes. However, co‐morbidities possibly constitute confounding factors, compromising the performance of proteomic aging models.
Cindy David Sarmento, G. Drouard, T. Saari et al.· Alzheimer's & Dementia· 0 citations
BACKGROUND
High body mass index (BMI) in adolescence is associated with accelerated biological aging, which might predict the onset of obesity-related diseases before they develop. Genetic factors may shape both adolescent BMI and weight trajectories.
METHODS
Participants were from the Young Finns Study (n = 3 596, ages 3-18 at baseline), followed from 1980 to 2018-2020. Biological aging was estimated using DNA methylation based epigenetic clocks DunedinPACE (years/calendar year) and PC-GrimAge (years) at three follow-ups (ages 15-56, n = 2045). Genetic predispositions to BMI and childhood body size were quantified using polygenic risk scores (PRSs) (941 and 286 genetic variants). BMI trajectories were modelled from BMI measured at ages 9, 12, 15 and 18 using latent growth curve modelling. Path analysis was used to examine whether genetic liability to BMI is associated with biological aging and if BMI trajectories in adolescence mediate this association. The causal effect of genetically predicted adolescent BMI on biological aging in adulthood was examined with Mendelian randomisation (MR) using individual-level data.
RESULTS
Higher level of adolescent BMI partly mediated the association between higher BMI-PRS and accelerated biological aging from late adolescence to middle adulthood. MR analyses supported a positive causal effect from genetically predicted adolescent BMI on biological aging, and the causal effect was more consistent when DunedinPACE was used to measure biological aging in 2011 (causal estimate = 0.020 [95% CI = 0.008, 0.031]) and 2018 (0.019 [0.003, 0.035]).
CONCLUSIONS
Our findings indicate that high BMI in adolescence may accelerate biological aging, especially in individuals with a genetic predisposition to high BMI. Adolescents with a genetic susceptibility to high BMI and elevated BMI might be prone to obesity-related health risks, highlighting early prevention strategies' importance.
Anni Pitkänen, Anna Kankaanpää, E. Raitoharju et al.· International Journal of Obe...· 0 citations
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