Changes in Loneliness, BDNF, and Biological Aging Predict Trajectories in a Blood-Based Epigenetic Measure of Cortical Aging: A Study of Older Black Americans

A recent epigenetic measure of aging has developed based on human cortex tissue. This cortical clock (CC) dramatically outperformed extant blood-based epigenetic clocks in predicting brain age and neurological degeneration. Unfortunately, measures that require brain tissue are of limited utility to investigators striving to identify everyday risk factors for dementia. The present study investigated the utility of using the CpG sites included in the CC to formulate a peripheral blood-based cortical measure of brain age (CC-Bd). To establish the utility of CC-Bd, we used growth curves with individually varying time points and longitudinal data from a sample of 694 aging African Americans. We examined whether three risk factors that have been linked to cognitive decline-loneliness, depression, and BDNFm-predicted CC-Bd after controlling for several factors, including three new-generation epigenetic clocks. Our findings showed that two clocks-DunedinPACE and PoAm-predicted CC-BD, but that increases in loneliness and BDNFm continued to be robust predictors of accelerated CC-Bd even after taking these effects into account. This suggests that CC-Bd is assessing something more than the pan-tissue epigenetic clocks but that, at least in part, brain health is also associated with the general aging of the organism.

The effects of epigenetic age and its acceleration on surface area, cortical thickness, and volume in young adults

DNA methylation age has been used in recent studies as an epigenetic marker of accelerated cellular aging, whose contribution to the brain structural changes was lately acknowledged. We aimed to characterize the association of epigenetic age (i.e. estimated DNA methylation age) and its acceleration with surface area, cortical thickness, and volume in healthy young adults. Using the multi-tissue method (Horvath S. DNA methylation age of human tissues and cell types. 2013. Genome Biol 14), epigenetic age was computed with saliva sample. Epigenetic age acceleration was derived from residuals after adjusting epigenetic age for chronological age. Multiple regression models were computed for 148 brain regions for surface area, cortical thickness, and volume using epigenetic age or accelerated epigenetic age as a predictor and controlling for sex. Epigenetic age was associated with surface area reduction of the left insula. It was also associated with cortical thinning and volume reduction in multiple regions, with prominent changes of cortical thickness in the left temporal regions and of volume in the bilateral orbital gyri. Finally, accelerated epigenetic age was negatively associated with right cuneus gyrus volume. Our findings suggest that understanding the mechanisms of epigenetic age acceleration in young individuals may yield valuable insights into the relationship between epigenetic aging and the cortical change and on the early development of neurocognitive pathology among young adults.

Cortical aging - new insights with multiparametric quantitative MRI

Understanding the microstructural changes related to physiological aging of the cerebral cortex is pivotal to differentiate healthy aging from neurodegenerative processes. The aim of this study was to investigate the age-related global changes of cortical microstructure and regional patterns using multiparametric quantitative MRI (qMRI) in healthy subjects with a wide age range. 40 healthy participants (age range: 2^nd to 8^th decade) underwent high-resolution qMRI including T1, PD as well as T2, T2* and T2′ mapping at 3 Tesla. Cortical reconstruction was performed with the FreeSurfer toolbox, followed by tests for correlations between qMRI parameters and age. Cortical T1 values were negatively correlated with age (p=0.007) and there was a widespread age-related decrease of cortical T1 involving the frontal and the parietotemporal cortex, while T2 was correlated positively with age, both in frontoparietal areas and globally (p=0.004). Cortical T2′ values showed the most widespread associations across the cortex and strongest correlation with age (r= -0.724, p=0.0001). PD and T2* did not correlate with age. Multiparametric qMRI allows to characterize cortical aging, unveiling parameter-specific patterns. Quantitative T2′ mapping seems to be a promising imaging biomarker of cortical age-related changes, suggesting that global cortical iron deposition is a prominent process in healthy aging.