Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with Layer-wise Relevance Propagation (LRP) to detect which brain features contribute to BA. Trained on magnetic resonance imaging (MRI) data of a population-based study (n = 2,637, 18–82 years), our models estimated age accurately based on single and multiple modalities, regionally restricted and whole-brain images (mean absolute errors 3.37–3.86 years). We find that BA estimates capture ageing at both small and large-scale changes, revealing gross enlargements of ventricles and subarachnoid spaces, as well as white matter lesions, and atrophies that appear throughout the brain. Divergence from expected ageing reflected cardiovascular risk factors and accelerated ageing was more pronounced in the frontal lobe. Applying LRP, our study demonstrates how superior deep learning models detect brain-ageing in healthy and at-risk individuals throughout adulthood.
A team of researchers affiliated with several institutions in Switzerland and the U.S. reports evidence that the genetics of longevity are influenced by both gender and age. In their paper published in the journal Science, the group describes their study of aging in mice and humans. João Pedro de Magalhães, with the University of Birmingham, has published a Perspective piece in the same journal issue outlining the technical challenges to understanding how aging works and the work done by the team on this new effort.
Scientists have been studying the aging process for many years but still do not have a good explanation for why organisms age and why some live longer than others. In this new effort, the researchers wondered if something in the genome plays a role in how long a species lives on average.
Noting that another team had created a very large dataset of information regarding aging in nearly 3,000 mice, the researchers found that it also contained genetic information. After obtaining access to the database, they analyzed that genetic information—more specifically, they conducted quantitative trait locus mapping. They found multiple loci that they could associate with longevity, some that were specific to one or the other gender. They also found that mice who weighed more during their early years or who had small litter sizes tended to die younger. They suggest the same genes that were associated with aging may have also played a role in the other two traits. The researchers also found that the aging-related genes they isolated appeared to remain dormant until the latter stages of a given individual’s life.
With more of us living into old age than at any other time, dementia is increasing steadily worldwide, with major individual, family, societal and economic consequences.
Treatment remains largely ineffective and aspects of the underlying pathophysiology are still unclear. But there is good evidence that neurodegenerative diseases —and their manifestation as dementia—are not an inevitable consequence of aging.
Many causes of dementia, including viral infections, are preventable.
Including decaffeinated and instant ones.
A new study conducted by Australian scientists suggests that consuming two to three cups of decaffeinated, ground, and instant coffee can lower the risk of developing cardiovascular disease and dying early.
“In this large, observational study, ground, instant, and decaffeinated coffee were associated with equivalent reductions in the incidence of cardiovascular disease and death from cardiovascular disease or any cause,” says study author Professor Peter Kistler of the Baker Heart and Diabetes Research Institute in a media release.
“The results suggest that mild to moderate intake of ground, instant, and decaffeinated coffee should be considered part of a healthy lifestyle.”
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Additionally, epigenetic changes were suggested to be a possible link [30, 31] between adverse childhood experiences and mortality as well as higher morbidity burden in late life [32]. It was proposed that this link could be mediated by health-adverse coping mechanisms (activated as a result of high levels of anxiety and depression) that are associated with adverse childhood experiences [33]. Some of these coping strategies, such as smoking, alcohol abuse and and a high BMI resulting from unhealthy eating habits, were shown to be associated with DNAmAA in some studies [34,35,36]. However, these results were not unequivocally replicated [37,38,39] (reviewed in ref. [40]).
Previous studies that examined the relationship between DNAmAA and stress operationalized stress as low socioeconomic status (SES) [41, 42], (childhood) trauma [26, 43,44,45], racial discrimination [46], or exposure to violence [47]. Many previous studies on the topic focused on changes in DNAm age during childhood as this period is known to be particularly prone to stress-related epigenetic changes [29].
In contrast, in this work we focus on older age which was shown to be the second most vulnerable phase in a person’s life in terms of epigenetics [29]. As epigenetic modifications remain even after the psychological stimulus has ceased there is the possibility of cumulating effects on the epigenome exerted by repeated psychological stressors [29]. Specifically, we analyzed the association between the amount of experienced stress (measured by Cohen’s Perceived Stress Scale [PSS] [48]) and several DNAm age estimators (i.e. the 7-CpG clock [49], Horvath’s clock [50], Hannum’s clock [51], PhenoAge [34], GrimAge [52]) in 1,100 older adults. While the PSS represents a well-established marker of perceived stress [48], to our knowledge it has not been investigated in the context of epigenetic aging before. While we were able to replicate well-established associations with perceived stress, none of the five epigenetic clocks analyzed in the current study were associated with the perception of stress.