If age is the strongest risk factor for Alzheimer’s and other neurodegenerative diseases, how come some nonagenarians stay sharp while others lose their edge? Genetics beyond the known genes linked to pathologies, such as amyloid plaques and neurofibrillary tangles, undoubtedly play a role in speeding up or slowing down a person’s rate of biological aging—but how to find the requisite variants? In the April 26 Cell Systems, Hervé Rhinn and Asa Abeliovich describe Δ-aging. It’s a new, unbiased approach to identify differences in age-related traits. In a nutshell, Δ-aging identifies people whose brains seems to be aging unusually fast or slowly by comparing an individual’s age-related cortical gene expression changes to normative rates of change in their peers. By using whole transcriptomes from thousands of healthy human prefrontal cortex samples, they established normative gene expression patterns and identified gene patterns in some people that change more slowly or faster than average.
Taking this a step further, Rhinn and Abeliovich ran a genome-wide association study. They used this Δ-aging measure—not clinical categories such as control versus Alzheimer’s or control versus disease X—to search for “upstream” master genetic regulators that might drive differential brain aging. Up popped none other than the frontotemporal dementia genes TMEM106B and progranulin, which reached genome-wide significance or trended strongly, respectively. TMEM106B regulates progranulin expression. The scientists report that TMEM106B had the greatest effect on microglial gene expression, hinting once again that modulating neuroinflammation is how a particular gene variant might fuel brain aging. What do you think of this new approach to find genes and pathways of brain aging? What are the caveats? And what else could be done with it?
Read the open access paper here. On April 20, 2017, readers joined Abeliovich, Rhinn, Rosa Rademakers, Jernej Ule, and Tony-Wyss Coray for a panel discussion.
No Available Further Reading
- Rhinn H, Abeliovich A. Differential Aging Analysis in Human Cerebral Cortex Identifies Variants in TMEM106B and GRN that Regulate Aging Phenotypes. Cell Syst. 2017 Mar 15; PubMed.