Biological aging undeniably affects human cognitive function.1 However, how this happens\u2014the underlying factors, interactions, and processes\u2014remains unclear. <\/p>\n
Michael Lodato<\/a>, a geneticist from the University of Massachusetts (UMass), thinks somatic mutations\u2014mutations that occur over an individual\u2019s lifetime\u2014play a key role in this phenomenon. In a study recently published in Nature, he and his research team conducted a detailed investigation of the genetic and genomic dynamics of the human brain across the lifespan, from infancy to centenarian.2 They found that while neurons accumulated somatic mutations with age, they did so in short housekeeping genes governing basic cell upkeep, rather than longer genes driving neuron-specific functions. <\/p>\n Michael Lodato, a geneticist from the University of Massachusetts, studies how neuron gene expression patterns change as humans age.<\/p>\n Faith Ninavaggi<\/a><\/p>\n Much of the research on brain aging<\/a> has centered on classical age-related diseases such as Alzheimer\u2019s disease, Parkinson\u2019s disease, and cancer. Yet executive brain function declines over time in the absence of these pathologies<\/a>, something paradoxically termed \u201chealthy aging.\u201d1 Researchers believe that this decline may be the consequence of accumulated somatic mutations stemming from DNA damage and repair events.3,4 \u201cSince neurons do not replicate, these mutations can have significant long-term consequences,\u201d Lodato explained.<\/p>\n Continue reading below…<\/p>\n He and his team want to understand how neurons age in the absence of disease in hopes of slowing it down: \u201cWe are seeing very specific types of mutations in neurons\u2014discrete mutation signatures\u2014which tell us that specific pathways are important for protecting the genome. If we can control these pathways, we may be able to slow the rate of mutational accumulation and protect the genome.\u201d Since neurons are post-mitotic and do not divide, single-cell resolution is necessary to detect neuronal mutations. Thus, Lodato turned to single-cell whole genome (scWGS) and single-nucleotide RNA sequencing (snRNA-seq).<\/p>\n Lodato, co-lead author Ailsa Jeffries<\/a>, and the rest of their team used these technologies to examine brain cells from 19 neurotypical donors ranging in age from younger than one year old to 104. They then turned to fellow UMass colleague Zhiping Weng<\/a> to help them analyze the data. Weng, a computational biologist, and her postdoctoral researcher and study coauthor Tianxiong Yu<\/a> focused on isolating aging-related effects from natural variability. \u201cWe basically tried every which way to defeat our hypotheses,\u201d Weng recalled. Lodato also pointed out that they compared their data to three other large datasets collected by other researchers to establish the extent of natural variability. Their efforts seem to have paid off. <\/p>\n \u201cThis is a really comprehensive and robust study that does a great job in pairing [genomic and transcriptomic] analyses,\u201d said Lauren Donovan<\/a>, a neuroscientist at Stanford University who was not associated with the study. <\/p>\n Zhiping Weng, a computational biologist from the University of Massachusetts, develops computational and machine-learning methods for analyzing large-scale omics datasets.<\/p>\n![\"Geneticist](\"https:\/\/www.europesays.com\/us\/wp-content\/uploads\/2025\/10\/091323lodato05-m.jpg\" "\\"Geneticist")
<\/p>\n![\"Zhiping](\"https:\/\/www.europesays.com\/us\/wp-content\/uploads\/2025\/10\/zhiping-weng3-m.png\" "\\"Zhiping")
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