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Aging Markers, Patterns Found in Longitudinal Multi-Omics Study

NEW YORK – By collecting genomic, metabolomic, clinical, and other data from healthy individuals over time, a Stanford University team has tracked down molecular markers for aging — demonstrating, in the process, that the specific pathways involved often vary from one individual to the next, producing distinct personal "ageotypes."

"Ageotypes may provide a molecular assessment of personal aging, reflective of personal lifestyle and medical history, that may ultimately be useful in monitoring and intervening in the aging process," corresponding author Michael Snyder, a researcher in the Department of Genetics at Stanford, and his colleagues wrote.

Although features such as telomere length or DNA methylation marks have been proposed as potential markers for aging, Snyder and his co-authors suggested that "a comprehensive view of the molecular changes that occur during aging in humans is not known," prompting them to take a far more detailed look at the process in more than 100 individuals.

As they reported in Nature Medicine on Monday, the researchers used exome sequencing, RNA sequencing, mass spectrometry-based metabolomic and proteomic profiling, cytokine assays, and targeted microbial gene sequencing, in combination with dozens of clinical lab tests, to follow clinical features, blood profiles, stool microbiome features, nasal microbial communities, and more over time in 106 healthy or prediabetic individuals between the ages of 29 and 75 years.

Results from the team's initial analyses — which included data from seven "omics" assays collected from participants over the course of almost 1,100 clinic visits — highlighted several known contributors to aging, such as age-related declines in the glomerular filtration rate of participants' kidneys, as well as new candidate markers, including rising levels of Clostridium bacteria in gut samples from aging individuals.

But it also pointed to molecular aging profiles that differed somewhat between the participants with or without insulin resistance, the authors explained, prompting them to take an even more detailed look at a subset of individuals who participated in particularly deep and extended data collection — a group that included a few representatives with waning physical activity, significant weight loss, or medication changes over the time considered.

"The frequent sampling of individuals over a potentially actionable time frame, which we arbitrarily defined as less than [two] years, enabled us to study how individuals change with time at a personal level," the researchers explained. "We focused on 43 individuals who had at least five healthy visits spanning at least 700 [days], which was sufficient for identifying analytes that changed with time."

There, the team found hundreds to thousands of potential age-related marker molecules per participant, though the aging markers and the specific pathways involved in aging varied from one individual to the next. While some individuals experienced age-related changes in liver, kidney, metabolic, and immune pathway activity, for example, others experienced shifts dominated by one or a few pathways as they aged.

"Our analysis shows that some individuals fall strongly into one or more of these aging pathways, suggesting that they have distinct ageotypes," the authors wrote, noting that "[i]t is possible that improvements in ageotype can be targeted at the individual level (such as, immune function or metabolic pathways) using selective interventions (such as, drugs) or in aggregate using broad lifestyle changes."

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