• Assessing gene activity by measuring messenger RNA (mRNA) transcript levels – transcriptomics – reveals differences in the aging rate between individuals. 
  • Slow-aging individuals exhibit blood immune cell levels indicative of less inflammation compared to fast-aging individuals.
  • Treatment with nicotinamide mononucleotide (NMN) or Metformin reduces the predicted biological age.

The world has a rapidly expanding population of people over age 65, termed the “silver tsunami.” Currently, scientists in the aging research field continue to gauge and compare how fast people age with newly devised aging clocks to enable research on the most effective means to combat the ravages of aging. This endeavor will require a standardized measurement of aging, though, with many in the aging research field turning toward transcriptomics – measuring RNA sequences as an indicator of gene activity. By using transcriptomics to assess people’s pace of aging, we can compare compounds that have previously been shown to counter aging in animal studies.

Published in Computational and Structural Biotechnology Journal, Ouyang and colleagues from Zhejiang University School of Medicine in China generate a transcriptomics-based aging clock. Using the clock, they demonstrate that applying NMN or metformin to blood samples reduces predicted age. The biological aging clock also differentiates between slow, average, and fast aging individuals based on their chronological age. The identified slow-aging individuals exhibit blood immune cell levels indicative of less inflammation than fast-aging individuals. The development of this aging clock may contribute to aging scientists’ quest for a standardized means to measure biological aging for comparing compounds that potentially increase the years we live in good health.

The Aging Clock Denotes Quick Aging, Slow Aging, and Average Aging Groups

The genes coded in our DNA are transcribed to mRNA before being translated into a protein, so by measuring mRNA levels, we can assess gene activity. The “transcriptome” encompasses the most active genes (mRNA transcripts) at a given time. The researchers analyzed the blood cell transcriptomes of 505 individuals aged 18 to 68 years and found that 1,138 mRNA transcripts significantly changed with age. Using statistical analyses, they used the mRNA transcript levels to determine gene activity and predict biological age – a person’s physiological age in relation to their age-matched counterparts. In doing so, Ouyang and colleagues found that people could be divided into three populations: slow-, average-, and quick-aging. For example, individuals with a biological age younger than their chronological age were considered slow-aging individuals.

Comparing chronological age to predicted age estimates aging rate.
(Shen et al., 2022 | Computational and Structural Biotechnology Journal) Comparing chronological age to predicted age estimates aging rate. Transcriptomic-based predicted age (dots) was compared to the chronological age (blue line) of each individual.  Quick-agers (yellow dots) had higher predicted ages compared to their chronological age, slow-agers (blue dots) had a lower predicted age, and average agers (gray) had the same predicted and chronological age. 

Slow Agers Have Blood Immune Cell Compositions Indicating Less Inflammation

To find out whether the slow-, average-, and quick-aging categorizations translate to physiological parameters like less inflammation, Ouyang and colleagues measured immune cell levels in the blood. They found that the slow-aging population had a higher ratio of lymphocyte to neutrophil immune cells compared to fast-aging participants, indicative of less systemic inflammation. These findings suggest that the slow-, average-, and quick-aging categories have physiological meaning and may portray the amount of inflammation in one’s body.

Slow-agers exhibit less systemic inflammation than quick-agers.
(Shen et al., 2022 | Computational and Structural Biotechnology Journal) Slow-agers exhibit less systemic inflammation than quick-agers. Slow-agers (blue) have higher lymphocyte immune cell counts (left) and lower neutrophil immune cell counts (right) compared to quick-agers (yellow). This means slow-agers have a higher lymphocyte-to-neutrophil ratio, indicating less inflammation throughout the body.

Since the China-based researchers developed their aging clock to compare compounds that may counter aging, they tested five compounds: nicotinamide mononucleotide (NMN), metformin, curcumin, aspirin, and resveratrol. Intriguingly, after incubating blood samples overnight with each of the compounds and then testing them with the aging clock, NMN and metformin significantly diminished the predicted age. Although incubating blood samples with age-deterring compounds may not directly translate to the effects of consuming them, these results provide some evidence that NMN and metformin may allay aging.

NMN and Metformin reduce predicted age.
(Shen et al., 2022 | Computational and Structural Biotechnology Journal) NMN and metformin reduce the predicted age. Incubating NMN or Metformin with blood samples and then applying the aging clock resulted in significantly lower biological ages than those without treatments.

Future Analyses Should Examine Long-Term NMN Use

“Our aging clock succeeded in evaluating the rejuvenation effect of molecules such as NMN and Metformin in vitro,” said Ouyang and colleagues.

While the findings in this publication may be somewhat of a far cry from what happens in the body when consuming NMN or Metformin, they do provide some evidence that these compounds confer healthspan-related benefits. A more rigorous, albeit time and resource-consuming, study could focus on comparing people’s biological age before and after taking the compounds for, perhaps, a year of daily consumption. Determining NMN and Metformin’s effects on biological age after long-term consumption would be a tell-tale way to see whether they actually allay the ravages of aging.