Key Points:
- Researchers measured thousands of molecules and microbes from each participant and found that they fluctuate across a lifespan.
- During mid-life and retirement age, there is a rapid increase in these molecules and microbes that may contribute to outcomes such as disease or reduced caffeine metabolism.
As part of a new study published in Nature Aging, Stanford scientists reveal that aging comes in waves. The study’s grand scale, in terms of breadth and number of samples, heightens its reliability, although limitations abound. The main finding was that age-related molecular and microbiome changes peak at ages 44 and 60. These findings run counter to a gradual increase in biological aging that parallels chronological aging, which might be expected.
Study Details
Many studies involve taking one sample from each participant at one time point. In contrast, the Stanford scientists took multiple samples from each participant at multiple time points across many months (median, 1.7 years), increasing robustness and reliability. From 108 participants between the ages of 25 and 75, a total of 5,405 samples were taken. This included not only the usual blood samples, but also stool, skin, mouth, and nose samples.
From immune cells found in the blood, the researchers measured over 10,000 mRNA transcripts, an indicator of which genes are active. Also from blood samples, 302 proteins, 814 metabolites, 846 lipids (e.g. fat and cholesterol), 66 cytokines (immune system-related signaling molecules), and 51 clinical lab tests, such as blood glucose levels, were measured. Additionally, over 52,000 gut and nasal microbe types were measured from stool and nasal swabs, while about 9,000 skin and oral microbe types were measured from skin and oral swabs. Overall, the researchers obtained an astonishing 246 million data points.
After adjusting for confounding factors like body mass index (BMI), sex, and ethnicity, the researchers found that only 6.6% of the molecules and microbes changed with age in a linear fashion. In other words, the majority of molecules fluctuated with age in a seemingly unpredictable manner, prompting the researchers to search for consistent patterns. As such, the researchers employed an algorithm designed to identify non-linear changes with age and found two distinct peaks at ages 44 and 60, as shown in the graph above.
The researchers found that elevations in cardiovascular disease (CVD)-related molecules were shared by both peaks, suggesting increased risk for CVD at these ages. Molecules implicated in type 2 diabetes, skin and muscle stability, and reduced caffeine metabolism were also observed at both peaks. Found only in peak one, around the age of 40, molecules related to reduced alcohol and lipid metabolism were found. In peak two, around the age of 60, elevations in molecules related to immune system decline were observed, confirming previous findings. Also at peak two were molecules related to a decline in carbohydrate metabolism and kidney function.
Study Limitations
The authors point out several limitations of their study. The primary limitation is that detailed behavioral data was not included in the analysis. That is, lifestyle factors such as physical activity levels, diet, and alcohol and caffeine consumption were not directly accounted for. Lifestyle factors like these can change many of the biomarkers measured, especially those pertaining to alcohol and caffeine metabolism, as well as oxygen carrier activity, which was found to be reduced around the age of 60.
Another limitation is the number of participants included in the study. Of the 108 participants, only eight were between the ages of 25 and 40, which reduces reliability in this age range. While artificial intelligence tools were used to extrapolate patterns from a few individuals, more participants spanning all ages, particularly above the age of 75 could paint a more accurate and broader picture of the biological changes that occur with aging. Moreover, participants were recruited from the community surrounding Stanford University, located in a suburb of San Jose, California, near some of the most affluent neighborhoods in the world. Therefore, the participants may not represent the general population of the United States.
Additionally, no functional assessments, such as grip strength, memory, or heart rate variability were made. Such assessments could be used to determine whether the biological changes measured lead to functional changes. Longer studies that follow participants over decades could also determine whether molecule and microbe changes lead to higher rates of mortality and diseases. However, a longer study incorporating more participants and functional assessments, (on top of taking multiple types of biological samples) would be quite the undertaking and may not be done, primarily due to funding issues.
Key Takeaways
Our understanding of the aging process is becoming more sophisticated with each discovery. The findings of Shen and colleagues from Stanford University reveal that thousands of molecules and microbes are altered during mid-life and retirement age. Whether the biological changes that occur during these key stages in life are caused by, or a result of psychological, sociocultural, behavioral, or economic factors requires further investigation.
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