Measuring Biological Age: A New Approach to Health
Discover how biological age impacts our understanding of health in older adults.
D. Bizzarri, E.B. van den Akker, M.J.T. Reinders, R. Pool, M. Beekman, N. Lakenberg, N. Drouin, K.E. Stecker, A.J.R. Heck, E.F. Knol, J.M. Vergeer, M.A. Ikram, M. Ghanbari, A.J. van Gool, D.I. Boomsma, P.E. Slagboom
― 7 min read
Table of Contents
- What is Biological Age?
- What Are Omics?
- The MetaboHealth Score
- Data Collection: The Power of Large Studies
- A Peek into the Blood: What the Markers Tell Us
- The Role of Inflammation
- The Impact of Lifestyle and Environment
- A Look into the Twins’ Data
- Identifying Key Proteins and Markers
- Conclusion: The Future of Aging Research
- Original Source
- Reference Links
As people live longer, the global population is aging. This raises important questions about how to measure the well-being of older individuals. One key concept is "Biological Age," which helps assess how vulnerable someone is to diseases, regardless of their actual age. Think of it as trying to figure out if someone’s car is running well, even if it looks shiny on the outside.
What is Biological Age?
Biological age refers to how well our bodies function compared to average health levels at various ages. For example, two people might be the same age, but one could be healthy and active while the other struggles with health issues. This difference may indicate their biological age is not the same.
Traditionally, researchers estimated biological age through various tests and measures. However, advancements have led to the use of comprehensive datasets that include molecular information, which provides a broader view of an individual’s health status.
What Are Omics?
Now, let's talk about omics—the world of science that studies the components of biological systems at various scales. This includes metabolomics (the study of metabolites) and proteomics (the study of Proteins). In simpler terms, metabolomics looks at the tiny substances in our bodies that help us function—like checking the fuel in our car. Proteomics, on the other hand, focuses on the proteins, which are the building blocks that keep everything running smoothly—like the engine parts of that car.
Using these scientific approaches allows researchers to see how an individual is doing health-wise without needing to wait for diseases to emerge fully.
The MetaboHealth Score
The MetaboHealth Score is one tool that researchers use to assess biological age. It is built from a bunch of factors, including metabolites and proteins found in the blood. Interestingly, this score can predict health risks, including the risk of dying within the next five years, based on just 14 metabolic markers. It’s like a doctor giving you a health report card based on a quick check-up!
While it started as a way to assess mortality risk, the MetaboHealth Score has been shown to predict other health conditions that can arise with aging, such as frailty, cognitive decline, and even respiratory issues. However, the exact reasons behind how it works are still somewhat of a mystery—like trying to understand why your car won't start on a rainy day.
Data Collection: The Power of Large Studies
To gather more information and validate their findings, researchers looked at participants from several large studies. These studies included thousands of individuals and allowed for a diverse pool of data. By comparing the blood profiles of people with high and low MetaboHealth Scores, scientists can identify patterns and markers that reveal more about biological age.
In their quest for information, researchers focused on two main groups of participants: older adults and monozygotic twins (twins who share nearly identical DNA). Twins can be particularly useful in research because they help reduce the effects of genetic differences. By comparing twins with different MetaboHealth Scores, researchers get a clearer picture of how these scores relate to health without the influence of genetics getting in the way.
A Peek into the Blood: What the Markers Tell Us
The researchers examined blood samples to discover which proteins and cytokines—substances that help regulate the immune system—were linked to the MetaboHealth Score. They found that some proteins were significantly higher in individuals with higher MetaboHealth scores, suggesting more Inflammation and a poorer health status. It's like noticing more smoke coming from an engine under stress.
Among the proteins studied, GDF15, IL6, and MIG stood out as being significantly higher in those with poorer health. GDF15 is often related to stress responses in the body, IL6 is known for its role in inflammation, and MIG is involved in immune responses. The presence of these markers indicates that the body might be struggling, similar to when you see warning lights on your dashboard.
The Role of Inflammation
Inflammation is a natural response of the body to fight off infections or injuries. However, chronic inflammation can lead to serious health issues, especially as we age. The researchers found that people with higher MetaboHealth scores had more inflammatory markers in their blood, suggesting that they might be dealing with long-term inflammation, which isn't great news.
Conversely, those with lower MetaboHealth scores tended to show healthier profiles with fewer inflammatory markers. This indicates a healthier state, much like a well-tuned car running smoothly without any warning lights flashing.
The Impact of Lifestyle and Environment
While biological factors play a big role in health, lifestyle and environment are equally important. The studies looked at various factors that could influence health, such as diet, physical activity, and medication use. The results showed that even small changes in these factors could impact health outcomes.
For instance, individuals with a higher MetaboHealth Score often had higher body mass indexes (BMI) and were more likely to take medications for high blood pressure. These factors can add a layer of complexity when interpreting the scores and how they relate to actual health.
A Look into the Twins’ Data
The use of monozygotic twins in the research provided fascinating insights. By examining twins with differing MetaboHealth Scores, researchers aimed to find out how much of the score's impact could be attributed to genetics versus lifestyle choices. The findings indicated that while genetics certainly play a role, environmental factors and lifestyle choices are also significant contributors.
For example, if one twin had a high MetaboHealth Score and the other a low one, this difference might not come down to genetics but rather lifestyle choices, such as diet and exercise. It’s a reminder that while we can inherit certain traits, our choices shape a big part of our health story.
Identifying Key Proteins and Markers
Among the various proteins in the blood that researchers studied, they were able to identify both positive and negative associations with the MetaboHealth Score. Positive associations indicated proteins linked to inflammation or potential health risks, while negative associations pointed to healthier protein profiles.
In a twist, some proteins associated with COVID-19 outcomes were found to differ between those with high and low MetaboHealth Scores. This connection hints at the potential of using the MetaboHealth Score to predict various health outcomes, including responses to infections. It's like having a multi-tool that can help diagnose different issues beyond just one.
Conclusion: The Future of Aging Research
This research underscores how measuring biological age through blood profiles can help us understand the health of our aging population. It highlights the connections between inflammation, lifestyle choices, and their impacts on biological age. The potential to use a simple score like MetaboHealth to assess health risks is promising.
As researchers continue to connect the dots, they hope to refine this score and improve its predictive power. The ultimate goal is to provide early warnings about health decline, allowing for proactive interventions—kind of like checking your engine oil before a road trip to avoid breakdowns.
Aging might be a natural process, but with the right tools and insights, we can navigate it more gracefully and healthily. As they say, it's not only about how old you are, but how well you are!
Original Source
Title: Extreme MetaboHealth scores in three cohort studies associate with plasma protein markers for inflammation and cholesterol transport.
Abstract: The MetaboHealth score is a highly informative health indicator in ageing studies and yet contains only a small number of metabolites. Here we estimate the heritability of the score in 726 monozygotic (MZ) and 450 dizygotic (DZ) twin pairs, and test for association with plasma proteins by comparing extreme scoring individuals selected from two large population cohorts -the Leiden Longevity Study (LLS) and the Rotterdam Study (RS) and discordant monozygotic twin pairs from the Netherlands Twin Register (NTR). The heritability for the MetaboHealth score was estimated at 40%. In 50 high and 50 low scoring MetaboHealth groups from LLS and RS, we uncovered significant differences in plasma proteins, notably in 3 (out of 15) cytokines (GDF15, IL6, and MIG), and 106 proteins (out of 289) as determined by Mass Spectrometry based proteomics analysis. A high MetaboHealth score associated with an increased level for 42 serum proteins, predominantly linked to inflammation and immune response, including CRP and HPT. A low score associated with decreased levels of 71 proteins enriched in high-density lipoprotein (HDL) remodeling and cholesterol transport pathways, featuring proteins such as APOA1, APOA2, APOA4, and TETN. In MZ twins selected for maximal discordance within a pair we found 68 serum proteins associated with the MetaboHealth score indicating that a minor part of the associations observed in LLS and RS is likely explained by genetic influences. Taken together, our study sheds light on the intricate interplay between MetaboHealth, plasma proteins, cytokines, and genetic influences, paving the way for future investigations aimed at optimizing this mortality risk indicator.
Authors: D. Bizzarri, E.B. van den Akker, M.J.T. Reinders, R. Pool, M. Beekman, N. Lakenberg, N. Drouin, K.E. Stecker, A.J.R. Heck, E.F. Knol, J.M. Vergeer, M.A. Ikram, M. Ghanbari, A.J. van Gool, D.I. Boomsma, P.E. Slagboom
Last Update: 2024-12-02 00:00:00
Language: English
Source URL: https://www.medrxiv.org/content/10.1101/2024.12.01.24318258
Source PDF: https://www.medrxiv.org/content/10.1101/2024.12.01.24318258.full.pdf
Licence: https://creativecommons.org/licenses/by-nc/4.0/
Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.
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