Can scientists predict the lifespan of a blood drop?

Can scientists predict the lifespan of a blood drop?

Discover how a new epigenetic clock measures how quickly you really age from a drop of blood or saliva.

Study:A blood-based intrinsic capacity epigenetic clock predicts mortality and is associated with clinical, immunological and lifestyle factors. Photo credit: Zapylaiev Kostiantyn/shuuterstock.com

A study recently published in the journalNatural tern constructed an intrinsic capacity clock (IC) to predict all-cause mortality based on various factors.

What is intrinsic capacity?

In 2015, the World Health Organization (WHO) introduced intrinsic capacity (IC), a critical component of healthy aging. Defined IC as “the sum of all physical and mental abilities that an individual can draw upon at any point in their life.”

IC promotes healthy aging by shifting the conventional focus of treatment of acute illnesses to assessing and maintaining an individual's functional capabilities. It is important to note that IC varies between individuals and typically peaks in early childhood and gradually declines after middle life. However, IC can be improved at any age through lifestyle changes.

The International Classification of Diseases, 11th Revision, recently standardized the clinical use of IC as a functional aging metric. To date, several studies have developed IC scores where a low IC score is associated with higher comorbidity, difficulty with daily activities, frailty, and increased falls. These studies have also established a link between IC and health-related factors.

Although IC can efficiently measure functionality, the current protocol for quantitative measures is very complex and requires sophisticated equipment and trained personnel. Furthermore, the exact molecular and cellular mechanisms associated with the age-related decline in IC are unclear.

About the study

The current study aimed to construct a new epigenetic predictor of IC (IC Clock) using data from the Inspiration Translational (Inspire-T) cohort. This cohort is an ongoing 10-year follow-up study evaluating IC changes and biomarkers of aging and age-related diseases. The participants are between 20 and 102 years old and have different functional capacities.

DNA profiling (DNAM) was performed on more than 1000 participants in the Inspire-T cohort. DNAM beta values ​​and IC scores were used to build a predictive model for IC using net elastic regression and ten-fold cross-validation.

The IC clock was applied to the Framingham Heart Study (FHS) to explore how DNAM IC was associated with mortality, clinical markers of health and lifestyle.

Transcriptomics data and cellular composition changes were considered to evaluate the molecular and cellular mechanisms of IC.

Study results

Clinical assessment tools have used IC values ​​(from 0 to 1) that represent age-related decline in various domains such as sensory, cognitive, psychological, locomotion, and vitality. An IC score of 1 indicated the best health outcome, while a zero score indicated the worst outcome.

All IC domains examined were negatively correlated with age. The current study found that males had higher IC scores in the psychological and vitality domains, while females had higher scores in the sensory domain. No gender differences were observed in the areas of cognition and locomotion.

A continuous two-phase model regression analysis showed that female participants experienced earlier sensory decline, while male participants experienced earlier cognitive decline. This finding implies that women maintain cognitive functions such as thinking, remembering and reasoning longer than men.

The overall IC score showed a robust positive correlation with each domain compared to the correlations between domains, highlighting the integrative nature of the IC score. The highest and lowest inter-domain correlations were found in the sensory and psychological domains, respectively.

The model that ranked best across all metrics examined, i.e., highest correlation, lowest error, and fewer cytosine-phosphate-guanine (CPG) defects, showed a correlation of 0.61 between IC and predicted values ​​based on DNAM. Although a strong correlation was observed based on age, CPGs with the highest coefficients showed almost zero correlation with chronological age.

The newly constructed IC clock was compared with first and second generation epigenetic clocks. A negative correlation between DNAM IC and the epigenetic clocks was observed, with the Phänkel giving the strongest correlation, followed by the Hannum clock. The current study found that DNAM IC can be calculated from saliva and blood samples.

The current study also identified the expression of 578 genes (e.g., e.g.Mcoln2AndCD28Genes)as significantly associated with DNAM -IC changes. CPGs in the IC clock showed a correlation of 0.21 with the expression of at least one significant gene. This observation confirmed the robust link between the IC clock and the identified gene expression signature of DNAM IC.

Gene Ontology (GO) analysis was performed to determine the biological processes associated with the gene expression signature of DNAM IC. The IC expression signature was highly enriched in genes involved in cellular senescence and chronic inflammation. The IC clock detected various aspects of immunosenescence in blood, which was associated with functional changes in immune aging.

The current study found that genomic instability, mitochondrial dysfunction and proteostasis loss were associated with the function of specific IC domains. Higher vitality scores were associated with mitochondrial electron transport genes. In comparison, higher psychological scores were related to DNA damage response pathways and higher sensory scores were related to proteostasis and immune response pathways.

Mortality data from the 1,680 individuals in the FHS were used to determine whether DNAM IC was associated with an increased risk of mortality from all causes or age-related conditions. DNAM IC was found to be more strongly associated with all-cause mortality risks. This study estimated that individuals with high DNAM -IC would live, on average, 5.5 years longer than individuals with low DNAM -IC.

In this study, this study showed that consuming fish rich in long-chain omega-3 fatty acids and adhering to recommended sugar levels could promote IC maintenance. Although a range of dietary factors were examined, only fish-derived omega-3 factors and adherence to sugar guidelines remained significant after adjusting for multiple tests.

The researchers also note that IC declines rapidly in very old age. Due to limited data in this age group, their predictive model is not as strong for individuals with extremely low IC values.

While the IC clock is strongly associated with mortality and health outcomes, the study cannot demonstrate that improving DNAM IC necessarily leads to better health outcomes or longer lifespans.

Conclusions

The current study identified a biological clock for age-related decline in IC based on multiple clinical, functional, immune and inflammatory components and lifestyle choices.

This IC clock can be estimated from blood and saliva and outperforms epigenetic clocks in predicting mortality risk. However, further research is needed to clarify causal relationships and validate the IC clock in more diverse populations and among those with very low functional capacity.

An individual's IC can be used to guide aging interventions, although these results should be interpreted taking into account the limitations of the study and the need for further validation.

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