Functional Age BioMarkers Part 1: Introduction and Overview

Welcome to part 1 of ODX's "Functional Age Biomarkers" Series. In this series of posts, the ODX Research Team explores 9 blood biomarkers that reflect physiological function and biological/functional age and can help predict 10-year mortality.

The ODX Functional Age Biomarkers Series

Dicken Weatherby, N.D. and Beth Ellen DiLuglio, MS, RDN, LDN

1. Functional Age Biomarkers Part 1: Introduction and Overview
2. Functional Age Biomarkers Part 2: Fasting Glucose
3. Functional Age BioMarkers Part 3: C-Reactive Protein (CRP)
4. Functional Age Biomarkers Part 4: Albumin
5. Functional Age BioMarkers Part 5: Alkaline Phosphatase
6. Functional Age BioMarkers Part 6: Creatinine
7. Functional Age BioMarkers Part 7: Red Cell Distribution Width (RDW)
8. Functional Age BioMarkers Part 8: Mean corpuscular volume (MCV)
9. Functional Age BioMarkers Part 9: Lymphocytes
10. Functional Age BioMarkers Part 10: WBCs

How biomarker changes contribute to biological/functional aging

Aging is a major contributor to chronic diseases and is a significant public health burden. However, individuals of the same chronological age can show considerable differences in age-related diseases and mortality risk, indicating variations in biological/functional aging processes. Recent research suggests that biological/functional age and aging acceleration predict morbidity and mortality risks better than chronological age (Tang 2024).

Aging is also associated with frailty, which is characterized by weakness, reduced physical activity, muscle loss (sarcopenia), and decreased resistance and response to stress. In general, function deteriorates, and metabolic homeostasis is disrupted with aging. However, these changes may be better reflected by evaluating biological age, which considers physiological function and competence, versus chronological age, which only considers the passing of time. Genetic and environmental factors can influence pathological (premature) aging and biological age. Environmental and lifestyle factors are modifiable, including toxin exposure, smoking, excess alcohol, drug use, mental stress, education, sedentary lifestyle, and frailty (Figuer 2021).

How to Measure Biological Age: Key Biomarkers

Researchers have made a breakthrough in identifying a pattern of blood biomarkers that consider physiological processes and changes contributing to aging and disease susceptibility. This set of biomarkers, which reflects physiological function and biological/functional age, can help predict 10-year mortality and empower individuals to take control of their health. Biological age, also known as "functional age," “phenotypic age,” or “PhenoAge,” is a powerful tool in this regard.

The biomarkers measured assess the physiological state of various systems, including cardiovascular, liver, kidney, immune, and metabolic systems. Evaluating biomarkers associated with physiological aging and dysfunction can help predict individual differences in cause-specific mortality, all-cause mortality, physical function, cognitive performance, facial aging, and remaining life expectancy. This evaluation is more reflective of true health than chronological age. Researchers reveal that the nine-biomarker panel biological age evaluation was superior and most predictive of (Levine 2023, Levine 2018):

• Lifespan years remaining
• Accumulation of chronic diseases
• Changes in physical and cognitive function
• Pro-inflammatory processes
• Accelerated aging in those with obesity or metabolic syndrome
• Higher biological age in those with Parkinson’s, Alzheimer’s, breast cancer, and HIV

Biological age predicted 10-year survival with 90% accuracy using the epigenetic clock based on these nine biomarkers (Levine 2023, Levine 2018):

• Fasting glucose: Reflects metabolic health
• C-reactive protein (CRP): Reflects inflammation
• Albumin: Reflects liver function, inflammation, malnutrition
• Alkaline phosphatase: Reflects liver function
• Creatinine: Reflects kidney function
• Red cell distribution width (RDW): Reflects inflammation and hematological function
• Lymphocyte %: Reflects immune function
• White blood cell count (WBC): Reflects immune function and inflammation
• Mean corpuscular volume (MCV): Reflects hematological function

The same nine-biomarker pattern was used to determine the biological age of 9,926 subjects from the third National Health and Nutrition Examination Survey (NHANES III). Measurement units for the nine biomarkers that reflect physiological health include (Levine 2018):

• Albumin g/L
• Alkaline phosphatase U/L
• Creatinine umol/L
• CRP mg/dL
• Glucose, serum, mmol/L
• Lymphocyte %
• MCV fL
• Red cell distribution width (RDW) %
• White blood cell count (WBC) 1000 cells/uL

The validity of this calculation for estimating morbidity and mortality was confirmed in NHANES IV. Follow-up confirmed that for each one-year increase in biological age, the risk of:

• All-cause mortality increased by 9%
• Mortality from aging-related diseases increased by 9%
• CVD mortality increased by 10%
• Cancer mortality increased by 7%
• Diabetes mortality increased by 20%
• Mortality from chronic lower respiratory disease increased by 9%

Retrospective calculation of biological age using the nine established biomarkers revealed a strong association between biological age and all-cause mortality in 609 multivessel coronary artery disease PCI patients. Each 10-year increase in biological age correlated with a 51% increase in mortality risk. Researchers note those with a higher biological age had more disease comorbidities (Ma 2022).

A biological age higher than chronological age helped differentiate non-survivors from survivors in a retrospective study of 2,950 critically ill hospitalized patients. Being phenotypically older was associated with an increased risk of mortality. This effect was “accelerated” in those with pre-existing chronic conditions, including cardiovascular disease, end-stage renal failure, diabetes mellitus, cirrhosis, immune disease, or those undergoing immunosuppressive therapy (Ho 2023).

Factors affecting biological age

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Source: Levine, Morgan E et al. “An epigenetic biomarker of aging for lifespan and healthspan.” Aging vol. 10,4 (2018): 573-591. doi:10.18632/aging.101414 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/29676998/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) 3.0 License

Physiological Function and Deterioration

Aging is associated with detrimental molecular and cellular changes often appearing after age 30. These changes are expressed as muscle, bone, and cartilage loss, adipose tissue increase, and hormonal changes (Dybiec 2022).

The nine biomarkers used to calculate biological age reflect crucial physiological changes associated with inflammation, impaired glucose regulation, compromised liver and kidney function, malnutrition, hematological alterations, and immune competence.

Calculating, addressing, and improving biological age can help reduce the risk of chronic disease and increase the likelihood of a longer healthspan.

Biological age predicted 10-year survival with 90% accuracy using the epigenetic clock based on these nine biomarkers (Levine 2023, Levine 2018):

• Fasting glucose: Reflects metabolic health
• C-reactive protein (CRP): Reflects inflammation
• Albumin: Reflects liver function, inflammation, malnutrition
• Alkaline phosphatase: Reflects liver function
• Creatinine: Reflects kidney function
• Red cell distribution width (RDW): Reflects inflammation and hematological function
• Lymphocyte %: Reflects immune function
• White blood cell count (WBC): Reflects immune function and inflammation
• Mean corpuscular volume (MCV): Reflects hematological function

References

Dybiec, J., et al. "Structural and Functional Changes in Aging Kidneys." *Int J Mol Sci.*, vol. 23, no. 23, 2022, doi:10.3390/ijms232315435.

Figuer, Andrea et al. “Premature Aging in Chronic Kidney Disease: The Outcome of Persistent Inflammation beyond the Bounds.” International journal of environmental research and public health vol. 18,15 8044. 29 Jul. 2021, doi:10.3390/ijerph18158044

Ho, Kwok M et al. “Biological age is superior to chronological age in predicting hospital mortality of the critically ill.” Internal and emergency medicine vol. 18,7 (2023): 2019-2028. doi:10.1007/s11739-023-03397-3

Levine, Morgan E et al. “An epigenetic biomarker of aging for lifespan and healthspan.” Aging vol. 10,4 (2018): 573-591. doi:10.18632/aging.101414 This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) 3.0 License.

Levine, Morgan. True Age: Cutting-edge Research to Help Turn Back the Clock. Penguin, 2023.

Ma, Qiong et al. “Association between Phenotypic Age and Mortality in Patients with Multivessel Coronary Artery Disease.” Disease markers vol. 2022 4524032. 13 Jan. 2022, doi:10.1155/2022/4524032

Tang, Ying et al. “C-reactive protein and ageing.” Clinical and experimental pharmacology & physiology vol. 44 Suppl 1 (2017): 9-14. doi:10.1111/1440-1681.12758

Tang F, et. al. Joint association of diabetes mellitus and inflammation status with biological ageing acceleration and premature mortality, Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 2024, https://doi.org/10.1016/j.dsx.2024.103050.