biological age

^[1]^[2]^[3]^[4]^[5]

Introduction

Biological age captures some of the variance in life expectancy for which chronological age is not accountable
quantifies the heterogeneity in the presentation of the aging phenotype in different individuals.
in the elderly, biological age may be estimated using the frailty index
the frailty index outperforms age & Klemera-Doubal's biological age estimates in the elderly, especially among the oldest old at high risk of mortality due to (at least in part) biological aging^[1]
a DNA methylation index, based on 38 CpG sites can predict mortality better than the frailty index based on health, function, & blood chemistry^[1]

biological age results from contributions of genetic predispositions & physiological responses to exposure accumulation over a lifespan^[1]
nonlinear patterns occur in molecular markers of aging^[5]
- dysregulation occurs at ~44 & ~60 years of chronological age^[5]
  - cardiovascular disease, lipid & alcohol metabolism changes at the 40-year transition
  - immune regulation & carbohydrate metabolism changes at the 60-year transition^[5]

3 commonly used methods to compute biological age
- principal components-PCA
- multiple regression-MLR
- Klemera-Doubal's method-KD
a structural equation model
- represents the relation between chronological age & biological age
- circumvents the need to impose arbitrary assumptions about the relation between chronological age & biological age
- provides tools to empirically test the validity of assumptions a researcher may wish to invoke^[2]
a structural equation model estimates of biological age differs from those estimates from principal components & multiple regression, but is comparable to Klemera-Doubal's method^[2]
5 groups of biomarkers
- waist circumference/ waist to hip rato
- blood pressure
- lipid profile
- blood glucose/glycosylated hemoglobin
- serum urea/creatinine ratio^[3]

↑ ^1.0 ^1.1 ^1.2 ^1.3 Kim S, Fuselier J, Welsh DA et al Feature Selection Algorithms Enhance the Accuracy of Frailty Indexes as Measures of Biological Age. J Gerontol A Biol Sci Med Sci. 2021 PMID: https://www.ncbi.nlm.nih.gov/pubmed/33471059 PMCID: PMC8277082 Free PMC article.
↑ ^2.0 ^2.1 ^2.2 Beltran-Sanchez H, Palloni A, Huangfu Y, McEniry MC. Modeling biological age and its link with the aging process. PNAS Nexus. 2022 Jul 26;1(3):pgac135. PMID: https://www.ncbi.nlm.nih.gov/pubmed/36741436 PMCID: PMC9923798 Free PMC article.
↑ ^3.0 ^3.1 Wei K, Peng S, Liu N et al All-Subset Analysis Improves the Predictive Accuracy of Biological Age for All-Cause Mortality in Chinese and U.S. Populations. J Gerontol A Biol Sci Med Sci. 2022 Nov 21;77(11):2288-2297. PMID: https://www.ncbi.nlm.nih.gov/pubmed/35417546 PMCID: PMC9923798 Free PMC article.
↑ ^4.0 ^4.1 ^4.2 Chen L, Zhang Y, Yu C et al Modeling biological age using blood biomarkers and physical measurements in Chinese adults. EBioMedicine. 2023 Mar;89:104458. PMID: https://www.ncbi.nlm.nih.gov/pubmed/36758480 PMCID: PMC9941058 Free PMC article. https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(23)00023-3/fulltext
↑ ^5.0 ^5.1 ^5.2 ^5.3 Shen X, Wang C, Zhou X, Zhou W, Hornburg D, Wu S, Snyder MP. Nonlinear dynamics of multi-omics profiles during human aging. Nat Aging. 2024 Aug 14. PMID: https://www.ncbi.nlm.nih.gov/pubmed/39143318 https://www.nature.com/articles/s43587-024-00692-2