Models for estimating the biological age of five organs using clinical biomarkers that are commonly measured in clinical practice settings

Bae, Chul Young; Kang, Youn‐Jung; Piao, Mei Hua; Cho, Belong; Cho, Kyung Hee; Park, Yong Kyu; Yu, Byung Yeon; Lee, Sang−Wha; Kim, Moon Jong; Lee, Sang Hyun; Kim, Yun Jin; Kim, Dae Hyun; Kim, Jong Sung; Oh, Jeong Eun

doi:10.1016/j.maturitas.2013.04.008

Cited by 26 publications

(23 citation statements)

References 43 publications

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“…Traditionally, aging biomarkers are often selected based on common clinical laboratory tests for the easy application in the clinical practice21 as well as the limitations of technology 9,60. However, clinical biomarkers may lower the accuracy of the BA formula 28.…”

Section: Criteria For Aging Biomarker Selectionmentioning

confidence: 99%

“…For example, a person may be physically in good shape, but not so cognitively, or vice versa. Thus, it is necessary to obtain various aging biomarkers from multiple systems and to combine them with efficient statistical models for reflecting overall aging of an individual 21. The statistical method employed plays an important role in BA estimation studies, determining the validity, specificity, and limitations of the BA model.…”

Section: Introductionmentioning

confidence: 99%

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Common methods of biological age estimation

Jia

Zhang

Chen

2017

CIA

100

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At present, no single indicator could be used as a golden index to estimate aging process. The biological age (BA), which combines several important biomarkers with mathematical modeling, has been proposed for >50 years as an aging estimation method to replace chronological age (CA). The common methods used for BA estimation include the multiple linear regression (MLR), the principal component analysis (PCA), the Hochschild’s method, and the Klemera and Doubal’s method (KDM). The fundamental differences in these four methods are the roles of CA and the selection criteria of aging biomarkers. In MLR and PCA, CA is treated as the selection criterion and an independent index. The Hochschild’s method and KDM share a similar concept, making CA an independent variable. Previous studies have either simply constructed the BA model by one or compared the four methods together. However, reviews have yet to illustrate and compare the four methods systematically. Since the BA model is a potential estimation of aging for clinical use, such as predicting onset and prognosis of diseases, improving the elderly’s living qualities, and realizing successful aging, here we summarize previous BA studies, illustrate the basic statistical steps, and thoroughly discuss the comparisons among the four common BA estimation methods.

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Section: Criteria For Aging Biomarker Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Common methods of biological age estimation

Jia

Zhang

Chen

2017

CIA

100

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“…Taking the opposite view, this research maintains that ‘inaccuracy’, i.e., the difference between CA and BA, is a repercussion of individual variations in longevity as well as individual differences in the onset and variations in the aging processes due to genetic, epigenetic, and environmental conditions (Bae et al, ; Belsky et al, ; Cho, Park, & Lim, ; de Rooij & Roseboom, ; Levine, ). Indeed, research in living populations found the estimated standard deviation of the difference between CA and BA varies between three and 10 years (Belsky et al, ; Hochschild, ; Klemera & Doubal, ), and because the health of individuals is highly heterogeneous, as is the rate of aging, discordances between BA and CA can take place from a young age (Belsky et al, ; Molinari, Gasser, & Largo, ; Wiweko et al, ) not just among older individuals as is often assumed.…”

Section: Introductionmentioning

confidence: 99%

“…Likewise, it is worth mentioning that CA, as the amount of elapsed time from birth to a specific moment in life or death, is not by itself a reliable indicator of an individual's physiological state and therefore cannot distinguish functional differences among individuals of the same age (Bae et al, ; Belsky et al, ; Levine, ). Rather, CA serves only as a proxy of the general biological state and rate of aging.…”

Section: Introductionmentioning

confidence: 99%

“…By contrast, BA conceived as the general state of health or physiological integrity of an individual at a specific point of the CA, is intended to assess the changes in growth and development of an individual as well as its gradual functional and structural decline that result in increased risk of disease, impairment, and mortality over a lifespan (Bae et al, ). This means, that in individuals of the same CA, age‐related changes and rates of coordinated physiological deterioration vary (Bae et al, ; Belsky et al, ; Horvath, ). Therefore, individuals with the greatest organismic deterioration relative to their same chronologically aged peers, are considered older with respect to their BA, and vice versa (Milne, ).…”

Section: Introductionmentioning

confidence: 99%

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Differences between biological and chronological age‐at‐death in human skeletal remains: A change of perspective

Couoh

2017

American J Phys Anthropol

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TCA can be used to estimate CA and its differences with BA, being less than 10 years, are similar to those found in living populations. Differences between CA and BA are due to intra-population variability, which could be the consequence of individual differences in aging. More research is needed to have confidence that under- and overestimations of BA are indicators of aging variability at the level of the individual.

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Models to Explore Genetics of Human Aging

Karasik

Newman

2015

Longevity Genes

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Genetic studies have bestowed insight into the biological mechanisms underlying inter-individual differences in susceptibility to (or resistance to) organisms’ aging. Recent advances in molecular and genetic epidemiology provide tools to explore the genetic sources of the variability in biological aging in humans. To be successful, the genetic study of a complex condition such as aging requires the clear definition of essential traits that can characterize the aging process phenotypically. Phenotypes of human aging have long relied on mortality rate or exceptional longevity. Genome-wide association studies (GWAS) have been shown to present an unbiased approach to the identification of new candidate genes for human diseases. The GWAS approach can also be used for positive health phenotypes such as longevity or a delay in age-related chronic disease, as well as for other age related changes such as loss of telomere length or lens transparency. Sequencing, either in targeted regions or across the whole genome can further identify rare variation that may contribute to the biological aging mechanisms. To date, the results of the GWAS for longevity are rather disappointing, possibly in part due to the small number of individuals with GWAS data who have reached advanced old age.Human aging phenotypes are needed that can be assessed prior to death, and should be both heritable and validated as predictors of longevity. Potentially, phenotypes that focus on “successful” or “healthy” aging will be more powerful as they can be measured in large numbers of people and also are clinically relevant.We postulate that construction of an integrated phenotype of aging can be achieved capitalizing on multiple traits that may have weak correlations, but a shared underlying genetic architecture. This is based on a hypothesis that convergent results from multiple individual aging-related traits will point out the pleiotropic signals responsible for the overall rate of aging of the organism. An approach would be to investigate traits that are linked to the state of many vital functions, disability, and ultimately survival rates, to identify common biological pathways that govern aging processes in humans. New composite aging phenotypes must be validated by predicting all-cause mortality, major chronic disease and disability late in life.

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Models for estimating the biological age of five organs using clinical biomarkers that are commonly measured in clinical practice settings

Cited by 26 publications

References 43 publications

Common methods of biological age estimation

Common methods of biological age estimation

Differences between biological and chronological age‐at‐death in human skeletal remains: A change of perspective

Models to Explore Genetics of Human Aging

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