Literature DB >> 30232762

Biomarkers of Aging.

Xiaojuan Bai1.   

Abstract

Biomarkers of aging are a biological parameter that can predict the functional status of an individual in the absence of disease and can be used to better predict morbidity and mortality, compared to using the chronological age alone. Most of aging biomarkers were gene, molecules, and protein, which were found in basic scientific researches, such as telomeres, proteomics, cytokines, etc. However, it is almost impossible for single biomarkers to fully reveal the mechanism of aging. Because of the complexity of aging process, the biomarkers of aging may need to be composed of multiple genes, proteins, and metabolites. The biological age is based on the setting of biological markers, which is a parameter for evaluating the functional status of the individual. Aging is not only dependent on the process of time. The chronological age is only the evaluation indicators of time scale in the aging process. Therefore, biological age can be more representative of the true degree of aging than chronological age, which provides a quantitative standard for individualized aging. According to the factor score, we established biological age score (BAS) = 0.248 (CA) + 0.195 (IMT) - 0.196 (EDV) - 0.167 (E/A) - 0.166 (MVEL) + 0.188 (PP) + 0.182(FIB) + 0.193 (CYSC) through 7 aging biomarkers selected from 108 variables. The study found the rate of aging was gradually increased before the age of 75 years old and afterward entered a stable plateau. In the future, the new approach may be needed to investigate the mechanisms and evaluation of aging.

Entities:  

Keywords:  BAS; Biological age; Biomarkers of aging; Chronological age

Mesh:

Substances:

Year:  2018        PMID: 30232762     DOI: 10.1007/978-981-13-1117-8_14

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  6 in total

Review 1.  Sex Differences in Molecular Mechanisms of Cardiovascular Aging.

Authors:  Vanessa Dela Justina; Jéssica S G Miguez; Fernanda Priviero; Jennifer C Sullivan; Fernanda R Giachini; R Clinton Webb
Journal:  Front Aging       Date:  2021-09-10

Review 2.  Epigenetic Clock: DNA Methylation in Aging.

Authors:  Shuang Jiang; Yuchen Guo
Journal:  Stem Cells Int       Date:  2020-07-08       Impact factor: 5.443

3.  Association of cathepsin B and cystatin C with an age-related pulmonary subclinical state in a healthy Chinese population.

Authors:  Nan Wang; Yajun Yuan; Xiaojuan Bai; Wen Han; Lulu Han; Bijuan Qing
Journal:  Ther Adv Respir Dis       Date:  2020 Jan-Dec       Impact factor: 4.031

4.  A Machine Learning-Based Aging Measure Among Middle-Aged and Older Chinese Adults: The China Health and Retirement Longitudinal Study.

Authors:  Xingqi Cao; Guanglai Yang; Xurui Jin; Liu He; Xueqin Li; Zhoutao Zheng; Zuyun Liu; Chenkai Wu
Journal:  Front Med (Lausanne)       Date:  2021-12-01

5.  Oxidation, Glycation, and Carbamylation of Salivary Biomolecules in Healthy Children, Adults, and the Elderly: Can Saliva Be Used in the Assessment of Aging?

Authors:  Mateusz Maciejczyk; Miłosz Nesterowicz; Julita Szulimowska; Anna Zalewska
Journal:  J Inflamm Res       Date:  2022-03-28

6.  Machine-Learning Analysis of Voice Samples Recorded through Smartphones: The Combined Effect of Ageing and Gender.

Authors:  Francesco Asci; Giovanni Costantini; Pietro Di Leo; Alessandro Zampogna; Giovanni Ruoppolo; Alfredo Berardelli; Giovanni Saggio; Antonio Suppa
Journal:  Sensors (Basel)       Date:  2020-09-04       Impact factor: 3.576

  6 in total

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