Biological Predictors of Aging and Potential of FTIR to Study Age-related Diseases and Aging Metabolic Fingerprint

abstract

Background: It is known that the increasing aging of population is the origin of enormous challenges to healthcare provision and treatment of age-related diseases, "aging" being a promissory research field. One of the emerging focus of aging research is to find suitable ways to increase health-span, rather than lifespan. In this way, metabolomic analysis seems promising once metabolite analysis is been used in several studies of human populations in order to understand both physiological and pathologic metabolic processes. Focus: Human metabolome changes along with age and those changes are certainly related to the onset of several age related diseases. It is expectable that the study of aging metabolome could help to understand molecular physiology of aging and age related diseases. In order to extract information from the data obtained by all metabolomics techniques applied in this research field it is crucial to recognize the corresponding metabolites, in particular the biological predictors of aging, that is, molecules that ultimately could be used to predict the aging status of tissues, organs or the entire individual. Prospect: This review presents an exhaustive list of the main classes of the biological predictors of aging, some of which are potential aging biomarkers. The gathered information can be used to sustain the information obtained by the several metabolomics approaches dedicated to the study of aging. This work also defines and characterizes aging, briefly summarizes the main theories and senescence mechanisms and describes the hallmarks of aging. An overview of Fourier Transform Infrared Spectroscopy technique and its potential to study the metabolome of aging is also presented.

keywords

CORONARY-HEART-DISEASE; TRANSFORM INFRARED-SPECTROSCOPY; DIPLOID CELL STRAINS; ALZHEIMERS-DISEASE; RAMAN-SPECTROSCOPY; CEREBROSPINAL-FLUID; DEHYDROEPIANDROSTERONE-SULFATE; DNA-DAMAGE; RHEUMATOID-ARTHRITIS; PATTERN-RECOGNITION

subject category

Endocrinology & Metabolism

authors

Graca, A; Magalhaes, S; Nunes, A

our authors

acknowledgements

This work was financed by UID/BIM/04501/2014, iBiMED, University of Aveiro and the Fundacao para a Ciencia e Tecnologia of the Ministry of Education and Science of Portugal.; Sandra Magalhaes is also funded with an individual research grant (BI/UI98/7395/2016) from iBiMED, co-funded by Fundacao para a Ciencia e Tecnologia and FEDER, within the project UID/BIM/04501/2013.

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