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The loss of proteostasis, which results in the accumulation of misfolded proteins, is one of the hallmarks of aging and is frequently associated with the aging process. Fibroblasts are a cellular model widely used in the study of aging and can mimic the loss of proteostasis that occurs in the human body. When studying human aging using fibroblasts, two approaches can be used: fibroblasts from the same donor aged in vitro until senescence or fibroblasts from donors of different ages. A previous study by our group showed that the first approach can be used in the study of aging. Thus, this work aimed to study the spectroscopic profile of human dermal fibroblasts from four donors of different ages using Fourier-transform infrared spectroscopy to identify changes in protein conformation and to compare results with those obtained in the previous study. Partial least squares regression analysis and peak intensity analysis suggested that fibroblasts from older donors were characterized by an increase in the levels of antiparallel β-sheets and a decrease in intermolecular β-sheets, in agreement with our previous results.

Abstract: In the last years, with the increase in the average life expectancy, the world’s population is progressively aging, which entails social, health and economic problems. In this sense, the need to better understand the physiology of the aging process becomes an urgent need. Since the study of aging in humans is challenging, cellular and animal models are widely used as alternatives. Omics, namely metabolomics, have emerged in the study of aging, with the aim of biomarker discovering, which may help to uncomplicate this complex process. This paper aims to summarize different models used for aging studies with their advantages and limitations. Also, this review gathers the published articles referring to biomarkers of aging already discovered using metabolomics approaches, comparing the results obtained in the different studies. Finally, the most frequently used senescence biomarkers are described, along with their importance in understanding aging.

Aging is a complex process which leads to progressive loss of fitness/capability/ability, increasing susceptibility to disease and, ultimately, death. Regardless of the organism, there are some features common to aging, namely, the loss of proteostasis and cell senescence. Mammalian cell lines have been used as models to study the aging process, in particular, cell senescence. Thus, the aim of this study was to characterize the senescence-associated metabolic profile of a long-term culture of human fibroblasts using Fourier Transform Infrared and Nuclear Magnetic Resonance spectroscopy. We sub-cultivated fibroblasts from a newborn donor from passage 4 to passage 17 and the results showed deep changes in the spectroscopic profile of cells over time. Late passage cells were characterized by a decrease in the length of fatty acid chains, triglycerides and cholesterol and an increase in lipid unsaturation. We also found an increase in the content of intermolecular β-sheets, possibly indicating an increase in protein aggregation levels in cells of later passages. Metabolic profiling by NMR showed increased levels of extracellular lactate, phosphocholine and glycine in cells at later passages. This study suggests that spectroscopy approaches can be successfully used to study changes concomitant with cell senescence and validate the use of human fibroblasts as a model to monitor the aging process.

Studying aging is important to further understand the molecular mechanisms underlying this physiological process and, ideally, to identify a panel of aging biomarkers. Animals, in particular mice, are often used in aging studies, since they mimic important features of human aging, age quickly, and are easy to manipulate. The present work describes the use of Fourier Transform Infrared (FTIR) spectroscopy to identify an age-related spectroscopic profile of the cardiac and skeletal muscle tissues of C57BL/6J female mice. We acquired ATR-FTIR spectra of cardiac and skeletal muscle at four different ages: 6, 12, 17 and 24 months (10 samples at each age) and analyzed the data using multivariate statistical tools (PCA and PLS) and peak intensity analyses. The results suggest deep changes in protein secondary structure in 24-month-old mice compared to both tissues in 6-month-old mice. Oligomeric structures decreased with age in both tissues, while intermolecular β-sheet structures increased with aging in cardiac muscle but not in skeletal muscle. Despite FTIR spectroscopy being unable to identify the proteins responsible for these conformational changes, this study gives insights into the potential of FTIR to monitor the aging process and identify an age-specific spectroscopic signature.

Myotonic dystrophy type 1 (DM1) is a hereditary disease characterized by progressive distal muscle weakness and myotonia. Patients with DM1 have abnormal lipid metabolism and a high propensity to develop a metabolic syndrome in comparison to the general population. It follows that metabolome evaluation in these patients is crucial and may contribute to a better characterization and discrimination between DM1 disease phenotypes and severities. Several experimental approaches are possible to carry out such an analysis, among them is Fourier-transform infrared spectroscopy (FTIR) which evaluates metabolic profiles by categorizing samples through their biochemical composition. In this study, FTIR spectra were acquired and analyzed using multivariate analysis (Principal Component Analysis) using skin DM1 patient-derived fibroblasts and controls. The results obtained showed a clear discrimination between both DM1-derived fibroblasts with different CTG repeat length and with the age of disease onset, this was evident given the distinct metabolic profiles obtained for the two groups. Discrimination could be attributed mainly to the altered lipid metabolism and proteins in the 1800–1500 cm−1 region. These results suggest that FTIR spectroscopy is a valuable tool to discriminate both DM1-derived fibroblasts with different CTG length and age of onset and to study the metabolomic profile of patients with DM1.

Life expectancy, and longevity have been increasing in recent years. However, this is, in most cases, accompanied by age-related diseases. Thus, it became essential to better understand the mechanisms inherent to aging, and to establish biomarkers that characterize this physiological process. Among all biomolecules, lipids appear to be a good target for the study of these biomarkers. In fact, some lipids have already been associated with age-related diseases. With the development of analytical techniques such as Mass Spectrometry, and Nuclear Magnetic Resonance, Lipidomics has been increasingly used to study pathological, and physiological states of an organism. Thus, the study of serum, and plasma lipidome in centenarians, and elderly individuals without age-related diseases can be a useful tool for the identification of aging biomarkers, and to understand physiological aging, and longevity. This review focus on the importance of lipids as biomarkers of aging, and summarize the changes in the lipidome that have been associated with aging, and longevity.