Associations between Specific Redox Biomarkers and Age in a Large European Cohort: The MARK‐AGE Project

Abstract

Oxidative stress and antioxidants play a role in age-related diseases and in the aging process. We here present data on protein carbonyls, 3-nitrotyrosine, malondialdehyde, and cellular and plasma antioxidants (glutathione, cysteine, ascorbic acid, uric acid, α-tocopherol, and lycopene) and their relation with age in the European multicenter study MARK-AGE. To avoid confounding, only data from countries which recruited subjects from all three study groups (five of eight centers) and only participants aged ≥55 years were selected resulting in data from 1559 participants. These included subjects from (1) the general population, (2) members from long-living families, and (3) their spouses. In addition, 683 middle-aged reference participants (35–54 years) served as a control. After adjustment for age, BMI, smoking status, gender, and country, there were differences in protein carbonyls, malondialdehyde, 3-nitrotyrosine, α-tocopherol, cysteine, and glutathione between the 3 study groups. Protein carbonyls and 3-nitrotyrosine as well as cysteine, uric acid, and lycopene were identified as independent biomarkers with the highest correlation with age. Interestingly, from all antioxidants measured, only lycopene was lower in all aged groups and from the oxidative stress biomarkers, only 3-nitrotyrosine was increased in the descendants from long-living families compared to the middle-aged control group. We conclude that both lifestyle and genetics may be important contributors to redox biomarkers in an aging population.

Nutritional Factors Modulating Alu Methylation in an Italian Sample from The Mark-Age Study Including Offspring of Healthy Nonagenarians

“…In our study, we observed that Alu methylation at the CpG1 site do not display marked age-related changes, but lower levels of methylation at this site were found in elderly subjects over 65 years compared to the age class 55-64 years. Regarding the other CpGs, we observed only a significant increase in the 55-64 years age class compared to the youngest age class (35)(36)(37)(38)(39)(40)(41)(42)(43)(44). This last finding would appear to be in contrast with previous results, where young subjects have higher Alu methylation levels than older ones [18].…”

“…Total glutathione and total free cysteine in whole blood were measured by RP-HPLC with UV-Vis detection after reduction and modifications as previously reported [37].…”

“…Plasma ascorbic acid and uric acid were analyzed by RP-HPLC and UV detection after reduction with tris-(2-carboxyethyl)-phosphine. The details of the method have been previously reported [37].…”

Measuring biological aging in humans: A quest

“…Several assays are available for measuring ROS generation, antioxidant defense, and oxidative damage to macromolecules in blood, cells, and tissues (Dikalov & Harrison, 2014;Starkov, 2010). The significance of these oxidative stress biomarkers for aging is uncertain, as in many cases they have been studies in specific medical conditions and not in the context of aging studies (Al Shahrani, Heales, Hargreaves, & Orford, 2017;Hayashi & Cortopassi, 2015;Weber et al, 2017). Studies that use multiple mitochondrial biomarkers have revealed only a slight intercorrelation between the markers and aging, suggesting that they tap into different biological dimensions (Lara et al, 2015;Larsen et al, 2012;Marrocco, Altieri, & Peluso, 2017;Xia, Chen, McDermott, & Han, 2017).…”

Epigenetic and redox biomarkers: Novel insights from the MARK-AGE study

“…Differences between RASIG and the other two groups, with no differences between GO and SGO, could be lifestyle-related while differences between GO and SGO (irrespective of the RASIG results) suggest a genetic contribution. The levels of redox biomarkers, such as protein carbonyls, 3-nitrotyrosine, malondialdehyde, and cellular and plasma antioxidants (glutathione, cysteine, ascorbic acid, uric acid, α-tocopherol, and lycopene) were analyzed and compared within the three different subgroups (Weber et al, 2017):…”