Cardiovascular health is associated with the epigenetic clock in the Berlin Aging Study II (BASE-II).

The epigenetic clock parameter DNAm age acceleration is a promising biomarker of aging. We have recently described an epigenetic clock based on only seven cytosine-phosphate-guanine sites, which is highly associated with chronological age. The aim of this study was to examine this epigenetic clock with respect to its relationship with cardiovascular health (CVH) in older adults. We used data from the Berlin Aging Study II (BASE-II; 1,671 participants; 68.8 ± 3.7 years old). CVH was operationalized using two different CVH scores, the Framingham Risk Score (FRS), and the Life's simple 7 (LS7). To adjust for potential confounding, e.g. by sex, we performed regression analyses. The LS7 score was higher, i.e. more favorable, in woman than in men (8.8 ± 2 vs. 8.2 ± 2, p < 0.001). DNAm age acceleration was associated with the FRS (ß = 0.122, p = 0.028) and with the LS7 (ß = -0.804, p = 0.032). In more detail, physical activity (ß = -0.461, p = 0.05), HDL-cholesterol (ß = 0.343, p = 0.03) and total cholesterol (ß = -0.364, p = 0.002) were associated with epigenetic age acceleration. We present evidence suggesting that better CVH is associated with decelerated biological aging measured by the epigenetic clock.

Gender score development in the Berlin Aging Study II: a retrospective approach.

In addition to biological sex, gender, defined as the sociocultural dimension of being a woman or a man, plays a central role in health. However, there are so far few approaches to quantify gender in a retrospective manner in existing study datasets. We therefore aimed to develop a methodology that can be retrospectively applied to assess gender in existing cohorts. We used baseline data from the Berlin Aging Study II (BASE-II), obtained in 2009-2014 from 1869 participants aged 60 years and older. We identified 13 gender-related variables and used them to construct a gender score by using primary component and logistic regression analyses. Of these, nine variables contributed to a gender score: chronic stress, marital status, risk-taking behaviour, personality attributes: agreeableness, neuroticism, extraversion, loneliness, conscientiousness, and level of education. Females and males differed significantly in the distribution of the gender score, but a significant overlap was also found. Thus, we were able to develop a gender score in a retrospective manner from already collected data that characterized participants in addition to biological sex. This approach will allow researchers to introduce the notion of gender retrospectively into a large number of studies.