Die Epigenetische Uhr und relative Leukozyten-Telomerlänge repräsentieren weitgehend unterschiedliche Aspekte des Alterns in der Berliner Altersstudie II (BASE-II)

Zusammenhänge zwischen DNA-Methylierungsmustern und altersassoziierten Phänotypen und Erkrankungen sind schon längere Zeit bekannt. Neuere Studien konnten eine Vorhersage des chronologischen Alters basierend auf dem Methylierungsstatus unterschiedlicher Subgruppen von Cytosin-Phosphat-Guanin-Dinukleotiden (CpG sites) in proliferierendem und nicht-proliferierendem Gewebe treffen. Daraufhin wurde vermutet, dass das DNA Methylierungsalter (DNAm age, epigenetic clock) und dessen Abweichung vom chronologischen Alter (DNAm acceleration), neben anderen Biomarkern wie der relativen Leukozyten-Telomerlänge (rLTL), zumindest teilweise, das biologische Alter reflektiert. Studien konnten Assoziationen zwischen Methylierungsalter und Gebrechlichkeit, kognitiven Einschränkungen, kardiovaskulären Erkrankungen und weiteren Phänotypen zeigen. Um die Bestimmung des Methylierungsalters für große Kohorten zu vereinfachen, gibt es ein kontinuierliches Bestreben die Anzahl der notwendigen CpG-Dinukleotide zu reduzieren. Das Ziel dieser Studie war die Adaptierung und Optimierung der kürzlich von Vidal-Bralo et al. veröffentlichten Methodik und die Validierung des resultierenden Methylierungsalters, sowie die Untersuchung der Beziehung zwischen DNAm age, DNAm acceleration und rLTL. Wir bestimmten das Methylierungsalter basierend auf sieben CpG-Dinukleotiden in 1.895 DNA-Proben von Probanden der Berliner Altersstudie II (BASE-II). Nach einer Bisulfit-Konversion erfolgt eine Amplifizierung der zu analysierenden DNA-Abschnitte durch eine Multiplex-Polymerasekettenreaktion (mPCR). Die Bestimmung der Methylierungsfraktionen der einzelnen CpG-Dinukleotide erfolgt über eine Primerverlängerung mit fluoreszierenden ddNTPs (methylation-senesitive single nucleotide primer extension, SNuPE). Die für die Messung des Methylierungsalters notwendige Anzahl der CpG-Dinukleotide konnten wir für diese Studie von acht auf sieben reduzieren. Im Ergebnis zeigte sich eine signifikante positive Korrelation zwischen Methylierungsalter und chronologischem Alter (N=1.895, R2=0,47, p<0,001), die auch nach Kontrolle für relevante Kovariablen (Geschlecht, Leukozytenverteilung, Alkoholkonsum und Rauchen) besteht. Die Genauigkeit der Altersschätzung kontrollierten wir über die Mittelwertdifferenz (mean difference = -0,3) und mittlere absolute Abweichung (mean absolute deviation = 6,3) zwischen Methylierungsalter und chronologischem Alter. Die DNAm age acceleration beschreibt den Anteil des gemessenen Methylierungsalters, der weder durch das chronologische Alter noch durch eine altersbedingte Veränderung der Leukozytenverteilung erklärt werden kann. Eine lineare Regressionsanalyse, die Alter, Geschlecht, Alkohol und Rauchen als Kovariablen einschließt, zeigt eine signifikante, aber schwach negative, Assoziation zwischen DNAm age acceleration und rLTL (ß=-0,002, p=0,007). Unsere Analysen weisen auf ein hohes Potential des Methylierungsalters als Biomarker für biologisches Alter hin. Mit den im Rahmen dieser Studie erhobenen Daten sind Analysen möglich, die wichtige Einblicke in den Zusammenhang zwischen Methylierungsalter und biologischem Alter erwarten lassen.Relationships between DNA methylation and age-associated phenotypes are known for many years, but only recently, studies were able to estimate chronological age based on methylation status in different sets of Cytosin-Phosohate-Guanin dinucleotides (CpG sites) in proliferating and non-proliferating tissue. It was suggested that DNA methylation age (DNAm age, epigenetic clock), similar to relative leukocyte telomere length (rLTL), could represent biological age. Indeed, associations between DNAm age and frailty, cognitive impairment, cardiovascular disease and other age-associated phenotypes have been described. Since the first epigenetic clock was published, there is a continuous endeavor to simplify the estimation of DNAm age in larger cohorts by reducing the required number of CpG sites. The goal of this study was the adaption and validation of the recently published DNAm age estimation method by Vidal-Bralo et al. and to investigate the relationship of DNAm age, DNAm age acceleration and rLTL. We determined the DNAm age and DNAm age acceleration based on seven CpG sites in 1,895 DNA samples from participants of the Berlin Aging Study II (BASE-II). The assay included a bisulfite conversion followed by a multiplex polymerase chain reaction (mPCR). The final methylation fraction of the specific CpG sites was determined by a methylation-sensitive single nucleotide primer extension (SNuPE). Our results showed a highly significant association between DNAm age and chronological age (N=1895, R2=0.47), which persisted after adjustment for covariates (sex, leukocyte distribution, alcohol, smoking). In this study, we were able to reduce the number of CpG sites from the eight sites described in the original protocol to seven sites, without a significant loss in the degree of chronological age prediction. The accuracy of our age estimation was assessed by the mean difference (mean difference=-0.3) and mean absolute deviation (MAD=6.3) between DNAm age and chronological age. DNAm age acceleration is the proportion of the DNAm age that could neither be explained by chronological age nor by age related changes in the leukocyte cell distribution. We investigated the relationship between DNAm age acceleration and rLTL and were able to show a weak but significant negative association between these biomarkers of biological age (ß=-0.002, p=0.007). DNAm age seems to be a sensitive biomarker that could be very valuable in examining phenotypes of aging which are not related to pathways affected by mitotic age as measured through rLTL. The data collected in this study will enable analyses with a high potential to get further insight into the relationship between DNAm age, DNAm age acceleration and biological age

Seven-CpG DNA Methylation Age Determined by Single Nucleotide Primer Extension and Illumina’s Infinium MethylationEPIC Array Provide Highly Comparable Results

DNA methylation age (DNAm age, epigenetic clock) is a novel and promising biomarker of aging. It is calculated from the methylation fraction of specific cytosine phosphate guanine sites (CpG sites) of genomic DNA. Several groups have proposed epigenetic clock algorithms and these differ mostly regarding the number and location of the CpG sites considered and the method used to assess the methylation status. Most epigenetic clocks are based on a large number of CpGs, e.g. as measured by DNAm microarrays. We have recently evaluated an epigenetic clock based on the methylation fraction of seven CpGs that were determined by methylation-sensitive single nucleotide primer extension (MS-SNuPE). This method is more cost-effective when compared to array-based technologies as only a few CpGs need to be examined. However, there is only little data on the correspondence in epigenetic age estimation using the 7-CpG clock and other algorithms. To bridge this gap, in this study we measured the 7-CpG DNAm age using two methods, via MS-SNuPE and via the MethylationEPIC array, in a sample of 1,058 participants of the Berlin Aging Study II (BASE-II), assessed as part of the GendAge study. On average, participants were 75.6 years old (SD: 3.7, age range: 64.9–90.0, 52.6% female). Agreement between methods was assessed by Bland-Altman plots. DNAm age was highly correlated between methods (Pearson’s r = 0.9) and Bland-Altman plots showed a difference of 3.1 years. DNAm age by the 7-CpG formula was 71.2 years (SD: 6.9 years, SNuPE) and 68.1 years (SD: 6.4 years, EPIC array). The mean of difference in methylation fraction between methods for the seven individual CpG sites was between 0.7 and 13 percent. To allow direct conversion of DNAm age obtained from both methods we developed an adjustment formula with a randomly selected training set of 529 participants using linear regression. After conversion of the Illumina data in a second and independent validation set, the adjusted DNAm age was 71.44 years (SD: 6.1 years, n = 529). In summary, we found the results of DNAm clocks to be highly comparable. Furthermore, we developed an adjustment formula that allows for direct conversion of DNAm age estimates between methods and enables one singular clock to be used in studies that employ either the Illumina or the SNuPE method

Sex-specific associations of serum selenium and selenoprotein P with type 2 diabetes mellitus and hypertension in the Berlin Aging Study II

Background: Selenium is essential for expression and proper function of a set of redox active selenoproteins implicated in aging-relevant diseases, e.g. type 2 diabetes mellitus (T2D) and hypertension. However, data in cohorts of older adults, particularly with respect to different Se biomarkers and sex-specific analyses are sparse. Objective: To assess associations of serum Se and selenoprotein P (SELENOP) concentrations with T2D and hypertension in a cohort of older females and males. Methods: This study included 1500 participants from the Berlin Aging Study II. Diagnosis of T2D was made in case of antidiabetic medication, self-reported T2D, or laboratory parameters. Diagnosis of hypertension was based on self-report, blood pressure measurement, or anti-hypertensive medication. Se was measured by spectroscopy, and SELENOP by ELISA. Multiple adjusted regression models quantified dose-dependent associations. Results: Participants had a median(IQR) age of 68 (65,71) years, and 767 (51%) were women. 191 (13%) participants had T2D and 1126 (75%) had hypertension. Se and SELENOP correlated significantly (r = 0.59, p < 0.001), and were elevated in those with self-reported Se supplementation. Serum Se and SELENOP were not associated with T2D in the whole cohort. In men, SELENOP was positively associated with T2D, OR (95%CI) for one mg/L increase in SELENOP was 1.22 (1.00,1.48). Se was non-linearly associated with hypertension, comparing to the lowest quartile (Q1), and participants with higher Se levels (Q3) had a lower OR (95%CI) of 0.66 (0.45,0.96), which was specific for men. SELENOP positively associated with hypertension, and OR (95%CI) per one mg/L increase was 1.15 (1.01,1.32). Conclusions: The data suggest a sex-specific interrelationship of Se status with T2D and hypertension, with apparent biomarker-specific associations

Epigenetic aging and perceived psychological stress in old age

Adverse effects of psychological stress on physical and mental health, especially in older age, are well documented. How perceived stress relates to the epigenetic clock measure, DNA methylation age acceleration (DNAmAA), is less well understood and existing studies reported inconsistent results. DNAmAA was estimated from five epigenetic clocks (7-CpG, Horvath's, Hannum's, PhenoAge and GrimAge DNAmAA). Cohen's Perceived Stress Scale (PSS) was used as marker of psychological stress. We analyzed data from 1,100 Berlin Aging Study II (BASE-II) participants assessed as part of the GendAge study (mean age = 75.6 years, SD = 3.8 years, 52.1% women). In a first step, we replicated well-established associations of perceived stress with morbidity, frailty, and symptoms of depression in the BASE-II cohort studied here. In a second step, we did not find any statistically significant association of perceived stress with any of the five epigenetic clocks in multiple linear regression analyses that adjusted for covariates. Although the body of literature suggests an association between higher DNAmAA and stress or trauma during early childhood, the current study found no evidence for an association of perception of stress with DNAmAA in older people. We discuss possible reasons for the lack of associations and highlight directions for future research

Using blood test parameters to define biological age among older adults: association with morbidity and mortality independent of chronological age validated in two separate birth cohorts

Biomarkers defining biological age are typically laborious or expensive to assess. Instead, in the current study, we identified parameters based on standard laboratory blood tests across metabolic, cardiovascular, inflammatory, and kidney functioning that had been assessed in the Berlin Aging Study (BASE) (n = 384) and Berlin Aging Study II (BASE-II) (n = 1517). We calculated biological age using those 12 parameters that individually predicted mortality hazards over 26 years in BASE. In BASE, older biological age was associated with more physician-observed morbidity and higher mortality hazards, over and above the effects of chronological age, sex, and education. Similarly, in BASE-II, biological age was associated with physician-observed morbidity and subjective health, over and above the effects of chronological age, sex, and education as well as alternative biomarkers including telomere length, DNA methylation age, skin age, and subjective age but not PhenoAge. We discuss the importance of biological age as one indicator of aging.Peer Reviewe

Epigenome-wide association study in peripheral tissues highlights DNA methylation profiles associated with episodic memory performance in humans

The decline in episodic memory (EM) performance is a hallmark of cognitive aging and an early clinical sign in Alzheimer&rsquo;s disease (AD). In this study, we conducted an epigenome-wide association study (EWAS) using DNA methylation (DNAm) profiles from buccal and blood samples for cross-sectional (n = 1019) and longitudinal changes in EM performance (n = 626; average follow-up time 5.4 years) collected under the auspices of the Lifebrain consortium project. The mean age of participants with cross-sectional data was 69 &plusmn; 11 years (30&ndash;90 years), with 50% being females. We identified 21 loci showing suggestive evidence of association (p &lt; 1 &times; 10&minus;5) with either or both EM phenotypes. Among these were SNCA, SEPW1 (both cross-sectional EM), ITPK1 (longitudinal EM), and APBA2 (both EM traits), which have been linked to AD or Parkinson&rsquo;s disease (PD) in previous work. While the EM phenotypes were nominally significantly (p &lt; 0.05) associated with poly-epigenetic scores (PESs) using EWASs on general cognitive function, none remained significant after correction for multiple testing. Likewise, estimating the degree of &ldquo;epigenetic age acceleration&rdquo; did not reveal significant associations with either of the two tested EM phenotypes. In summary, our study highlights several interesting candidate loci in which differential DNAm patterns in peripheral tissue are associated with EM performance in humans

Self-reported and accelerometer-based assessment of physical activity in older adults: results from the Berlin Aging Study II

Abstract Physical activity (PA) has a substantial impact on health and mortality. Besides questionnaires that rely on subjective assessment of activity levels, accelerometers can help to objectify an individual’s PA. In this study, variables estimating PA and sleep time obtained through the wGT3X-BT activity monitor (ActiGraph LLC, USA) in 797 participants of the Berlin Aging Study II (BASE-II) were analyzed. Self-reports of PA and sleep time were recorded with Rapid Assessment of Physical Activity (RAPA) and the Pittsburgh Sleep Quality Index sleep questionnaire (PSQI). Total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglycerides (TG), fasting glucose, and hemoglobin A1c (HbA1c) were determined in an accredited standard laboratory. Of all participants, 760 fulfilled the PA wear-time criteria. In this sample mean age was 75.6 years (SD: 3.8 years, range 66.0–94.1 years) and 53% of the included participants were women. Average wear time was 23.2 h/day (SD 1.3 h/day). Statistically significant differences between RAPA groups were found for all accelerometric variables except energy expenditure. Post-hoc analysis, however, suggested low agreement between subjective and device-based assessment of physical activity. TC, HDL-C, LDL-C, TG, fasting glucose and HbA1c were weakly correlated with accelerometric variables (Pearson’s r ≤ 0.25). Device-based average sleep time per night (mean sleep time = 6.91 h, SD = 1.3, n = 720) and self-reported average sleep time per night (mean sleep time = 7.1 h, SD = 1.15 h, n = 410) were in a comparable range and moderately correlated (Pearson’s r = 0.31, p < 0.001, n = 410). Results from this study suggest that self-reported PA obtained through the RAPA and device-based measures assessed by accelerometers are partially inconsistent in terms of the physical activity level of the participants. Self-reported and device-based measures of average sleep time per night, however, were comparable

Epigenetic aging in patients diagnosed with coronary artery disease: results of the LipidCardio study

Abstract Introduction People age biologically at different rates. Epigenetic clock-derived DNA methylation age acceleration (DNAmAA) is among the most promising markers proposed to assess the interindividual differences in biological age. Further research is needed to evaluate the characteristics of the different epigenetic clock biomarkers available with respect to the health domains they reflect best. Methods In this study, we have analyzed 779 participants of the LipidCardio study (mean chronological age 69.9 ± 11.0 years, 30.6% women) who underwent diagnostic angiography at the Charité University Hospital in Berlin, Germany. DNA methylation age (DNAm age) was measured by methylation-sensitive single nucleotide primer extension (MS-SNuPE) and calculated with the 7-CpG clock. We compared the biological age as assessed as DNAmAA of participants with an angiographically confirmed coronary artery disease (CAD, n = 554) with participants with lumen reduction of 50% or less (n = 90) and patients with a normal angiogram (n = 135). Results Participants with a confirmed CAD had on average a 2.5-year higher DNAmAA than patients with a normal angiogram. This association did not persist after adjustment for sex in a logistic regression analysis. High-density lipoprotein, low-density lipoprotein, triglycerides, lipoprotein (a), estimated glomerular filtration rate, physical activity, BMI, alcohol consumption, and smoking were not associated with DNAmAA. Conclusion The association between higher DNAmAA and angiographically confirmed CAD seems to be mainly driven by sex

Sex-specific associations of serum selenium and selenoprotein P with type 2 diabetes mellitus and hypertension in the Berlin Aging Study II

Background: Selenium is essential for expression and proper function of a set of redox active selenoproteins implicated in aging-relevant diseases, e.g. type 2 diabetes mellitus (T2D) and hypertension. However, data in cohorts of older adults, particularly with respect to different Se biomarkers and sex-specific analyses are sparse. Objective: To assess associations of serum Se and selenoprotein P (SELENOP) concentrations with T2D and hypertension in a cohort of older females and males. Methods: This study included 1500 participants from the Berlin Aging Study II. Diagnosis of T2D was made in case of antidiabetic medication, self-reported T2D, or laboratory parameters. Diagnosis of hypertension was based on self-report, blood pressure measurement, or anti-hypertensive medication. Se was measured by spectroscopy, and SELENOP by ELISA. Multiple adjusted regression models quantified dose-dependent associations. Results: Participants had a median(IQR) age of 68 (65,71) years, and 767 (51%) were women. 191 (13%) participants had T2D and 1126 (75%) had hypertension. Se and SELENOP correlated significantly (r = 0.59, p < 0.001), and were elevated in those with self-reported Se supplementation. Serum Se and SELENOP were not associated with T2D in the whole cohort. In men, SELENOP was positively associated with T2D, OR (95%CI) for one mg/L increase in SELENOP was 1.22 (1.00,1.48). Se was non-linearly associated with hypertension, comparing to the lowest quartile (Q1), and participants with higher Se levels (Q3) had a lower OR (95%CI) of 0.66 (0.45,0.96), which was specific for men. SELENOP positively associated with hypertension, and OR (95%CI) per one mg/L increase was 1.15 (1.01,1.32). Conclusions: The data suggest a sex-specific interrelationship of Se status with T2D and hypertension, with apparent biomarker-specific associations