Life-course socioeconomic factors are associated with markers of epigenetic aging in a population-based study.

Adverse socioeconomic circumstances negatively affect the functioning of biological systems, but the underlying mechanisms remain only partially understood. Here, we explore the associations between life-course socioeconomic factors and four markers of epigenetic aging in a population-based setting. We included 684 participants (52 % women, mean age 52.6 ± 15.5 years) from a population and family-based Swiss study. We used nine life-course socioeconomic indicators as the main exposure variables, and four blood-derived, second generation markers of epigenetic aging as the outcome variables (Levine's DNAmPhenoAge, DunedinPoAm38, GrimAge epigenetic age acceleration (EAA), and the mortality risk score (MS)). First, we investigated the associations between socioeconomic indicators and markers of epigenetic aging via mixed-effect linear regression models, adjusting for age, sex, participant's recruitment center, familial structure (random-effect covariate), seasonality of blood sampling, and technical covariates. Second, we implemented counterfactual mediation analysis to investigate life-course and intermediate mechanisms underlying the socioeconomic gradient in epigenetic aging. Effect-size estimates were assessed using regression coefficients and counterfactual mediation parameters, along with their respective 95 % confidence intervals. Individuals reporting a low father's occupation, adverse financial conditions in childhood, a low income, having financial difficulties, or experiencing unfavorable socioeconomic trajectories were epigenetically older and had a higher mortality risk score than their more advantaged counterparts. Specifically, this corresponded to an average increase of 1.1-1.5 years for Levine's epigenetic age (ß and 95 %CI range, ß (minimum and maximum): 1.1-1.5 95 %CI[0.0-0.2; 2.3-3.0]), 1.1-1.5 additional years for GrimAge (ß: 1.1-1.5 95 %CI[0.2-0.6; 1.9-3.0]), a 1-3 % higher DunedinPoAm38 age acceleration (ß: 0.01-0.03 95 %CI[0.00; 0.03-0.04]), and a 10-50 % higher MS score (ß: 0.1-0.4 95 %CI[0.0-0.2; 0.3-0.4]) for the aforementioned socioeconomic indicators. By exploring the life-course mechanisms underlying the socioeconomic gradient in epigenetic aging, we found that both childhood and adulthood socioeconomic factors contributed to epigenetic aging, and that detrimental lifestyle factors mediated the relation between socioeconomic circumstances in adulthood and EAA (31-89 % mediated proportion). This study provides emerging evidence for an association between disadvantaged life-course socioeconomic circumstances and detrimental epigenetic aging patterns, supporting the "sensitive-period" life-course model. Counterfactual mediation analyses further indicated that the effect of socioeconomic factors in adulthood operates through detrimental lifestyle factors, whereas associations involving early-life socioeconomic factors were less clear.

Changes of lipoprotein(a) levels with endogenous steroid hormones.

BACKGROUND: Lipoprotein(a) [Lp(a)] is an LDL-like molecule that is likely causal for cardiovascular events and Lp(a) variability has been shown to be mostly of genetic origin. Exogenous hormones (hormone replacement therapy) seem to influence Lp(a) levels, but the impact of endogenous hormone levels on Lp(a) is still unknown. The aim of the study was to assess the effect of endogenous steroid hormone metabolites on Lp(a). METHODS: Lipoprotein(a) levels were measured in 1,021 participants from the Swiss Kidney Project on Genes in Hypertension, a family-based, multicentre, population-based prospective cohort study. Endogenous levels of 28 steroid hormone precursors were measured in 24-h urine collections from 883 individuals. Of the participants with Lp(a) data, 1,011 participants had also genotypes available. RESULTS: The participants had an average age of 51 years and 53% were female. Median Lp(a) levels were 62 mg/L, and the 90th percentile was 616 mg/L. The prevalence of a Lp(a) elevation ≥700 mg/L was 3.2%. Forty-three per cent of Lp(a) variability was explained respectively by: age (2%, p < .001), LDL-C (1%, p = .001), and two SNPs (39%, p value<2⋅10-16 ). Of the 28 endogenous steroid hormones assessed, androstenetriol, androsterone, 16α-OH-DHEA and estriol were nominatively associated with serum Lp(a) levels in univariable analyses and explained 0.4%-1% of Lp(a) variability, but none of them reached significance in multivariable models. CONCLUSIONS: In this contemporary population-based study, the prevalence of a Lp(a) elevation ≥700 mg/L was 3.2%. The effect of endogenous steroid hormone levels of Lp(a) variability was small at best, suggesting a negligible impact on the wide range of Lp(a) variability.

[And which stone type are you?] / Und welcher Steintyp sind Sie?

And which stone type are you? Abstract. Knowledge about the stone type is essential for therapy, prophylaxis and prognosis of kidney stone disease. Stone types can completely change in the course of a stone disease and therefore every kidney stone should be analyzed. This narrative review deals with some aspects of methods for analysis and types of kidney stones, with frequencies of different stone types as well as with general and specific mechanisms of kidney stone formation and seeks to stimulate a more in-depth study of this topic.