Identification of early molecular markers for breast cancer

<p>Abstract</p> <p>Background</p> <p>The ductal carcinoma <it>in situ </it>(DCIS) of the mammary gland represents an early, pre-invasive stage in the development of invasive breast carcinoma. Since DCIS is a curable disease, it would be highly desirable to identify molecular markers that allow early detection. Mice transgenic for the WAP-SV40 early genome region were used as a model for DCIS development. Gene expression profiling was carried out on DCIS-bearing mice and control animals. Additionally, a set of human DCIS and invasive mammary tumors were analyzed in a similar fashion. Enhanced expression of these marker genes in human and murine samples was validated by quantitative RT-PCR. Besides, marker gene expression was also validated by immunohistochemistry of human samples. Furthermore <it>in silico </it>analyses using an online microarray database were performed.</p> <p>Results</p> <p>In DCIS-mice seven genes were identified that were significantly up-regulated in DCIS: DEPDC1, NUSAP1, EXO1, RRM2, FOXM1, MUC1 and SPP1. A similar up-regulation of homologues of the murine genes was observed in human DCIS samples. Enhanced expression of these genes in DCIS and IDC (invasive ductal carcinoma) was validated by quantitative RT-PCR and immunohistochemistry.</p> <p>Conclusions</p> <p>By comparing murine markers for the ductal carcinoma <it>in situ </it>(DCIS) of the mammary gland with genes up-regulated in human DCIS-samples we were able to identify a set of genes which might allow early detection of DCIS and invasive carcinomas in the future. The similarities between gene expression in DCIS and invasive carcinomas in our data suggest that the early detection and treatment of DCIS is of utmost relevance for the survival of patients who are at high risk of developing breast carcinomas.</p

Epigenetic Signatures at AQP3 and SOCS3 Engage in Low-Grade Inflammation across Different Tissues

Background Elevated levels of C-reactive protein (CRP, determined by a high-sensitivity assay) indicate low-grade inflammation which is implicated in many age-related disorders. Epigenetic studies on CRP might discover molecular mechanisms underlying CRP regulation. We aimed to identify DNA methylation sites related to CRP concentrations in cells and tissues regulating low-grade inflammation. Results Genome-wide DNA methylation was measured in peripheral blood in 1,741 participants of the KORA F4 study using Illumina HumanMethylation450 BeadChip arrays. Four CpG sites (located at BCL3, AQP3, SOCS3, and cg19821297 intergenic at chromosome 19p13.2, P <= 1.01E-07) were significantly hypomethylated at high CRP concentrations independent of various confounders including age, sex, BMI, smoking, and white blood cell composition. Findings were not sex-specific. CRP-related top genes were enriched in JAK/STAT pathways (Benjamini-Hochberg corrected P < 0.05). Results were followed-up in three studies using DNA from peripheral blood (EPICOR, n = 503) and adipose tissue (TwinsUK, n = 368) measured as described above and from liver tissue (LMU liver cohort, n = 286) measured by MALDI-TOF mass spectrometry using EpiTYPER. CpG sites at the AQP3 locus (significant p-values in peripheral blood = 1.72E-03 and liver tissue = 1.51E-03) and the SOCS3 locus (p-values in liver < 2.82E-05) were associated with CRP in the validation panels. Conclusions Epigenetic modifications seem to engage in low-grade inflammation, possibly via JAK/STAT mediated pathways. Results suggest a shared relevance across different tissues at the AQP3 locus and highlight a role of DNA methylation for CRP regulation at the SOCS3 locus

Dairying, diseases and the evolution of lactase persistence in Europe

Update notice Author Correction: Dairying, diseases and the evolution of lactase persistence in Europe (Nature, (2022), 608, 7922, (336-345), 10.1038/s41586-022-05010-7) Nature, Volume 609, Issue 7927, Pages E9, 15 September 2022In European and many African, Middle Eastern and southern Asian populations, lactase persistence (LP) is the most strongly selected monogenic trait to have evolved over the past 10,000 years(1). Although the selection of LP and the consumption of prehistoric milk must be linked, considerable uncertainty remains concerning their spatiotemporal configuration and specific interactions(2,3). Here we provide detailed distributions of milk exploitation across Europe over the past 9,000 years using around 7,000 pottery fat residues from more than 550 archaeological sites. European milk use was widespread from the Neolithic period onwards but varied spatially and temporally in intensity. Notably, LP selection varying with levels of prehistoric milk exploitation is no better at explaining LP allele frequency trajectoriesthan uniform selection since the Neolithic period. In the UK Biobank(4,5) cohort of 500,000 contemporary Europeans, LP genotype was only weakly associated with milk consumption and did not show consistent associations with improved fitness or health indicators. This suggests that other reasons for the beneficial effects of LP should be considered for its rapid frequency increase. We propose that lactase non-persistent individuals consumed milk when it became available but, under conditions of famine and/or increased pathogen exposure, this was disadvantageous, driving LP selection in prehistoric Europe. Comparison of model likelihoods indicates that population fluctuations, settlement density and wild animal exploitation-proxies for these drivers-provide better explanations of LP selection than the extent of milk exploitation. These findings offer new perspectives on prehistoric milk exploitation and LP evolution.Peer reviewe

DNA methylation and lipid metabolism: an EWAS of 226 metabolic measures

Background: The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) (N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances.Results: We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study (N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts (N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations (p value -10), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations.Conclusion: Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.</p

DNA methylation-based measures of biological age:meta-analysis predicting time to death

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p ≤ 8.2 x 10-9), independent of chronological age, even after adjusting for additional risk factors (p < 5.4 x 10-4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p≤ 7.5 x 10-43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality

Minimum Information about T Regulatory Cells: A Step toward Reproducibility and Standardization.

Cellular therapies with CD4+ T regulatory cells (Tregs) hold promise of efficacious treatment for the variety of autoimmune and allergic diseases as well as posttransplant complications. Nevertheless, current manufacturing of Tregs as a cellular medicinal product varies between different laboratories, which in turn hampers precise comparisons of the results between the studies performed. While the number of clinical trials testing Tregs is already substantial, it seems to be crucial to provide some standardized characteristics of Treg products in order to minimize the problem. We have previously developed reporting guidelines called minimum information about tolerogenic antigen-presenting cells, which allows the comparison between different preparations of tolerance-inducing antigen-presenting cells. Having this experience, here we describe another minimum information about Tregs (MITREG). It is important to note that MITREG does not dictate how investigators should generate or characterize Tregs, but it does require investigators to report their Treg data in a consistent and transparent manner. We hope this will, therefore, be a useful tool facilitating standardized reporting on the manufacturing of Tregs, either for research purposes or for clinical application. This way MITREG might also be an important step toward more standardized and reproducible testing of the Tregs preparations in clinical applications

Temporal and spatial analysis of the 2014-2015 Ebola virus outbreak in West Africa

West Africa is currently witnessing the most extensive Ebola virus (EBOV) outbreak so far recorded. Until now, there have been 27,013 reported cases and 11,134 deaths. The origin of the virus is thought to have been a zoonotic transmission from a bat to a two-year-old boy in December 2013 (ref. 2). From this index case the virus was spread by human-to-human contact throughout Guinea, Sierra Leone and Liberia. However, the origin of the particular virus in each country and time of transmission is not known and currently relies on epidemiological analysis, which may be unreliable owing to the difficulties of obtaining patient information. Here we trace the genetic evolution of EBOV in the current outbreak that has resulted in multiple lineages. Deep sequencing of 179 patient samples processed by the European Mobile Laboratory, the first diagnostics unit to be deployed to the epicentre of the outbreak in Guinea, reveals an epidemiological and evolutionary history of the epidemic from March 2014 to January 2015. Analysis of EBOV genome evolution has also benefited from a similar sequencing effort of patient samples from Sierra Leone. Our results confirm that the EBOV from Guinea moved into Sierra Leone, most likely in April or early May. The viruses of the Guinea/Sierra Leone lineage mixed around June/July 2014. Viral sequences covering August, September and October 2014 indicate that this lineage evolved independently within Guinea. These data can be used in conjunction with epidemiological information to test retrospectively the effectiveness of control measures, and provides an unprecedented window into the evolution of an ongoing viral haemorrhagic fever outbreak.status: publishe

Dynamisches Pausenmanagement: Individuelle, intelligente Steuerung von Pausen mittels Datenanalyse von Vitalparametern aus Wearables

Im Zuge des Wandels der Arbeit ist die unternehmensinterne Pausenorganisation vor neue Herausforderungen gestellt. Aufgrund Arbeitsverdichtung und hohen psychischen Arbeitsanforderungen fallen Pausen häufig aus, werden unterbrochen oder zu spät genommen. Vor allem Lagerarbeiter oder Pflegekräfte sind hiervon betroffen. Die Folgen sind nicht nur auf Mitarbeiterseite spürbar: Neben kurzfristigen negativen Beanspruchungsfolgen steigt das Risiko von Erkrankungen, Unfällen, Fehlzeiten oder Mitarbeiterfluktuation. In dem Beitrag wird eine digitale Lösung diskutiert, Pausen individuell und auf physiologischen Stressparametern basierend zu empfehlen