Primary open-angle glaucoma (POAG), is a heritable common cause of blindness world-wide. To identify risk loci, we conduct a large multi-ethnic meta-analysis of genome-wide association studies on a total of 34,179 cases and 349,321 controls, identifying 44 previously unreported risk loci and confirming 83 loci that were previously known. The majority of loci have broadly consistent effects across European, Asian and African ancestries. Cross-ancestry data improve fine-mapping of causal variants for several loci. Integration of multiple lines of genetic evidence support the functional relevance of the identified POAG risk loci and highlight potential contributions of several genes to POAG pathogenesis, including SVEP1, RERE, VCAM1, ZNF638, CLIC5, SLC2A12, YAP1, MXRA5, and SMAD6. Several drug compounds targeting POAG risk genes may be potential glaucoma therapeutic candidates.

Sample size calculation is a crucial step in study design but is not yet fully established for RNA sequencing (RNA-seq) analyses. To evaluate feasibility and provide guidance, we evaluated RNA-seq sample size tools identified from a systematic search. The focus was on whether real pilot data would be needed for reliable results and on identifying tools that would perform well in scenarios with different levels of biological heterogeneity and fold changes (FCs) between conditions. We used simulations based on real data for tool evaluation. In all settings, the six evaluated tools provided widely different answers, which were strongly affected by FC. Although all tools failed for small FCs, some tools can at least be recommended when closely matching pilot data are available and relatively large FCs are anticipated.

Background: Exposure to ionizing radiation induces complex stress responses in cells, which can lead to adverse health effects such as cancer. Although a variety of studies investigated gene expression and affected pathways in human fibroblasts after exposure to ionizing radiation, the understanding of underlying mechanisms and biological effects is still incomplete due to different experimental settings and small sample sizes. Therefore, this study aims to identify the time point with the highest number of differentially expressed genes and corresponding pathways in primary human fibroblasts after irradiation at two preselected time points. Methods: Fibroblasts from skin biopsies of 15 cell donors were exposed to a high (2Gy) and a low (0.05Gy) dose of X-rays. RNA was extracted and sequenced 2 h and 4 h after exposure. Differentially expressed genes with an adjusted p-value < 0.05 were flagged and used for pathway analyses including prediction of upstream and downstream effects. Principal component analyses were used to examine the effect of two different sequencing runs on quality metrics and variation in expression and alignment and for explorative analysis of the radiation dose and time point of analysis. Results: More genes were differentially expressed 4 h after exposure to low and high doses of radiation than after 2 h. In experiments with high dose irradiation and RNA sequencing after 4 h, inactivation of the FAT10 cancer signaling pathway and activation of gluconeogenesis I, glycolysis I, and prostanoid biosynthesis was observed taking p-value (< 0.05) and (in) activating z-score (≥2.00 or ≤ − 2.00) into account. Two hours after high dose irradiation, inactivation of small cell lung cancer signaling was observed. For low dose irradiation experiments, we did not detect any significant (p < 0.05 and z-score ≥ 2.00 or ≤ − 2.00) activated or inactivated pathways for both time points. Conclusions: Compared to 2 h after irradiation, a higher number of differentially expressed genes were found 4 h after exposure to low and high dose ionizing radiation. Differences in gene expression were related to signal transduction pathways of the DNA damage response after 2 h and to metabolic pathways, that might implicate cellular senescence, after 4 h. The time point 4 h will be used to conduct further irradiation experiments in a larger sample.

RNA-sequencing (RNA-seq) has become an established way for measuring gene expression in model organisms and humans. While methods development for refining the corresponding data processing and analysis pipeline is ongoing, protocols for typical steps have been proposed and are widely used. Several user interfaces have been developed for making such analysis steps accessible to life scientists without extensive knowledge of command line tools. We performed a systematic search and evaluation of such interfaces to investigate to what extent these can indeed facilitate RNA-seq data analysis. We found a total of 29 open source interfaces, and six of the more widely used interfaces were evaluated in detail. Central criteria for evaluation were ease of configuration, documentation, usability, computational demand and reporting. No interface scored best in all of these criteria, indicating that the final choice will depend on the specific perspective of users and the corresponding weighting of criteria. Considerable technical hurdles had to be overcome in our evaluation. For many users, this will diminish potential benefits compared with command line tools, leaving room for future improvement of interfaces.

Development of primary liver cancer is a multistage process. Detailed understanding of sequential epigenetic alterations is largely missing. Here, we performed Infinium Human Methylation 450k BeadChips and RNA-Seq analyses for genome-wide methylome and transcriptome profiling of cirrhotic liver ( n = 7), low- ( n = 4) and high-grade ( n = 9) dysplastic lesions, and early ( n = 5) and progressed ( n = 3) hepatocellular carcinomas (HCC) synchronously detected in 8 patients with HCC with chronic hepatitis B infection. Integrative analyses of epigenetically driven molecular changes were identified and validated in 2 independent cohorts comprising 887 HCCs. Mitochondrial DNA sequencing was further employed for clonality analyses, indicating multiclonal origin in the majority of investigated HCCs. Alterations in DNA methylation progressively increased from liver cirrhosis (CL) to dysplastic lesions and reached a maximum in early HCCs. Associated early alterations identified by Ingenuity Pathway Analysis (IPA) involved apoptosis, immune regulation, and stemness pathways, while late changes centered on cell survival, proliferation, and invasion. We further validated 23 putative epidrivers with concomitant expression changes and associated with overall survival. Functionally, Striatin 4 (STRN4) was demonstrated to be epigenetically regulated, and inhibition of STRN4 significantly suppressed tumorigenicity of HCC cell lines. Overall, application of integrative genomic analyses defines epigenetic driver alterations and provides promising targets for potentially novel therapeutic approaches.

Objective: Systemic PaO₂ oscillations occur during cyclic recruitment and derecruitment of atelectasis in acute respiratory failure and might harm brain tissue integrity. Design: Controlled animal study. Setting: University research laboratory. Subjects: Adult anesthetized pigs. Interventions: Pigs were randomized to a control group (anesthesia and extracorporeal circulation for 20 hr with constant PaO₂, n = 10) or an oscillation group (anesthesia and extracorporeal circulation for 20 hr with artificial PaO₂ oscillations [3 cycles min^–1], n = 10). Five additional animals served as native group (n = 5). Measurements and Main Results: Outcome following exposure to artificial PaO₂ oscillations compared with constant PaO₂ levels was measured using 1) immunohistochemistry, 2) real-time polymerase chain reaction for inflammatory markers, 3) receptor autoradiography, and 4) transcriptome analysis in the hippocampus. Our study shows that PaO₂ oscillations are transmitted to brain tissue as detected by novel ultrarapid oxygen sensing technology. PaO₂ oscillations cause significant decrease in NISSL-stained neurons (p < 0.05) and induce inflammation (p < 0.05) in the hippocampus and a shift of the balance of hippocampal neurotransmitter receptor densities toward inhibition (p < 0.05). A pathway analysis suggests that cerebral immune and acute-phase response may play a role in mediating PaO₂ oscillation–induced brain injury. Conclusions: Artificial PaO₂ oscillations cause mild brain injury mediated by inflammatory pathways. Although artificial PaO₂ oscillations and endogenous PaO₂ oscillations in lung-diseased patients have different origins, it is likely that they share the same noxious effect on the brain. Therefore, PaO₂ oscillations might represent a newly detected pathway potentially contributing to the crosstalk between acute lung and remote brain injury.