An unbiased assessment of the role of imprinted genes in an intergenerational model of developmental programming.

Environmental factors during early life are critical for the later metabolic health of the individual and of future progeny. In our obesogenic environment, it is of great socioeconomic importance to investigate the mechanisms that contribute to the risk of metabolic ill health. Imprinted genes, a class of functionally mono-allelic genes critical for early growth and metabolic axis development, have been proposed to be uniquely susceptible to environmental change. Furthermore, it has also been suggested that perturbation of the epigenetic reprogramming of imprinting control regions (ICRs) may play a role in phenotypic heritability following early life insults. Alternatively, the presence of multiple layers of epigenetic regulation may in fact protect imprinted genes from such perturbation. Unbiased investigation of these alternative hypotheses requires assessment of imprinted gene expression in the context of the response of the whole transcriptome to environmental assault. We therefore analyse the role of imprinted genes in multiple tissues in two affected generations of an established murine model of the developmental origins of health and disease using microarrays and quantitative RT-PCR. We demonstrate that, despite the functional mono-allelicism of imprinted genes and their unique mechanisms of epigenetic dosage control, imprinted genes as a class are neither more susceptible nor protected from expression perturbation induced by maternal undernutrition in either the F1 or the F2 generation compared to other genes. Nor do we find any evidence that the epigenetic reprogramming of ICRs in the germline is susceptible to nutritional restriction. However, we propose that those imprinted genes that are affected may play important roles in the foetal response to undernutrition and potentially its long-term sequelae. We suggest that recently described instances of dosage regulation by relaxation of imprinting are rare and likely to be highly regulated

Expression of the Splicing Factor Gene SFRS10 Is Reduced in Human Obesity and Contributes to Enhanced Lipogenesis

SummaryAlternative mRNA splicing provides transcript diversity and may contribute to human disease. We demonstrate that expression of several genes regulating RNA processing is decreased in both liver and skeletal muscle of obese humans. We evaluated a representative splicing factor, SFRS10, downregulated in both obese human liver and muscle and in high-fat-fed mice, and determined metabolic impact of reduced expression. SFRS10-specific siRNA induces lipogenesis and lipid accumulation in hepatocytes. Moreover, Sfrs10 heterozygous mice have increased hepatic lipogenic gene expression, VLDL secretion, and plasma triglycerides. We demonstrate that LPIN1, a key regulator of lipid metabolism, is a splicing target of SFRS10; reduced SFRS10 favors the lipogenic β isoform of LPIN1. Importantly, LPIN1β-specific siRNA abolished lipogenic effects of decreased SFRS10 expression. Together, our results indicate that reduced expression of SFRS10, as observed in tissues from obese humans, alters LPIN1 splicing, induces lipogenesis, and therefore contributes to metabolic phenotypes associated with obesity

Prevalence of Microvascular and Macrovascular Disease in the Glycemia Reduction Approaches in Diabetes - A Comparative Effectiveness (GRADE) Study Cohort

Aims: The Glycemia Reduction Approaches in Diabetes - A Comparative Effectiveness (GRADE) trial is a randomized clinical trial comparing glycemic effects of four diabetes medications added to metformin in type 2 diabetes (T2D). Microvascular and macrovascular diseases are secondary outcomes. We evaluated the prevalence and risk factor relationships for microvascular and macrovascular complications in the GRADE cohort at study entry. Methods: Complication prevalence and risk factors were analyzed based on data from screening in all consenting participants meeting GRADE eligibility. Logistic regression and Z-statistics were used to assess risk factor relationships with complications. Results: We enrolled 5047 T2D participants [mean age 57 years; 36% female; mean known T2D duration 4 years (all < 10 years); mean HbA1c 8.0% (∼64 mmol/mol) at screening]. Urinary albumin/creatinine ratio (ACR) ≥ 30 mg/gram was present in 15.9% participants; peripheral neuropathy (by Michigan Neuropathy Screening Instrument) in 21.5%; cardiovascular autonomic neuropathy by electrocardiography-derived indices in 9.7%; self-reported retinopathy in 1.0%. Myocardial infarction ascertained by self-report or electrocardiogram was present in 7.3%, and self-reported history of stroke in 2.0%. Conclusions: In the GRADE cohort with < 10 years of T2D and a mean HbA1c of 8.0%, diabetes complications were present in a substantial fraction of participants, more so than might otherwise have been expected

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group

Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at √s = 13 TeV

Abstract The parton-level top quark (t) forward-backward asymmetry and the anomalous chromoelectric (d̂ t) and chromomagnetic (μ̂ t) moments have been measured using LHC pp collisions at a center-of-mass energy of 13 TeV, collected in the CMS detector in a data sample corresponding to an integrated luminosity of 35.9 fb−1. The linearized variable AFB(1) is used to approximate the asymmetry. Candidate t t ¯ events decaying to a muon or electron and jets in final states with low and high Lorentz boosts are selected and reconstructed using a fit of the kinematic distributions of the decay products to those expected for t t ¯ final states. The values found for the parameters are AFB(1)=0.048−0.087+0.095(stat)−0.029+0.020(syst),μ̂t=−0.024−0.009+0.013(stat)−0.011+0.016(syst), and a limit is placed on the magnitude of | d̂ t| &lt; 0.03 at 95% confidence level. [Figure not available: see fulltext.

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe