ROR-γ drives androgen receptor expression and represents a therapeutic target in castration-resistant prostate cancer.

The androgen receptor (AR) is overexpressed and hyperactivated in human castration-resistant prostate cancer (CRPC). However, the determinants of AR overexpression in CRPC are poorly defined. Here we show that retinoic acid receptor-related orphan receptor γ (ROR-γ) is overexpressed and amplified in metastatic CRPC tumors, and that ROR-γ drives AR expression in the tumors. ROR-γ recruits nuclear receptor coactivator 1 and 3 (NCOA1 and NCOA3, also known as SRC-1 and SRC-3) to an AR-ROR response element (RORE) to stimulate AR gene transcription. ROR-γ antagonists suppress the expression of both AR and its variant AR-V7 in prostate cancer (PCa) cell lines and tumors. ROR-γ antagonists also markedly diminish genome-wide AR binding, H3K27ac abundance and expression of the AR target gene network. Finally, ROR-γ antagonists suppressed tumor growth in multiple AR-expressing, but not AR-negative, xenograft PCa models, and they effectively sensitized CRPC tumors to enzalutamide, without overt toxicity, in mice. Taken together, these results establish ROR-γ as a key player in CRPC by acting upstream of AR and as a potential therapeutic target for advanced PCa

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179

Online coupling of reverse-phase and hydrophilic interaction liquid chromatography for protein and glycoprotein characterization

We have developed a novel system for coupling reverse-phase (RP) and hydrophilic interaction liquid chromatography (HILIC) online in a micro-flow scheme. In this approach, the inherent solvent incompatibility between RP and HILIC is overcome through the use of constant-pressure online solvent mixing, which allows our system to perform efficient separations of both hydrophilic and hydrophobic compounds for mass spectrometry-based proteomics applications. When analyzing the tryptic digests of bovine serum albumin, ribonuclease B, and horseradish peroxidase, we observed near-identical coverage of peptides and glycopeptides when using online RP-HILIC—with only a single sample injection event—as we did from two separate RP and HILIC analyses. The coupled system was also capable of concurrently characterizing the peptide and glycan portions of deglycosylated glycoproteins from one injection event, as confirmed, for example, through our detection of 23 novel glycans from turkey ovalbumin. Finally, we validated the applicability of using RP-HILIC for the analysis of highly complex biological samples (mouse chondrocyte lysate, deglycosylated human serum). The enhanced coverage and efficiency of online RP-HILIC makes it a viable technique for the comprehensive separation of components displaying dramatically different hydrophobicities, such as peptides, glycopeptides, and glycans

Common Polymorphisms in MTNR1B, G6PC2 and GCK Are Associated with Increased Fasting Plasma Glucose and Impaired Beta-Cell Function in Chinese Subjects

BACKGROUND: Previous studies identified melatonin receptor 1B (MTNR1B), islet-specific glucose 6 phosphatase catalytic subunit-related protein (G6PC2), glucokinase (GCK) and glucokinase regulatory protein (GCKR) as candidate genes for type 2 diabetes (T2D) acting through elevated fasting plasma glucose (FPG). We examined the associations of the reported common variants of these genes with T2D and glucose homeostasis in three independent Chinese cohorts. METHODOLOGY/PRINCIPAL FINDINGS: Five single nucleotide polymorphisms (SNPs), MTNR1B rs10830963, G6PC2 rs16856187 and rs478333, GCK rs1799884 and GCKR rs780094, were genotyped in 1644 controls (583 adults and 1061 adolescents) and 1342 T2D patients. The G-allele of MTNR1B rs10830963 and the C-alleles of both G6PC2 rs16856187 and rs478333 were associated with higher FPG (0.0034<P<6.6x10(-5)) in healthy controls. In addition to our previous report for association with FPG, the A-allele of GCK rs1799884 was also associated with reduced homeostasis model assessment of beta-cell function (HOMA-B) (P=0.0015). Together with GCKR rs780094, the risk alleles of these SNPs exhibited dosage effect in their associations with increased FPG (P=2.9x10(-9)) and reduced HOMA-B (P=1.1x10(-3)). Meta-analyses strongly supported additive effects of MTNR1B rs10830963 and G6PC2 rs16856187 on FPG. CONCLUSIONS/SIGNIFICANCE: Common variants of MTNR1B, G6PC2 and GCK are associated with elevated FPG and impaired insulin secretion, both individually and jointly, suggesting that these risk alleles may precipitate or perpetuate hyperglycemia in predisposed individuals

Genetic Associations of Type 2 Diabetes with Islet Amyloid Polypeptide Processing and Degrading Pathways in Asian Populations

10.1371/journal.pone.0062378PLoS ONE86

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead