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Abstract Background As precision medicine advances, polygenic scores (PGS) have become increasingly important for clinical risk assessment. Many methods have been developed to create polygenic models with increased accuracy for risk prediction. Our select and shrink with summary statistics (S4) PGS method has previously been shown to accurately predict the polygenic risk of epithelial ovarian cancer. Here, we applied S4 PGS to 12 phenotypes for UK Biobank participants, and compared it with the LDpred2 and a combined S4 + LDpred2 method. Results The S4 + LDpred2 method provided overall improved PGS accuracy across a variety of phenotypes for UK Biobank participants. Additionally, the S4 + LDpred2 method had the best estimated PGS accuracy in Finnish and Japanese populations. We also addressed the challenge of limited genotype level data by developing the PGS models using only GWAS summary statistics. Conclusions Taken together, the S4 + LDpred2 method represents an improvement in overall PGS accuracy across multiple phenotypes and populations.

Abstract Background Little is known about the role of global DNA methylation in recurrence and chemoresistance of high grade serous ovarian cancer (HGSOC). Methods We performed whole genome bisulfite sequencing and transcriptome sequencing in 62 primary and recurrent tumors from 28 patients with stage III/IV HGSOC, of which 11 patients carried germline, pathogenic BRCA1 and/or BRCA2 mutations. Results Landscapes of genome-wide methylation (on average 24.2 million CpGs per tumor) and transcriptomes in primary and recurrent tumors showed extensive heterogeneity between patients but were highly preserved in tumors from the same patient. We identified significant differences in the burden of differentially methylated regions (DMRs) in tumors from BRCA1/2 compared to non-BRCA1/2 carriers (mean 659 DMRs and 388 DMRs in paired comparisons respectively). We identified overexpression of immune pathways in BRCA1/2 carriers compared to non-carriers, implicating an increased immune response in improved survival (P = 0.006) in these BRCA1/2 carriers. Conclusion These findings indicate methylome and gene expression programs established in the primary tumor are conserved throughout disease progression, even after extensive chemotherapy treatment, and that changes in methylation and gene expression are unlikely to serve as drivers for chemoresistance in HGSOC.

Summary: Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the TERT and CLPTM1L genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.

Abstract Background The development of next generation sequencing (NGS) methods led to a rapid rise in the generation of large genomic datasets, but the development of user-friendly tools to analyze and visualize these datasets has not developed at the same pace. This presents a two-fold challenge to biologists; the expertise to select an appropriate data analysis pipeline, and the need for bioinformatics or programming skills to apply this pipeline. The development of graphical user interface (GUI) applications hosted on web-based servers such as Shiny can make complex workflows accessible across operating systems and internet browsers to those without programming knowledge. Results We have developed GENAVi (Gene Expression Normalization Analysis and Visualization) to provide a user-friendly interface for normalization and differential expression analysis (DEA) of human or mouse feature count level RNA-Seq data. GENAVi is a GUI based tool that combines Bioconductor packages in a format for scientists without bioinformatics expertise. We provide a panel of 20 cell lines commonly used for the study of breast and ovarian cancer within GENAVi as a foundation for users to bring their own data to the application. Users can visualize expression across samples, cluster samples based on gene expression or correlation, calculate and plot the results of principal components analysis, perform DEA and gene set enrichment and produce plots for each of these analyses. To allow scalability for large datasets we have provided local install via three methods. We improve on available tools by offering a range of normalization methods and a simple to use interface that provides clear and complete session reporting and for reproducible analysis. Conclusion The development of tools using a GUI makes them practical and accessible to scientists without bioinformatics expertise, or access to a data analyst with relevant skills. While several GUI based tools are currently available for RNA-Seq analysis we improve on these existing tools. This user-friendly application provides a convenient platform for the normalization, analysis and visualization of gene expression data for scientists without bioinformatics expertise.

Objective: Insulin resistance is a common feature of polycystic ovary syndrome (PCOS). The insulin signaling pathway consists of two major pathways, the metabolic and the mitogenic cascades. The many components of these pathways have not been comprehensively analyzed for differential expression in insulin-responsive tissues in PCOS. The goal of this study was to determine whether the core elements of the insulin signal transduction cascade were differentially expressed in subcutaneous adipose tissue (SAT) between PCOS and controls. Materials/methods: Quantitative real-time PCR for 36 insulin signaling pathway genes was performed in subcutaneous adipose tissue from 22 white PCOS and 13 healthy controls. Results: Genes in the insulin signaling pathway were not differentially expressed in subcutaneous adipose tissue between PCOS and controls (P > 0.05 for all). Components mainly of the mitogenic pathway were correlated with both androgens and metabolic phenotypes. Expression levels of five genes (MKNK1, HRAS, NRAS, KRAS, and GSK3A) were positively correlated with total testosterone level (ρ > 0, P

Purpose ? The aim of this paper is to investigate competitive pricing strategies of apparel brands and retailers. Design/methodology/approach ? The paper begins with a broad discussion of competition by examining Porter's five forces model, and narrows by examining price competition within price tiers in the retail apparel industry according to store format and brands. Included are case studies of apparel retailers and brands incorporating concepts of pricing strategies, brand positioning, and price competition, with a focus on retail channel relationships. The paper analyzes the impact of price competition on apparel retailers and brands, and further examines price tiers as a competitive strategy. Findings ? The study reveals that the concept of price tiers is applicable to apparel retailers and brands. Price tiering is a vehicle for market positioning for the retail apparel industry. Retailers are enacting a price tier strategy by branding their retail store formats or engaging store brands as a vehicle of differentiation for a tier. Retailers and brands can be successful with a price tier strategy, unless they fail to differentiate between tiers on factors other than on price alone. Research limitations/implications ? The lack of relevant price competition literature, relating to the retailer apparel industry, forced the exploration of price competition literature from grocery and automotive sectors. Originality/value ? The paper provides useful information on the impact of price competition on apparel retailers and brands, and also price tiers as a competitive strategy. [ABSTRACT FROM AUTHOR]

[This corrects the article DOI: 10.1371/journal.pgen.1007813.].

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health.

Genome wide association studies (GWAS) have revealed 11 independent risk loci for polycystic ovary syndrome (PCOS), a common disorder in young women characterized by androgen excess and oligomenorrhea. To put these risk loci and the single nucleotide polymorphisms (SNPs) therein into functional context, we measured DNA methylation and gene expression in subcutaneous adipose tissue biopsies to identify PCOS-specific alterations. Two genes from the LHCGR region, STON1-GTF2A1L and LHCGR, were overexpressed in PCOS. In analysis stratified by obesity, LHCGR was overexpressed only in non-obese PCOS women. Although not differentially expressed in the entire PCOS group, INSR was underexpressed in obese PCOS subjects only. Alterations in gene expression in the LHCGR, RAB5B and INSR regions suggest that SNPs in these loci may be functional and could affect gene expression directly or indirectly via epigenetic alterations. We identified reduced methylation in the LHCGR locus and increased methylation in the INSR locus, changes that are concordant with the altered gene expression profiles. Complex patterns of meQTL and eQTL were identified in these loci, suggesting that local genetic variation plays an important role in gene regulation. We propose that non-obese PCOS women possess significant alterations in LH receptor expression, which drives excess androgen secretion from the ovary. Alternatively, obese women with PCOS possess alterations in insulin receptor expression, with underexpression in metabolic tissues and overexpression in the ovary, resulting in peripheral insulin resistance and excess ovarian androgen production. These studies provide a genetic and molecular basis for the reported clinical heterogeneity of PCOS.

Crohn's disease (CD) is a complex disorder resulting from the interaction of intestinal microbiota with the host immune system in genetically susceptible individuals. The largest meta-analysis of genome-wide association to date identified 71 CD-susceptibility loci in individuals of European ancestry. An important epidemiological feature of CD is that it is 2-4 times more prevalent among individuals of Ashkenazi Jewish (AJ) descent compared to non-Jewish Europeans (NJ). To explore genetic variation associated with CD in AJs, we conducted a genome-wide association study (GWAS) by combining raw genotype data across 10 AJ cohorts consisting of 907 cases and 2,345 controls in the discovery stage, followed up by a replication study in 971 cases and 2,124 controls. We confirmed genome-wide significant associations of 9 known CD loci in AJs and replicated 3 additional loci with strong signal (p

Polycystic ovary syndrome (PCOS) is the leading cause of anovulatory infertility in women. It is also associated with metabolic disturbances that place women at increased risk for obesity and type 2 diabetes. There is strong evidence for familial clustering of PCOS and a genetic predisposition. However, the gene(s) responsible for the PCOS phenotypes have not been elucidated. This two-phase family-based and case-control genetic study was designed to address the question of whether SNPs identified as susceptibility loci for obesity in genome-wide association studies (GWAS) are also associated with PCOS and elevated BMI. Members of 439 families having at least one offspring with PCOS were genotyped for 15 SNPs previously shown to be associated with obesity. Linkage and association with PCOS was assessed using the transmission/disequilibrium test (TDT). These SNPs were also analyzed in an independent case-control study involving 395 women with PCOS and 176 healthy women with regular menstrual cycles. Only one of these 15 SNPs (rs2815752 in NEGR1) was found to have a nominally significant association with PCOS (χ(2) = 6.11, P = 0.013), but this association failed to replicate in the case-control study. While not associated with PCOS itself, five SNPs in FTO and two in MC4R were associated with BMI as assessed with a quantitative-TDT analysis, several of which replicated association with BMI in the case-control cohort. These findings demonstrate that certain SNPs associated with obesity contribute to elevated BMI in PCOS, but do not appear to play a major role in PCOS per se. These findings support the notion that PCOS phenotypes are a consequence of an oligogenic/polygenic mechanism.

Novel pathways in polycystic ovary syndrome (PCOS) are being identified in gene expression studies in PCOS tissues; such pathways may contain key genes in disease etiology. Previous expression studies identified both dickkopf homolog 1 (DKK1) and DnaJ (Hsp40) homolog, subfamily B, member 1 (DNAJB1) as differentially expressed in PCOS tissue, implicating them as candidates for PCOS susceptibility. To test this, we genotyped a discovery cohort of 335 PCOS cases and 198 healthy controls for three DKK1 single nucleotide polymorphisms (SNPs) and four DNAJB1 SNPs and a replication cohort of 396 PCOS cases and 306 healthy controls for 1 DKK1 SNP and 1 DNAJB1 SNP. SNPs and haplotypes were determined and tested for association with PCOS and component phenotypes. We found that no single nucleotide polymorphisms were associated with PCOS risk; however, the major allele of rs1569198 from DKK1 was associated with increased total testosterone (discovery cohort P = 0.0035) and dehydroepiandrosterone sulfate (replication cohort P = 0.05). Minor allele carriers at rs3962158 from DNAJB1 had increased fasting insulin (discovery cohort P = 0.003), increased HOMA-IR (discovery cohort P = 0.006; replication cohort P = 0.036), and increased HOMA-%B (discovery cohort P = 0.004). Carriers of haplotype 2 at DNAJB1 also had increased fasting insulin, HOMA-IR, and HOMA-%B. These findings suggest that genetic variation in DKK1 and DNAJB1 may have a role in the hyperandrogenic and metabolic dysfunction of PCOS, respectively. Our results also demonstrate the utility of gene expression data as a source of novel candidate genes in PCOS, a complex and still incompletely defined disease, for which alternative methods of gene identification are needed.