Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan genomics initiative and the UK Biobank with a visual catalog: PRSWeb.

Polygenic risk scores (PRS) are designed to serve as single summary measures that are easy to construct, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The primary focus of this paper is to demonstrate how we can combine PRS and electronic health records data to better understand the shared and unique genetic architecture and etiology of disease subtypes that may be both related and heterogeneous. PRS construction strategies often depend on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. We consider several choices for constructing a PRS using data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict not just the primary phenotype but also secondary phenotypes derived from electronic health records (EHR). This study was conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. We examine the three most common skin cancer subtypes in the USA: basal cell carcinoma, cutaneous squamous cell carcinoma, and melanoma. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate PRS associations with secondary traits. PheWAS results are then replicated using population-based UK Biobank data and compared across various PRS construction methods. We develop an accompanying visual catalog called PRSweb that provides detailed PheWAS results and allows users to directly compare different PRS construction methods

tqdm/tqdm: tqdm v4.19.5 stable

A fast, extensible progress bar for Python and CL

Selected metabolic and hormonal profiles during maintenance of spontaneous ovarian cysts in dairy cows

Contents: Information is lacking regarding the relationship between metabolic and hormonal profiles and the maintenance of spontaneous ovarian cyst disease in dairy cows. For this reason, the concentrations of non-esterified fatty acids (NEFA), insulin-like growth factor I (IGF-I) and cortisol (C) were investigated during the spontaneous course of ovarian cyst disease in dairy cows (n=6) between the 7th and 16th weeks post-partum (PP). The control group consisted of normally cycling cows (n=6). Blood samples were collected twice a day, and plasma was analysed using different techniques. Progesterone and 15-ketodihydro-PGF2α plasma profiles were investigated to confirm the ovulatory or anovulatory conditions of the cows. Cortisol plasma levels were not significantly different among sampling times within each group or between the two groups. NEFA plasma levels were significantly higher in cycling cows compared to cystic cows at the 16th week PP (p<0.01), but with rather low values, indicating by now sparse mobilization of fat stores. Insulin-like growth factor I plasma concentrations were higher in cystic cows during the 8th, 10th, 11th (p<0.01) and 16th week PP (p<0.05), indicating that the presence of ovarian cysts coincides with increased IGF-I levels. These results suggest no influence of cortisol and NEFA levels in cysts maintenance, while a possible involvement of IGF-I can be suspected not only in the pathogenesis, as already known, but also in the maintenance of spontaneous cystic ovarian disease in cattle. © 2010 Blackwell Verlag GmbH

Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci.

Few studies have explored the impact of rare variants (minor allele frequency &lt; 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland. We identify 303 novel association signals, more than one third at variants rare or enriched in Finns. Many of these signals identify genes not previously implicated in metabolite genome-wide association studies and suggest mechanisms for diseases and disease-related traits

Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices

Abstract Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10−72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10−4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10−5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids