Despite strong vetting for disease activity, only 10% of candidate new molecular entities in early stage clinical trials are eventually approved. Analyzing historical pipeline data, Nelson et al. ...2015 (Nat. Genet.) concluded pipeline drug targets with human genetic evidence of disease association are twice as likely to lead to approved drugs. Taking advantage of recent clinical development advances and rapid growth in GWAS datasets, we extend the original work using updated data, test whether genetic evidence predicts future successes and introduce statistical models adjusting for target and indication-level properties. Our work confirms drugs with genetically supported targets were more likely to be successful in Phases II and III. When causal genes are clear (Mendelian traits and GWAS associations linked to coding variants), we find the use of human genetic evidence increases approval by greater than two-fold, and, for Mendelian associations, the positive association holds prospectively. Our findings suggest investments into genomics and genetics are likely to be beneficial to companies deploying this strategy.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The commensal gut microbiota has been implicated as a determinant in several human diseases and conditions. There is mounting evidence that the gut microbiota of laboratory mice (Mus musculus) ...similarly modulates the phenotype of mouse models used to study human disease and development. While differing model phenotypes have been reported using mice purchased from different vendors, the composition and uniformity of the fecal microbiota in mice of various genetic backgrounds from different vendors is unclear. Using culture-independent methods and robust statistical analysis, we demonstrate significant differences in the richness and diversity of fecal microbial populations in mice purchased from two large commercial vendors. Moreover, the abundance of many operational taxonomic units, often identified to the species level, as well as several higher taxa, differed in vendor- and strain-dependent manners. Such differences were evident in the fecal microbiota of weanling mice and persisted throughout the study, to twenty-four weeks of age. These data provide the first in-depth analysis of the developmental trajectory of the fecal microbiota in mice from different vendors, and a starting point from which researchers may be able to refine animal models affected by differences in the gut microbiota and thus possibly reduce the number of animals required to perform studies with sufficient statistical power.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Summary
Phenome-wide association studies (PheWASs) are known to be a powerful tool in discovery and replication of genetic association studies. To reduce the computational burden of PheWAS ...in the large cohorts, such as the UK Biobank, the SAIGE method has been proposed to control for case–control imbalance and sample relatedness in a tractable manner. However, SAIGE is still computationally intensive when deployed in analyzing the associations of thousands of ICD10-coded phenotypes with whole-genome imputed genotype data. Here, we present a new high-performance statistical R package (SAIGEgds) for large-scale PheWAS using generalized linear mixed models. The package implements the SAIGE method in optimized C++ codes, taking advantage of sparse genotype dosages and integrating the efficient genomic data structure file format. Benchmarks using the UK Biobank White British genotype data (N ≈ 430 K) with coronary heart disease and simulated cases show that the implementation in SAIGEgds is 5–6 times faster than the SAIGE R package. When used in conjunction with high-performance computing clusters, SAIGEgds provides an efficient analysis pipeline for biobank-scale PheWAS.
Availability and implementation
https://bioconductor.org/packages/SAIGEgds; vignettes included.
Supplementary information
Supplementary data are available at Bioinformatics online.
We developed a novel approach for conducting multisample, multigene, ultradeep bisulfite sequencing analysis of DNA methylation patterns in clinical samples. A massively parallel ...sequencing-by-synthesis method (454 sequencing) was used to directly sequence >100 bisulfite PCR products in a single sequencing run without subcloning. We showed the utility, robustness, and superiority of this approach by analyzing methylation in 25 gene-related CpG rich regions from >40 cases of primary cells, including normal peripheral blood lymphocytes, acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), and mantle cell lymphoma (MCL). A total of 294,631 sequences was generated with an average read length of 131 bp. On average, >1,600 individual sequences were generated for each PCR amplicon far beyond the few clones (<20) typically analyzed by traditional bisulfite sequencing. Comprehensive analysis of CpG methylation patterns at a single DNA molecule level using clustering algorithms revealed differential methylation patterns between diseases. A significant increase in methylation was detected in ALL and FL samples compared with CLL and MCL. Furthermore, a progressive spreading of methylation was detected from the periphery toward the center of select CpG islands in the ALL and FL samples. The ultradeep sequencing also allowed simultaneous analysis of genetic and epigenetic data and revealed an association between a single nucleotide polymorphism and the methylation present in the LRP1B promoter. This new generation of methylome sequencing will provide digital profiles of aberrant DNA methylation for individual human cancers and offers a robust method for the epigenetic classification of tumor subtypes.
The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.
To ...determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.
We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).
This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.
The rapid rise in natural gas extraction using hydraulic fracturing increases the potential for contamination of surface and ground water from chemicals used throughout the process. Hundreds of ...products containing more than 750 chemicals and components are potentially used throughout the extraction process, including more than 100 known or suspected endocrine-disrupting chemicals. We hypothesized that a selected subset of chemicals used in natural gas drilling operations and also surface and ground water samples collected in a drilling-dense region of Garfield County, Colorado, would exhibit estrogen and androgen receptor activities. Water samples were collected, solid-phase extracted, and measured for estrogen and androgen receptor activities using reporter gene assays in human cell lines. Of the 39 unique water samples, 89%, 41%, 12%, and 46% exhibited estrogenic, antiestrogenic, androgenic, and antiandrogenic activities, respectively. Testing of a subset of natural gas drilling chemicals revealed novel antiestrogenic, novel antiandrogenic, and limited estrogenic activities. The Colorado River, the drainage basin for this region, exhibited moderate levels of estrogenic, antiestrogenic, and antiandrogenic activities, suggesting that higher localized activity at sites with known natural gas–related spills surrounding the river might be contributing to the multiple receptor activities observed in this water source. The majority of water samples collected from sites in a drilling-dense region of Colorado exhibited more estrogenic, antiestrogenic, or antiandrogenic activities than reference sites with limited nearby drilling operations. Our data suggest that natural gas drilling operations may result in elevated endocrine-disrupting chemical activity in surface and ground water.
The pathogenesis of inflammatory bowel diseases (IBD), Crohn's disease and ulcerative colitis, is due in part to interactions between the immune system, genetics, the environment, and endogenous ...microbiota. Gonadal sex hormones (GSH), such as estrogen, are thought to be involved in the development of IBD as variations in disease severity occur during pregnancy, menopause, or oral contraceptives use. In certain strains of mice, infection with Helicobacter hepaticus triggers IBD-like mucosal inflammation that is more severe in female mice than in males, suggesting a role for GSH in this model. To determine the role of estrogen signaling in microbiota-induced intestinal inflammation, estrogen receptor (ER) α and β knock-out (KO) mice, ER agonists, and adoptive transfers were utilized. We demonstrate that, when signaling is limited to ERβ on a non-CD4+ cell subset, disease is less severe and this correlates with decreased expression of pro-inflammatory mediators.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Genome-wide association studies have successfully discovered thousands of common variants associated with human diseases and traits, but the landscape of rare variations in human disease has not been ...explored at scale. Exome-sequencing studies of population biobanks provide an opportunity to systematically evaluate the impact of rare coding variations across a wide range of phenotypes to discover genes and allelic series relevant to human health and disease. Here, we present results from systematic association analyses of 4,529 phenotypes using single-variant and gene tests of 394,841 individuals in the UK Biobank with exome-sequence data. We find that the discovery of genetic associations is tightly linked to frequency and is correlated with metrics of deleteriousness and natural selection. We highlight biological findings elucidated by these data and release the dataset as a public resource alongside the Genebass browser for rapidly exploring rare-variant association results.
Display omitted
•Public release of gene-based association statistics for 4,529 diseases and traits•Genebass, a browser framework to display rare-variant associations•Tight coupling between frequency, natural selection, and power for genetic discovery•Biological signal between SCRIB and white-matter integrity (from MRI)
Karczewski et al. generated a massive-scale association dataset between rare genetic mutations and thousands of diseases and traits and released these data in the Genebass browser. They quantify the influence of natural selection and gene function on association discovery and highlight an association between SCRIB and a brain-imaging trait.
Cardiac injury induces myocyte apoptosis and necrosis, resulting in the secretion and/or release of intracellular proteins. Currently, myocardial injury can be detected by analysis of a limited ...number of biomarkers in blood or coronary artery perfusate. However, the complete proteomic signature of protein release from necrotic cardiac myocytes is unknown. Therefore, we undertook a proteomic-based study of proteins released from cultured neonatal rat cardiac myocytes in response to H2O2 (necrosis) or staurosporine (apoptosis) to identify novel specific markers of cardiac myocyte cell death. Necrosis and apoptosis resulted in the identification of 147 and 79 proteins, respectively. Necrosis resulted in a relative increase in the amount of many proteins including the classical necrotic markers lactate dehydrogenase (LDH), high-mobility group B1 (HMGB1), myoglobin, enolase, and 14-3-3 proteins. Additionally, we identified several novel markers of necrosis including HSP90, α-actinin, and Trim72, many of which were elevated over control levels earlier than classical markers of necrotic injury. In contrast, the majority of identified proteins remained at low levels during apoptotic cell death, resulting in no candidate markers for apoptosis being identified. Blotting for a selection of these proteins confirmed their release during necrosis but not apoptosis. We were able to confirm the presence of classical necrotic markers in the extracellular milieu of necrotic myocytes. We also were able to identify novel markers of necrotic cell death with relatively early release profiles compared with classical protein markers of necrosis. These results have implications for the discovery of novel biomarkers of necrotic myocyte injury, especially in the context of ischemia-reperfusion injury.
Due to poor correlation between steady state mRNA levels and protein product, purely transcriptomic profiling methods may miss genes posttranscriptionally regulated by RNA binding proteins (RBPs) and ...microRNAs (miRNAs). RNA immunoprecipitation (RIP) methods developed to identify in vivo targets of RBPs have greatly elucidated those mRNAs which may be regulated via transcript stability and translation. The RBP HuR (ELAVL1) and family members are major stabilizers of mRNA. Many labs have identified HuR mRNA targets; however, many of these analyses have been performed in cell lines and oftentimes are not independent biological replicates. Little is known about how HuR target mRNAs behave in conditional knock-out models. In the present work, we performed HuR RIP-Seq and RNA-Seq to investigate HuR direct and indirect targets using a novel conditional knock-out model of HuR genetic ablation during CD4+ T activation and Th2 differentiation. Using independent biological replicates, we generated a high coverage RIP-Seq data set (>160 million reads) that was analyzed using bioinformatics methods specifically designed to find direct mRNA targets in RIP-Seq data. Simultaneously, another set of independent biological replicates were sequenced by RNA-Seq (>425 million reads) to identify indirect HuR targets. These direct and indirect targets were combined to determine canonical pathways in CD4+ T cell activation and differentiation for which HuR plays an important role. We show that HuR may regulate genes in multiple canonical pathways involved in T cell activation especially the CD28 family signaling pathway. These data provide insights into potential HuR-regulated genes during T cell activation and immune mechanisms.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
PDF
