Open Targets Platform: supporting systematic drug-target identification and prioritisation.

The Open Targets Platform (https://www.targetvalidation.org/) provides users with a queryable knowledgebase and user interface to aid systematic target identification and prioritisation for drug discovery based upon underlying evidence. It is publicly available and the underlying code is open source. Since our last update two years ago, we have had 10 releases to maintain and continuously improve evidence for target-disease relationships from 20 different data sources. In addition, we have integrated new evidence from key datasets, including prioritised targets identified from genome-wide CRISPR knockout screens in 300 cancer models (Project Score), and GWAS/UK BioBank statistical genetic analysis evidence from the Open Targets Genetics Portal. We have evolved our evidence scoring framework to improve target identification. To aid the prioritisation of targets and inform on the potential impact of modulating a given target, we have added evaluation of post-marketing adverse drug reactions and new curated information on target tractability and safety. We have also developed the user interface and backend technologies to improve performance and usability. In this article, we describe the latest enhancements to the Platform, to address the fundamental challenge that developing effective and safe drugs is difficult and expensive.

Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics.

Open Targets Genetics (https://genetics.opentargets.org) is an open-access integrative resource that aggregates human GWAS and functional genomics data including gene expression, protein abundance, chromatin interaction and conformation data from a wide range of cell types and tissues to make robust connections between GWAS-associated loci, variants and likely causal genes. This enables systematic identification and prioritisation of likely causal variants and genes across all published trait-associated loci. In this paper, we describe the public resources we aggregate, the technology and analyses we use, and the functionality that the portal offers. Open Targets Genetics can be searched by variant, gene or study/phenotype. It offers tools that enable users to prioritise causal variants and genes at disease-associated loci and access systematic cross-disease and disease-molecular trait colocalization analysis across 92 cell types and tissues including the eQTL Catalogue. Data visualizations such as Manhattan-like plots, regional plots, credible sets overlap between studies and PheWAS plots enable users to explore GWAS signals in depth. The integrated data is made available through the web portal, for bulk download and via a GraphQL API, and the software is open source. Applications of this integrated data include identification of novel targets for drug discovery and drug repurposing.

A role for NPY-NPY2R signaling in albuminuric kidney disease.

Albuminuria is an independent risk factor for the progression to end-stage kidney failure, cardiovascular morbidity, and premature death. As such, discovering signaling pathways that modulate albuminuria is desirable. Here, we studied the transcriptomes of podocytes, key cells in the prevention of albuminuria, under diabetic conditions. We found that Neuropeptide Y (NPY) was significantly down-regulated in insulin-resistant vs. insulin-sensitive mouse podocytes and in human glomeruli of patients with early and late-stage diabetic nephropathy, as well as other nondiabetic glomerular diseases. This contrasts with the increased plasma and urinary levels of NPY that are observed in such conditions. Studying NPY-knockout mice, we found that NPY deficiency in vivo surprisingly reduced the level of albuminuria and podocyte injury in models of both diabetic and nondiabetic kidney disease. In vitro, podocyte NPY signaling occurred via the NPY2 receptor (NPY2R), stimulating PI3K, MAPK, and NFAT activation. Additional unbiased proteomic analysis revealed that glomerular NPY-NPY2R signaling predicted nephrotoxicity, modulated RNA processing, and inhibited cell migration. Furthermore, pharmacologically inhibiting the NPY2R in vivo significantly reduced albuminuria in adriamycin-treated glomerulosclerotic mice. Our findings suggest a pathogenic role of excessive NPY-NPY2R signaling in the glomerulus and that inhibiting NPY-NPY2R signaling in albuminuric kidney disease has therapeutic potential.

High-throughput sequencing of peripheral blood for minimal residual disease monitoring in childhood precursor B-cell acute lymphoblastic leukemia: A prospective feasibility study.

BACKGROUND: Minimal residual disease (MRD) measured on end-of-induction bone marrow (BM) is the most important biomarker for guiding therapy in pediatric acute lymphoblastic leukemia (ALL). Due to limited sensitivity of current approaches, peripheral blood (PB) is not a reliable source for identifying patients needing treatment changes. We sought to determine if high-throughput sequencing (HTS) (next-generation sequencing) of rearranged immunoglobulin and T-cell receptor genes can overcome this and be used to measure MRD in PB. PROCEDURE: We employed a quantitative HTS approach to accurately measure MRD from one million cell equivalents of DNA from 17 PB samples collected at day 29 after induction therapy in patients with precursor B-cell ALL. We compared these results to the gold-standard real-time PCR result obtained from their paired BM samples, median follow-up 49 months. RESULTS: With the increased sensitivity, detecting up to one abnormal cell in a million normal cells, we were able to detect MRD in the PB by HTS in all those patients requiring treatment intensification (MRD ≥ 0.005% in BM). CONCLUSION: This is proof of principle that using the increased sensitivity of HTS, PB can be used to measure MRD and stratify children with ALL. The method is cost effective, rapid, accurate, and reproducible, with inherent advantages in children. Importantly, increasing the frequency testing by PB as opposed to intermittent BM sampling may allow extension of the dynamic range of MRD, giving a more complete picture of the kinetics of disease remission while improving relapse prediction and speed of detection.

The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019.

The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 109 individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.

Network expansion of genetic associations defines a pleiotropy map of human cell biology.

Interacting proteins tend to have similar functions, influencing the same organismal traits. Interaction networks can be used to expand the list of candidate trait-associated genes from genome-wide association studies. Here, we performed network-based expansion of trait-associated genes for 1,002 human traits showing that this recovers known disease genes or drug targets. The similarity of network expansion scores identifies groups of traits likely to share an underlying genetic and biological process. We identified 73 pleiotropic gene modules linked to multiple traits, enriched in genes involved in processes such as protein ubiquitination and RNA processing. In contrast to gene deletion studies, pleiotropy as defined here captures specifically multicellular-related processes. We show examples of modules linked to human diseases enriched in genes with known pathogenic variants that can be used to map targets of approved drugs for repurposing. Finally, we illustrate the use of network expansion scores to study genes at inflammatory bowel disease genome-wide association study loci, and implicate inflammatory bowel disease-relevant genes with strong functional and genetic support.

An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci.

Genome-wide association studies (GWASs) have identified many variants associated with complex traits, but identifying the causal gene(s) is a major challenge. In the present study, we present an open resource that provides systematic fine mapping and gene prioritization across 133,441 published human GWAS loci. We integrate genetics (GWAS Catalog and UK Biobank) with transcriptomic, proteomic and epigenomic data, including systematic disease-disease and disease-molecular trait colocalization results across 92 cell types and tissues. We identify 729 loci fine mapped to a single-coding causal variant and colocalized with a single gene. We trained a machine-learning model using the fine-mapped genetics and functional genomics data and 445 gold-standard curated GWAS loci to distinguish causal genes from neighboring genes, outperforming a naive distance-based model. Our prioritized genes were enriched for known approved drug targets (odds ratio = 8.1, 95% confidence interval = 5.7, 11.5). These results are publicly available through a web portal ( http://genetics.opentargets.org ), enabling users to easily prioritize genes at disease-associated loci and assess their potential as drug targets.

A map of transcriptional heterogeneity and regulatory variation in human microglia.

Microglia, the tissue-resident macrophages of the central nervous system (CNS), play critical roles in immune defense, development and homeostasis. However, isolating microglia from humans in large numbers is challenging. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery. Using single-cell and bulk RNA sequencing, we identify how age, sex and clinical pathology influence microglia gene expression and which genetic variants have microglia-specific functions using expression quantitative trait loci (eQTL) mapping. We follow up one of our findings using a human induced pluripotent stem cell-based macrophage model to fine-map a candidate causal variant for Alzheimer's disease at the BIN1 locus. Our study provides a population-scale transcriptional map of a critically important cell for human CNS development and disease.

A comparative analysis of rod bipolar cell transcriptomes identifies novel genes implicated in night vision.

In the mammalian retina, rods and a specialised rod-driven signalling pathway mediate visual responses under scotopic (dim light) conditions. As rods primarily signal to rod bipolar cells (RBCs) under scoptic conditions, disorders that affect rod or RBC function are often associated with impaired night vision. To identify novel genes expressed by RBCs and, therefore, likely to be involved in night vision, we took advantage of the adult Bhlhe23-/- mouse retina (that lacks RBCs) to derive the RBC transcriptome. We found that genes expressed by adult RBCs are mainly involved in synaptic structure and signalling, whereas genes that influence RBC development are also involved in the cell cycle and transcription/translation. By comparing our data with other published retinal and bipolar cell transcriptomes (where we identify RBCs by the presence of Prkca and/or Pcp2 transcripts), we have derived a consensus for the adult RBC transcriptome. These findings ought to facilitate further research into physiological mechanisms underlying mammalian night vision as well as proposing candidate genes for patients with inherited causes of night blindness.

Education and myopia: assessing the direction of causality by mendelian randomisation.

OBJECTIVES: To determine whether more years spent in education is a causal risk factor for myopia, or whether myopia is a causal risk factor for more years in education. DESIGN: Bidirectional, two sample mendelian randomisation study. SETTING: Publically available genetic data from two consortiums applied to a large, independent population cohort. Genetic variants used as proxies for myopia and years of education were derived from two large genome wide association studies: 23andMe and Social Science Genetic Association Consortium (SSGAC), respectively. PARTICIPANTS: 67 798 men and women from England, Scotland, and Wales in the UK Biobank cohort with available information for years of completed education and refractive error. MAIN OUTCOME MEASURES: Mendelian randomisation analyses were performed in two directions: the first exposure was the genetic predisposition to myopia, measured with 44 genetic variants strongly associated with myopia in 23andMe, and the outcome was years in education; and the second exposure was the genetic predisposition to higher levels of education, measured with 69 genetic variants from SSGAC, and the outcome was refractive error. RESULTS: Conventional regression analyses of the observational data suggested that every additional year of education was associated with a more myopic refractive error of -0.18 dioptres/y (95% confidence interval -0.19 to -0.17; P<2e-16). Mendelian randomisation analyses suggested the true causal effect was even stronger: -0.27 dioptres/y (-0.37 to -0.17; P=4e-8). By contrast, there was little evidence to suggest myopia affected education (years in education per dioptre of refractive error -0.008 y/dioptre, 95% confidence interval -0.041 to 0.025, P=0.6). Thus, the cumulative effect of more years in education on refractive error means that a university graduate from the United Kingdom with 17 years of education would, on average, be at least -1 dioptre more myopic than someone who left school at age 16 (with 12 years of education). Myopia of this magnitude would be sufficient to necessitate the use of glasses for driving. Sensitivity analyses showed minimal evidence for genetic confounding that could have biased the causal effect estimates. CONCLUSIONS: This study shows that exposure to more years in education contributes to the rising prevalence of myopia. Increasing the length of time spent in education may inadvertently increase the prevalence of myopia and potential future visual disability.

Shared genetic origin of asthma, hay fever and eczema elucidates allergic disease biology.

Asthma, hay fever (or allergic rhinitis) and eczema (or atopic dermatitis) often coexist in the same individuals, partly because of a shared genetic origin. To identify shared risk variants, we performed a genome-wide association study (GWAS; n = 360,838) of a broad allergic disease phenotype that considers the presence of any one of these three diseases. We identified 136 independent risk variants (P < 3 × 10-8), including 73 not previously reported, which implicate 132 nearby genes in allergic disease pathophysiology. Disease-specific effects were detected for only six variants, confirming that most represent shared risk factors. Tissue-specific heritability and biological process enrichment analyses suggest that shared risk variants influence lymphocyte-mediated immunity. Six target genes provide an opportunity for drug repositioning, while for 36 genes CpG methylation was found to influence transcription independently of genetic effects. Asthma, hay fever and eczema partly coexist because they share many genetic risk variants that dysregulate the expression of immune-related genes.

Accurate Sample Assignment in a Multiplexed, Ultrasensitive, High-Throughput Sequencing Assay for Minimal Residual Disease.

High-throughput sequencing (HTS) (next-generation sequencing) of the rearranged Ig and T-cell receptor genes promises to be less expensive and more sensitive than current methods of monitoring minimal residual disease (MRD) in patients with acute lymphoblastic leukemia. However, the adoption of new approaches by clinical laboratories requires careful evaluation of all potential sources of error and the development of strategies to ensure the highest accuracy. Timely and efficient clinical use of HTS platforms will depend on combining multiple samples (multiplexing) in each sequencing run. Here we examine the Ig heavy-chain gene HTS on the Illumina MiSeq platform for MRD. We identify errors associated with multiplexing that could potentially impact the accuracy of MRD analysis. We optimize a strategy that combines high-purity, sequence-optimized oligonucleotides, dual indexing, and an error-aware demultiplexing approach to minimize errors and maximize sensitivity. We present a probability-based, demultiplexing pipeline Error-Aware Demultiplexer that is suitable for all MiSeq strategies and accurately assigns samples to the correct identifier without excessive loss of data. Finally, using controls quantified by digital PCR, we show that HTS-MRD can accurately detect as few as 1 in 10(6) copies of specific leukemic MRD.

Reprogramming pig fetal fibroblasts reveals a functional LIF signaling pathway.

Distinct signaling pathways are reported to maintain pluripotency in embryo-derived stem cells. Mouse embryonic stem cells (ESCs) respond to leukemia inhibitory factor (LIF) and bone morphogenetic protein (BMP)-mediated activity, whereas human ESCs depend upon Fibroblast growth factor (FGF) and activin signaling. In the majority of mammals investigated, however, the signals that support stem cell pluripotency are not well defined, as is evident by the persistent difficulties in maintaining authentic stable ESC lines. Induction of pluripotency by transcription factor-mediated reprogramming could provide an alternative way to produce ESC-like cells from nonpermissive species, and facilitate identification of core ESC signaling requirements. To evaluate the effectiveness of this approach in pigs, we transduced porcine foetal fibroblasts with retroviruses expressing Oct4, Sox2, Klf4, and c-Myc, and maintained the resulting cultures in medium containing either LIF or FGF2. Alkaline phosphatase positive colonies with compact, mouse ESC-like morphology were preferentially recovered using serum-free medium supplemented with LIF. These cell lines expressed the endogenous stem cell transcription factors, OCT4, NANOG, and SOX2, and the cell surface marker SSEA-4, consistent with acquisition of an undifferentiated state. However, restricted differentiation potential, and persistent expression of retroviral transgenes indicated that reprogramming was incomplete. Interestingly, LIF activated both the transcription factor STAT3 and its target gene SOCS3, and stimulated cell growth, indicating functional coupling of the signaling pathway in these cells. This demonstration of LIF-dependence in reprogrammed pig cells supports the notion that the connection between LIF/STAT3 signaling and the core regulatory network of pluripotent stem cells is a conserved pathway in mammals.