Empowering the discovery of novel target-disease associations via machine learning approaches in the open targets platform.

BACKGROUND: The Open Targets (OT) Platform integrates a wide range of data sources on target-disease associations to facilitate identification of potential therapeutic drug targets to treat human diseases. However, due to the complexity that targets are usually functionally pleiotropic and efficacious for multiple indications, challenges in identifying novel target to indication associations remain. Specifically, persistent need exists for new methods for integration of novel target-disease association evidence and biological knowledge bases via advanced computational methods. These offer promise for increasing power for identification of the most promising target-disease pairs for therapeutic development. Here we introduce a novel approach by integrating additional target-disease features with machine learning models to further uncover druggable disease to target indications. RESULTS: We derived novel target-disease associations as supplemental features to OT platform-based associations using three data sources: (1) target tissue specificity from GTEx expression profiles; (2) target semantic similarities based on gene ontology; and (3) functional interactions among targets by embedding them from protein-protein interaction (PPI) networks. Machine learning models were applied to evaluate feature importance and performance benchmarks for predicting targets with known drug indications. The evaluation results show the newly integrated features demonstrate higher importance than current features in OT. In addition, these also show superior performance over association benchmarks and may support discovery of novel therapeutic indications for highly pursued targets. CONCLUSION: Our newly generated features can be used to represent additional underlying biological relatedness among targets and diseases to further empower improved performance for predicting novel indications for drug targets through advanced machine learning models. The proposed methodology enables a powerful new approach for systematic evaluation of drug targets with novel indications.

Assessment of rosacea symptom severity by genome-wide association study and expression analysis highlights immuno-inflammatory and skin pigmentation genes.

Rosacea is a common, chronic skin disease of variable severity with limited treatment options. The cause of rosacea is unknown, but it is believed to be due to a combination of hereditary and environmental factors. Little is known about the genetics of the disease. We performed a genome-wide association study (GWAS) of rosacea symptom severity with data from 73 265 research participants of European ancestry from the 23andMe customer base. Seven loci had variants associated with rosacea at the genome-wide significance level (P < 5 × 10-8). Further analyses highlighted likely gene regions or effector genes including IRF4 (P = 1.5 × 10-17), a human leukocyte antigen (HLA) region flanked by PSMB9 and HLA-DMB (P = 2.2 × 10-15), HERC2-OCA2 (P = 4.2 × 10-12), SLC45A2 (P = 1.7 × 10-10), IL13 (P = 2.8 × 10-9), a region flanked by NRXN3 and DIO2 (P = 4.1 × 10-9), and a region flanked by OVOL1and SNX32 (P = 1.2 × 10-8). All associations with rosacea were novel except for the HLA locus. Two of these loci (HERC-OCA2 and SLC45A2) and another precedented variant (rs1805007 in melanocortin 1 receptor) with an association P value just below the significance threshold (P = 1.3 × 10-7) have been previously associated with skin phenotypes and pigmentation, two of these loci are linked to immuno-inflammation phenotypes (IL13 and PSMB9-HLA-DMA) and one has been associated with both categories (IRF4). Genes within three loci (PSMB9-HLA-DMA, HERC-OCA2 and NRX3-DIO2) were differentially expressed in a previously published clinical rosacea transcriptomics study that compared lesional to non-lesional samples. The identified loci provide specificity of inflammatory mechanisms in rosacea, and identify potential pathways for therapeutic intervention.

Uncovering new disease indications for G-protein coupled receptors and their endogenous ligands.

BACKGROUND: The Open Targets Platform integrates different data sources in order to facilitate identification of potential therapeutic drug targets to treat human diseases. It currently provides evidence for nearly 2.6 million potential target-disease pairs. G-protein coupled receptors are a drug target class of high interest because of the number of successful drugs being developed against them over many years. Here we describe a systematic approach utilizing the Open Targets Platform data to uncover and prioritize potential new disease indications for the G-protein coupled receptors and their ligands. RESULTS: Utilizing the data available in the Open Targets platform, potential G-protein coupled receptor and endogenous ligand disease association pairs were systematically identified. Intriguing examples such as GPR35 for inflammatory bowel disease and CXCR4 for viral infection are used as illustrations of how a systematic approach can aid in the prioritization of interesting drug discovery hypotheses. Combining evidences for G-protein coupled receptors and their corresponding endogenous peptidergic ligands increases confidence and provides supportive evidence for potential new target-disease hypotheses. Comparing such hypotheses to the global pharma drug discovery pipeline to validate the approach showed that more than 93% of G-protein coupled receptor-disease pairs with a high overall Open Targets score involved receptors with an existing drug discovery program. CONCLUSIONS: The Open Targets gene-disease score can be used to prioritize potential G-protein coupled receptors-indication hypotheses. In addition, availability of multiple different evidence types markedly increases confidence as does combining evidence from known receptor-ligand pairs. Comparing the top-ranked hypotheses to the current global pharma pipeline serves validation of our approach and identifies and prioritizes new therapeutic opportunities.

Network-Based Identification and Prioritization of Key Regulators of Coronary Artery Disease Loci.

OBJECTIVE: Recent genome-wide association studies of coronary artery disease (CAD) have revealed 58 genome-wide significant and 148 suggestive genetic loci. However, the molecular mechanisms through which they contribute to CAD and the clinical implications of these findings remain largely unknown. We aim to retrieve gene subnetworks of the 206 CAD loci and identify and prioritize candidate regulators to better understand the biological mechanisms underlying the genetic associations. APPROACH AND RESULTS: We devised a new integrative genomics approach that incorporated (1) candidate genes from the top CAD loci, (2) the complete genetic association results from the 1000 genomes-based CAD genome-wide association studies from the Coronary Artery Disease Genome Wide Replication and Meta-Analysis Plus the Coronary Artery Disease consortium, (3) tissue-specific gene regulatory networks that depict the potential relationship and interactions between genes, and (4) tissue-specific gene expression patterns between CAD patients and controls. The networks and top-ranked regulators according to these data-driven criteria were further queried against literature, experimental evidence, and drug information to evaluate their disease relevance and potential as drug targets. Our analysis uncovered several potential novel regulators of CAD such as LUM and STAT3, which possess properties suitable as drug targets. We also revealed molecular relations and potential mechanisms through which the top CAD loci operate. Furthermore, we found that multiple CAD-relevant biological processes such as extracellular matrix, inflammatory and immune pathways, complement and coagulation cascades, and lipid metabolism interact in the CAD networks. CONCLUSIONS: Our data-driven integrative genomics framework unraveled tissue-specific relations among the candidate genes of the CAD genome-wide association studies loci and prioritized novel network regulatory genes orchestrating biological processes relevant to CAD.

The epigenetic signature of systemic insulin resistance in obese women.

AIMS/HYPOTHESIS: Insulin resistance (IR) links obesity to type 2 diabetes. The aim of this study was to explore whether white adipose tissue (WAT) epigenetic dysregulation is associated with systemic IR by genome-wide CG dinucleotide (CpG) methylation and gene expression profiling in WAT from insulin-resistant and insulin-sensitive women. A secondary aim was to determine whether the DNA methylation signature in peripheral blood mononuclear cells (PBMCs) reflects WAT methylation and, if so, can be used as a marker for systemic IR. METHODS: From 220 obese women, we selected a total of 80 individuals from either of the extreme ends of the distribution curve of HOMA-IR, an indirect measure of systemic insulin sensitivity. Genome-wide transcriptome and DNA CpG methylation profiling by array was performed on subcutaneous (SAT) and visceral (omental) adipose tissue (VAT). CpG methylation in PBMCs was assayed in the same cohort. RESULTS: There were 647 differentially expressed genes (false discovery rate [FDR] 10%) in SAT, all of which displayed directionally consistent associations in VAT. This suggests that IR is associated with dysregulated expression of a common set of genes in SAT and VAT. The average degree of DNA methylation did not differ between the insulin-resistant and insulin-sensitive group in any of the analysed tissues/cells. There were 223 IR-associated genes in SAT containing a total of 336 nominally significant differentially methylated sites (DMS). The 223 IR-associated genes were over-represented in pathways related to integrin cell surface interactions and insulin signalling and included COL5A1, GAB1, IRS2, PFKFB3 and PTPRJ. In VAT there were a total of 51 differentially expressed genes (FDR 10%); 18 IR-associated genes contained a total of 29 DMS. CONCLUSIONS/INTERPRETATION: In individuals discordant for insulin sensitivity, the average DNA CpG methylation in SAT and VAT is similar, although specific genes, particularly in SAT, display significantly altered expression and DMS in IR, possibly indicating that epigenetic regulation of these genes influences metabolism.

Modulating the human gut microbiome as an emerging therapeutic paradigm.

The human body is actually a vast and changing ecosystem comprised of billions of microbial organisms, known collectively as the microbiome. Within the last few years, the study of the microbiome and its impact on human health has been a rapidly growing area of biomedical science. The gut intestinal tract microbiome has been a particular focus of research given its potential role in many inflammatory and metabolic diseases as well as drug metabolism. Although a nascent field, the potential for modulating the gut microbiome or human host interactions associated with these microbes offers new therapeutic strategies for many chronic diseases, in particular obesity, diabetes and inflammatory bowel diseases. Here we provide an overview of present knowledge about the gut microbiome, its putative role in metabolic diseases and the potential for microbiome focused treatments from the drug development perspective.

A Hidradenitis Suppurativa molecular disease signature derived from patient samples by high-throughput RNA sequencing and re-analysis of previously reported transcriptomic data sets.

Hidradenitis suppurativa (HS) is a common, debilitating inflammatory skin disease linked to immune dysregulation and abnormalities in follicular structure and function. Several studies have characterized the transcriptomic profile of affected and unaffected skin in small populations. In this study of 20 patients, RNA from lesional and matching non-lesional skin biopsies in 20 subjects were used to identify an expression-based HS disease signature. This was followed by differential expression and pathway enrichment analyses, as well as jointly reanalyzing our findings with previously published transcriptomic profiles. We establish an RNA-Seq based HS expression disease signature that is mostly consistent with previous reports. Bulk-RNA profiles from 104 subjects in 7 previously reported data sets identified a disease signature of 118 differentially regulated genes compared to three control data sets from non-lesional skin. We confirmed previously reported expression profiles and further characterized dysregulation in complement activation and host response to bacteria in disease pathogenesis. Changes in the transcriptome of lesional skin in this cohort of HS patients is consistent with smaller previously reported populations. The findings further support the significance of immune dysregulation, in particular with regard to bacterial response mechanisms. Joint analysis of this and previously reported cohorts indicate a remarkably consistent expression profile.

Microglia ferroptosis is regulated by SEC24B and contributes to neurodegeneration.

Iron dysregulation has been implicated in multiple neurodegenerative diseases, including Parkinson's disease (PD). Iron-loaded microglia are frequently found in affected brain regions, but how iron accumulation influences microglia physiology and contributes to neurodegeneration is poorly understood. Here we show that human induced pluripotent stem cell-derived microglia grown in a tri-culture system are highly responsive to iron and susceptible to ferroptosis, an iron-dependent form of cell death. Furthermore, iron overload causes a marked shift in the microglial transcriptional state that overlaps with a transcriptomic signature found in PD postmortem brain microglia. Our data also show that this microglial response contributes to neurodegeneration, as removal of microglia from the tri-culture system substantially delayed iron-induced neurotoxicity. To elucidate the mechanisms regulating iron response in microglia, we performed a genome-wide CRISPR screen and identified novel regulators of ferroptosis, including the vesicle trafficking gene SEC24B. These data suggest a critical role for microglia iron overload and ferroptosis in neurodegeneration.

Inhibition of apical sodium-dependent bile acid transporter as a novel treatment for diabetes.

Bile acids are recognized as metabolic modulators. The present study was aimed at evaluating the effects of a potent Asbt inhibitor (264W94), which blocks intestinal absorption of bile acids, on glucose homeostasis in Zucker Diabetic Fatty (ZDF) rats. Oral administration of 264W94 for two wk increased fecal bile acid concentrations and elevated non-fasting plasma total Glp-1. Treatment of 264W94 significantly decreased HbA1c and glucose, and prevented the drop of insulin levels typical of ZDF rats in a dose-dependent manner. An oral glucose tolerance test revealed up to two-fold increase in plasma total Glp-1 and three-fold increase in insulin in 264W94 treated ZDF rats at doses sufficient to achieve glycemic control. Tissue mRNA analysis indicated a decrease in farnesoid X receptor (Fxr) activation in small intestines and the liver but co-administration of a Fxr agonist (GW4064) did not attenuate 264W94 induced glucose lowering effects. In summary, our results demonstrate that inhibition of Asbt increases bile acids in the distal intestine, promotes Glp-1 release and may offer a new therapeutic strategy for type 2 diabetes mellitus.

Genome-Wide Association Study and Gene-Based Analysis of Participants With Hemophilia A and Inhibitors in the My Life, Our Future Research Repository.

Introduction: Up to 30% of individuals with hemophilia A develop inhibitors to replacement factor VIII (FVIII), rendering the treatment ineffective. The underlying mechanism of inhibitor development remains poorly understood. The My Life, Our Future Research Repository (MLOF RR) has gathered F8 and F9 mutational information, phenotypic data, and biological material from over 11,000 participants with hemophilia A (HA) and B as well as carriers enrolled across US hemophilia treatment centers, including over 5,000 whole-genome sequences. Identifying genes associated with inhibitors may contribute to our understanding of why certain patients develop those neutralizing antibodies. Aim and Methods: Here, we performed a genome-wide association study and gene-based analyses to identify genes associated with inhibitors in participants with HA from the MLOF RR. Results: We identify a genome-wide significant association within the human leukocyte antigen (HLA) locus in participants with HA with F8 intronic inversions. HLA typing revealed independent associations with the HLA alleles major histocompatibility complex, class II, DR beta 1 (HLA DRB1*15:01) and major histocompatibility complex, class II, DQ beta 1 (DQB1*03:03). Variant aggregation tests further identified low-frequency variants within GRID2IP (glutamate receptor, ionotropic, delta 2 [GRID2] interacting protein 1) significantly associated with inhibitors. Conclusion: Overall, our study confirms the association of DRB1*15:01 with FVIII inhibitors and identifies a novel association of DQB1*03:03 in individuals with HA carrying intronic inversions of F8. In addition, our results implicate GRID2IP, encoding GRID2-interacting protein, with the development of inhibitors, and suggest an unrecognized role of this gene in autoimmunity.

An integrative network-based approach for drug target indication expansion.

BACKGROUND: The identification of a target-indication pair is regarded as the first step in a traditional drug discovery and development process. Significant investment and attrition occur during discovery and development before a molecule is shown to be safe and efficacious for the selected indication and becomes an approved drug. Many drug targets are functionally pleiotropic and might be good targets for multiple indications. Methodologies that leverage years of scientific contributions on drug targets to allow systematic evaluation of other indication opportunities are critical for both patients and drug discovery and development scientists. METHODS: We introduced a network-based approach to systematically screen and prioritize disease indications for drug targets. The approach fundamentally integrates disease genomics data and protein interaction network. Further, the methodology allows for indication identification by leveraging state-of-art network algorithms to generate and compare the target and disease subnetworks. RESULTS: We first evaluated the performance of our method on recovering FDA approved indications for 15 randomly selected drug targets. The results showed superior performance when compared with other state-of-art approaches. Using this approach, we predicted novel indications supported by literature evidence for several highly pursued drug targets such as IL12/IL23 combination. CONCLUSIONS: Our results demonstrated a potential global approach for indication expansion strategies. The proposed methodology enables rapid and systematic evaluation of both individual and combined drug targets for novel indications. Additionally, this approach provides novel insights on expanding the role of genes and pathways for developing therapeutic intervention strategies.

The essentiality of drug targets: an analysis of current literature and genomic databases.

Essential genes encode proteins thought to be crucial for the survival of an organism. However, the role of essential genes in human disease and their suitability as drug targets is less clear. Here, we use a recent catalog of nearly 9000 known essential and nonessential genes to evaluate their involvement as therapeutic targets in human diseases. We find that essential genes are more likely than nonessential genes to play a part in specific therapeutic areas such as cardiovascular diseases and neoplasms. We also find significant differences between essential and nonessential genes among protein classes relevant to drug discovery. Taken together, our analyses suggest that the essentiality status of a potential new target is an important consideration in drug discovery.

Multi-omics integration reveals molecular networks and regulators of psoriasis.

BACKGROUND: Psoriasis is a complex multi-factorial disease, involving both genetic susceptibilities and environmental triggers. Genome-wide association studies (GWAS) and epigenome-wide association studies (EWAS) have been carried out to identify genetic and epigenetic variants that are associated with psoriasis. However, these loci cannot fully explain the disease pathogenesis. METHODS: To achieve a comprehensive mechanistic understanding of psoriasis, we conducted a systems biology study, integrating multi-omics datasets including GWAS, EWAS, tissue-specific transcriptome, expression quantitative trait loci (eQTLs), gene networks, and biological pathways to identify the key genes, processes, and networks that are genetically and epigenetically associated with psoriasis risk. RESULTS: This integrative genomics study identified both well-characterized (e.g., the IL17 pathway in both GWAS and EWAS) and novel biological processes (e.g., the branched chain amino acid catabolism process in GWAS and the platelet and coagulation pathway in EWAS) involved in psoriasis. Finally, by utilizing tissue-specific gene regulatory networks, we unraveled the interactions among the psoriasis-associated genes and pathways in a tissue-specific manner and detected potential key regulatory genes in the psoriasis networks. CONCLUSIONS: The integration and convergence of multi-omics signals provide deeper and comprehensive insights into the biological mechanisms associated with psoriasis susceptibility.

Preclinical evaluation of EPHX2 inhibition as a novel treatment for inflammatory bowel disease.

Epoxyeicosatrienoic acids (EETs) are signaling lipids produced by cytochrome P450 epoxygenation of arachidonic acid, which are metabolized by EPHX2 (epoxide hydrolase 2, alias soluble epoxide hydrolase or sEH). EETs have pleiotropic effects, including anti-inflammatory activity. Using a Connectivity Map (CMAP) approach, we identified an inverse-correlation between an exemplar EPHX2 inhibitor (EPHX2i) compound response and an inflammatory bowel disease patient-derived signature. To validate the gene-disease link, we tested a pre-clinical tool EPHX2i (GSK1910364) in a mouse disease model, where it showed improved outcomes comparable to or better than the positive control Cyclosporin A. Up-regulation of cytoprotective genes and down-regulation of proinflammatory cytokine production were observed in colon samples obtained from EPHX2i-treated mice. Follow-up immunohistochemistry analysis verified the presence of EPHX2 protein in infiltrated immune cells from Crohn's patient tissue biopsies. We further demonstrated that GSK2256294, a clinical EPHX2i, reduced the production of IL2, IL12p70, IL10 and TNFα in both ulcerative colitis and Crohn's disease patient-derived explant cultures. Interestingly, GSK2256294 reduced IL4 and IFNγ in ulcerative colitis, and IL1ß in Crohn's disease specifically, suggesting potential differential effects of GSK2256294 in these two diseases. Taken together, these findings suggest a novel therapeutic use of EPHX2 inhibition for IBD.

Gut microbiome differences between metformin- and liraglutide-treated T2DM subjects.

INTRODUCTION: Metformin and glucagon-like peptide-1 (GLP-1) agonists are widely used for treating type two diabetes mellitus (T2DM). While recent studies suggest these drugs might modify the gastrointestinal tract (GIT) microbiome, further confirmation is required from human clinical trials. MATERIALS AND METHODS: Here, we compare, in patients with T2DM, the effects of metformin (n = 18 subjects) and liraglutide (n = 19), a GLP-1 agonist, on their GIT microbiomes over a 42 day period (n = 74 samples) using 16S ribosomal RNA (rRNA) sequencing. RESULTS: We found that these drugs had markedly different effects on the microbiome composition. At both baseline and Day 42, subjects taking metformin had a significant increase (Baseline adj. P = .038, Day 42 adj. P = .041) in the relative abundance of the bacterial genus Sutterella, whereas liraglutide dosing is associated with a significant increase (Baseline adj. P = .048, Day 42 adj. P = .003) in the genus Akkermansia, a GIT bacteria positively associated with gut barrier homoeostasis. Bacteroides and Akkermansia relative abundances were also significantly associated with duration of subject diabetes (adj P < .05). Specifically, there was a significantly higher abundance of Akkermansia in subjects with short and medium durations than those with long duration of diabetes. DISCUSSION: To our knowledge, this is the first report of GLP-1 agonist-associated changes in the human microbiome and its differentiating effects to metformin. Our study suggests that modulation of the GIT microbiome is a potentially important component in the mechanism of action of these drugs.

BET Inhibition Improves NASH and Liver Fibrosis.

Non-alcoholic fatty liver disease (NAFLD) is a leading form of chronic liver disease with large unmet need. Non-alcoholic steatohepatitis (NASH), a progressive variant of NAFLD, can lead to fibrosis, cirrhosis, and hepatocellular carcinoma. To identify potential new therapeutics for NASH, we used a computational approach based on Connectivity Map (CMAP) analysis, which pointed us to bromodomain and extra-terminal motif (BET) inhibitors for treating NASH. To experimentally validate this hypothesis, we tested a small-molecule inhibitor of the BET family of proteins, GSK1210151A (I-BET151), in the STAM mouse NASH model at two different dosing timepoints (onset of NASH and progression to fibrosis). I-BET151 decreased the non-alcoholic fatty liver disease activity score (NAS), a clinical endpoint for assessing the severity of NASH, as well as progression of liver fibrosis and interferon-γ expression. Transcriptional characterization of these mice through RNA-sequencing was consistent with predictions from the CMAP analysis of a human NASH signature and pointed to alterations in molecular mechanisms related to interferon signaling and cholesterol biosynthesis, as well as reversal of gene expression patterns linked to fibrotic markers. Altogether, these results suggest that inhibition of BET proteins may present a novel therapeutic opportunity in the treatment of NASH and liver fibrosis.

Correction to: HIF prolyl hydroxylase inhibition protects skeletal muscle from eccentric contraction induced injury.

Following publication of the original article [1], the authors flagged that there is a discrepancy with the Availability of data and materials statement on page 12 of the article.

HIF prolyl hydroxylase inhibition protects skeletal muscle from eccentric contraction-induced injury.

BACKGROUND: In muscular dystrophy and old age, skeletal muscle repair is compromised leading to fibrosis and fatty tissue accumulation. Therefore, therapies that protect skeletal muscle or enhance repair would be valuable medical treatments. Hypoxia-inducible factors (HIFs) regulate gene transcription under conditions of low oxygen, and HIF target genes EPO and VEGF have been associated with muscle protection and repair. We tested the importance of HIF activation following skeletal muscle injury, in both a murine model and human volunteers, using prolyl hydroxylase inhibitors that stabilize and activate HIF. METHODS: Using a mouse eccentric limb injury model, we characterized the protective effects of prolyl hydroxylase inhibitor, GSK1120360A. We then extended these studies to examine the impact of EPO modulation and infiltrating immune cell populations on muscle protection. Finally, we extended this study with an experimental medicine approach using eccentric arm exercise in untrained volunteers to measure the muscle-protective effects of a clinical prolyl hydroxylase inhibitor, daprodustat. RESULTS: GSK1120360A dramatically prevented functional deficits and histological damage, while accelerating recovery after eccentric limb injury in mice. Surprisingly, this effect was independent of EPO, but required myeloid HIF1α-mediated iNOS activity. Treatment of healthy human volunteers with high-dose daprodustat reduced accumulation of circulating damage markers following eccentric arm exercise, although we did not observe any diminution of functional deficits with compound treatment. CONCLUSION: The results of these experiments highlight a novel skeletal muscle protective effect of prolyl hydroxylase inhibition via HIF-mediated expression of iNOS in macrophages. Partial recapitulation of these findings in healthy volunteers suggests elements of consistent pharmacology compared to responses in mice although there are clear differences between these two systems.

Uncovering novel repositioning opportunities using the Open Targets platform.

The recently developed Open Targets platform consolidates a wide range of comprehensive evidence associating known and potential drug targets with human diseases. We have harnessed the integrated data from this platform for novel drug repositioning opportunities. Our computational workflow systematically mines data from various evidence categories and presents potential repositioning opportunities for drugs that are marketed or being investigated in ongoing human clinical trials, based on evidence strength on target-disease pairing. We classified these novel target-disease opportunities in several ways: (i) number of independent counts of evidence; (ii) broad therapy area of origin; and (iii) repositioning within or across therapy areas. Finally, we elaborate on one example that was identified by this approach.