Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19.
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ABSTRACT:
SUBMITTER: Gaziano L
PROVIDER: S-EPMC7612986 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature
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Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19.
Gaziano Liam L Giambartolomei Claudia C Pereira Alexandre C AC Gaulton Anna A Posner Daniel C DC Swanson Sonja A SA Ho Yuk-Lam YL Iyengar Sudha K SK Kosik Nicole M NM Vujkovic Marijana M Gagnon David R DR Bento A Patrícia AP Barrio-Hernandez Inigo I Rönnblom Lars L Hagberg Niklas N Lundtoft Christian C Langenberg Claudia C Pietzner Maik M Valentine Dennis D Gustincich Stefano S Tartaglia Gian Gaetano GG Allara Elias E Surendran Praveen P Burgess Stephen S Zhao Jing Hua JH Peters James E JE Prins Bram P BP Angelantonio Emanuele Di ED Devineni Poornima P Shi Yunling Y Lynch Kristine E KE DuVall Scott L SL Garcon Helene H Thomann Lauren O LO Zhou Jin J JJ Gorman Bryan R BR Huffman Jennifer E JE O'Donnell Christopher J CJ Tsao Philip S PS Beckham Jean C JC Pyarajan Saiju S Muralidhar Sumitra S Huang Grant D GD Ramoni Rachel R Beltrao Pedro P Danesh John J Hung Adriana M AM Chang Kyong-Mi KM Sun Yan V YV Joseph Jacob J Leach Andrew R AR Edwards Todd L TL Cho Kelly K Gaziano J Michael JM Butterworth Adam S AS Casas Juan P JP
Nature medicine 20210409 4
Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patie ...[more]
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Project description:BackgroundThere are no effective pharmacological treatments for sarcopenia. We aim to identify potential therapeutic targets for sarcopenia by integrating various publicly available datasets.MethodsWe integrated druggable genome data, cis-eQTL/cis-pQTL from human blood and skeletal muscle tissue, and GWAS summary data of sarcopenia-related traits to analyse the potential causal relationships between drug target genes and sarcopenia using the Mendelian Randomization (MR) method. Sensitivity analyses and Bayesian colocalization were employed to validate the causal relationships. We also assessed the side effects or additional indications of the identified drug targets using a phenome-wide MR (Phe-MR) approach and investigated actionable drugs for target genes using available databases.ResultsMR analysis identified 17 druggable genes with potential causation to sarcopenia in human blood or skeletal muscle tissue. Six of them (HP, HLA-DRA, MAP 3K3, MFGE8, COL15A1, and AURKA) were further confirmed by Bayesian colocalization (PPH4 > 90%). The up-regulation of HP [higher ALM (beta: 0.012, 95% CI: 0.007-0.018, P = 1.2*10-5) and higher grip strength (OR: 0.96, 95% CI: 0.94-0.98, P = 4.2*10-5)], MAP 3K3 [higher ALM (beta: 0.24, 95% CI: 0.21-0.26, P = 1.8*10-94), higher grip strength (OR: 0.82, 95% CI: 0.75-0.90, P = 2.1*10-5), and faster walking pace (beta: 0.03, 95% CI: 0.02-0.05, P = 8.5*10-6)], and MFGE8 [higher ALM (muscle eQTL, beta: 0.09, 95% CI: 0.06-0.11, P = 6.1*10-13; blood pQTL, beta: 0.05, 95% CI: 0.03-0.07, P = 3.8*10-09)], as well as the down-regulation of HLA-DRA [lower ALM (beta: -0.09, 95% CI: -0.11 to -0.08, P = 5.4*10-36) and lower grip strength (OR: 1.13, 95% CI: 1.07-1.20, P = 1.8*10-5)] and COL15A1 [higher ALM (muscle eQTL, beta: -0.07, 95% CI: -0.10 to -0.04, P = 3.4*10-07; blood pQTL, beta: -0.05, 95% CI: -0.06 to -0.03, P = 1.6*10-07)], decreased the risk of sarcopenia. AURKA in blood (beta: -0.16, 95% CI: -0.22 to -0.09, P = 2.1*10-06) and skeletal muscle (beta: 0.03, 95% CI: 0.02 to 0.05, P = 5.3*10-05) tissues showed an inverse relationship with sarcopenia risk. The Phe-MR indicated that the six potential therapeutic targets for sarcopenia had no significant adverse effects. Drug repurposing analysis supported zinc supplementation and collagenase clostridium histolyticum might be potential therapeutics for sarcopenia by activating HP and inhibiting COL15A1, respectively.ConclusionsOur research indicated MAP 3K3, MFGE8, COL15A1, HP, and HLA-DRA may serve as promising targets for sarcopenia, while the effectiveness of zinc supplementation and collagenase clostridium histolyticum for sarcopenia requires further validation.
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Project description:Psychiatric disorders impose tremendous economic burden on society and are leading causes of disability worldwide. However, only limited drugs are available for psychiatric disorders and the efficacy of most currently used drugs is poor for many patients. To identify novel therapeutic targets for psychiatric disorders, we performed genome-wide Mendelian randomization analyses by integrating brain-derived molecular quantitative trait loci (mRNA expression and protein abundance quantitative trait loci) of 1263 actionable proteins (targeted by approved drugs or drugs in clinical phase of development) and genetic findings from large-scale genome-wide association studies (GWASs). Using transcriptome data, we identified 25 potential drug targets for psychiatric disorders, including 12 genes for schizophrenia, 7 for bipolar disorder, 7 for depression, and 1 (TIE1) for attention deficit and hyperactivity. We also identified 10 actionable drug targets by using brain proteome data, including 4 (HLA-DRB1, CAMKK2, P2RX7, and MAPK3) for schizophrenia, 1 (PRKCB) for bipolar disorder, 6 (PSMB4, IMPDH2, SERPINC1, GRIA1, P2RX7 and TAOK3) for depression. Of note, MAPK3 and HLA-DRB1 were supported by both transcriptome and proteome-wide MR analyses, suggesting that these two proteins are promising therapeutic targets for schizophrenia. Our study shows the power of integrating large-scale GWAS findings and transcriptomic and proteomic data in identifying actionable drug targets. Besides, our findings prioritize actionable novel drug targets for development of new therapeutics and provide critical drug-repurposing opportunities for psychiatric disorders.
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Project description:BackgroundHyperemesis gravidarum (HG), excessive vomiting in pregnancy, occurs in 0.3-10.8% of pregnancies and is associated with maternal and fetal morbidity. Despite the existence of several off-label treatment options that have shown clinical effectiveness in managing HG symptoms, the variability in treatment response highlights the need for more effective therapies. Our study aims to identify novel therapeutic targets that could lead to the development of additional, more effective treatment options.MethodsA two-sample Mendelian randomization (MR) analysis was performed to estimate the causal effects of blood-druggable genes on HG. Summary statistics for HG were obtained from the FinnGen study and UK Biobank. Cis-expression quantitative trait loci (cis-eQTL) for blood druggable genes were obtained from the eQTLGen Consortium and used as genetic instrumental variables. Another MR method, summary level mendelian randomization (SMR), was used to further confirm our results. We also used eQTL data of other vomiting-related tissues, brain regions, and esophagus, to validate our MR results. Finally, the potential side effects of the druggable genes for HG treatment were assessed using a phenome-wide MR.ResultsOverall, 2499 unique druggable genes were gathered. Two blood drug targets (OVGP1 and LGALS1) showed significant MR results in two independent datasets. No significant heterogeneity of instrumental variables or pleiotropy was detected. In addition, SMR analysis further confirmed the significance of these two prior druggable genes in the brain and esophagus tissues. Further phenome-wide MR analysis revealed no association between genetic proxies of OVGP1, and LGALS1 has been detected in increasing the risk of adverse pregnancy outcomes and other common diseases.ConclusionsThis study provides genetic evidence that targeting two druggable genes for HG has potential therapeutic advantages. This information is of considerable value in guiding and prioritizing the development of more effective therapies for HG.
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Project description:PurposeDiabetes and its complications cause a heavy burden of disease worldwide. In recent years, Mendelian randomization (MR) has been widely used to discover the pathogenesis and epidemiology of diseases, as well as to discover new therapeutic targets. Therefore, based on systematic "druggable" genomics, we aim to identify new therapeutic targets for diabetes and analyze its pathophysiological mechanisms to promote its new therapeutic strategies.Material and methodWe used double sample MR to integrate the identified druggable genomics to evaluate the causal effect of quantitative trait loci (eQTLs) expressed by druggable genes in blood on type 1 and 2 diabetes (T1DM and T2DM). Repeat the study using different data sources on diabetes and its complications to verify the identified genes. Not only that, we also use Bayesian co-localization analysis to evaluate the posterior probabilities of different causal variations, shared causal variations, and co-localization probabilities to examine the possibility of genetic confounding. Finally, using diabetes markers with available genome-wide association studies data, we evaluated the causal relationship between established diabetes markers to explore possible mechanisms.ResultOverall, a total of 4,477 unique druggable genes have been gathered. After filtering using methods such as Bonferroni significance (P<1.90e-05), the MR Steiger directionality test, Bayesian co-localization analysis, and validation with different datasets, Finally, 7 potential druggable genes that may affect the results of T1DM and 7 potential druggable genes that may affect the results of T2DM were identified. Reverse MR suggests that C4B may play a bidirectional role in the pathogenesis of T1DM, and none of the other 13 target genes have a reverse causal relationship. And the 7 target genes in T2DM may each affect the biomarkers of T2DM to mediate the pathogenesis of T2DM.ConclusionThis study provides genetic evidence supporting the potential therapeutic benefits of targeting seven druggable genes, namely MAP3K13, KCNJ11, REG4, KIF11, CCNE2, PEAK1, and NRBP1, for T2DM treatment. Similarly, targeting seven druggable genes, namely ERBB3, C4B, CD69, PTPN22, IL27, ATP2A1, and LT-β, has The potential therapeutic benefits of T1DM treatment. This will provide new ideas for the treatment of diabetes and also help to determine the priority of drug development for diabetes.
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Project description:BackgroundChronic obstructive pulmonary disease (COPD) is a prevalent condition that significantly impacts public health. Unfortunately, there are few effective treatment options available. Mendelian randomization (MR) has been utilized to repurpose existing drugs and identify new therapeutic targets. The objective of this study is to identify novel therapeutic targets for COPD.MethodsCis-expression quantitative trait loci (cis-eQTL) were extracted for 4,317 identified druggable genes from genomics and proteomics data of whole blood (eQTLGen) and lung tissue (GTEx Consortium). Genome-wide association studies (GWAS) data for doctor-diagnosed COPD, spirometry-defined COPD (Forced Expiratory Volume in one second [FEV1]/Forced Vital Capacity [FVC] <0.7), and FEV1 were obtained from the cohort of FinnGen, UK Biobank and SpiroMeta consortium. We employed Summary-data-based Mendelian Randomization (SMR), HEIDI test, and colocalization analysis to assess the causal effects of druggable gene expression on COPD and lung function. The reliability of these druggable genes was confirmed by eQTL two-sample MR and protein quantitative trait loci (pQTL) SMR, respectively. The potential effects of druggable genes were assessed through the phenome-wide association study (PheWAS). Information on drug repurposing for COPD was collected from multiple databases.ResultsA total of 31 potential druggable genes associated with doctor-diagnosed COPD, spirometry-defined COPD, and FEV1 were identified through SMR, HEIDI test, and colocalization analysis. Among them, 22 genes (e.g., MMP15, PSMA4, ERBB3, and LMCD1) were further confirmed by eQTL two-sample MR and protein SMR analyses. Gene-level PheWAS revealed that ERBB3 expression might reduce inflammation, while GP9 and MRC2 were associated with other traits. The drugs Montelukast (targeting the MMP15 gene) and MARIZOMIB (targeting the PSMA4 gene) may reduce the risk of spirometry-defined COPD. Additionally, an existing small molecule inhibitor of the APH1A gene has the potential to increase FEV1.ConclusionsOur findings identified 22 potential drug targets for COPD and lung function. Prioritizing clinical trials that target these identified druggable genes with existing drugs or novel medications will be beneficial for the development of COPD treatments.
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Project description:BackgroundDrug repurposing provides a cost-effective approach to address the need for breast cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR) and then validate the candidate drugs using population-based analyses.MethodsWe identified genetic instruments for 1406 actionable targets of approved non-oncological drugs based on gene expression, DNA methylation, and protein expression quantitative trait loci (eQTL, mQTL, and pQTL, respectively). Genome-wide association study (GWAS) summary statistics were obtained from the Breast Cancer Association Consortium (122,977 cases, 105,974 controls). We further conducted a nested case-control study using data retrieved from Swedish registers to validate the candidate drugs that were identified from MR analyses.FindingsWe identified six significant MR associations with gene expression levels (TUBB, MDM2, CSK, ULK3, MC1R and KCNN4) and two significant associations with gene methylation levels across 21 CpG islands (RPS23 and MAPT). Results from the nested case-control study showed that the use of raloxifene (targeting MAPT) was associated with 35% reduced breast cancer risk (odds ratio, OR, 0.65; 95% confidence interval, CI, 0.51-0.83). However, usage of estradiol, tolterodine, and nitrofurantoin (also targeting MAPT) was associated with increased breast cancer risk, with adjusted ORs and 95% CI of 1.10 (1.07-1.13), 1.16 (1.09-1.24), and 1.09 (1.05-1.13), respectively. The effect of raloxifene and nitrofurantoin lost significance in further validation analyses using active-comparator and new-user design.InterpretationThis large-scale MR analysis, combined with population-based validation, identified eight druggable target genes for breast cancer and suggested that raloxifene is an effective chemoprevention against breast cancer.FundingSwedish Research Council, Cancerfonden, Crafoordska Stiftelsen, Allmänna Sjukhusets i Malmö Stiftelsen för bekämpande av cancer, 111 Project and MAS cancer.
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Project description:BackgroundAlzheimer's disease (AD) is the leading cause of dementia. Currently, there are no effective disease-modifying treatments for AD. Mendelian randomisation (MR) has been widely used to repurpose licensed drugs and discover novel therapeutic targets. Thus, we aimed to identify novel therapeutic targets for AD and analyse their pathophysiological mechanisms and potential side effects.MethodsA two-sample MR integrating the identified druggable genes was performed to estimate the causal effects of blood and brain druggable expression quantitative trait loci (eQTLs) on AD. A repeat study was conducted using different blood and brain eQTL data sources to validate the identified genes. Using AD markers with available genome-wide association studies data, we evaluated the causal relationship between established AD markers to explore possible mechanisms. Finally, the potential side effects of the druggable genes for AD treatment were assessed using a phenome-wide MR.ResultsOverall, 5883 unique druggable genes were aggregated; 33 unique potential druggable genes for AD were identified in at least one dataset (brain or blood), and 5 were validated in a different dataset. Among them, three prior druggable genes (epoxide hydrolase 2 (EPHX2), SERPINB1 and SIGLEC11) reached significant levels in both blood and brain tissues. EPHX2 may mediate the pathogenesis of AD by affecting the entire hippocampal volume. Further phenome-wide MR analysis revealed no potential side effects of treatments targeting EPHX2, SERPINB1 or SIGLEC11.ConclusionsThis study provides genetic evidence supporting the potential therapeutic benefits of targeting the three druggable genes for AD treatment, which will be useful for prioritising AD drug development.
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Project description:BackgroundMendelian randomization (MR) has been used to identify drug targets in many conditions. Height is a classic complex trait affected by genetic and early-life environmental factors. No systematic screening has been conducted to identify drugs that interact with height. We investigated the causal relationship between genes and height, and systematically screened for interactive drugs that may promote or delay growth.MethodsWe performed MR using summary statistics from the Genetic Investigation of ANthropometric Traits consortium (N=253,288), the UK Biobank (N=461,950), and the BioBank Japan Project (N=159,095). Gene expression-single-nucleotide polymorphism associations represented by cis-expression quantitative trait loci data were obtained from the Genotype-Tissue Expression study and were used as genetic instruments. We performed annotation and enrichment analyses of the genes. Interactive drugs were identified through drug-gene interactions.ResultsOf the 27,094 genes screened, 209 had causal associations with height, including genes associated with height and short stature phenotypes (AMZ1, GNA12, NPPC, UQCC1, and ZBTB38), genes associated with height in a few studies (ANKIB1, CEP250, DCAF16, HIST1H4E, and HLA-C), and genes without previous evidence (BTN2A2 and RBMS1P1). Enrichment analysis showed that transcriptional regulation by RUNX1 was the most enriched pathway. Interactive drugs were identified, including amoxicillin, atenolol, infliximab, colchicine, propionyl-L-carnitine, BMN-111, and tamoxifen, which were known to have a positive effect on height. We also identified drugs that had a negative effect on height, including antineoplastic drugs, corticosteroids, and antiepileptic drugs. Moreover, many interactive drugs have not been previously reported to be associated with height.ConclusionsOur results suggest that many genes have causal effects on height. By interrogating drug-gene interactions, interactive drugs have been identified as having both positive and negative effects on growth, which would help make clinical decisions.
| S-EPMC11621899 | biostudies-literature
Project description:There have been no new drugs for the treatment of schizophrenia in several decades and treatment resistance represents a major unmet clinical need. The drugs that exist are based on serendipitous clinical observations rather than an evidence-based understanding of disease pathophysiology. In the present review, we address these bottlenecks by integrating common, rare, and expression-related schizophrenia risk genes with knowledge of the druggability of the human genome as a whole. We highlight novel drug repurposing opportunities, clinical trial candidates which are supported by genetic evidence, and unexplored therapeutic opportunities in the lesser-known regions of the schizophrenia genome. By identifying translational gaps and opportunities across the schizophrenia disease space, we discuss a framework for translating increasingly well-powered genetic association studies into personalized treatments for schizophrenia and initiating the vital task of characterizing clinically relevant drug targets in underexplored regions of the human genome.
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Project description:BackgroundHeart failure (HF) is a prevalent cause of mortality and morbidity. The molecular drivers of HF are still largely unknown.ResultsWe aimed to identify circulating proteins causally associated with HF by leveraging genome-wide genetic association data for HF including 47,309 cases and 930,014 controls. We performed two-sample Mendelian randomization (MR) with multiple cis instruments as well as network and enrichment analysis using data from blood protein quantitative trait loci (pQTL) (2,965 blood proteins) measured in 3,301 individuals. Nineteen blood proteins were causally associated with HF, were not subject to reverse causality and were enriched in ligand-receptor and glycosylation molecules. Network pathway analysis of the blood proteins showed enrichment in NF-kappa B, TGF beta, lipid in atherosclerosis and fluid shear stress. Cross-phenotype analysis of HF identified genetic overlap with cardiovascular drugs, myocardial infarction, parental longevity and low-density cholesterol. Multi-trait MR identified causal associations between HF-associated blood proteins and cardiovascular outcomes. Multivariable MR showed that association of BAG3, MIF and APOA5 with HF were mediated by the blood pressure and coronary artery disease. According to the directional effect and biological action, 7 blood proteins are targets of existing drugs or are tractable for the development of novel therapeutics. Among the pathways, sialyl Lewis x and the activin type II receptor are potential druggable candidates.ConclusionsIntegrative MR analyses of the blood proteins identified causally-associated proteins with HF and revealed pleiotropy of the blood proteome with cardiovascular risk factors. Some of the proteins or pathway related mechanisms could be targeted as novel treatment approach in HF.
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