Identifying Novel Psoriatic Disease Drug Targets Using a Genetics-Based Priority Index Pipeline

Background: Despite numerous genome-wide association studies conducted in psoriasis and psoriatic arthritis, only a small fraction of the identified genes has been therapeutically targeted. Objective: We sought to identify and analyze potential therapeutic targets for psoriasis and psoriatic arthritis (PsA) using the priority index (Pi), a genetics-dependent drug target prioritization approach. Methods: Significant genetic variants from GWAS for psoriasis, PsA, and combined psoriatic disease were annotated and run through the Pi pipeline. Potential drug targets were identified based on genomic predictors, annotation predictors, pathway enrichment, and pathway crosstalk. Results: Several gene targets were identified for psoriasis and PsA that demonstrated biological associations to their respective diseases. Some are currently being explored as potential therapeutic targets (i.e. ICAM1, NF-kB, REV3 L, ADRA1B for psoriasis; CCL11 for PsA); others have not yet been investigated (i.e. LNPEP, LCE3 for psoriasis; UBLCP1 for PsA). Additionally, many nodal points of potential intervention were identified as promising therapeutic targets. Of these, some are currently being studied such as TYK2 for psoriasis, and others have yet to be explored (i.e. PPP2CA, YAP1, PI3 K, AKT, FOXO1, RELA, CSF2, IFNGR1, IFNGR2 for psoriasis; GNAQ, PLCB1, GNAI2 for PsA). Conclusion: Through Pi, we identified data-driven candidate therapeutic gene targets and pathways for psoriasis and PsA. Given the sparse PsA specific genetic studies and PsA specific drug targets, this analysis could prove to be particularly valuable in the pipeline for novel psoriatic therapies.

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Microbial Genome-Wide Association Studies: Lessons from Human GWAS

10.1101/093211 ◽

2016 ◽

Cited By ~ 4

Author(s):

Robert A. Power ◽

Julian Parkhill ◽

Tulio de Oliveira

Keyword(s):

Disease Transmission ◽

Drug Targets ◽

Association Studies ◽

Genome Wide Association ◽

Microbial Genome ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Disease Aetiology ◽

Number Of Microorganisms ◽

Potential Drug Targets

AbstractThe reduced costs of sequencing have led to the availability of whole genome sequences for a large number of microorganisms, enabling the application of microbial genome wide association studies (GWAS). Given the successes of human GWAS in understanding disease aetiology and identifying potential drug targets, microbial GWAS is likely to further advance our understanding of infectious diseases. By building on the success of GWAS, microbial GWAS have the potential to rapidly provide important insights into pressing global health problems, such as antibiotic resistance and disease transmission. In this review, we outline the methodologies of GWAS, the state of the field of microbial GWAS today, and how lessons from GWAS can direct the future of the field.

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The open targets post-GWAS analysis pipeline

Bioinformatics ◽

10.1093/bioinformatics/btaa020 ◽

2020 ◽

Vol 36 (9) ◽

pp. 2936-2937 ◽

Cited By ~ 4

Author(s):

Gareth Peat ◽

William Jones ◽

Michael Nuhn ◽

José Carlos Marugán ◽

William Newell ◽

...

Keyword(s):

Drug Targets ◽

Gene Expression Regulation ◽

Association Studies ◽

Genome Wide Association Studies ◽

Protein Coding ◽

Data Resource ◽

Coding Regions ◽

Genome Wide ◽

Causal Genes ◽

Interactive Data

Abstract Motivation Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug targets, i.e. causal protein-coding genes, therefore, requires crossing the genetics results with functional data. Results We present a novel data integration pipeline that analyses GWAS results in the light of experimental epigenetic and cis-regulatory datasets, such as ChIP-Seq, Promoter-Capture Hi-C or eQTL, and presents them in a single report, which can be used for inferring likely causal genes. This pipeline was then fed into an interactive data resource. Availability and implementation The analysis code is available at www.github.com/Ensembl/postgap and the interactive data browser at postgwas.opentargets.io.

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Genomics-driven drug discovery based on disease-susceptibility genes

Inflammation and Regeneration ◽

10.1186/s41232-021-00158-7 ◽

2021 ◽

Vol 41 (1) ◽

Author(s):

Kyuto Sonehara ◽

Yukinori Okada

Keyword(s):

Drug Discovery ◽

Drug Targets ◽

Disease Susceptibility ◽

Mendelian Randomization ◽

Association Studies ◽

Drug Repurposing ◽

Susceptibility Genes ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Disease Associations

AbstractGenome-wide association studies have identified numerous disease-susceptibility genes. As knowledge of gene–disease associations accumulates, it is becoming increasingly important to translate this knowledge into clinical practice. This challenge involves finding effective drug targets and estimating their potential side effects, which often results in failure of promising clinical trials. Here, we review recent advances and future perspectives in genetics-led drug discovery, with a focus on drug repurposing, Mendelian randomization, and the use of multifaceted omics data.

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Current Challenges in the Genetics of Psoriatic Arthritis: A Report from the GRAPPA 2009 Annual Meeting

The Journal of Rheumatology ◽

10.3899/jrheum.101123 ◽

2011 ◽

Vol 38 (3) ◽

pp. 564-566 ◽

Cited By ~ 2

Author(s):

PROTON RAHMAN

Keyword(s):

Psoriatic Arthritis ◽

Annual Meeting ◽

Association Studies ◽

Environment Interaction ◽

Genome Wide Association Studies ◽

Novel Genes ◽

Gene Environment Interaction ◽

Gene Environment ◽

Genome Wide

Psoriasis and psoriatic arthritis (PsA) are heterogeneous diseases. While both have a strong genetic basis, it is strongest for PsA, where fewer investigators are studying its genetics. Over the last year the number of independent genetic loci associated with psoriasis has substantially increased, mostly due to completion of multiple genome-wide association studies (GWAS) in psoriasis. At least 2 GWAS efforts are now under way in PsA to identify novel genes in this disease; a metaanalysis of genome-wide scans and further studies must follow to examine the genetics of disease expression, epistatic interaction, and gene-environment interaction. In the long term, it is anticipated that genome-wide sequencing is likely to generate another wave of novel genes in PsA. At the annual meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) in Stockholm, Sweden, in 2009, members discussed issues and challenges regarding the advancement of the genetics of PsA; results of those discussions are summarized here.

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Informing disease modelling with brain-relevant functional genomic annotations

Brain ◽

10.1093/brain/awz295 ◽

2019 ◽

Vol 142 (12) ◽

pp. 3694-3712 ◽

Cited By ~ 4

Author(s):

Regina H Reynolds ◽

John Hardy ◽

Mina Ryten ◽

Sarah A Gagliano Taliun

Keyword(s):

Genetic Association ◽

Association Studies ◽

Therapeutic Targets ◽

Genome Wide Association ◽

Disease Modelling ◽

Genome Wide Association Studies ◽

Functional Genomic ◽

Genome Wide ◽

Neuropsychiatric Diseases ◽

Association Data

How can we best translate the success of genome-wide association studies for neurological and neuropsychiatric diseases into therapeutic targets? Reynolds et al. critically assess existing brain-relevant functional genomic annotations and the tools available for integrating such annotations with summary-level genetic association data.

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Comment on ‘Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets’ by Lam et al.

Twin Research and Human Genetics ◽

10.1017/thg.2018.12 ◽

2018 ◽

Vol 21 (2) ◽

pp. 84-88 ◽

Cited By ~ 6

Author(s):

W. David Hill

Keyword(s):

Genetic Information ◽

Drug Targets ◽

Large Scale ◽

Association Studies ◽

Meta Analysis ◽

Genetic Correlations ◽

Data Sets ◽

Genome Wide Association Studies ◽

Nootropic Drug ◽

Genome Wide

Intelligence and educational attainment are strongly genetically correlated. This relationship can be exploited by Multi-Trait Analysis of GWAS (MTAG) to add power to Genome-wide Association Studies (GWAS) of intelligence. MTAG allows the user to meta-analyze GWASs of different phenotypes, based on their genetic correlations, to identify association's specific to the trait of choice. An MTAG analysis using GWAS data sets on intelligence and education was conducted by Lam et al. (2017). Lam et al. (2017) reported 70 loci that they described as ‘trait specific’ to intelligence. This article examines whether the analysis conducted by Lam et al. (2017) has resulted in genetic information about a phenotype that is more similar to education than intelligence.

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Biomarkers for Comorbidities in Psoriasis: A Report from the Grappa 2011 Annual Meeting

The Journal of Rheumatology ◽

10.3899/jrheum.120821 ◽

2012 ◽

Vol 39 (11) ◽

pp. 2193-2195 ◽

Cited By ~ 1

Author(s):

DAFNA D. GLADMAN

Keyword(s):

Psoriatic Arthritis ◽

Annual Meeting ◽

Research Team ◽

Association Studies ◽

Differentially Expressed ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Current Database ◽

And Cartilage

Biomarkers are being recognized that will help identify patients with psoriasis who may be destined to develop psoriatic arthritis (PsA). Recent genome-wide association studies have identified genes that are common to both psoriasis and PsA, as well as differentially expressed in the 2 conditions. Further, biomarkers of inflammation and cartilage can differentiate between patients with PsA and those with psoriasis without arthritis. An overview of these biomarkers was presented at the 2011 annual meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis. Additionally, a report was presented from the current database of the International Psoriasis and Psoriatic Arthritis Research Team, a group of dermatologists and rheumatologists with the objective to improve the lives of patients with psoriasis and PsA.

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Long Noncoding RNAs and Circular RNAs in Autoimmune Diseases

Biomolecules ◽

10.3390/biom10071044 ◽

2020 ◽

Vol 10 (7) ◽

pp. 1044 ◽

Cited By ~ 2

Author(s):

Valeria Lodde ◽

Giampaolo Murgia ◽

Elena Rita Simula ◽

Maristella Steri ◽

Matteo Floris ◽

...

Keyword(s):

Autoimmune Diseases ◽

Lupus Erythematosus ◽

Drug Targets ◽

Association Studies ◽

Genetic Regulation ◽

Response To Therapy ◽

Circular Rnas ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Substantial Progress

Immune responses are essential for the clearance of pathogens and the repair of injured tissues; however, if these responses are not properly controlled, autoimmune diseases can occur. Autoimmune diseases (ADs) are a family of disorders characterized by the body’s immune response being directed against its own tissues, with consequent chronic inflammation and tissue damage. Despite enormous efforts to identify new drug targets and develop new therapies to prevent and ameliorate AD symptoms, no definitive solutions are available today. Additionally, while substantial progress has been made in drug development for some ADs, most treatments only ameliorate symptoms and, in general, ADs are still incurable. Hundreds of genetic loci have been identified and associated with ADs by genome-wide association studies. However, the whole list of molecular factors that contribute to AD pathogenesis is still unknown. Noncoding (nc)RNAs, such as microRNAs, circular (circ)RNAs, and long noncoding (lnc)RNAs, regulate gene expression at different levels in various diseases, including ADs, and serve as potential drug targets as well as biomarkers for disease progression and response to therapy. In this review, we will focus on the potential roles and genetic regulation of ncRNA in four autoimmune diseases—systemic lupus erythematosus, rheumatoid arthritis, multiple sclerosis, and type 1 diabetes mellitus.

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Using functional genomics to advance the understanding of psoriatic arthritis

Rheumatology ◽

10.1093/rheumatology/keaa283 ◽

2020 ◽

Vol 59 (11) ◽

pp. 3137-3146

Author(s):

Chenfu Shi ◽

Magnus Rattray ◽

Anne Barton ◽

John Bowes ◽

Gisela Orozco

Keyword(s):

Psoriatic Arthritis ◽

Functional Genomics ◽

Complex Disease ◽

Association Studies ◽

Joint Damage ◽

Underlying Disease ◽

Genome Wide Association Studies ◽

Disease Mechanism ◽

Genome Wide ◽

Functional Mechanisms

Abstract Psoriatic arthritis (PsA) is a complex disease where susceptibility is determined by genetic and environmental risk factors. Clinically, PsA involves inflammation of the joints and the skin, and, if left untreated, results in irreversible joint damage. There is currently no cure and the few treatments available to alleviate symptoms do not work in all patients. Over the past decade, genome-wide association studies (GWAS) have uncovered a large number of disease-associated loci but translating these findings into functional mechanisms and novel targets for therapeutic use is not straightforward. Most variants have been predicted to affect primarily long-range regulatory regions such as enhancers. There is now compelling evidence to support the use of chromatin conformation analysis methods to discover novel genes that can be affected by disease-associated variants. Here, we will review the studies published in the field that have given us a novel understanding of gene regulation in the context of functional genomics and how this relates to the study of PsA and its underlying disease mechanism.

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Coverage Rate of ADME Genes: Application to CYP2C8, CYP2D6 and CYP3A Genes for Personalized Chloroquine Treatment Against Coronavirus

10.21203/rs.3.rs-22808/v1 ◽

2020 ◽

Author(s):

Nabil Zaid ◽

Loubna Khalki ◽

Imane Hadri ◽

Jihane Toughza ◽

Oussama Badad ◽

...

Keyword(s):

Drug Response ◽

Statistical Data ◽

Association Studies ◽

Therapeutic Targets ◽

Coverage Rate ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Chloroquine Treatment ◽

New Therapeutic Targets

Abstract Background: The latest studies have shown the effectiveness of Chloroquine against Coronavirus. However, since the tolerance and effectiveness of statistical data must be taken into account before proposing treatment to a patient, these promising results are often lacking.Since the CYP2C8, CYP2D6 and CYP3A Absorption, Distribution, Metabolism and Elimination (ADME) genes are involved in the drug response of Chloroquine, we are interested in studying the variations of these genes.Methods: The purpose of this study is to make a comparison between the various current genotyping and enrichment platforms, to know which of them allows the best coverage. Conclusions: This will allow us to carry out genome-wide association studies (GWAS) with the aim of finding new therapeutic targets against Coronavirus using Chloroquine.

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