Genetic studies as a tool for identifying novel potential targets for treatment of COPD.
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ABSTRACT:
SUBMITTER: Manichaikul A
PROVIDER: S-EPMC5871433 | biostudies-literature | 2017 Nov
REPOSITORIES: biostudies-literature
Publications
Genetic studies as a tool for identifying novel potential targets for treatment of COPD.
Manichaikul Ani A Nguyen Jennifer N JN
The European respiratory journal 20171130 5
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Project description:Despite the status of chronic obstructive pulmonary disease (COPD) as a major global health problem, no currently available therapies can limit COPD progression. Therefore, an urgent need exists for the development of new and effective treatments for COPD. An improved understanding in the molecular pathogenesis of COPD can potentially identify molecular targets to facilitate the development of new therapeutic modalities. Among the best approaches for understanding the molecular basis of COPD include gene expression profiling techniques, such as serial analysis of gene expression or microarrays. Using these methods, recent studies have mapped comparative gene expression profiles of lung tissues from patients with different stages of COPD relative to healthy smokers or non-smokers. Such studies have revealed a number of differentially-regulated genes associated with COPD progression, which include genes involved in the regulation of inflammation, extracellular matrix, cytokines, chemokines, apoptosis, and stress responses. These studies have shed new light on the molecular mechanisms of COPD, and suggest novel targets for clinical treatments.
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Project description:BackgroundEndometriosis (EM) is a chronic painful condition that predominantly affects women of reproductive age. Currently, surgery or medication can only provide limited symptom relief. This study used a comprehensive genetic analytical approach to explore potential drug targets for EM in the plasma proteome.MethodsIn this study, 2,923 plasma proteins were selected as exposure and EM as outcome for two-sample Mendelian randomization (MR) analyses. The plasma proteomic data were derived from the UK Biobank Pharmaceutical Proteomics Project (UKB-PPP), while the EM dataset from the FinnGen consortium R10 release data. Several sensitivity analyses were performed, including summary-data-based MR (SMR) analyses, heterogeneity in dependent instruments (HEIDI) test, reverse MR analyses, steiger detection test, and bayesian co-localization analyses. Furthermore, proteome-wide association study (PWAS) and single-cell transcriptomic analyses were also conducted to validate the findings.ResultsSix significant (p < 3.06 × 10-5) plasma protein-EM pairs were identified by MR analyses. These included EPHB4 (OR = 1.40, 95% CI: 1.20 - 1.63), FSHB (OR = 3.91, 95% CI: 3.13 - 4.87), RSPO3 (OR = 1.60, 95% CI: 1.38 - 1.86), SEZ6L2 (OR = 1.44, 95% CI: 1.23 - 1.68) and WASHC3 (OR = 2.00, 95% CI: 1.54 - 2.59) were identified as risk factors, whereas KDR (OR = 0.80, 95% CI: 0.75 - 0.90) was found to be a protective factor. All six plasma proteins passed the SMR test (P < 8.33 × 10-3), but only four plasma proteins passed the HEIDI heterogeneity test (PHEIDI > 0.05), namely FSHB, RSPO3, SEZ6L2 and EPHB4. These four proteins showed strong evidence of co-localization (PPH4 > 0.7). In particular, RSPO3 and EPHB4 were replicated in the validated PWAS. Single-cell analyses revealed high expression of SEZ6L2 and EPHB4 in stromal and epithelial cells within EM lesions, while RSPO3 exhibited elevated expression in stromal cells and fibroblasts.ConclusionOur study identified FSHB, RSPO3, SEZ6L2, and EPHB4 as potential drug targets for EM and highlighted the critical role of stromal and epithelial cells in disease development. These findings provide new insights into the diagnosis and treatment of EM.
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Project description:Biological indicator and lung proteomics analyses were performed to identify potential therapeutic targets.
2024-07-27 | PXD054322 |
Project description:This study aimed to identify potential novel drug candidates and targets for Parkinson's disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR < 0.1 and their corresponding targets were identified. Some target genes of the ten drugs significantly overlapped with PD-related genes or already known therapeutic targets for PD. Nine differentially expressed drug-target genes with p < 0.05 were screened. This work will facilitate further research into the possible efficacy of new drugs for PD and will provide valuable clues for drug design.
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Project description:BackgroundAllergic rhinitis (AR) is a pervasive global health issue, and currently, there is a scarcity of targeted drug therapies available. This study aims to identify potential druggable target genes for AR using Mendelian randomization (MR) analysis.MethodsMR analysis was conducted to assess the causal effect of expression quantitative trait loci (eQTL) in the blood on AR. Data on AR were collected from 2 datasets: FinnGen(R9) (11,009 cases and 359,149 controls) and UK Biobank (25,486 cases and 87,097 controls). Colocalization analysis was utilized to assess the common causal genetic variations between the identified drug target genes and AR. We also employed available genome-wide association studies (GWAS) data to gauge the impact of druggable genes on AR biomarkers and other allergic diseases.ResultsThis study employs MR to analyze the relationship between 3410 druggable genes and AR. After Bonferroni correction, 10 genes were found to be significantly associated with AR risk (P < 0.05/3410). Colocalization analysis revealed a significant causal relationship between the expression variation of CFL1 and EFEMP2 genes and AR, sharing direct causal variants (colocalization probability PP.H3 + PP.H4 > 0.8), highlighting their importance as potential therapeutic targets for AR. The CFL1 gene showed a causal link with levels of thymic stromal lymphopoietin (TSLP), eosinophil count, and interleukin-13 (IL-13) (P = 0.016, 7.45E-16, 0.00091, respectively). EFEMP2 was also causally related to eosinophil count, IL-13, and interleukin-17 (IL-17) (P = 0.00012, 0.00091, 0.032, respectively). PheWAS analysis revealed significant associations of CFL1 with asthma, whereas EFEMP2 showed associations with both asthma and eczema. Protein-Protein Interaction (PPI) network analysis further unveiled the direct interactions of EFEMP2 and CFL1 with proteins related to immune regulation and inflammatory responses, with 77.64% of the network consisting of direct bindings, indicating their key roles in modulating AR-related immune and inflammatory responses. Notably, there was an 8.01% significant correlation between immune-related pathways and genes involved in inflammatory responses.ConclusionThese genes present notable associations with AR biomarkers and other autoimmune diseases, offering valuable targets for developing new AR therapies.
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Project description:BackgroundAdvanced stage/recurrent clear cell ovarian cancers (CCOCs) are characterized by a low response to chemotherapy and a poor prognosis. There is growing interest in investigating novel/molecular targeted therapies in patients with CCOC in histotype-specific trials. However, CCOCs are not a uniform entity and comprise a number of molecular subtypes and it is unlikely that a single approach to treatment will be appropriate for all patients. The aim of this study was to analyze the results of a multiplatform profiling panel in CCOCs to identify potential therapeutic targets.Patients and methodsTumor profiling was performed on 521 CCOCs. They were grouped into pure (n = 422) and mixed (n = 99) CCOC for analysis. Testing included a combination of DNA sequencing (including next-generation sequencing) using a 46-gene panel, immunohistochemistry, fluorescent or chromogenic in situ hybridization, and RNA fragment analysis.ResultsThe most common findings were in the PIK3CA/Akt/mTOR pathway, with 61% of all CCOCs showing a molecular alteration in one of these pathway components. Next-generation sequencing revealed PIK3CA mutations in 50% of pure CCOCs. Significant differences were observed between pure and mixed CCOCs with respect to hormone receptor expression (9% vs 34.7% for ER, 13.45 vs 26.4% for PR), cMET (24.1% vs 11.6%), PD-1 tumor infiltrating lymphocytes (48.1% vs 100%), expression of PD-L1 (7.4% vs 25%), and TOPO1 (41% vs 27.1%) on immunohistochemistry, whereas next-generation sequencing revealed significant differences in mutation frequency in PIK3CA (50% vs 18.5%), TP53 (18.1% vs 57.7%), KRAS (12.4% vs 3.7%), and cMET (1.9% vs 11.1%).ConclusionsThis large study confirms that the PIK3CA/Akt/mTOR pathway is commonly altered in CCOCs, and highlights the significant differences between pure and mixed CCOCs. Clear cell ovarian cancers are molecularly heterogeneous and there are a number of potential therapeutic targets which could be tested in clinical trials.
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