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| http://dx.doi.org/10.1136/jmg.35.2.174-a | DOI Listing |
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Multi-omics analysis reveals novel causal pathways in psoriasis pathogenesis.
J Transl Med
January 2025
Department of Academic Research, The Second Hospital of Shandong University, Jinan, Shandong, China.
Background: To elucidate the genetic and molecular mechanisms underlying psoriasis by employing an integrative multi-omics approach, using summary-data-based Mendelian randomization (SMR) to infer causal relationships among DNA methylation, gene expression, and protein levels in relation to psoriasis risk.
Methods: We conducted SMR analyses integrating genome-wide association study (GWAS) summary statistics with methylation quantitative trait loci (mQTL), expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data. Publicly available datasets were utilized, including psoriasis GWAS data from the European Molecular Biology Laboratory-European Bioinformatics Institute and the UK Biobank.
Analysis of key lncRNA related to Parkinson's disease based on gene co-expression weight networks.
Neurosciences (Riyadh)
January 2025
From the School of Clinical Medicine (Liang, Luo, Jia), Shandong Second Medical University, Weifang, from the Department of Neurology (Liang, Zhao, Lin, Li, Luo, Jia) , Beijing Shijingshan Hospital, Shijingshan Teaching Hospital of Capital Medical University, Beijing, and from the Department of Neurology (Li), Affiliated Hospital of Weifang Medical University, Weifang, China.
Objectives: To identify a key Long chain non-coding RNAs (lncRNAs) related to PD and provide a new perspective on the role of LncRNAs in Parkinson's disease (PD) pathophysiology.
Methods: Our study involved analyzing gene chips from the substantia nigra and white blood cells, both normal and PD-inclusive, in the Gene Expression Omnibus (GEO) database, utilizing a weighted gene co-expression network analysis (WGCNA). The technique of WGCNA facilitated the examination of differentially expressed genes (DEGs) in the substantia nigra and the white blood cells of individuals with PD.
Clinical significance of a new early diagnostic model for bladder cancer based on genome-wide microarray profiling of serum exosomal lncRNAs.
Int Urol Nephrol
January 2025
Department of Nuclear Medicine, Linyi People's Hospital, Shandong Second Medical University, 27 Jiefang Road, Linyi, 276003, Shandong, China.
Purpose: The aim of our report was to recognize bladder cancer (BC)-specific serum exosome-derived long non-coding RNAs (lncRNAs) profile for early diagnosis of BC.
Methods: Potential BC-specific exosomal lncRNA indicators were discerned by genome-wide microarray profiling analysis of serum exosomes from 10 healthy participants and 10 early stage BC patients (Ta and T1), followed by multi-stage validation through quantitative real-time PCR (qRT-PCR) in BC cells, culture solution as well as 200 serum specimens and 50 tissue specimens from non-muscle-invasive bladder cancer (NMIBC) patients. The diagnostic panel was established using logistic regression and evaluated by receiver-operating characteristic (ROC) curve.
Long noncoding RNAs are emerging as critical regulators of biological processes. While there are over 20,000 lncRNAs annotated in the human genome we do not know the function for the majority. Here we performed a high-throughput CRISPRi screen to identify those lncRNAs that are important in viability in human monocytes using the cell line THP1.
View Article and Find Full Text PDFA pyroptosis-related lncRNA risk model for the prediction of prognosis and immunotherapy response in head and neck squamous cell carcinoma.
Front Oncol
November 2024
Department of Otorhinolaryngology, Head and Neck Surgery, The Second Affiliated Hospital, Harbin Medical University, Harbin, China.
Background: Recent research has highlighted pyroptosis as a key factor in cancer progression. This study aims to explore the association between pyroptosis-related signatures and overall survival (OS) in head and neck squamous cell carcinoma (HNSC) and develop a pyroptosis-related long non-coding RNA (lncRNA) risk model to predict prognosis and response to immunotherapy in HNSC.
Methods: We extracted expression data for 18 pyroptosis-related genes and identified lncRNA probes specific to HNSC by using datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA).
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