Identification of therapeutic targets in osteoarthritis by combining heterogeneous transcriptional datasets, drug-induced expression profiles, and known drug-target interactions

Costa, Maria Claudia; Angelini, Claudia; Franzese, Monica; Iside, Concetta; Salvatore, Marco; Laezza, Luigi; Napolitano, Francesco; Ceccarelli, Michele

doi:10.1186/s12967-024-05006-z

Cited by 4 publications

(1 citation statement)

References 92 publications

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“…For example, patients with rheumatoid arthritis exhibit increased Flt3L levels in both serum and the synovial uid of in amed joints 98 . Moreover, DNER is associated with in ammation of articular cartilage 99 . This suggests that the genetic variant regulating APOBEC3G might simultaneously regulate its gene expression as well as the levels of Flt3L and DNER, thereby participating in the pathogenesis of SS.…”

Section: Discussionmentioning

confidence: 99%

Interplay of Interferon signalling gene expression, DNA Methylation, and inflammatory cytokines in Sjögren’s Syndrome: a multi-omics Mendelian randomization study

He,

Pang,

Shan

et al. 2024

Preprint

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Background Abnormal activation of the interferon (IFN) signalling plays a central role in the progression of Sjögren’s syndrome (SS). However, the causal relationship between IFN signalling and SS remains unclear, with complex interactions existing among genetic variants, epigenetic modifications, inflammatory cytokine levels, and the expression of IFN-associated genes. Thus, in order to reveal the potential causality and interaction mechanisms among IFN-associated gene expression, DNA methylation, inflammatory cytokines, and SS, our analysis was conducted using a multi-omics summary data-based Mendelian randomization (SMR) approach. Methods Genes associated with IFN signalling were extracted from the GeneCards database, and transcriptomic datasets for SS were obtained from the Gene Expression Omnibus (GEO) database. Linear regression models and meta-analysis identified IFN-associated differentially expressed genes (DEGs) in SS. Using a three-step SMR method, an integrated analysis of expression quantitative trait loci (eQTLs) and DNA methylation QTLs (mQTLs) with SS genome-wide association study (GWAS) from FinnGen was performed to reveal causal relationships between blood IFN-associated gene expression, DNA methylation, and SS pathogenesis. Then use SS GWAS data from UK Biobank for validation. Through colocalization analysis, integrating analysis of blood IFN-associated causal genes eQTLs with inflammatory cytokines GWAS was performed to identify potential interactions between blood IFN gene expression and inflammatory cytokines. Meanwhile, minor salivary gland (MSG) tissue eQTLs from GTEx V8 and SS GWAS were integrated by SMR to identify MSG IFN-associated causal genes. Through colocalization analysis, integrating analysis of MSG IFN-associated causal genes eQTLs with inflammatory cytokines GWAS was performed to identify potential interactions between IFN-associated causal gene expression in MSG and inflammatory cytokines. Results A total of 331 IFN-associated DEGs were identified by integrative analysis of three transcriptomic datasets and 711 IFN-associated genes. These DEGs are predominantly enriched in T-cells, macrophages, monocytes, and natural killer cells. Five blood IFN-associated genes: SH2B3, LGALS9, CD40, GRB2, and DTX3L, were identified as SS-causal genes using a three-step SMR approach. Three of these genes, LGALS9, SH2B3, and CD40, are involved in the interaction between gene expression and inflammatory cytokines through colocalization analysis. Furthermore, SMR and colocalization analysis also identified thirteen putative MSG IFN-associated genes, four of which were involved in gene–inflammatory cytokines interactions: APOBEC3G, IFI27L2, TMEM50B, and SH2B3. Conclusions This study uncovered a causal relationship between interferon signalling and SS, revealing complex interactions among IFN-associated causal gene expression, DNA methylation, and inflammatory cytokines in SS pathogenesis. This offers new evidence for the involvement of interferon signalling in the pathogenic process of SS and provides fresh insights into the interactions among epigenetic, genetic variants, and inflammatory cytokines for in-depth studies of pathogenesis and molecular mechanisms.

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Section: Discussionmentioning

confidence: 99%

Interplay of Interferon signalling gene expression, DNA Methylation, and inflammatory cytokines in Sjögren’s Syndrome: a multi-omics Mendelian randomization study

He,

Pang,

Shan

et al. 2024

Preprint

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Two heads are better than one: Unravelling the potential Impact of Artificial Intelligence in nanotechnology

Naik,

Jagtap

2024

Nano TransMed

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Transcriptome‐wide RNA m6A methylation profiles in an endemic osteoarthropathy, Kashin‐Beck disease

Zhang,

Yang,

Deng

et al. 2024

J Cellular Molecular Medi

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Kashin‐Beck disease (KBD) is a chronic degenerative, disabling disease of the bones and joints and its exact aetiology and pathogenesis remain uncertain. This study is to investigate the role of m6A modification in the pathogenesis of KBD. Combined analysis of m6A MeRIP‐Seq and RNA‐Seq were used to analyse human peripheral blood samples from three KBD patients and three normal controls (NC). Bioinformatic methods were used to analyse m6A‐modified differential genes and RT‐qPCR was performed to validate the mRNA expression of several KBD‐related genes. The results indicated that the total of 16,811 genes were modified by m6A in KBD group, of which 4882 genes were differential genes. A large number of differential genes were associated with regulation of transcription, signal transduction and protein binding. KEGG analysis showed that m6A‐enriched genes participated the pathways of Vitamin B6 metabolism, endocytosis and Rap 1 signalling pathway. There was a positive association between m6A abundance and levels of gene expression, that there were 6 hypermethylated and upregulated genes (hyper‐up), 23 hypomethylated and downregulated genes (hypo‐down) in KBD group compared with NC. In addition, the mRNA expression of levels of MMP8, IL32 and GPX1 were verified and the protein–protein interaction networks of these key factors were constructed. Our study showed that m6A modifications may play a vital role in modulating gene expression, which represents a new clue to reveal the pathogenesis of KBD.

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Identification of therapeutic targets in osteoarthritis by combining heterogeneous transcriptional datasets, drug-induced expression profiles, and known drug-target interactions

Cited by 4 publications

References 92 publications

Interplay of Interferon signalling gene expression, DNA Methylation, and inflammatory cytokines in Sjögren’s Syndrome: a multi-omics Mendelian randomization study

Interplay of Interferon signalling gene expression, DNA Methylation, and inflammatory cytokines in Sjögren’s Syndrome: a multi-omics Mendelian randomization study

Two heads are better than one: Unravelling the potential Impact of Artificial Intelligence in nanotechnology

Transcriptome‐wide RNA m6A methylation profiles in an endemic osteoarthropathy, Kashin‐Beck disease

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