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 3 publications

(1 citation statement)

References 91 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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Mendelian randomization analysis identified potential genes pleiotropically associated with gout

Wang,

Chen,

Yao

et al. 2024

Front. Genet.

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BackgroundThis study aims to prioritize genes potentially involved in multifactorial or causal relationships with gout.MethodsUsing the Summary Data-based Mendelian Randomization (SMR) approach, this research analyzed expression quantitative trait loci (eQTL) data from blood and renal tissues and genome-wide association study (GWAS) data related to gout. It sought to identify genetic loci potentially involved in gout. Heterogeneity testing was conducted with the HEIDI test, and results were adjusted for the False Discovery Rate (FDR). Blood cis-eQTL data were sourced from the eQTLGen Consortium’s summary-level data, and renal tissue data came from the V8 release of the GTEx eQTL summary data. Gout GWAS data was sourced from the FinnGen Documentation of the R10 release.ResultSMR analysis identified 14 gene probes in the eQTLGen blood summary-level data significantly associated with gout. The top five ranked genes are: ENSG00000169231 (labeled THBS3, PSMR = 4.16 × 10−13), ENSG00000231064 (labeled THBS3-AS1, PSMR = 1.88 × 10−8), ENSG00000163463 (labeled KRTCAP2, PSMR = 3.88 × 10−6), ENSG00000172977 (labeled KAT5, PSMR = 1.70 × 10−5), and ENSG00000161395 (labeled PGAP3, PSMR = 3.24 × 10−5). Notably, increased expression of KRTCAP2 and PGAP3 is associated with an increased risk of gout, whereas increased expression of THBS3, THBS3-AS1, and KAT5 is associated with a reduced gout risk. No significant gene associations with gout were observed in renal tissue, likely due to the limited sample size of kidney tissue.ConclusionOur findings have highlighted several genes potentially involved in the pathogenesis of gout. These results offer valuable insights into the mechanisms of gout and identify potential therapeutic targets for its treatment.

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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 3 publications

References 91 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

Mendelian randomization analysis identified potential genes pleiotropically associated with gout

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