Multi-omics analysis reveals novel causal pathways in psoriasis pathogenesis
Abstract 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...
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BMC
2025-01-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-025-06099-w |
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| author | Hua Guo Jinyang Gao Liping Gong Yanqing Wang |
| author_facet | Hua Guo Jinyang Gao Liping Gong Yanqing Wang |
| author_sort | Hua Guo |
| collection | DOAJ |
| description | Abstract 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. Heterogeneity in dependent instruments (HEIDI) test and colocalization analyses were performed to identify shared causal variants, and multi-omics integration was employed to construct potential regulatory pathways. Results Our analyses identified significant causal associations between DNA methylation, gene expression, protein abundance, and psoriasis risk. We discovered two pathways involving the long non-coding RNA RP11-977G19.11 and apolipoprotein F (APOF). Methylation at sites cg26804944 and cg02705573 was negatively associated with RP11-977G19.11 expression. Reduced expression of RP11-977G19.11 was linked to increased APOF levels, which were positively associated with a higher risk of psoriasis. Methylation at sites cg00172967, cg00294382, and cg24773560 was positively associated with RP11-977G19.11 expression. Elevated expression of RP11-977G19.11 was associated with decreased APOF levels, reducing the risk of psoriasis. Colocalization analysis highlighted APOF as a key protein in psoriasis pathogenesis. Validation using skin tissue, EBV-transformed lymphocytes data and inflammation-related protein panels confirmed the associations of RP11-977G19.11 and APOF with psoriasis. Conclusions Our multi-omics analysis provides preliminary evidence for potential molecular mechanisms in psoriasis pathogenesis. Through the integration of GWAS and molecular QTL data, we identify candidate pathways that may be relevant to disease biology. While these findings require extensive experimental validation, they offer a framework for future investigations into the molecular basis of psoriasis. |
| format | Article |
| id | doaj-art-e36efb67a8124e85ad0369688112b425 |
| institution | Kabale University |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-e36efb67a8124e85ad0369688112b4252025-01-26T12:50:23ZengBMCJournal of Translational Medicine1479-58762025-01-0123111310.1186/s12967-025-06099-wMulti-omics analysis reveals novel causal pathways in psoriasis pathogenesisHua Guo0Jinyang Gao1Liping Gong2Yanqing Wang3Department of Academic Research, The Second Hospital of Shandong UniversitySchool of Basic Medical Sciences, Cheeloo College of Medicine, Shandong UniversityDepartment of Academic Research, The Second Hospital of Shandong UniversityDepartment of Academic Research, The Second Hospital of Shandong UniversityAbstract 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. Heterogeneity in dependent instruments (HEIDI) test and colocalization analyses were performed to identify shared causal variants, and multi-omics integration was employed to construct potential regulatory pathways. Results Our analyses identified significant causal associations between DNA methylation, gene expression, protein abundance, and psoriasis risk. We discovered two pathways involving the long non-coding RNA RP11-977G19.11 and apolipoprotein F (APOF). Methylation at sites cg26804944 and cg02705573 was negatively associated with RP11-977G19.11 expression. Reduced expression of RP11-977G19.11 was linked to increased APOF levels, which were positively associated with a higher risk of psoriasis. Methylation at sites cg00172967, cg00294382, and cg24773560 was positively associated with RP11-977G19.11 expression. Elevated expression of RP11-977G19.11 was associated with decreased APOF levels, reducing the risk of psoriasis. Colocalization analysis highlighted APOF as a key protein in psoriasis pathogenesis. Validation using skin tissue, EBV-transformed lymphocytes data and inflammation-related protein panels confirmed the associations of RP11-977G19.11 and APOF with psoriasis. Conclusions Our multi-omics analysis provides preliminary evidence for potential molecular mechanisms in psoriasis pathogenesis. Through the integration of GWAS and molecular QTL data, we identify candidate pathways that may be relevant to disease biology. While these findings require extensive experimental validation, they offer a framework for future investigations into the molecular basis of psoriasis.https://doi.org/10.1186/s12967-025-06099-wPsoriasisMulti-omicsMendelian randomizationDNA methylationGene expressionProtein levels |
| spellingShingle | Hua Guo Jinyang Gao Liping Gong Yanqing Wang Multi-omics analysis reveals novel causal pathways in psoriasis pathogenesis Journal of Translational Medicine Psoriasis Multi-omics Mendelian randomization DNA methylation Gene expression Protein levels |
| title | Multi-omics analysis reveals novel causal pathways in psoriasis pathogenesis |
| title_full | Multi-omics analysis reveals novel causal pathways in psoriasis pathogenesis |
| title_fullStr | Multi-omics analysis reveals novel causal pathways in psoriasis pathogenesis |
| title_full_unstemmed | Multi-omics analysis reveals novel causal pathways in psoriasis pathogenesis |
| title_short | Multi-omics analysis reveals novel causal pathways in psoriasis pathogenesis |
| title_sort | multi omics analysis reveals novel causal pathways in psoriasis pathogenesis |
| topic | Psoriasis Multi-omics Mendelian randomization DNA methylation Gene expression Protein levels |
| url | https://doi.org/10.1186/s12967-025-06099-w |
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