Functional Genomics in Psoriasis Rossi, Stefano; Richards, Ellie Louise; Orozco, Gisela ...
International journal of molecular sciences,
07/2024, Letnik:
25, Številka:
13
Journal Article
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Psoriasis is an autoimmune cutaneous condition that significantly impacts quality of life and represents a burden on society due to its prevalence. Genome-wide association studies (GWASs) have ...pinpointed several psoriasis-related risk loci, underlining the disease’s complexity. Functional genomics is paramount to unveiling the role of such loci in psoriasis and disentangling its complex nature. In this review, we aim to elucidate the main findings in this field and integrate our discussion with gold-standard techniques in molecular biology—i.e., Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)—and high-throughput technologies. These tools are vital to understanding how disease risk loci affect gene expression in psoriasis, which is crucial in identifying new targets for personalized treatments in advanced precision medicine.
Susceptibility to rheumatic diseases, such as osteoarthritis, rheumatoid arthritis, ankylosing spondylitis, systemic lupus erythematosus, juvenile idiopathic arthritis and psoriatic arthritis, ...includes a large genetic component. Understanding how an individual's genetic background influences disease onset and outcome can lead to a better understanding of disease biology, improved diagnosis and treatment, and, ultimately, to disease prevention or cure. The past decade has seen great progress in the identification of genetic variants that influence the risk of rheumatic diseases. The challenging task of unravelling the function of these variants is ongoing. In this Review, the major insights from genetic studies, gained from advances in technology, bioinformatics and study design, are discussed in the context of rheumatic disease. In addition, pivotal genetic studies in the main rheumatic diseases are highlighted, with insights into how these studies have changed the way we view these conditions in terms of disease overlap, pathways of disease and potential new therapeutic targets. Finally, the limitations of genetic studies, gaps in our knowledge and ways in which current genetic knowledge can be fully translated into clinical benefit are examined.
Genome-wide association studies have reported more than 100 risk loci for rheumatoid arthritis (RA). These loci are shown to be enriched in immune cell-specific enhancers, but the analysis so far has ...excluded stromal cells, such as synovial fibroblasts (FLS), despite their crucial involvement in the pathogenesis of RA. Here we integrate DNA architecture, 3D chromatin interactions, DNA accessibility, and gene expression in FLS, B cells, and T cells with genetic fine mapping of RA loci.
We identify putative causal variants, enhancers, genes, and cell types for 30-60% of RA loci and demonstrate that FLS account for up to 24% of RA heritability. TNF stimulation of FLS alters the organization of topologically associating domains, chromatin state, and the expression of putative causal genes such as TNFAIP3 and IFNAR1. Several putative causal genes constitute RA-relevant functional networks in FLS with roles in cellular proliferation and activation. Finally, we demonstrate that risk variants can have joint-specific effects on target gene expression in RA FLS, which may contribute to the development of the characteristic pattern of joint involvement in RA.
Overall, our research provides the first direct evidence for a causal role of FLS in the genetic susceptibility for RA accounting for up to a quarter of RA heritability.
Whilst susceptibility variants for many complex diseases, such as rheumatoid arthritis (RA), have been well characterised, the mechanism by which risk is mediated is still unclear for many loci. This ...is especially true for the majority of variants that do not affect protein-coding regions. lncRNA represent a group of molecules that have been shown to be enriched amongst variants associated with RA and other complex diseases, compared to random variants. In order to establish to what degree direct disruption of lncRNA may represent a potential mechanism for mediating RA susceptibility, we chose to further explore this overlap. By testing the ability of annotated features to improve a model of disease susceptibility, we were able to demonstrate a local enrichment of enhancers from immune-relevant cell types amongst RA susceptibility variants (log2 enrichment 3.40). This was not possible for lncRNA annotations in general, however a small, but significant enrichment was observed for immune-enriched lncRNA (log2 enrichment 0.867002). This enrichment was no longer apparent when the model was conditioned on immune-relevant enhancers (log2 enrichment -0.372734), suggesting that direct disruption of lncRNA sequence, independent of enhancer disruption, does not represent a major mechanism by which susceptibility to complex diseases is mediated. Furthermore, we demonstrated that, in keeping with general lncRNA characteristics, immune-enriched lncRNA are expressed at low levels that may not be amenable to functional characterisation.
Since 2005, thousands of genome-wide association studies (GWAS) have been published, identifying hundreds of thousands of genetic variants that increase risk of complex traits such as autoimmune ...diseases. This wealth of data has the potential to improve patient care, through personalized medicine and the identification of novel drug targets. However, the potential of GWAS for clinical translation has not been fully achieved yet, due to the fact that the functional interpretation of risk variants and the identification of causal variants and genes are challenging. The past decade has seen the development of great advances that are facilitating the overcoming of these limitations, by utilizing a plethora of genomics and epigenomics tools to map and characterize regulatory elements and chromatin interactions, which can be used to fine map GWAS loci, and advance our understanding of the biological mechanisms that cause disease.
There is a need to identify effective treatments for rheumatic diseases, and while genetic studies have been successful it is unclear which genes contribute to the disease. Using our existing Capture ...Hi-C data on three rheumatic diseases, we can identify potential causal genes which are targets for existing drugs and could be repositioned for use in rheumatic diseases.
High confidence candidate causal genes were identified using Capture Hi-C data from B cells and T cells. These genes were used to interrogate drug target information from DrugBank to identify existing treatments, which could be repositioned to treat these diseases. The approach was refined using Ingenuity Pathway Analysis to identify enriched pathways and therefore further treatments relevant to the disease.
Overall, 454 high confidence genes were identified. Of these, 48 were drug targets (108 drugs) and 11 were existing therapies used in the treatment of rheumatic diseases. After pathway analysis refinement, 50 genes remained, 13 of which were drug targets (33 drugs). However considering targets across all enriched pathways, a further 367 drugs were identified for potential repositioning.
Capture Hi-C has the potential to identify therapies which could be repositioned to treat rheumatic diseases. This was particularly successful for rheumatoid arthritis, where six effective, biologic treatments were identified. This approach may therefore yield new ways to treat patients, enhancing their quality of life and reducing the economic impact on healthcare providers. As additional cell types and other epigenomic data sets are generated, this prospect will improve further.
Despite the success of TNF-inhibitor therapy in rheumatoid arthritis treatment, up to 40% of patients fail to respond adequately. This study aimed to identify transcriptome-based biomarkers of ...adalimumab response in rheumatoid arthritis (RA) to aid timely switching in non-responder patients and provide a better mechanistic understanding of the pathways involved in response/non-response.
The Affymetrix Human Transcriptome Array 2.0 (HTA) was used to measure the transcriptome in whole blood at pre-treatment and at 3 months in EULAR good- and non-responders to adalimumab therapy. Differential expression of transcripts was analysed at the transcript level using multiple linear regression. Differentially expressed genes were validated in independent samples using OpenArray™ RT-qPCR.
In total, 813 transcripts were differentially expressed between pre-treatment and 3 months in adalimumab good-responders. No significant differential expression was observed between good- and non-responders at either time-point and no significant changes were observed in non-responders between time-points. OpenArray™ RT-qPCR was performed for 104 differentially expressed transcripts in good-responders, selected based on magnitude of effect or p value or based on prior association with RA or the immune system, validating differential expression for 17 transcripts.
An early transcriptome signature of DAS28 response to adalimumab has been identified and replicated in independent datasets. Whilst treat-to-target approaches encourage early switching in non-responsive patients, registry evidence suggests that this does not always occur. The results herein could guide the development of a blood test to distinguish responders from non-responders at 3 months and support clinical decisions to switch non-responsive patients to an alternative therapy.
Genome sequencing has revealed over 300 million genetic variations in human populations. Over 90% of variants are single nucleotide polymorphisms (SNPs), the remainder include short deletions or ...insertions, and small numbers of structural variants. Hundreds of thousands of these variants have been associated with specific phenotypic traits and diseases through genome wide association studies which link significant differences in variant frequencies with specific phenotypes among large groups of individuals. Only 5% of disease-associated SNPs are located in gene coding sequences, with the potential to disrupt gene expression or alter of the function of encoded proteins. The remaining 95% of disease-associated SNPs are located in non-coding DNA sequences which make up 98% of the genome. The role of non-coding, disease-associated SNPs, many of which are located at considerable distances from any gene, was at first a mystery until the discovery that gene promoters regularly interact with distal regulatory elements to control gene expression. Disease-associated SNPs are enriched at the millions of gene regulatory elements that are dispersed throughout the non-coding sequences of the genome, suggesting they function as gene regulation variants. Assigning specific regulatory elements to the genes they control is not straightforward since they can be millions of base pairs apart. In this review we describe how understanding 3D genome organization can identify specific interactions between gene promoters and distal regulatory elements and how 3D genomics can link disease-associated SNPs to their target genes. Understanding which gene or genes contribute to a specific disease is the first step in designing rational therapeutic interventions.
Evidence is beginning to emerge that there may be susceptibility loci for rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) that are common to both diseases.
To investigate single ...nucleotide polymorphisms that have been reported to be associated with SLE in a UK cohort of patients with RA and controls.
3962 patients with RA and 9275 controls were included in the study. Eleven SNPs mapping to confirmed SLE loci were investigated. These mapped to the TNFSF4, BANK1, TNIP1, PTTG1, UHRF1BP1, ATG5, JAZF1, BLK, KIAA1542, ITGAM and UBE2L3 loci. Genotype frequencies were compared between patients with RA and controls using the trend test.
The SNPs mapping to the BLK and UBE2L3 loci showed significant evidence for association with RA. Two other SNPs, mapping to ATG5 and KIAA1542, showed nominal evidence for association with RA (p=0.02 and p=0.02, respectively) but these were not significant after applying a Bonferroni correction. Additionally, a significant global enrichment in carriage of SLE alleles in patients with RA compared with controls (p=9.1×10(-7)) was found. Meta-analysis of this and previous studies confirmed the association of the BLK and UBE2L3 gene with RA at genome-wide significance levels (p<5×10(-8)). Together, the authors estimate that the SLE and RA overlapping loci, excluding HLA-DRB1 alleles, identified so far explain ∼5.8% of the genetic susceptibility to RA as a whole.
The findings confirm the association of the BLK and UBE2L3 loci with RA, thus adding to the list of loci showing overlap between RA and SLE.
Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in ...any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. Transcriptome-wide study of TNF-inhibitor therapy in rheumatoid arthritis reveals early signature of successful treatment RAW_REF_TEXT James Oliver1 na1, /RAW_REF_TEXT RAW_REF_TEXT Nisha Nair1 na1, /RAW_REF_TEXT RAW_REF_TEXT Gisela Orozco1, /RAW_REF_TEXT RAW_REF_TEXT Samantha Smith1, /RAW_REF_TEXT RAW_REF_TEXT Kimme L. Hyrich2,3, /RAW_REF_TEXT RAW_REF_TEXT Ann Morgan4, /RAW_REF_TEXT RAW_REF_TEXT John Isaacs5,6, /RAW_REF_TEXT RAW_REF_TEXT Anthony G. Wilson7, /RAW_REF_TEXT RAW_REF_TEXT BRAGGSS, /RAW_REF_TEXT RAW_REF_TEXT Anne Barton1,2 na2 & /RAW_REF_TEXT RAW_REF_TEXT Darren Plant 1,2 na2 /RAW_REF_TEXT Arthritis Research & Therapy volume 23, Article number: 139 (2021) Cite this article RAW_REF_TEXT 107 Accesses /RAW_REF_TEXT RAW_REF_TEXT 1 Altmetric /RAW_REF_TEXT RAW_REF_TEXT Metrics details /RAW_REF_TEXT The Original Article was published on 10 March 2021 Correction to: Transcriptome-wide study of TNF-inhibitor therapy in rheumatoid arthritis reveals early signature of successful treatment RAW_REF_TEXT James Oliver1 na1, Nisha Nair1 na1, Gisela Orozco1, Samantha Smith1, Kimme L. Hyrich2,3, Ann Morgan4, John Isaacs5,6, Anthony G. Wilson7, BRAGGSS, Anne Barton1,2 na2 & Darren Plant 1,2 na2 /RAW_REF_TEXT Arthritis Research & Therapy volume 23, Article number: 139 (2021) Cite this article RAW_REF_TEXT 107 Accesses 1 Altmetric Metrics details
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