Multiple Changes of Gene Expression and Function Reveal Genomic and Phenotypic Complexity in SLE-like Disease

Wilbe, Maria; Kozyrev, Sergey V.; Farias, Fabiana H.G.; Bremer, Hanna; Hedlund, Anna; Pielberg, Gerli; Seppälä, Eija H.; Gustafson, Ulla; Lohi, Hannes; Carlborg, Örjan; Andersson, Gerhard; Hansson-Hamlin, Helene; Lindblad‐Toh, Kerstin

doi:10.1371/journal.pgen.1005248

Cited by 25 publications

(16 citation statements)

References 74 publications

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“…To screen for functional relationships among the vitiligo candidate genes, we carried out pathway analysis of the protein products of all positional candidate genes at all 48 confirmed loci and the seven suggestive loci using g:PROFILER 10 , PANTHER 11 , and STRING 12 . To assess enrichment of association signals in different functional genomic categories contributing to vitiligo heritability, we applied stratified LD score regression 51 to the combined CMH GWAS123 summary statistics.…”

Section: Methodsmentioning

confidence: 99%

“…Considering proteins encoded at the 23 newly confirmed vitiligo candidate loci, at least twelve (CTLA4, TICAM1, PTPRC, FARP2, UBE2E2, NRROS, CPVL, ARID5B, PTPN1, TNFSF11, TNFRSF11A, IRF3, and perhaps also IL1RAPL1) play roles in immune regulation, and PPP3CA may regulate FOXP3 via NFATC2 and is associated with canine lupus 12 . Six (FASLG, BCL2L11, BCL2L12, SERPINB9, NEK6, BAD) are regulators of apoptosis, particularly involving immune cells.…”

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confidence: 99%

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Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants

et al. 2016

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Vitiligo is an autoimmune disease in which depigmented skin results from destruction of melanocytes1, with epidemiologic association with other autoimmune diseases2. In previous linkage and genome-wide association studies (GWAS1, GWAS2), we identified 27 vitiligo susceptibility loci in patients of European (EUR) ancestry. We carried out a third GWAS (GWAS3) in EUR subjects, with augmented GWAS1 and GWAS2 controls, genome-wide imputation, and meta-analysis of all three GWAS, followed by an independent replication. The combined analyses, with 4,680 cases and 39,586 controls, identified 23 new loci and 7 suggestive loci, most encoding immune and apoptotic regulators, some also associated with other autoimmune diseases, as well as several melanocyte regulators. Bioinformatic analyses indicate a predominance of causal regulatory variation, some corresponding to eQTL at these loci. Together, the identified genes provide a framework for vitiligo genetic architecture and pathobiology, highlight relationships to other autoimmune diseases and melanoma, and offer potential targets for treatment.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants

et al. 2016

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“…were enhanced, PPP3CA gene acts in the downstream of BCR via MAPK signaling pathway, was also had a higher expression in CaN®NEAF, KEGG module in SLE patients. Similarly, the strong association of PPP3CA with SLE-like disease has been described as newly [57]. The transcription factor AP-1…”

Section: Discussionmentioning

confidence: 93%

An integrative Bayesian network approach to highlight key drivers in systemic lupus erythematosus

Maleknia

Salehi

Sharifi‐Zarchi

et al. 2020

Preprint

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Background: To perceive a comprehensive illustration of the systemic lupus erythematosus (SLE), as a complex and multifactorial disease, draw a biological challenge. Dealing with this challenge needs employing sophisticated bioinformatics algorithms to discover the unknown aspects. This study aimed to distinguish key molecular characteristics of SLE pathogenesis, which may serve as effective targets for therapeutic intervention. Methods: In the present study, six gene expression microarray datasets included SLE patients (n=220) and healthy controls (n=135) were collected. We integrated the datasets by cross-platform normalization. Subsequently, through BNrich method, the structures of Bayesian networks (BNs) were extracted from SLE, TCR and BCR signaling pathways and the parameters of BNs were estimated using integrated datasets. Finally, a meta-analysis was performed to distinguish the signaling pathways alterations in the SLE pathogenesis. Results: We identified the most dysregulated genes involved in the clearance mechanism (most inhibition in MACROH2A2 and H4C9, most activation in SNRPD3, MACROH2A1 and RO60). Augmented autoantigens presentation by MHCII (HLA-DQA1, HLA-DOB and HLA-DPB1) and CD80 and CD86 to CD28 biological functions were also observed. The increased expression of FCGR1A, C8G, C7 and C9 genes and decreasing biological functions in edges from C1R and C1S to C2 and from C1R to C4B, all involved in end-organ damage, were detected. On the other hand, many of subnetworks alterations of TCR and BCR reported in previous research (PI3K/AKT, MAPK, AP-1 transcription factor). Conclusions: Overall, the BNrich as a hybridized network construction method, which integrates intergenic relations inferred from signaling pathways and gene expression profiling, can be employed to study complex diseases. Here we applied BNrich and highlighted significant genes and intergenic relationships and systemic alterations in SLE, TCR and BCR signaling pathways.

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“…These results suggested that the highly co-expressed genes in the same module have potential biological significance [ 6 ]. Each module might represent specific clinical features of RC patients [ 3 , 22 ].…”

Section: Resultsmentioning

confidence: 99%

Identification of two novel biomarkers of rectal carcinoma progression and prognosis via co-expression network analysis

Sun

et al. 2017

Oncotarget

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mRNA expression profiles provide important insights on a diversity of biological processes involved in rectal carcinoma (RC). Our aim was to comprehensively map complex interactions between the mRNA expression patterns and the clinical traits of RC. We employed the integrated analysis of five microarray datasets and The Cancer Genome Atlas rectal adenocarcinoma database to identify 2118 consensual differentially expressed genes (DEGs) in RC and adjacent normal tissue samples, and then applied weighted gene co-expression network analysis to parse DEGs and eight clinical traits in 66 eligible RC samples. A total of 16 co-expressed gene modules were identified. The green-yellow and salmon modules were most appropriate to the pathological stage (R = 0.36) and the overall survival (HR =13.534, P = 0.014), respectively. A diagnostic model of the five pathological stage hub genes (SCG3, SYP, CDK5R2, AP3B2, and RUNDC3A) provided a powerful classification accuracy between localized RC and non-localized RC. We also found increased Secretogranin III (SCG3) expression with higher pathological stage and poorer prognosis in the test and validation set. The increased Homer scaffolding protein 2 (HOMER2) expression with the favorable survival prediction efficiency significantly correlated with the markedly reduced overall survival of RC patients and the higher pathological stage during the test and validation set. Our findings indicate that the SCG3 and HOMER2 mRNA levels should be further evaluated as predictors of pathological stage and survival in patients with RC.

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Multiple Changes of Gene Expression and Function Reveal Genomic and Phenotypic Complexity in SLE-like Disease

Cited by 25 publications

References 74 publications

Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants

Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants

An integrative Bayesian network approach to highlight key drivers in systemic lupus erythematosus

Identification of two novel biomarkers of rectal carcinoma progression and prognosis via co-expression network analysis

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