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- Carlsson Almlöf, Jonas, et al.
(författare)
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Novel risk genes for systemic lupus erythematosus predicted by random forest classification
- 2017
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies have identified risk loci for SLE, but a large proportion of the genetic contribution to SLE still remains unexplained. To detect novel risk genes, and to predict an individual's SLE risk we designed a random forest classifier using SNP genotype data generated on the "Immunochip" from 1,160 patients with SLE and 2,711 controls. Using gene importance scores defined by the random forest classifier, we identified 15 potential novel risk genes for SLE. Of them 12 are associated with other autoimmune diseases than SLE, whereas three genes (ZNF804A, CDK1, and MANF) have not previously been associated with autoimmunity. Random forest classification also allowed prediction of patients at risk for lupus nephritis with an area under the curve of 0.94. By allele-specific gene expression analysis we detected cis-regulatory SNPs that affect the expression levels of six of the top 40 genes designed by the random forest analysis, indicating a regulatory role for the identified risk variants. The 40 top genes from the prediction were overrepresented for differential expression in B and T cells according to RNA-sequencing of samples from five healthy donors, with more frequent over-expression in B cells compared to T cells.
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| 2. |
- Diaz-Gallo, Lina-Marcela, et al.
(författare)
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Four Systemic Lupus Erythematosus Subgroups, Defined by Autoantibodies Status, Differ Regarding HLA-DRB1 Genotype Associations and Immunological and Clinical Manifestations
- 2022
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Ingår i: ACR Open Rheumatology. - : Wiley. - 2578-5745. ; 4:1, s. 27-39
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The heterogeneity of systemic lupus erythematosus (SLE) constitutes clinical and therapeutical challenges. We therefore studied whether unrecognized disease subgroups can be identified by using autoantibody profiling together with HLA-DRB1 alleles and immunological and clinical data.Methods: An unsupervised cluster analysis was performed based on detection of 13 SLE-associated autoantibodies (double-stranded DNA, nucleosomes, ribosomal P, ribonucleoprotein [RNP] 68, RNPA, Smith [Sm], Sm/RNP, Sjögren's syndrome antigen A [SSA]/Ro52, SSA/Ro60, Sjögren's syndrome antigen B [SSB]/La, cardiolipin [CL]-Immunoglobulin G [IgG], CL-Immunoglobulin M [IgM], and β2 glycoprotein I [β2 GPI]-IgG) in 911 patients with SLE from two cohorts. We evaluated whether each SLE subgroup is associated with HLA-DRB1 alleles, clinical manifestations (n = 743), and cytokine levels in circulation (n = 446).Results: Our analysis identified four subgroups among the patients with SLE. Subgroup 1 (29.3%) was dominated by anti-SSA/Ro60/Ro52/SSB autoantibodies and was strongly associated with HLA-DRB1*03 (odds ratio [OR] = 4.73; 95% confidence interval [CI] = 4.52-4.94). Discoid lesions were more common for this disease subgroup (OR = 1.71, 95% CI = 1.18-2.47). Subgroup 2 (28.7%) was dominated by anti-nucleosome/SmRNP/DNA/RNPA autoantibodies and associated with HLA-DRB1*15 (OR = 1.62, 95% CI = 1.41-1.84). Nephritis was most common in this subgroup (OR = 1.61, 95% CI = 1.14-2.26). Subgroup 3 (23.8%) was characterized by anti-ß2 GPI-IgG/anti-CL-IgG/IgM autoantibodies and a higher frequency of HLA-DRB1*04 compared with the other patients with SLE. Vascular events were more common in Subgroup 3 (OR = 1.74, 95% CI = 1.2-2.5). Subgroup 4 (18.2%) was negative for the investigated autoantibodies, and this subgroup was not associated with HLA-DRB1. Additionally, the levels of eight cytokines significantly differed among the disease subgroups.Conclusion: Our findings suggest that four fairly distinct subgroups can be identified on the basis of the autoantibody profile in SLE. These four SLE subgroups differ regarding associations with HLA-DRB1 alleles and immunological and clinical features, suggesting dissimilar disease pathways.
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| 3. |
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| 4. |
- Imgenberg-Kreuz, Juliana, et al.
(författare)
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DNA methylation mapping identifies gene regulatory effects in patients with systemic lupus erythematosus
- 2018
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 77:5, s. 736-743
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: Systemic lupus erythematosus (SLE) is a chronic autoimmune condition with heterogeneous presentation and complex aetiology where DNA methylation changes are emerging as a contributing factor. In order to discover novel epigenetic associations and investigate their relationship to genetic risk for SLE, we analysed DNA methylation profiles in a large collection of patients with SLE and healthy individuals.Methods: DNA extracted from blood from 548 patients with SLE and 587 healthy controls were analysed on the Illumina HumanMethylation 450 k BeadChip, which targets 485 000 CpG sites across the genome. Single nucleotide polymorphism (SNP) genotype data for 196 524 SNPs on the Illumina ImmunoChip from the same individuals were utilised for methylation quantitative trait loci (cis-meQTLs) analyses.Results: We identified and replicated differentially methylated CpGs (DMCs) in SLE at 7245 CpG sites in the genome. The largest methylation differences were observed at type I interferon-regulated genes which exhibited decreased methylation in SLE. We mapped cis-meQTLs and identified genetic regulation of methylation levels at 466 of the DMCs in SLE. The meQTLs for DMCs in SLE were enriched for genetic association to SLE, and included seven SLE genome-wide association study (GWAS) loci: PTPRC (CD45), MHC-class III, UHRF1BP1, IRF5, IRF7, IKZF3 and UBE2L3. In addition, we observed association between genotype and variance of methylation at 20 DMCs in SLE, including at the HLA-DQB2 locus.Conclusions: Our results suggest that several of the genetic risk variants for SLE may exert their influence on the phenotype through alteration of DNA methylation levels at regulatory regions of target genes.
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| 6. |
- Sandling, Johanna K., et al.
(författare)
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Molecular pathways in patients with systemic lupus erythematosus revealed by gene-centred DNA sequencing
- 2021
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 80:1, s. 109-117
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: Systemic lupus erythematosus (SLE) is an autoimmune disease with extensive heterogeneity in disease presentation between patients, which is likely due to an underlying molecular diversity. Here, we aimed at elucidating the genetic aetiology of SLE from the immunity pathway level to the single variant level, and stratify patients with SLE into distinguishable molecular subgroups, which could inform treatment choices in SLE. Methods: We undertook a pathway-centred approach, using sequencing of immunological pathway genes. Altogether 1832 candidate genes were analysed in 958 Swedish patients with SLE and 1026 healthy individuals. Aggregate and single variant association testing was performed, and we generated pathway polygenic risk scores (PRS). Results: We identified two main independent pathways involved in SLE susceptibility: T lymphocyte differentiation and innate immunity, characterised by HLA and interferon, respectively. Pathway PRS defined pathways in individual patients, who on average were positive for seven pathways. We found that SLE organ damage was more pronounced in patients positive for the T or B cell receptor signalling pathways. Further, pathway PRS-based clustering allowed stratification of patients into four groups with different risk score profiles. Studying sets of genes with priors for involvement in SLE, we observed an aggregate common variant contribution to SLE at genes previously reported for monogenic SLE as well as at interferonopathy genes. Conclusions: Our results show that pathway risk scores have the potential to stratify patients with SLE beyond clinical manifestations into molecular subsets, which may have implications for clinical follow-up and therapy selection.
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