| 1. |
- Abelson, Anna-Karin, et al.
(författare)
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STAT4 Associates with SLE through two independent effects that correlate with gene expression and act additively with IRF5 to increase risk
- 2009
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 68:11, s. 1746-1753
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVES: To confirm and define the genetic association of STAT4 and systemic lupus erythematosus, investigate the possibility of correlations with differential splicing and/or expression levels, and genetic interaction with IRF5. METHODS: 30 tag SNPs were genotyped in an independent set of Spanish cases and controls. SNPs surviving correction for multiple tests were genotyped in 5 new sets of cases and controls for replication. STAT4 cDNA was analyzed by 5'-RACE PCR and sequencing. Expression levels were measured by quantitative PCR. RESULTS: In the fine-mapping, four SNPs were significant after correction for multiple testing, with rs3821236 and rs3024866 as the strongest signals, followed by the previously associated rs7574865, and by rs1467199. Association was replicated in all cohorts. After conditional regression analyses, two major independent signals represented by SNPs rs3821236 and rs7574865, remained significant across the sets. These SNPs belong to separate haplotype blocks. High levels of STAT4 expression correlated with SNPs rs3821236, rs3024866 (both in the same haplotype block) and rs7574865 but not with other SNPs. We also detected transcription of alternative tissue-specific exons 1, indicating presence of tissue-specific promoters of potential importance in the expression of STAT4. No interaction with associated SNPs of IRF5 was observed using regression analysis. CONCLUSIONS: These data confirm STAT4 as a susceptibility gene for SLE and suggest the presence of at least two functional variants affecting levels of STAT4. Our results also indicate that both genes STAT4 and IRF5 act additively to increase risk for SLE.
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| 2. |
- Ainsbury, Elizabeth, et al.
(författare)
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Integration of new biological and physical retrospective dosimetry methods into EU emergency response plans - joint RENEB and EURADOS inter-laboratory comparisons
- 2017
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Ingår i: International Journal of Radiation Biology. - : Informa UK Limited. - 0955-3002 .- 1362-3095. ; 93:1, s. 99-109
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: RENEB, 'Realising the European Network of Biodosimetry and Physical Retrospective Dosimetry,' is a network for research and emergency response mutual assistance in biodosimetry within the EU. Within this extremely active network, a number of new dosimetry methods have recently been proposed or developed. There is a requirement to test and/or validate these candidate techniques and inter-comparison exercises are a well-established method for such validation. Materials and methods: The authors present details of inter-comparisons of four such new methods: dicentric chromosome analysis including telomere and centromere staining; the gene expression assay carried out in whole blood; Raman spectroscopy on blood lymphocytes, and detection of radiation induced thermoluminescent signals in glass screens taken from mobile phones. Results: In general the results show good agreement between the laboratories and methods within the expected levels of uncertainty, and thus demonstrate that there is a lot of potential for each of the candidate techniques. Conclusions: Further work is required before the new methods can be included within the suite of reliable dosimetry methods for use by RENEB partners and others in routine and emergency response scenarios.
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| 3. |
- Castillejo-Lopez, Casimiro, et al.
(författare)
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Genetic and physical interaction of the B-cell systemic lupus erythematosus-associated genes BANK1 and BLK
- 2012
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 71:1, s. 136-142
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Tidskriftsartikel (refereegranskat)abstract
- ObjectivesAltered signalling in B cells is a predominant feature of systemic lupus erythematosus (SLE). The genes BANK1 and BLK were recently described as associated with SLE. BANK1 codes for a B-cell-specific cytoplasmic protein involved in B-cell receptor signalling and BLK codes for an Src tyrosine kinase with important roles in B-cell development. To characterise the role of BANK1 and BLK in SLE, a genetic interaction analysis was performed hypothesising that genetic interactions could reveal functional pathways relevant to disease pathogenesis.MethodsThe GPAT16 method was used to analyse the gene-gene interactions of BANK1 and BLK. Confocal microscopy was used to investigate co-localisation, and immunoprecipitation was used to verify the physical interaction of BANK1 and BLK.ResultsEpistatic interactions between BANK1 and BLK polymorphisms associated with SLE were observed in a discovery set of 279 patients and 515 controls from northern Europe. A meta-analysis with 4399 European individuals confirmed the genetic interactions between BANK1 and BLK. As BANK1 was identified as a binding partner of the Src tyrosine kinase LYN, the possibility that BANK1 and BLK could also show a protein-protein interaction was tested. The co-immunoprecipitation and co-localisation of BLK and BANK1 were demonstrated. In a Daudi cell line and primary naive B cells endogenous binding was enhanced upon B-cell receptor stimulation using anti-IgM antibodies.ConclusionsThis study shows a genetic interaction between BANK1 and BLK, and demonstrates that these molecules interact physically. The results have important consequences for the understanding of SLE and other autoimmune diseases and identify a potential new signalling pathway.
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| 4. |
- Kozyrev, Sergey V, et al.
(författare)
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Functional variants in the B-cell gene BANK1 are associated with systemic lupus erythematosus
- 2008
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 40:2, s. 211-216
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Tidskriftsartikel (refereegranskat)abstract
- Systemic lupus erythematosus (SLE) is a prototypical autoimmune disease characterized by production of autoantibodies and complex genetic inheritance(1-3). In a genome-wide scan using 85,042 SNPs, we identified an association between SLE and a nonsynonymous substitution (rs10516487, R61H) in the B-cell scaffold protein with ankyrin repeats gene, BANK1. We replicated the association in four independent case-control sets (combined P = 3.7 x 10(-10); OR = 1.38). We analyzed BANK1 cDNA and found two isoforms, one full-length and the other alternatively spliced and lacking exon 2 (Delta 2), encoding a protein without a putative IP3R-binding domain. The transcripts were differentially expressed depending on a branch point-site SNP, rs17266594, in strong linkage disequilibrium (LD) with rs10516487. A third associated variant was found in the ankyrin domain (rs3733197, A383T). Our findings implicate BANK1 as a susceptibility gene for SLE, with variants affecting regulatory sites and key functional domains. The disease-associated variants could contribute to sustained B cell-receptor signaling and B-cell hyperactivity characteristic of this disease.
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| 5. |
- Wirapati, Pratyaksha, et al.
(författare)
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Detecting Epistasis with Restricted Response Patterns in Pairs of Biallelic Loci
- 2011
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Ingår i: Annals of Human Genetics. - : Wiley. - 0003-4800 .- 1469-1809. ; 75:1, s. 133-145
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Tidskriftsartikel (refereegranskat)abstract
- P>Well-established examples of genetic epistasis between a pair of loci typically show characteristic patterns of phenotypic distributions in joint genotype tables. However, inferring epistasis given such data is difficult due to the lack of power in commonly used approaches, which decompose the epistatic patterns into main plus interaction effects followed by testing the interaction term. Testing additive-only or all terms may have more power, but they are sensitive to nonepistatic patterns. Alternatively, the epistatic patterns of interest can be enumerated and the best matching one is found by searching through the possibilities. Although this approach requires multiple testing correction over possible patterns, each pattern can be fitted with a regression model with just one degree of freedom and thus the overall power can still be high, if the number of possible patterns is limited. Here we compare the power of the linear decomposition and pattern search methods, by applying them to simulated data generated under several patterns of joint genotype effects with simple biological interpretations. Interaction-only tests are the least powerful; while pattern search approach is the most powerful if the range of possibilities is restricted, but still includes the true pattern.
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