OBJECTIVES: To confirm and define the genetic association of STAT4 and systemic lupus erythematosus (SLE), 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 five new sets of cases and controls for replication. STAT4 cDNA was analysed 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. Transcription of alternative tissue-specific exons 1, indicating the presence of tissue-specific promoters of potential importance in the expression of STAT4, was also detected. 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. The results also indicate that the genes STAT4 and IRF5 act additively to increase the risk for SLE.
OBJECTIVES: To confirm and define the genetic association of STAT4 and systemic lupus erythematosus (SLE), 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 five new sets of cases and controls for replication. STAT4 cDNA was analysed 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. Transcription of alternative tissue-specific exons 1, indicating the presence of tissue-specific promoters of potential importance in the expression of STAT4, was also detected. 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. The results also indicate that the genes STAT4 and IRF5 act additively to increase the risk for SLE.
Authors: Ludmila Prokunina; Casimiro Castillejo-López; Fredrik Oberg; Iva Gunnarsson; Louise Berg; Veronica Magnusson; Anthony J Brookes; Dmitry Tentler; Helga Kristjansdóttir; Gerdur Gröndal; Anne Isine Bolstad; Elisabet Svenungsson; Ingrid Lundberg; Gunnar Sturfelt; Andreas Jönssen; Lennart Truedsson; Guadalupe Lima; Jorge Alcocer-Varela; Roland Jonsson; Ulf B Gyllensten; John B Harley; Donato Alarcón-Segovia; Kristján Steinsson; Marta E Alarcón-Riquelme Journal: Nat Genet Date: 2002-10-28 Impact factor: 38.330
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Authors: Chieko Kyogoku; Carl D Langefeld; Ward A Ortmann; Annette Lee; Scott Selby; Victoria E H Carlton; Monica Chang; Paula Ramos; Emily C Baechler; Franak M Batliwalla; Jill Novitzke; Adrienne H Williams; Clarence Gillett; Peter Rodine; Robert R Graham; Kristin G Ardlie; Patrick M Gaffney; Kathy L Moser; Michelle Petri; Ann B Begovich; Peter K Gregersen; Timothy W Behrens Journal: Am J Hum Genet Date: 2004-07-23 Impact factor: 11.025
Authors: Eimear E Kenny; Alexander Gusev; Kaitlin Riegel; Dieter Lütjohann; Jennifer K Lowe; Jacqueline Salit; Julian B Maller; Markus Stoffel; Mark J Daly; David M Altshuler; Jeffrey M Friedman; Jan L Breslow; Itsik Pe'er; Ephraim Sehayek Journal: Proc Natl Acad Sci U S A Date: 2009-08-10 Impact factor: 11.205