PMC:2495071 / 12065-14560 JSONTXT

{"project":"2_test","denotations":[{"id":"18656179-11791212-2045968","span":{"begin":1593,"end":1595},"obj":"11791212"},{"id":"18656179-16460651-2045968","span":{"begin":1593,"end":1595},"obj":"16460651"},{"id":"18656179-16460651-2045969","span":{"begin":2029,"end":2031},"obj":"16460651"}],"text":"Computational Biology and Statistics\nIn order to attenuate the problem of deliberately setting up thresholds for ELISA and MX1 values to declare cases and controls, a binary-trait case-control association study was supported by continuous trait analysis for single HLA alleles and haplotypes. This bilateral approach was used for the initial study group as well as for the validation group. For identification of genetic variation of anti-IFN-β formation, the continuous normalized antibody reactivities were directly compared among carriers of different alleles. In the binary-trait case-control study, patients were considered antibody positive (cases) if the anti-IFN-β levels exceeded the 25% cutoff value. Otherwise, patients were considered antibody negative (controls). Additionally, antibody-positive patients were considered NABs positive if their MX1 mRNAs were reduced below 50% of MX1 levels of newly treated patients. The remaining antibody-positive patients who had not significantly reduced MX1 mRNA levels were considered BABs positive. For the testing of differences of location parameters for MX1 gene expression and anti-IFN-β levels, the two-sided nonparametric Wilcoxon test was applied. p values were adjusted for multiple testing with the false-discovery rate (FDR). For identification of haplotype-specific associations with continuous (MX1 and anti-IFN-β levels) and binomial trait types (NABS, BABs, and control subgroups), the genetic analysis package (gap) of the R Project for statistical computing was applied with score tests for association as described by 20, 21. Haplotype-specific scores have been calculated with a score test for ambiguous haplotypes. The score statistics are given byUβ=∑i=1N(yi−y˜i)a(ϕ)Ep(Xgi)where yi denotes the measured trait, y˜i a mean trait value, and a(ϕ) a measure of variation. Ep(Xgi) denotes expectation value over the posterior distribution of the null hypothesis. The score statistics provide a measure for the covariation of a haplotype and the examined trait.21 However, this analysis has explorative character, because the results are based on the maximization of probabilities rather than a known linkage phase.\nMultiple sequence alignments were generated with the CLUSTALW application. The sequences of HLA alleles were obtained from the HLA repository at the European Bioinformatics Institute (EBI). Linkage disequilibrium (LD) tests for HLA alleles as well as multilocus analysis for LD were done with the PyPop package."}