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Analysis of susceptibility loci for juvenile idiopathic arthritis in the extended Mhc region using high resolution Snp and Hla allele typing

Biesiada J., Sudman M., Wagner M., Rupert A., Hollenbach J., Haas J. P., Meller J., Thompson S. D.

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

2014

Vol. 18, No 4

305--320

Juvenile idiopathic arthritis ( JIA ) spans several pediatric arthropathies that involve autoimmune responses. Primary genetic risk factors for JIA have been mapped to Major Histocompatibility Complex ( MHC ) class I and class II genes. Recent genome-wide association studies using SNP arrays have shown that the nonHLA genetic component of JIA involves multiple low-risk loci, reinforcing the notion that JIA is a complex genetic trait with a strong HLA component. In this work, with the goal of detailed mapping and analysis of lin kage disequilibrium ( LD ) patterns and associations with JIA in the extended MHC (x MHC ) region, we combined SNP data from Affymetrix SNP Array 6.0 and Immunochip ( IC ) platforms with high resolution typing of 8 classical HLA genes. A cohort of about 800 affected individuals and about 500 ethnically matched controls from the Cincinnati region, as well as secondary validation cohorts of affected individuals and matched controls from Germany were used to perform the an alysis, and to assess reproducibility of the results across different platforms and p opulations. Accurate high resolution maps of linkage with classical HLA genes and association with individual HLA alleles were generated. High concordance of results obtained using Affymetrix SNP Array 6.0 and IC was observed, with an additional resolution and improved mapping of associat ions provided by the latter in some regions. Several new peaks of statistically signific ant and reproducible association with JIA outside the regions of strong LD with classical HLA genes were observed, including one peak in the class III region, and one in the telomeric end of x MHC . Conditional analysis provided further evidence that these associations appear t o be independent of classical HLA genes studied here. The results and observed association patterns ar e further discussed in the context of other recent studies on autoimmune diseases, includin g the role of HLA DRB 1 in adult Rheumatoid Arthritis.

Computational approach to understanding Autism Spectrum Disorders

Duch W., Nowak W., Meller J., Osiński G., Dobosz K., Mikołajewski D., Wójcik G. M.

Computer Science

2012

Vol. 13 (2)

47-61

Every year the prevalence of Autism Spectrum of Disorders (ASD) is rising. Is there a unifying mechanism of various ASD cases at the genetic, molecular, cellular or systems level? The hypothesis advanced in this paper is focused on neural dysfunctions that lead to problems with attention in autistic people. Simulations of attractor neural networks performing cognitive functions help to assess system long-term neurodynamics. The Fuzzy Symbolic Dynamics (FSD) technique is used for the visualization of attractors in the semantic layer of the neural model of reading. Large-scale simulations of brain structures characterized by a high order of complexity requires enormous computational power, especially if biologically motivated neuron models are used to investigate the influence of cellular structure dysfunctions on the network dynamics. Such simulations have to be implemented on computer clusters in a grid-based architectures.