Insights into the molecular genetics of celiac disease : Applying family- and population-based strategies

Celiac disease, or gluten intolerance, is triggered by dietary glutens in genetically susceptible individuals and it affects approximately 1% of the Caucasian population. The best known genetic risk factors for celiac disease are HLA DQ2 and DQ8 heterodimers, which are necessary for the development of the disease. However, they alone are not sufficient for disease induction, other risk factors are required. This thesis investigated genetic factors for celiac disease, concentrating on susceptibility loci on chromosomes 5q31-q33, 19p13 and 2q12 previously reported in genome-wide linkage and association studies. In addition, a novel genotyping method for the detection of HLA DQ2 and DQ8 coding haplotypes was validated. This study was conducted using Finnish and Hungarian family materials, and Finnish, Hungarian and Italian case-control materials. Genetic linkage and association were analysed in these materials using candidate gene and fine-mapping approaches. The results confirmed linkage to celiac disease on the chromosomal regions 5q31-q33 and 19p13. Fine-mapping on chromosome 5q31-q33 revealed several modest associations in the region, and highlighted the need for further investigations to locate the causal risk variants. The MYO9B gene on chromosome 19p13 showed evidence for linkage and association particularly with dermatitis herpetiformis, the skin manifestation of celiac disease. This implies a potential difference in the genetic background of the intestinal and skin forms of the disease, although studies on larger samplesets are required. The IL18RAP locus on chromosome 2q12, shown to be associated with celiac disease in a previous genome-wide association study and a subsequent follow-up, showed association in the Hungarian population in this study. The expression of IL18RAP was further investigated in small intestinal tissue and in peripheral blood mononuclear cells. The results showed that IL18RAP is expressed in the relevant tissues. Two putative isoforms of IL18RAP were detected by Western blot analysis, and the results suggested that the ratios and total levels of these isoforms may contribute to the aetiology of celiac disease. A novel genotyping method for celiac disease-associated HLA haplotypes was also validated in this thesis. The method utilises single-nucleotide polymorphisms tagging these HLA haplotypes with high sensitivity and specificity. Our results suggest that this method is transferable between populations, and it is suitable for large-scale analysis. In conclusion, this doctorate study provides an insight into the roles of the 5q31-q33, MYO9B, IL18RAP and HLA loci in the susceptibility to celiac disease in the Finnish, Hungarian and Italian populations, highlighting the need for further studies at these genetic loci and examination of the function of the candidate genes.

Mapping Road Infrastructure in Developing Countries Applying Remote Sensing and GIS - The Case of the Taita Hills, Kenya

Road transport and infrastructure has a fundamental meaning for the developing world. Poor quality and inadequate coverage of roads, lack of maintenance operations and outdated road maps continue to hinder economic and social development in the developing countries. This thesis focuses on studying the present state of road infrastructure and its mapping in the Taita Hills, south-east Kenya. The study is included as a part of the TAITA-project by the Department of Geography, University of Helsinki. The road infrastructure of the study area is studied by remote sensing and GIS based methodology. As the principal dataset, true colour airborne digital camera data from 2004, was used to generate an aerial image mosaic of the study area. Auxiliary data includes SPOT satellite imagery from 2003, field spectrometry data of road surfaces and relevant literature. Road infrastructure characteristics are interpreted from three test sites using pixel-based supervised classification, object-oriented supervised classifications and visual interpretation. Road infrastructure of the test sites is interpreted visually from a SPOT image. Road centrelines are then extracted from the object-oriented classification results with an automatic vectorisation process. The road infrastructure of the entire image mosaic is mapped by applying the most appropriate assessed data and techniques. The spectral characteristics and reflectance of various road surfaces are considered with the acquired field spectra and relevant literature. The results are compared with the experimented road mapping methods. This study concludes that classification and extraction of roads remains a difficult task, and that the accuracy of the results is inadequate regardless of the high spatial resolution of the image mosaic used in this thesis. Visual interpretation, out of all the experimented methods in this thesis is the most straightforward, accurate and valid technique for road mapping. Certain road surfaces have similar spectral characteristics and reflectance values with other land cover and land use. This has a great influence for digital analysis techniques in particular. Road mapping is made even more complicated by rich vegetation and tree canopy, clouds, shadows, low contrast between roads and surroundings and the width of narrow roads in relation to the spatial resolution of the imagery used. The results of this thesis may be applied to road infrastructure mapping in developing countries on a more general context, although with certain limits. In particular, unclassified rural roads require updated road mapping schemas to intensify road transport possibilities and to assist in the development of the developing world.

HFST—Framework for Compiling and Applying Morphologies

HFST–Helsinki Finite-State Technology ( hfst.sf.net ) is a framework for compiling and applying linguistic descriptions with finite-state methods. HFST currently connects some of the most important finite-state tools for creating morphologies and spellers into one open-source platform and supports extending and improving the descriptions with weights to accommodate the modeling of statistical information. HFST offers a path from language descriptions to efficient language applications in key environments and operating systems. HFST also provides an opportunity to exchange transducers between different software providers in order to get the best out of each finite-state library.