Subpopulation difference scanning: a strategy for exclusion mapping of susceptibility genes.

BACKGROUND: Association mapping is a common strategy for finding disease-related genes in complex disorders. Different association study designs exist, such as case-control studies or admixture mapping. METHODS: We propose a strategy, subpopulation difference scanning (SDS), to exclude large fractions of the genome as locations of genes for complex disorders. This strategy is applicable to genes explaining disease incidence differences within founder populations, for example, in cardiovascular diseases in Finland. RESULTS: The strategy consists of genotyping a set of markers from unrelated individuals sampled from subpopulations with differing disease incidence but otherwise as similar as possible. When comparing allele or haplotype frequencies between the subpopulations, the genomic areas with little difference can be excluded as possible locations for genes causing the difference in incidence, and other areas therefore targeted with case-control studies. As tests of this strategy, we use real and simulated data to show that under realistic assumptions of population history and disease risk parameters, the strategy saves efforts of sampling and genotyping and most efficiently detects genes of low risk--that is, those most difficult to find with other strategies. CONCLUSION: In contrast to admixture mapping that uses the mixing of two different populations, the SDS strategy takes advantage of drift within highly related subpopulations.

L1CAM, INP10, P-cadherin, tPA and ITGB4 over-expression in malignant pleural mesotheliomas revealed by combined use of cDNA and tissue microarray.

Malignant pleural mesothelioma (MM) is a rare tumour with high mortality, which can exhibit various morphologies classified as epithelioid, biphasic and sarcomatoid subtypes. To investigate the molecular changes in these tumours, we studied gene expression patterns by combined use of cDNA arrays and tumour tissue microarrays (TMA). Deregulation of the expression of 588 cancer-related genes was screened in 16 MM comprising all three subtypes and compared with references, i.e. normal mesothelial cell lines and pleural mesothelium. Array data were analysed using three statistical methods; principal component analysis (PCA), permutation test and receiver operating characteristic (ROC) curves. Eleven genes were verified by real-time RT-PCR. Genes encoding two adhesion molecules [COL1A2 and integrin beta4 (ITGB4)] and a chemokine (INP10) were up-regulated in MM compared with both the cell lines and pleural mesothelium. There was a type-specific up-regulation of semaphorin E, ITGB4 and P-cadherin in epithelioid MM, matrix metalloproteinase 9 (MMP9) and tissue-type plasminogen activator (tPA) in sarcomatoid MM and neural cell adhesion molecule L1 (L1CAM) and INP10 in biphasic MM. Immunohistochemistry on TMA containing 47 MM (26 epithelioid, 15 sarcomatoid and six biphasic) was performed for five proteins, ITGB4, P-cadherin, tPA, INP10 and L1CAM. INP10 expression was increased in MM in general compared with normal mesothelium, while increased expression of P-cadherin, L1CAM and ITGB4 was more specific in MMs exhibiting an epithelioid growth pattern. The over-expression of tPA was more frequent in epithelioid MM despite higher mRNA levels in sarcomatoid and biphasic MM. We conclude that several proteins, associated with cell adhesion either directly (ITGB4, L1CAM, P-cadherin) or as a regulatory factor (INP10), are differentially expressed in MM. In particular, INP10, ITGB4 and COL1A2 were up-regulated in MM compared with both reference sample types, suggesting a relationship with development of these tumours.

Expression of myeloid-specific genes in childhood acute lymphoblastic leukemia - a cDNA array study.

Several specific cytogenetic changes are known to be associated with childhood acute lymphoblastic leukemia (ALL), and many of them are important prognostic factors for the disease. Little is known, however, about the changes in gene expression in ALL. Recently, the development of cDNA array technology has enabled the study of expression of hundreds to thousands of genes in a single experiment. We used the cDNA array method to study the gene expression profiles of 17 children with precursor-B ALL. Normal B cells from adenoids were used as reference material. We discuss the 25 genes that were most over-expressed compared to the reference. These included four genes that are normally expressed only in the myeloid lineages of the hematopoietic cells: RNASE2, GCSFR, PRTN3 and CLC. We also detected over-expression of S100A12, expressed in nerve cells but also in myeloid cells. In addition to the myeloid-specific genes, other over-expressed genes included AML1, LCP2 and FGF6. In conclusion, our study revealed novel information about gene expression in childhood ALL. The data obtained may contribute to further studies of the pathogenesis and prognosis of childhood ALL.