We performed a genome scan at an average resolution of 8 cM in 719 Finnish sib pairs with type 2 diabetes. Our strongest results are for chromosome 20, where we observe a weighted maximum LOD score (MLS) of 2.15 at map position 69.5 cM from pter and secondary weighted LOD-score peaks of 2.04 at 56.5 cM and 1.99 at 17.5 cM. Our next largest MLS is for chromosome 11 (MLS = 1.75 at 84.0 cM), followed by chromosomes 2 (MLS = 0.87 at 5.5 cM), 10 (MLS = 0.77 at 75.0 cM), and 6 (MLS = 0.61 at 112.5 cM), all under an additive model. When we condition on chromosome 2 at 8.5 cM, the MLS for chromosome 20 increases to 5.50 at 69.0 cM (P=.0014). An ordered-subsets analysis based on families with high or low diabetes-related quantitative traits yielded results that support the possible existence of disease-predisposing genes on chromosomes 6 and 10. Genomewide linkage-disequilibrium analysis using microsatellite marker data revealed strong evidence of association for D22S423 (P=.00007). Further analyses are being carried out to confirm and to refine the location of these putative diabetes-predisposing genes.

Our work demonstrates the feasibility of collecting a large number of affected sib-pair families with NIDDM to provide data that will enable a whole genome search approach, including linkage analysis.

We have investigated gene amplification of fibroblast growth factor receptor-4 (FGFR4) gene in 30 primary breast tumor samples and 15 gynecological tumor samples. Ten percent of the breast tumors showed 2- to 4-fold amplification. Amplification was found more frequently in estrogen- and progesterone-receptor-positive tumors and in tumors with high lymph-node involvement. Breast tumor samples were also analyzed for the amplification of fgfr3 and erbB2 genes and the chromosome 11q13 located genes hst1/int2/bcl1/sea. erbB2 gene was amplified 2- to 13-fold in 13% of the cases, but no amplification of int2/hst1/bcl1/sea amplicon was found. Gynecological tumors were also analyzed for the amplification of fgfr4 and fgfr3 genes and for int2 and hst1 oncogenes. Eleven of the 15 gynecological tumors were ovarian neoplasms including 2 benign tumors; the remainder comprised 1 ovarian metastasis of breast cancer; 1 endometrial cancer; 1 uterine leiomyosarcoma and 1 carcinosarcoma of the fallopian tube. In gynecological tumors, fgfr4 gene was found to be amplified in 2 ovarian tumors. Amplification of hst1 was found in 1 benign ovarian tumor. Thus, the fgfr4 gene may be involved in breast and ovarian tumorigenesis.

Large-scale genotyping is required to generate dense identity-by-descent maps to map genes for human complex disease. In some studies the number of genotypes needed can approach or even exceed I million. Generally, linkage and linkage disequilibrium analyses depend on clear allele identification and subsequent allele frequency estimation. Accurate grouping or categorization of each allele in the sample (allele calling or binning) is therefore an absolute requirement. Hence, a genotyping system that can reliably achieve this is necessary. In the case of affected sib-pair analysis without parents, the need for accurate allele calling is even more critical. We describe methods that permit precise sizing of alleles across multiple gels using the fluorescence-based, Applied Biosystems (ABI) genotyping technology and discuss ways to reduce genotyping error rates. Using database utilities, we show how to minimize intergel allele size variation, to combine data effectively from different models of ABI sequencing machines, and automatically bin alleles. The final data can then be converted into a format ready for analysis by statistical genetic packages such as MENDEL.

Type 2 diabetes mellitus is a complex disorder encompassing multiple metabolic defects. We report results from an autosomal genome scan for type 2 diabetes-related quantitative traits in 580 Finnish families ascertained for an affected sibling pair and analyzed by the variance components-based quantitative-trait locus (QTL) linkage approach. We analyzed diabetic and nondiabetic subjects separately, because of the possible impact of disease on the traits of interest. In diabetic individuals, our strongest results were observed on chromosomes 3 (fasting Cpeptide/glucose: maximum LOD score [MLS] p 3.13 at 53.0 cM) and 13 (body-mass index: MLS p 3.28 at 5.0 cM). In nondiabetic individuals, the strongest results were observed on chromosomes 10 (acute insulin response: MLS p 3.11 at 21.0 cM), 13 (2-h insulin: MLS p 2.86 at 65.5 cM), and 17 (fasting insulin/glucose ratio: MLS p 3.20 at 9.0 cM). In several cases, there was evidence for overlapping signals between diabetic and nondiabetic individuals; therefore we performed joint analyses. In these joint analyses, we observed strong signals for chromosomes 3 (body-mass index: MLS p 3.43 at 59.5 cM), 17 (empirical insulin-resistance index: MLS p 3.61 at 0.0 cM), and 19 (empirical insulin-resistance index: MLS p 2.80 at 74.5 cM). Integrating genome-scan results from the companion article by Ghosh et al., we identify several regions that may harbor susceptibility genes for type 2 diabetes in the Finnish population.

Type 2 diabetes mellitus is a complex disorder encompassing multiple metabolic defects. We report results from an autosomal genome scan for type 2 diabetes-related quantitative traits in 580 Finnish families ascertained for an affected sibling pair and analyzed by the variance components-based quantitative-trait locus (QTL) linkage approach. We analyzed diabetic and nondiabetic subjects separately, because of the possible impact of disease on the traits of interest. In diabetic individuals, our strongest results were observed on chromosomes 3 (fasting Cpeptide/glucose: maximum LOD score [MLS] p 3.13 at 53.0 cM) and 13 (body-mass index: MLS p 3.28 at 5.0 cM). In nondiabetic individuals, the strongest results were observed on chromosomes 10 (acute insulin response: MLS p 3.11 at 21.0 cM), 13 (2-h insulin: MLS p 2.86 at 65.5 cM), and 17 (fasting insulin/glucose ratio: MLS p 3.20 at 9.0 cM). In several cases, there was evidence for overlapping signals between diabetic and nondiabetic individuals; therefore we performed joint analyses. In these joint analyses, we observed strong signals for chromosomes 3 (body-mass index: MLS p 3.43 at 59.5 cM), 17 (empirical insulin-resistance index: MLS p 3.61 at 0.0 cM), and 19 (empirical insulin-resistance index: MLS p 2.80 at 74.5 cM). Integrating genome-scan results from the companion article by Ghosh et al., we identify several regions that may harbor susceptibility genes for type 2 diabetes in the Finnish population.

Analysis of most hematologic neoplasms indicates the involvement of one or more cell lineages in the bone marrow and/or the blood but rules out the involvement of all lineages in any one neoplasm. It is important to detect lineage involvement in order to clarify which stem cells are involved in leukemia, to predict prognosis, and to select appropriate treatment. Our aim was to study the cell lineage involvement of some of the recurrent chromosomal abnormalities seen in hematological neoplasms. The direct morphology-antibody-chromosomes (MAC) method was used. The deletion 20q in myeloproliferative diseases (MPD), the deletion of 5q and t(1;7) in myelodysplastic syndromes (MDS), and t(3;3) in acute myeloid leukemia subtype M7 (AML-M7) were seen in all or at least in two myeloid lineages. These were interpreted as stem cell abnormalities. Deletion 13q in MPD, t(8;21) in AML-M2 and t(15;17) in AML-M3 were seen in granulocytic lineages only; t(14;18) in non-Hodgkin's lymphoma and trisomy 12 as the sole abnormality in chronic lymphocytic leukemia (B-CLL) were seen only in immunoglobulin light chain clonal B cells; inversion 14 in T-CLL was seen only in T cells, whereas t(15;14) in acute lymphocytic leukemia with eosinophilia (ALL-EO) was seen in lymphoid stem cells but not in mature granulocytes or lymphocytes. Additional abnormalities (in addition to the Philadelphia chromosome) in chronic myeloid leukemia (CML) were seen in all myeloid cell lineages and also in mature granulocytes, B cells, and large granular lymphocytes. Abnormalities in Hodgkin's disease were restricted to CD30-positive Reed-Sternberg cells. Trisomy 8 and monosomy 7 are abnormalities that may be present in either stem cells or any of the single cell lineages.

We performed a genome scan at an average resolution of 8 cM in 719 Finnish sib pairs with type 2 diabetes. Our strongest results are for chromosome 20, where we observe a weighted maximum LOD score (MLS) of 2.15 at map position 69.5 cM from pter and secondary weighted LOD-score peaks of 2.04 at 56.5 cM and 1.99 at 17.5 cM. Our next largest MLS is for chromosome 11 (MLS = 1.75 at 84.0 cM), followed by chromosomes 2 (MLS = 0.87 at 5.5 cM), 10 (MLS = 0.77 at 75.0 cM), and 6 (MLS = 0.61 at 112.5 cM), all under an additive model. When we condition on chromosome 2 at 8.5 cM, the MLS for chromosome 20 increases to 5.50 at 69.0 cM (P=.0014). An ordered-subsets analysis based on families with high or low diabetes-related quantitative traits yielded results that support the possible existence of disease-predisposing genes on chromosomes 6 and 10. Genomewide linkage-disequilibrium analysis using microsatellite marker data revealed strong evidence of association for D22S423 (P=.00007). Further analyses are being carried out to confirm and to refine the location of these putative diabetes-predisposing genes.