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Two Insulin Gene Single Nucleotide Polymorphisms Associated with Type 1 Diabetes Risk in the Finnish and Swedish Populations
We have developed high-throughput tests for the detection of the insulin gene region SNPs −23HphI and −2221MspI. The potential of these markers to enhance the efficiency of type 1 diabetes risk screening was then evaluated by analyzing them in Finnish and Swedish populations. Blood spots on filter p...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
IOS Press
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3850817/ https://www.ncbi.nlm.nih.gov/pubmed/17473382 http://dx.doi.org/10.1155/2007/574363 |
Sumario: | We have developed high-throughput tests for the detection of the insulin gene region SNPs −23HphI and −2221MspI. The potential of these markers to enhance the efficiency of type 1 diabetes risk screening was then evaluated by analyzing them in Finnish and Swedish populations. Blood spots on filter paper were analyzed using PCR followed by sequence-specific hybridization and time-resolved fluorometry reading. Distribution of the genotypes at both positions differed significantly among the affected children compared to the controls. The risk genotypes (CC, AA) were significantly more common in Finland than in Sweden, both among patients and controls. The VNTR genotype homozygous for the protective class III alleles showed a significantly stronger protective effect than the heterozygote (p = 0.02). Analyzing both SNPs enabled the detection of VNTR class III subclasses IIIA and IIIB. The observed significance between effects of the protective genotypes was due to the strong protective effect of the IIIA/IIIA genotype. IIIA/IIIA was the only genotype with significant discrepancy between protective effects compared to the other class III genotypes. These observations suggest that heterogeneity between the protective IDDM2 lineages could exist, and analyzing both −23HphI and −2221MspI would thus potentially enhance the sensitivity and specificity of type 1 diabetes risk estimation. |
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