Aims/hypothesis In a population-based cohort of elderly men with well-defined phenotypes and biochemical markers related to type 2 diabetes mellitus, we analysed two single nucleotide polymorphisms (SNPs), rs7903146 and rs12255372, in the transcription factor 7-like 2 gene (TCF7L2), which are associated with an increased risk of type 2 diabetes mellitus. Materials and methods The 1,142 subjects were from the population-based Uppsala Longitudinal Study of Adult Men cohort study (see http://www.pubcare.uu.se/ULSAM/, last accessed in May 2007). Insulin sensitivity was assessed using a euglycaemic-hyperinsulinaemic clamp; fasting intact and 32-33 split proinsulin, immunoreactive insulin and specific insulin were measured in plasma samples. The SNPs rs7903146 and rs12255372 were genotyped using a fluorescent homogeneous single base extension assay. The SNP genotypes were analysed against diabetes prevalence at age 70 using logistic regression and against quantitative biochemical measures using linear regression analysis. Results We replicated the association with type 2 diabetes mellitus for both SNPs in this cohort of elderly males. The highest significant odds ratio (2.15, 95% CI 1.20-3.85) was found for SNP rs7903146. The odds ratio for SNP rs12255372 was 1.69 (95% CI 1.20-2.39). Both TCF7L2 SNPs were found to be significantly associated with plasma proinsulin when adjusting for insulin sensitivity, both in the whole cohort and when the diabetic subjects were excluded. Analysis for fasting plasma insulin or insulin sensitivity did not give significant results. Conclusions/interpretation The association between the risk alleles of the two SNPs studied and levels of proinsulin in plasma, identified when adjusting for insulin sensitivity using euglycaemic-hyperinsulinaemic clamp measurements in this study, is an important novel finding.

Human body height is a complex genetic trait with high heritability. We performed an association study of 17 candidate genes for height in the Uppsala Longitudinal Study of Adult Men (ULSAM) that consists of 1153 elderly men of age 70 born in the central region of Sweden. First we genotyped a panel of 137 single nucleotide polymorphism (SNPs) evenly distributed across the candidate genes in the ULSAM cohort. We identified 4 SNPs in the estrogen receptor gene (ESR1) on chromosome 6q25.1 with suggestive signals of association (p<0.05) with standing body height. This result was followed up by genotyping the same 25 SNPs in the ESR1 gene as in ULSAM in a second population cohort, the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) cohort that consist of 507 males and 509 females of age 70 from the same geographical region as ULSAM. One SNP, rs2179922 located in intron 4 of ESR1 showed and association signal (p = 0.0056) in the male samples from the PIVUS cohort. Homozygote carriers of the G-allele of the SNP rs2179922 were on average 0.90 cm taller than individuals with the two other genotypes at this SNP in the ULSAM cohort and 2.3 cm taller in the PIVUS cohort. No association was observed for the females in the PIVUS cohort.

Multiallelic short tandem repeat polymorphisms, or microsatellites, are useful markers in genome wide scans to identify chromosomal regions containing genes underlying disease loci. The biallelic single nucleotide polymorphism (SNP) can be used to fine map previously identified large candidate regions or to test functional candidate genes by association analysis. In the GenomEUtwin project the population based impact of susceptibility genes for six multifactorial traits will be studied. A genome wide panel of informative human microsatellite markers will be analyzed by fluorescent capillary electrophoresis in well characterized twin and population samples. Contrary to microsatellites, selection of the most informative panels of SNPs is hampered by imperfect data on the allele frequencies and population distribution of SNPs markers in the databases. Therefore, selection of SNPs requires a substantial amount of bioinformatics, and, the SNPs need to be validated experimentally in the relevant populations prior to genotyping large sample sets. In the GenomEUtwin project, large scale genotyping of SNPs will be performed using the SNPstreamUHT and MassARRAY genotyping systems that are based on the primer extension reaction principle combined with fluorescent and mass spectrometric detection, respectively. Production of the genotyping data will be a joint effort by GenomEUtwin partners at the University of Helsinki, the National Public Health Institute in Helsinki, Finland and Uppsala University, Sweden. All genotyping data will be stored in a common database established specifically for the GenomEUtwin project, from where it can be accessed by the twin research centres that provided the samples for genotyping.

BackgroundEach of the human genes or transcriptional units is likely to contain single nucleotide polymorphisms that may give rise to sequence variation between individuals and tissues on the level of RNA. Based on recent studies, differential expression of the two alleles of heterozygous coding single nucleotide polymorphisms (SNPs) may be frequent for human genes. Methods with high accuracy to be used in a high throughput setting are needed for systematic surveys of expressed sequence variation. In this study we evaluated two formats of multiplexed, microarray based minisequencing for quantitative detection of imbalanced expression of SNP alleles. We used a panel of ten SNPs located in five genes known to be expressed in two endothelial cell lines as our model system.ResultsThe accuracy and sensitivity of quantitative detection of allelic imbalance was assessed for each SNP by constructing regression lines using a dilution series of mixed samples from individuals of different genotype. Accurate quantification of SNP alleles by both assay formats was evidenced for by R2 values > 0.95 for the majority of the regression lines. According to a two sample t-test, we were able to distinguish 1–9% of a minority SNP allele from a homozygous genotype, with larger variation between SNPs than between assay formats. Six of the SNPs, heterozygous in either of the two cell lines, were genotyped in RNA extracted from the endothelial cells. The coefficient of variation between the fluorescent signals from five parallel reactions was similar for cDNA and genomic DNA. The fluorescence signal intensity ratios measured in the cDNA samples were compared to those in genomic DNA to determine the relative expression levels of the two alleles of each SNP. Four of the six SNPs tested displayed a higher than 1.4-fold difference in allelic ratios between cDNA and genomic DNA. The results were verified by allele-specific oligonucleotide hybridisation and minisequencing in a microtiter plate format.ConclusionsWe conclude that microarray based minisequencing is an accurate and accessible tool for multiplexed screening for imbalanced allelic expression in multiple samples and tissues in parallel.

Multiallelic short tandem repeat polymorphisms, or microsatellites, are useful markers in genome wide scans to identify chromosomal regions containing genes underlying disease loci. The biallelic single nucleotide polymorphism (SNP) can be used to fine map previously identified large candidate regions or to test functional candidate genes by association analysis. In the GenomEUtwin project the population based impact of susceptibility genes for six multifactorial traits will be studied. A genome wide panel of informative human microsatellite markers will be analyzed by fluorescent capillary electrophoresis in well characterized twin and population samples. Contrary to microsatellites, selection of the most informative panels of SNPs is hampered by imperfect data on the allele frequencies and population distribution of SNPs markers in the databases. Therefore, selection of SNPs requires a substantial amount of bioinformatics, and, the SNPs need to be validated experimentally in the relevant populations prior to genotyping large sample sets. In the GenomEUtwin project, large scale genotyping of SNPs will be performed using the SNPstreamUHT and MassARRAY genotyping systems that are based on the primer extension reaction principle combined with fluorescent and mass spectrometric detection, respectively. Production of the genotyping data will be a joint effort by GenomEUtwin partners at the University of Helsinki, the National Public Health Institute in Helsinki, Finland and Uppsala University, Sweden. All genotyping data will be stored in a common database established specifically for the GenomEUtwin project, from where it can be accessed by the twin research centres that provided the samples for genotyping.