Risk alleles of USF1 gene predict cardiovascular disease of women in two prospective studies.

Upstream transcription factor 1 (USF1) is a ubiquitously expressed transcription factor controlling several critical genes in lipid and glucose metabolism. Of some 40 genes regulated by USF1, several are involved in the molecular pathogenesis of cardiovascular disease (CVD). Although the USF1 gene has been shown to have a critical role in the etiology of familial combined hyperlipidemia, which predisposes to early CVD, the gene's potential role as a risk factor for CVD events at the population level has not been established. Here we report the results from a prospective genetic-epidemiological study of the association between the USF1 variants, CVD, and mortality in two large Finnish cohorts. Haplotype-tagging single nucleotide polymorphisms exposing all common allelic variants of USF1 were genotyped in a prospective case-cohort design with two distinct cohorts followed up during 1992-2001 and 1997-2003. The total number of follow-up years was 112,435 in 14,140 individuals, of which 2,225 were selected for genotyping based on the case-cohort study strategy. After adjustment for conventional risk factors, we observed an association of USF1 with CVD and mortality among females. In combined analysis of the two cohorts, female carriers of a USF1 risk haplotype had a 2-fold risk of a CVD event (hazard ratio [HR] 2.02; 95% confidence interval [CI] 1.16-3.53; p = 0.01) and an increased risk of all-cause mortality (HR 2.52; 95% CI 1.46-4.35; p = 0.0009). A putative protective haplotype of USF1 was also identified. Our study shows how a gene identified in exceptional families proves to be important also at the population level, implying that allelic variants of USF1 significantly influence the prospective risk of CVD and even all-cause mortality in females.

Evaluating whole genome amplification via multiply-primed rolling circle amplification for SNP genotyping of samples with low DNA yield.

The amount of available DNA is often a limiting factor in pursuing genetic analyses of large-scale population cohorts. An association between higher DNA yield from blood and several phenotypes associated with inflammatory states has recently been demonstrated, suggesting that exclusion of samples with very low DNA yield may lead to biased results in statistical analyses. Whole genome amplification (WGA) could present a solution to the DNA concentration-dependent sample selection. The aim was to thoroughly assess WGA for samples with low DNA yield, using the multiply-primed rolling circle amplification method. Fifty-nine samples were selected with the lowest DNA yield (less than 7.5 microg) among 799 samples obtained for one population cohort. The genotypes obtained from two replicate WGA samples and the original genomic DNA were compared by typing 24 single nucleotide polymorphisms (SNPs). Multiple genotype discrepancies were identified for 13 of the 59 samples. The largest portion of discrepancies was due to allele dropout in heterozygous genotypes in WGA samples. Pooling the WGA DNA replicates prior to genotyping markedly improved genotyping reproducibility for the samples, with only 7 discrepancies identified in 4 samples. The nature of discrepancies was mostly homozygote genotypes in the genomic DNA and heterozygote genotypes in the WGA sample, suggesting possible allele dropout in the genomic DNA sample due to very low amounts of DNA template. Thus, WGA is applicable for low DNA yield samples, especially if using pooled WGA samples. A higher rate of genotyping errors requires that increased attention be paid to genotyping quality control, and caution when interpreting results.