Search

Context: The risk of many conditions, including prostate cancer, breast cancer, and osteoporosis, is associated with serum levels of sex steroids., Objective: The aim of the study was to identify genetic variations in sex steroid-related genes that are associated with serum levels of estradiol (E2) and/or testosterone in men., Design: Genotyping of 604 single nucleotide polymorphisms in 50 sex steroid-related candidate genes was performed in the Gothenburg Osteoporosis and Obesity Determinants (GOOD) study (n = 1041 men; age, 18.9 +/- 0.6 yr). Replications of significant associations were performed in the Osteoporotic Fractures in Men (MrOS) Sweden study (n = 2568 men; age, 75.5 +/- 3.2 yr) and in the MrOS US study (n = 1922 men; age, 73.5 +/- 5.8 yr). Serum E2, testosterone, and estrone (E1) levels were analyzed using gas chromatography/mass spectrometry., Results: The screening in the GOOD cohort identified the single nucleotide polymorphism rs2470152 in intron 1 of the CYP19 gene, which codes for aromatase, responsible for the final step of the biosynthesis of E2 and E1, to be most significantly associated with serum E2 levels (P = 2 x 10(-6)). This association was confirmed both in the MrOS Sweden study (P = 9 x 10(-7)) and in the MrOS US study (P = 1 x 10(-4)). When analyzed in all subjects (n = 5531), rs2470152 was clearly associated with both E2 (P = 2 x 10(-14)) and E1 (P = 8 x 10(-19)) levels. In addition, this polymorphism was modestly associated with lumbar spine BMD (P < 0.01) and prevalent self-reported fractures (P < 0.05)., Conclusions: rs2470152 of the CYP19 gene is clearly associated with serum E2 and E1 levels in men.

Rapid development in the annotation of human genetic variation has increased the numbers of single nucleotide polymorphisms (SNPs) in candidate genes by several orders of magnitude. The selection of both useful target SNPs for disease-gene association studies and SNPs associated with the treatment response is therefore an increasingly challenging task. We describe a workflow for selecting SNPs based on their putative function and frequency in candidate genes extracted from PubMed resources. The annotation of each SNP and its frequency in a Caucasian population was assessed in several databases. Approximately 4000 SNPs were identified from an initial 233 candidate genes. In a case study, we performed actual genotyping of 1030 of these SNPs in 213 genes and obtained 710 successfully genotyped SNPs. Using the flow-chart outlined here, only 87 SNPs were monomorphic (approximately 12%). This study reports the frequency of SNPs in a Caucasian population, selected in silico, using a candidate gene approach and validated by actually genotyping 193 individuals. The selected genotypes represent a valuable set of verified candidate SNPs for pharmacogenetic studies in Caucasian populations.

We aimed to develop a microarray genotyping system for multiplex analysis of a panel of single nucleotide polymorphisms (SNPs) in genes encoding proteins involved in blood pressure regulation, and to apply this system in a pilot study demonstrating its feasibility in the pharmacogenetics of hypertension. A panel of 74 SNPs in 25 genes involved in blood pressure regulation was selected from the SNP databases, and genotyped in DNA samples of 97 hypertensive patients. The patients had been randomized to double-blind treatment with either the angiotensin II type 1 receptor blocker irbesartan or the beta 1-adrenergic receptor blocker atenolol. Genotyping was performed using a microarray based DNA polymerase assisted 'minisequencing' single nucleotide primer extension assay with fluorescence detection. The observed genotypes were related to the blood pressure reduction using stepwise multiple regression analysis. The allele frequencies of the selected SNPs were determined in the Swedish population. The established microarray-based genotyping system was validated and allowed unequivocal multiplex genotyping of the panel of 74 SNPs in every patient. Almost 7200 SNP genotypes were generated in the study. Profiles of four or five SNP-genotypes that may be useful as predictors of blood pressure reduction after antihypertensive treatment were identified. Our results highlight the potential of microarray-based technology for SNP genotyping in pharmacogenetics.