Genotyping of Single Nucleotide Polymorphisms in DNA Isolated from Serum Using Sequenom MassARRAY Technology.

BACKGROUND: Large epidemiologic studies have the potential to make valuable contributions to the assessment of gene-environment interactions because they prospectively collected detailed exposure data. Some of these studies, however, have only serum or plasma samples as a low quantity source of DNA. METHODS: We examined whether DNA isolated from serum can be used to reliably and accurately genotype single nucleotide polymorphisms (SNPs) using Sequenom multiplex SNP genotyping technology. We genotyped 81 SNPs using samples from 158 participants in the NYU Women's Health Study. Each participant had DNA from serum and at least one paired DNA sample isolated from a high quality source of DNA, i.e. clots and/or cell precipitates, for comparison. RESULTS: We observed that 60 of the 81 SNPs (74%) had high call frequencies (≥95%) using DNA from serum, only slightly lower than the 85% of SNPs with high call frequencies in DNA from clots or cell precipitates. Of the 57 SNPs with high call frequencies for serum, clot, and cell precipitate DNA, 54 (95%) had highly concordant (>98%) genotype calls across all three sample types. High purity was not a critical factor to successful genotyping. CONCLUSIONS: Our results suggest that this multiplex SNP genotyping method can be used reliably on DNA from serum in large-scale epidemiologic studies.

Unravelling the genetic basis of renal diseases; from single gene to multifactorial disorders.

Chronic kidney disease is common with up to 5% of the adult population reported to have an estimated glomerular filtration rate of < 60 ml/min/1.73 m(2). A large number of pathogenic mutations have been identified that are responsible for 'single gene' renal disorders, such as autosomal dominant polycystic kidney disease and X-linked Alport syndrome. These single gene disorders account for < 15% of the burden of end-stage renal disease that requires dialysis or kidney transplantation. It has proved more difficult to identify the genetic susceptibility underlying common, complex, multifactorial kidney conditions, such as diabetic nephropathy and hypertensive nephrosclerosis. This review describes success to date and explores strategies currently employed in defining the genetic basis for a number of renal disorders. The complementary use of linkage studies, candidate gene and genome-wide association analyses are described and a collation of renal genetic resources highlighted.

Targeted genome-wide investigation identifies novel SNPs associated with diabetic nephropathy.

Loci contributing to complex disease have been identified by focusing on genome-wide scans utilising non-synonymous single nucleotide polymorphisms (nsSNPs). We employed Illumina's HNS12 BeadChip (13,917 high-value SNPs) which was specifically designed to capture nsSNPs and ideally complements more dense genome-wide association studies that fail to consider many of these putatively functional variants. The HNS12 panel also includes 870 tag SNPs covering the major histocompatibility region. All individuals genotyped in this study were Caucasians with (cases) and without (controls) diabetic nephropathy. About 449 individuals with type 2 diabetes (203 cases, 246 controls) were genotyped in the initial study. 1,467 individuals with type 1 diabetes (718 cases, 749 controls) were genotyped in the follow up study. 11,152 SNPs were successfully analysed and ranked for association with diabetic nephropathy based on significance (P) values. The top ranked 32 SNPs were subsequently genotyped using MassARRAY iPLEX(™) and TaqMan technologies to investigate association of these polymorphisms with nephropathy in individuals with type 1 diabetes. The top ranked nsSNP, rs1543547 (P = 10(-5)), is located in RAET1L, a major histocompatibility class I-related gene at 6q25.1. Of particular interest, multiple nsSNPs within the top ranked (0.2%) SNPs are within several plausible candidate genes for nephropathy on 3q21.3 and 6p21.3.

Polymorphisms in XPC and ERCC2 genes, smoking and breast cancer risk.

To evaluate the associations of breast cancer risk with polymorphisms in the XPC and XPD/ERCC2 DNA nucleotide excision repair genes, a case-control study nested within a prospective cohort of 14,274 women was conducted. Genotypes were characterized for 612 incident, invasive breast cancer cases and their 1:1 matched controls. The homozygous variant of a poly(AT) insertion/deletion polymorphism in intron 9 of the XPC gene (XPC-PAT+/+), was associated with breast cancer risk [odds ratio (OR) = 1.45, 95% confidence interval: 1.07-1.97], after adjustment for other breast cancer risk factors. The breast cancer risk associated with XPC-PAT+/+ did not differ by age at diagnosis. There was an indication of an interaction (p = 0.08) between the XPC-PAT+/+ genotype and cigarette smoking. Ever smokers with the XPC-PAT+/+ genotype were at elevated risk of breast cancer (OR = 1.56, CI: 0.95-2.58), but no differences were observed among never smokers. Analyses of the ERCC2 Lys751Gln polymorphism did not show an association with breast cancer risk, either overall or at younger ages. The results suggest that breast cancer risk is related to the XPC haplotype tagged by the XPC-PAT+/+ insertion-deletion polymorphism in intron 9. Further study of the XPC haplotypes and their interactions with smoking in relation to breast cancer risk is needed.