Low-penetrance susceptibility variants and postmenopausal oestrogen receptor positive breast cancer

The risk of breast cancer (BC) in women is high and many factors including genetic factors increase the risk for the disease. It is revealed that the variations of low-penetrance susceptibility genes are important for carcinogenesis as they interact with the environmental and hereditary factors. Recently, the list of BC-associated common single nucleotide polymorphisms (SNPs) and chromosomal loci in low-penetrance susceptibility genes have been expanded in genomewide association studies. FGFR2, LSP1, MAP3K1, TGFB1, TOX3, 2q35 and 8q loci variations are some examples for these common SNPs. These SNPs and their association with BC risk was investigated in many different populations. Therefore in this study, we aimed to evaluate low-penetrance susceptibility SNPs; namely FGFR2 rs1219648, rs2981579, rs2981582; MAP3K1 rs889312; TOX3 rs3803662; LSP1 rs909116, rs3817198 and SLC4A7 rs4973768 together, for the first time in Turkish postmenopausal oestrogen receptor positive BC cases. Following the DNA isolation, multiplex PCR and matrix-assisted laser desorption/ionization mass spectrometry with time of flight measurement (MALDI-TOF) based SNP analysis were performed. MAP3K1 rs889312 SNP demonstrated the strongest association with BC risk among the other low penetrant SNPs, it was also associated with BC risk in a dominant model. Only in a ressesive model, TOX3 rs3803662 was associated with BC risk. In addition, rs4973768 CC and rs909116 CC genotypes are correlated with higher tumour size which is not reported in the literature as yet; on the other hand there are no associations between any of the other SNP genotypes and clinopathological parameters. In our opinion, MAP3K1 rs889312 may be a good BC susceptibility biomarker candidate for Turkish population.

Controlling Linkage Disequilibrium in Association Tests: Revisiting APOE Association in Alzheimer's Disease

The allele frequencies of markers as well as linkage disequilibrium (LD) can be changed in cases due to the LD between markers and the disease allele, exhibiting spurious associations of markers. To identify the true association, classical statistical tests for dealing with confounders have been applied to draw a conclusion as to whether the association of variants comes from LD with the known disease allele. However, a more direct test considering LD using estimated haplotype frequencies may be more efficient. The null hypothesis is that the different allele frequencies of a variant between cases and controls come solely from the increased disease allele frequency and the LD relationship with the disease allele. The haplotype frequencies of controls are estimated using the expectation maximization (EM) algorithm from the genotype data. The estimated frequencies are applied to calculate the expected haplotype frequencies in cases corresponding to the increase or decrease of the causative or protective alleles. The suggested method was applied to previously published data, and several APOE variants showed association with Alzheimer's disease independent from the APOE epsilon4 variant, rs429358, regardless of LD showing significant simulated p-values. The test results support the possibility that there may be more than one common disease variant in a locus.