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The relationship between eight GWAS-identified single-nucleotide polymorphisms and primary breast cancer outcomes.

ABSTRACT: Several single-nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified through genome-wide association studies (GWAS). We investigated whether eight risk SNPs identified in GWAS were associated with breast cancer disease-free survival (DFS) and overall survival (OS) rates.A cohort of 739 white women with early-stage breast cancer was genotyped for eight GWAS-identified SNPs (rs2981582, rs1219648 [FGFR2], rs3803662, rs12443621, rs8051542 [TOX3], rs999737 [RAD51L1], rs6504950 [17q23], and rs4973768 [3p24]). Relationships between SNPs and breast cancer outcomes were evaluated using Cox proportional hazard regression models. The cumulative effects of SNPs on breast cancer outcomes were assessed by computing the number of at-risk genotypes.At a median follow-up of 121 months (range: 188-231 months) for survivors, 237 deaths (32%) and 186 breast cancer events (25%) were identified among the 739 patients. After adjusting for age, clinical stage, and treatment, rs12443621 (16q12; p = .03) and rs6504950 (17q23; p = .008) were prognostic for OS but not DFS. A higher risk for death was also found in the multivariable analysis of patients harboring three or four at-risk genotypes of the GWAS SNPs compared to patients carrying two or less at-risk genotypes (hazard ratio: 1.60, 95% confidence interval: 1.23-2.24; p = .0008).The study results suggest that previously identified breast cancer risk susceptibility loci, rs12443621 (16q12) and rs6504950 (17q23), may influence breast cancer prognosis or comorbid conditions associated with overall survival. The precise molecular mechanisms through which these risk SNPs, as well as others that were not included in the analysis, influence clinical outcomes remain to be determined.

SUBMITTER: Bayraktar S

PROVIDER: S-EPMC3662839 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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The relationship between eight GWAS-identified single-nucleotide polymorphisms and primary breast cancer outcomes.

Bayraktar Soley S Thompson Patricia A PA Yoo Suk-Young SY Do Kim-anh KA Sahin Aysegul A AA Arun Banu K BK Bondy Melissa L ML Brewster Abenaa M AM

The oncologist 20130501 5

<h4>Background</h4>Several single-nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified through genome-wide association studies (GWAS). We investigated whether eight risk SNPs identified in GWAS were associated with breast cancer disease-free survival (DFS) and overall survival (OS) rates.<h4>Patients and methods</h4>A cohort of 739 white women with early-stage breast cancer was genotyped for eight GWAS-identified SNPs (rs2981582, rs1219648 [FGFR2], rs3803662, r ...[more]

PMID: 23635555

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Project description:BackgroundPrimary hyperparathyroidism (PHPT) affects mainly cortical bone. It is thought that parathyroid hormone (PTH) indirectly regulates the activity of osteoclasts by means of the osteoprotegerin/ligand of the receptor activator of nuclear factor-κβ (OPG/RANKL) system. Several studies have confirmed that OPG (osteoprotegerin) and RANKL (ligand of the receptor activator of nuclear factor-κβ) loci are determinants of bone mineral density (BMD) in the general population. The aim of this study is to analyze the relationship between fractures and BMD and the rs3102735 (163 A/G), rs3134070 (245 T/G) and rs2073618 (1181 G/C) SNPs of the OPG and the rs2277438 SNP of the RANKL, in patients with sporadic PHPT.MethodsWe enrolled 298 Caucasian patients with PHPT and 328 healthy volunteers in a cross-sectional study. We analyzed anthropometric data, history of fractures or renal lithiasis, biochemical determinants including markers for bone remodelling, BMD measurements in the lumbar spine, total hip, femoral neck and distal radius, and genotyping for the SNPs to be studied.ResultsRegarding the age of diagnosis, BMI, menopause status, frequency of fractures or renal lithiasis, we found no differences between genotypes in any of the SNPs studied in the PHPT group. Significant lower BMD in the distal radius with similar PTH levels was found in the minor allele homozygotes (GG) compared to heterozygotes and major allele homozygotes in both OPG rs3102735 (163 A/G) and OPG rs3134070 (245 T/G) SNPs in those with PHPT compared to control subjects. We found no differences between genotypes of the OPG rs2073618 (1181 G/C) SNP with regard to BMD in the PHPT subjects. In the evaluation of rs2277438 SNP of the RANKL in PHPT patients, we found a non significant trend towards lower BMD in the 1/3 distal radius and at total hip in the minor allele homocygotes (GG) genotype group versus heterocygotes and major allele homocygotes (AA).ConclusionsOur study provides the first evaluation of the relationship between SNPs of the OPG/RANK system and sporadic PHPT. Subjects with PHPT and minor homocygote genotype (GG) for the OPG rs3102735 (163 A/G) and OPG rs3134070 (245 T/G) SNPs have lower BMD in the distal radius, and this association does not appear to be mediated by differences in PTH serum levels.

Project description:Interactions among genomic loci (also known as epistasis) have been suggested as one of the potential sources of missing heritability in single locus analysis of genome-wide association studies (GWAS). The computational burden of searching for interactions is compounded by the extremely low threshold for identifying significant p-values due to multiple hypothesis testing corrections. Utilizing prior biological knowledge to restrict the set of candidate SNP pairs to be tested can alleviate this problem, but systematic studies that investigate the relative merits of integrating different biological frameworks and GWAS data have not been conducted.We developed four biologically based frameworks to identify pairwise interactions among candidate SNP pairs as follows: (1) for each human protein-coding gene, a set of SNPs associated with that gene was constructed providing a gene-based interaction model, (2) for each known biological pathway, a set of SNPs associated with the genes in the pathway was constructed providing a pathway-based interaction model, (3) a set of SNPs associated with genes in a disease-related subnetwork provides a network-based interaction model, and (4) a framework is based on the function of SNPs. The last approach uses expression SNPs (eSNPs or eQTLs), which are SNPs or loci that have defined effects on the abundance of transcripts of other genes. We constructed pairs of eSNPs and SNPs located in the target genes whose expression is regulated by eSNPs. For all four frameworks the SNP sets were exhaustively tested for pairwise interactions within the sets using a traditional logistic regression model after excluding genes that were previously identified to associate with the trait. Using previously published GWAS data for type 2 diabetes (T2D) and the biologically based pair-wise interaction modeling, we identify twelve genes not seen in the previous single locus analysis.We present four approaches to detect interactions associated with complex diseases. The results show our approaches outperform the traditional single locus approaches in detecting genes that previously did not reach significance; the results also provide novel drug targets and biomarkers relevant to the underlying mechanisms of disease.

Project description:Genetic risk factors for osteoporosis, a prevalent disease associated with aging, have been examined in many genome-wide association studies (GWASs). A major challenge is to prioritize transcription-regulatory GWAS-derived variants that are likely to be functional. Given the critical role of epigenetics in gene regulation, we have used an unusual epigenetics-based and transcription-based approach to identify some of the credible regulatory single-nucleotide polymorphisms (SNPs) relevant to osteoporosis from 38 reported bone mineral density (BMD) GWASs. Using Roadmap databases, we prioritized SNPs based upon their overlap with strong enhancer or promoter chromatin preferentially in osteoblasts relative to 12 heterologous cell culture types. We also required that these SNPs overlap open chromatin (Deoxyribonuclease I [DNaseI]-hypersensitive sites) and DNA sequences predicted to bind to osteoblast-relevant transcription factors in an allele-specific manner. From >50,000 GWAS-derived SNPs, we identified 14 novel and credible regulatory SNPs (Tier-1 SNPs) for osteoporosis risk. Their associated genes, BICC1, LGR4, DAAM2, NPR3, or HMGA2, are involved in osteoblastogenesis or bone homeostasis and regulate cell signaling or enhancer function. Four of these genes are preferentially expressed in osteoblasts. BICC1, LGR4, and DAAM2 play important roles in canonical Wnt signaling, a pathway critical for bone formation and repair. The transcription factors predicted to bind to the Tier-1 SNP-containing DNA sequences also have bone-related functions. We present evidence that some of the Tier-1 SNPs exert their effects on BMD risk indirectly through little-studied long noncoding RNA (lncRNA) genes, which may, in turn, control the nearby bone-related protein-encoding gene. Our study illustrates a method to identify novel BMD-related causal regulatory SNPs for future study and to prioritize candidate regulatory GWAS-derived SNPs, in general. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

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The relationship between eight GWAS-identified single-nucleotide polymorphisms and primary breast cancer outcomes.

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The relationship between eight GWAS-identified single-nucleotide polymorphisms and primary breast cancer outcomes.

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