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Purpose: Although most patients with estrogen receptor (ER)–positive breast cancer benefit from endocrine therapies, a significant proportion do not. Our aim was to identify inherited genetic variations that might predict survival among patients receiving adjuvant endocrine therapies.Experimental Design: We performed a meta-analysis of two genome-wide studies; Helsinki Breast Cancer Study, 805 patients, with 240 receiving endocrine therapy and Prospective study of Outcomes in Sporadic versus Hereditary breast cancer, 536 patients, with 155 endocrine therapy patients, evaluating 486,478 single-nucleotide polymorphisms (SNP). The top four associations from the endocrine treatment subgroup were further investigated in two independent datasets totaling 5,011 patients, with 3,485 receiving endocrine therapy.Results: A meta-analysis identified a common SNP rs8113308, mapped to 19q13.41, associating with reduced survival among endocrine-treated patients [hazard ratio (HR), 1.69; 95% confidence interval (CI), 1.37–2.07; P = 6.34 × 10−7] and improved survival among ER-negative patients, with a similar trend in ER-positive cases not receiving endocrine therapy. In a multivariate analysis adjusted for conventional prognostic factors, we found a significant interaction between the rs8113308 and endocrine treatment, indicating a predictive, treatment-specific effect of the SNP rs8113308 on breast cancer survival, with the per-allele HR for interaction 2.16 (95% CI, 1.30–3.60; Pinteraction = 0.003) and HR = 7.77 (95% CI, 0.93–64.71) for the homozygous genotype carriers. A biologic rationale is suggested by in silico functional analyses.Conclusions: Our findings suggest carrying the rs8113308 rare allele may identify patients who will not benefit from adjuvant endocrine treatment. Clin Cancer Res; 21(18); 4086–96. ©2015 AACR.

Legends to Supplementary Figures S1 to S6. This document comprises the legends to the supplementary figures.

Supplementary Figure S5. Regional plot using P-values derived from univariate Cox's regression model from HEBCS and POSH GWS meta-analysis and includes both imputed and the genotyped SNPs 250 kb either side of the rs8113308.

Supplementary Figure S1. REMARK diagram describing work flow and sample selection in this study.

Supplementary Methods and Supplementary Tables S1-S6. Supplementary Table S1. Univariate Cox's regression analysis within estrogen receptor positive patients receiving endocrine treatment with stage-1 meta-analysis fullfilling the P-value thresholds. Supplementary Table S2. Association for SNP rs8113308 with clinical and pathological features of the breast cancer tumors in a pooled set of HEBCS GWS, POSH GWS and POSH validation. Supplementary Table S3. Association for SNP rs4767413 with clinical and pathological features of the breast cancer tumors in a pooled set of HEBCS GWS, POSH GWS and POSH validation. Supplementary Table S4. Cis eQTL analysis. Expression in ER positive breast tumor and in ER negative breast tumor from METABRIC. Supplementary Table S5. Peripheral blood eQTL. Supplementary Table S6. Trans eQTL analysis. Expression in ER positive breast tumor and in ER negative breast tumor from METABRIC.

Supplementary Figure S6. Protein-protein interaction network.

Supplementary Figure S3. Kaplan-Meier plots of cumulative 10-year survival of rs8113308 genotypes in POSH validation dataset

Supplementary Figure S4. Forest plots of hazard ratios and their confidence intervals separately for studies HEBCS GWS and POSH GWS (stage-1) and POSH validation and SUCCESS-A (stage-2) along with the meta-analysis P-value of the stage-1 and stage-2.

PDF file - 53K, Regional plot of p-values arising from cox-proportional hazard models, 250 kb either side of the rs3785982 variant in stage-1. P-values are from imputed data alone.

PDF file - 52K, Regional plot of p-values arising from cox-proportional hazard models, 250 kb either side of the rs2774307 variant in stage-1. P-values are from imputed data alone.

PDF file - 36K, Principal Components of whole genome data from the POSH study. The plot shows first two principal component based on post quality control genome wide data.

PDF file - 45K

PDF file - 55K, Regional plot of p-values arising from cox-proportional hazard models, 250 kb either side of the rs3884558 variant in stage-1. P-values are from imputed data alone.

PDF file - 54K, Regional plot of p-values arising from cox-proportional hazard models, 250 kb either side of the rs1387389 variant in stage-1. P-values are from imputed data alone.

Purpose: Although most patients with estrogen receptor (ER)–positive breast cancer benefit from endocrine therapies, a significant proportion do not. Our aim was to identify inherited genetic variations that might predict survival among patients receiving adjuvant endocrine therapies. Experimental Design: We performed a meta-analysis of two genome-wide studies; Helsinki Breast Cancer Study, 805 patients, with 240 receiving endocrine therapy and Prospective study of Outcomes in Sporadic versus Hereditary breast cancer, 536 patients, with 155 endocrine therapy patients, evaluating 486,478 single-nucleotide polymorphisms (SNP). The top four associations from the endocrine treatment subgroup were further investigated in two independent datasets totaling 5,011 patients, with 3,485 receiving endocrine therapy. Results: A meta-analysis identified a common SNP rs8113308, mapped to 19q13.41, associating with reduced survival among endocrine-treated patients [hazard ratio (HR), 1.69; 95% confidence interval (CI), 1.37–2.07; P = 6.34 × 10−7] and improved survival among ER-negative patients, with a similar trend in ER-positive cases not receiving endocrine therapy. In a multivariate analysis adjusted for conventional prognostic factors, we found a significant interaction between the rs8113308 and endocrine treatment, indicating a predictive, treatment-specific effect of the SNP rs8113308 on breast cancer survival, with the per-allele HR for interaction 2.16 (95% CI, 1.30–3.60; Pinteraction = 0.003) and HR = 7.77 (95% CI, 0.93–64.71) for the homozygous genotype carriers. A biologic rationale is suggested by in silico functional analyses. Conclusions: Our findings suggest carrying the rs8113308 rare allele may identify patients who will not benefit from adjuvant endocrine treatment. Clin Cancer Res; 21(18); 4086–96. ©2015 AACR.

Background Self‐rated health ( SRH ) is a strong predictor of mortality in different populations. However, the associations between SRH measures and risk of ischemic heart disease ( IHD ) have not been extensively explored, especially in a Chinese population. Methods and Results More than 500 000 adults from 10 cities in China were followed from baseline (2004–2008) through December 31, 2013. Global and age‐comparative SRH were reported from baseline questionnaires. Incident IHD cases were identified through links to well‐established disease registry systems and the national health insurance system. During 3 423 542 person‐years of follow‐up, we identified 24 705 incident cases of IHD . In multivariable‐adjusted models, both global and age‐comparative SRH was significantly associated with incident IHD . Compared with excellent SRH , the hazard ratios for good, fair, and poor SRH were 1.02 (95% confidence interval [CI], 0.98–1.07), 1.32 (95% CI, 1.27–1.37), and 1.76 (95% CI, 1.68–1.85), respectively. Compared with better age‐comparative SRH , the hazard ratios for same and worse age‐comparative SRH were 1.23 (95% CI, 1.19–1.27) and 1.78 (95% CI, 1.70–1.86), respectively. The associations persisted in all subgroup analyses, although they were slightly modified by study location, education, and income levels. Conclusions A simple questionnaire for self‐assessment of health status was significantly associated with incident IHD in Chinese adults. Individuals and healthcare providers can use SRH measures as a convenient tool for assessing future IHD risk.

Copy number variants (CNVs) play important roles in a number of human diseases and in pharmacogenetics. Powerful methods exist for CNV detection in whole genome sequencing (WGS) data, but such data are costly to obtain. Many disease causal CNVs span or are found in genome coding regions (exons), which makes CNV detection using whole exome sequencing (WES) data attractive. If reliably validated against WGS-based CNVs, exome-derived CNVs have potential applications in a clinical setting. Several algorithms have been developed to exploit exome data for CNV detection and comparisons made to find the most suitable methods for particular data samples. The results are not consistent across studies. Here, we review some of the exome CNV detection methods based on depth of coverage profiles and examine their performance to identify problems contributing to discrepancies in published results. We also present a streamlined strategy that uses a single metric, the likelihood ratio, to compare exome methods, and we demonstrated its utility using the VarScan 2 and eXome Hidden Markov Model (XHMM) programs using paired normal and tumour exome data from chronic lymphocytic leukaemia patients. We use array-based somatic CNV (SCNV) calls as a reference standard to compute prevalence-independent statistics, such as sensitivity, specificity and likelihood ratio, for validation of the exome-derived SCNVs. We also account for factors known to influence the performance of exome read depth methods, such as CNV size and frequency, while comparing our findings with published results.

Summary Recent studies have tested genetic variation at the C1QA, C1QB and C1QC (complement component 1, q subcomponent, A chain, complement component 1, q subcomponent, B chain and complement component 1, q subcomponent, c chain) loci in relation to systemic lupus erythematosus (SLE) risk. Evidence for a significant effect of C1Q locus gene polymorphisms on SLE predisposition remains unclear. We aimed to identify associations between common C1Q polymorphisms and SLE risk and serum C1q, C3 and C4 levels. We performed family-based association tests in 295 nuclear families with one affected proband. Tag-single nucleotide polymorphisms (SNPs) ranging from 35·4 kb upstream of the C1QA gene to 28 kb downstream of the C1QB gene were selected to represent the entire C1Q gene locus. We performed transmission disequilibrium tests for affectation status and continuous traits, including C1q, C3 and C4 levels using family-based association tests (FBAT). There was no evidence for a significant role of C1Q locus gene polymorphisms in SLE risk predisposition. The strongest association was observed with a variant in the 3′UTR region of the C1QB gene (rs294223, P = 0·06). We found nominally significant associations with a second variant (rs7549888) in the 3′UTR region of the C1QB gene and C1q (P = 0·01), C3 (P = 0·004) and C4 levels (P = 0·01). In a large family-based association study of C1Q gene cluster polymorphisms no evidence for a genetic role of C1Q locus SNP in SLE risk predisposition was obtained in patients of European ancestry. This is in contrast to other cohorts, in which single variants associated with C1Q, C3 and C4 levels and nephritis have been studied and shown associations.

Large population-based registry studies have shown that breast cancer prognosis is inherited. Here we analyse single-nucleotide polymorphisms (SNPs) of genes implicated in human immunology and inflammation as candidates for prognostic markers of breast cancer survival involving 1,804 oestrogen receptor (ER)-negative patients treated with chemotherapy (279 events) from 14 European studies in a prior large-scale genotyping experiment, which is part of the Collaborative Oncological Gene-environment Study (COGS) initiative. We carry out replication using Asian COGS samples (n=522, 53 events) and the Prospective Study of Outcomes in Sporadic versus Hereditary breast cancer (POSH) study (n=315, 108 events). Rs4458204_A near CCL20 (2q36.3) is found to be associated with breast cancer-specific death at a genome-wide significant level (n=2,641, 440 events, combined allelic hazard ratio (HR)=1.81 (1.49–2.19); P for trend=1.90 × 10−9). Such survival-associated variants can represent ideal targets for tailored therapeutics, and may also enhance our current prognostic prediction capabilities., Studies have shown that breast cancer prognosis is hereditary. Here the authors show that a genetic variant in CCL20, a chemokine ligand involved in immune response, is significantly associated with breast cancer survival and may therefore represent an important therapeutic or prognostic target.

Genome-Wide Association Studies (GWAS) have begun to investigate associations between inherited genetic variations and breast cancer prognosis. Here, we report our findings from a GWAS conducted in 536 patients with early-onset breast cancer aged 40 or less at diagnosis and with a mean follow-up period of 4.1 years (SD = 1.96). Patients were selected from the Prospective Study of Outcomes in Sporadic versus Hereditary breast cancer. A Bonferroni correction for multiple testing determined that a P value of 1.0 × 10−7 was a statistically significant association signal. Following quality control, we identified 487,496 single nucleotide polymorphisms (SNP) for association tests in stage 1. In stage 2, 35 SNPs with the most significant associations were genotyped in 1,516 independent cases from the same early-onset cohort. In stage 2, 11 SNPs remained associated in the same direction (P ≤ 0.05). Fixed effects meta-analysis models identified one SNP associated at close to genome wide level of significance 556 kb upstream of the ARRDC3 locus [HR = 1.61; 95% confidence interval (CI), 1.33–1.96; P = 9.5 × 10−7]. Four further associations at or close to the PBX1, RORα, NTN1, and SYT6 loci also came close to genome-wide significance levels (P = 10−6). In the first ever GWAS for the identification of SNPs associated with prognosis in patients with early-onset breast cancer, we report a SNP upstream of the ARRDC3 locus as potentially associated with prognosis (median follow-up time for genotypes: CC = 4 years, CT = 3 years, and TT = 2.7 years; Wilcoxon rank-sum test CC vs. CT, P = 4 × 10−4 and CT vs. TT, P = 0.76). Four further loci may also be associated with prognosis. Cancer Res; 73(6); 1883–91. ©2012 AACR.

BACKGROUND: Genome wide association studies (GWAS), mostly in Europeans have identified several common variants as associated with key lipid traits. Replication of these genetic effects in South Asian populations is important since it would suggest wider relevance for these findings. Given the rising prevalence of metabolic disorders and heart disease in the Indian sub-continent, these studies could be of future clinical relevance. METHODS: We studied seven common variants associated with a variety of lipid traits in previous GWASs. The study sample comprised of 3178 sib-pairs recruited as participants for the Indian Migration Study (IMS). Associations with various lipid parameters and quantitative traits were analyzed using the Fulker genetic association model. RESULTS: We replicated five of the 7 main effect associations with p-values ranging from 0.03 to 1.97x10(-7). We identified particularly strong association signals at rs662799 in APOA5 (beta=0.18 s.d, p=1.97 x 10(-7)), rs10503669 in LPL (beta =-0.18 s.d, p=1.0 x 10(-4)) and rs780094 in GCKR (beta=0.11 s.d, p=0.001) loci in relation to triglycerides. In addition, the GCKR variant was also associated with total cholesterol (beta=0.11 s.d, p=3.9x10(-4)). We also replicated the association of rs562338 in APOB (p=0.03) and rs4775041 in LIPC (p=0.007) with LDL-cholesterol and HDL-cholesterol respectively. CONCLUSIONS: We report associations of five loci with various lipid traits with the effect size consistent with the same reported in Europeans. These results indicate an overlap of genetic effects pertaining to lipid traits across the European and Indian populations.

Over the last two decades candidate gene association studies and genome-wide linkage scans have met with little success in characterizing risk variants for hypertension. Several factors could be responsible for the relative lack of success, although our understanding of the genetics has evolved to support the belief that there are multiple common risk variants, which are associated with hypertension with modest effect sizes. Genome-wide association studies (GWAS) have successfully identified risk loci for several complex polygenic disease states. Until recently, the productivity of GWAS with respect to identifying risk loci for hypertension was limited. In this paper we describe the recent success of GWAS of hypertension in identifying over a dozen loci associated with essential hypertension. We will review these findings, and place these results in the context of the future potential of pharmocogenetics of hypertension.

Background. Levels of the proinfl ammatory cytokine interleukin-18 (IL-18) are raised in old age and are associated with reduced physical functioning. Previous studies have indicated that the C allele of the rs5744256 polymorphism in the IL-18 gene is strongly associated with reduced circulating IL-18 levels. This variant has previously been associated with improved locomotor performance in old age, but the fi nding requires independent replication. Methods. We examined the association between the IL-18 polymorphism rs5744256 and physical functioning in three cohorts with a total of 4,107 participants aged 60 – 85 years: the English Longitudinal Study of Ageing, Caerphilly, and Boyd Orr. We meta-analyzed ( N = 6,141) the results with data from the original paper reporting this association: IowaEstablished Populations for Epidemiological Study of the Elderly and InCHIANTI cohorts. Physical functioning was assessed by timed walks or the get up and go test. As locomotor performance tests differed between the cohorts and the distributions of times to complete the test (in seconds) were positively skewed, we used the reciprocal transformation and computed study-specifi c z scores. Results. Based on the three new studies, the estimated linear regression coeffi cient per C allele was 0.011 (95% confi dence interval [95% CI]: � 0.04 to 0.06). A meta-analysis that pooled the data from all studies showed weak evidence of an effect, with a regression coeffi cient of 0.047 (95% CI: 0.010 to 0.083). Conclusions. We did not replicate an association between the IL-18 rs5744256 polymorphism and the physical function in people aged 60 – 85 years. However, pooling data from all studies suggested a weak association of the C allele of the rs5744256 single nucleotide polymorphism on improving walking times in old age .