Astrid Irwanto

Assessing interactions between the associations of common genetic susceptibility variants, reproductive history and body mass index with breast cancer risk in the breast cancer association consortium: a combined case-control study.

IntroductionSeveral common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium.MethodsWe evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects.ResultsThese analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar.ConclusionsThe relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified.

A combined analysis of genome-wide association studies in breast cancer.

In an attempt to identify common disease susceptibility alleles for breast cancer, we performed a combined analysis of three genome-wide association studies (GWAS), involving 2,702 women of European ancestry with invasive breast cancer and 5,726 controls. Tests for association were performed for 285,984 SNPs. Evidence for association with SNPs in genes in specific pathways was assessed using a permutation-based approach. We confirmed associations with loci reported by previous GWAS on 1p11.2, 2q35, 3p, 5p12, 8q24, 10q23.13, 14q24.1 and 16q. Six SNPs with the strongest signals of association with breast cancer, and which have not been reported previously, were typed in two further studies; however, none of the associations could be confirmed. Suggestive evidence for an excess of associations was found for genes involved in the regulation of actin cytoskeleton, glycan degradation, alpha-linolenic acid metabolism, circadian rhythm, hematopoietic cell lineage and drug metabolism. Androgen and oestrogen metabolism, a pathway previously found to be associated with the development of postmenopausal breast cancer, was marginally significant (Pxa0=xa00.051 [unadjusted]). These results suggest that further analysis of SNPs in these pathways may identify associations that would be difficult to detect through agnostic single SNP analyses. More effort focused in these aspects of oncology can potentially open up promising avenues for the understanding of breast cancer and its prevention.

Common Breast Cancer Susceptibility Loci Are Associated with Triple-Negative Breast Cancer

Triple-negative breast cancers are an aggressive subtype of breast cancer with poor survival, but there remains little known about the etiologic factors that promote its initiation and development. Commonly inherited breast cancer risk factors identified through genome-wide association studies display heterogeneity of effect among breast cancer subtypes as defined by the status of estrogen and progesterone receptors. In the Triple Negative Breast Cancer Consortium (TNBCC), 22 common breast cancer susceptibility variants were investigated in 2,980 Caucasian women with triple-negative breast cancer and 4,978 healthy controls. We identified six single-nucleotide polymorphisms, including rs2046210 (ESR1), rs12662670 (ESR1), rs3803662 (TOX3), rs999737 (RAD51L1), rs8170 (19p13.1), and rs8100241 (19p13.1), significantly associated with the risk of triple-negative breast cancer. Together, our results provide convincing evidence of genetic susceptibility for triple-negative breast cancer.

A Genome-wide Association Study of Early-Onset Breast Cancer Identifies PFKM as a Novel Breast Cancer Gene and Supports a Common Genetic Spectrum for Breast Cancer at Any Age

Early-onset breast cancer (EOBC) causes substantial loss of life and productivity, creating a major burden among women worldwide. We analyzed 1,265,548 Hapmap3 single-nucleotide polymorphisms (SNP) among a discovery set of 3,523 EOBC incident cases and 2,702 population control women ages ≤ 51 years. The SNPs with smallest P values were examined in a replication set of 3,470 EOBC cases and 5,475 control women. We also tested EOBC association with 19,684 genes by annotating each gene with putative functional SNPs, and then combining their P values to obtain a gene-based P value. We examined the gene with smallest P value for replication in 1,145 breast cancer cases and 1,142 control women. The combined discovery and replication sets identified 72 new SNPs associated with EOBC (P < 4 × 10−8) located in six genomic regions previously reported to contain SNPs associated largely with later-onset breast cancer (LOBC). SNP rs2229882 and 10 other SNPs on chromosome 5q11.2 remained associated (P < 6 × 10−4) after adjustment for the strongest published SNPs in the region. Thirty-two of the 82 currently known LOBC SNPs were associated with EOBC (P < 0.05). Low power is likely responsible for the remaining 50 unassociated known LOBC SNPs. The gene-based analysis identified an association between breast cancer and the phosphofructokinase-muscle (PFKM) gene on chromosome 12q13.11 that met the genome-wide gene-based threshold of 2.5 × 10−6. In conclusion, EOBC and LOBC seem to have similar genetic etiologies; the 5q11.2 region may contain multiple distinct breast cancer loci; and the PFKM gene region is worthy of further investigation. These findings should enhance our understanding of the etiology of breast cancer. Cancer Epidemiol Biomarkers Prev; 23(4); 658–69. ©2014 AACR.

A genome-wide association scan on estrogen receptor-negative breast cancer.

IntroductionBreast cancer is a heterogeneous disease and may be characterized on the basis of whether estrogen receptors (ER) are expressed in the tumour cells. ER status of breast cancer is important clinically, and is used both as a prognostic indicator and treatment predictor. In this study, we focused on identifying genetic markers associated with ER-negative breast cancer risk.MethodsWe conducted a genome-wide association analysis of 285,984 single nucleotide polymorphisms (SNPs) genotyped in 617 ER-negative breast cancer cases and 4,583 controls. We also conducted a genome-wide pathway analysis on the discovery dataset using permutation-based tests on pre-defined pathways. The extent of shared polygenic variation between ER-negative and ER-positive breast cancers was assessed by relating risk scores, derived using ER-positive breast cancer samples, to disease state in independent, ER-negative breast cancer cases.ResultsAssociation with ER-negative breast cancer was not validated for any of the five most strongly associated SNPs followed up in independent studies (1,011 ER-negative breast cancer cases, 7,604 controls). However, an excess of small P-values for SNPs with known regulatory functions in cancer-related pathways was found (global P = 0.052). We found no evidence to suggest that ER-negative breast cancer shares a polygenic basis to disease with ER-positive breast cancer.ConclusionsER-negative breast cancer is a distinct breast cancer subtype that merits independent analyses. Given the clinical importance of this phenotype and the likelihood that genetic effect sizes are small, greater sample sizes and further studies are required to understand the etiology of ER-negative breast cancers.

A functional brain-derived neurotrophic factor (BDNF) gene variant increases the risk of moderate-to-severe allergic rhinitis

BACKGROUNDnBrain-derived neurotrophic factor (BDNF) is a secretory protein that has been implicated in the pathogenesis of allergic rhinitis (AR), atopic asthma, and eczema, but it is currently unknown whether BDNF polymorphisms influence susceptibility to moderate-to-severe AR.nnnOBJECTIVEnWe sought to identify disease associations and the functional effect of BDNF genetic variants in patients with moderate-to-severe AR.nnnMETHODSnTagging single nucleotide polymorphisms (SNPs) spanning the BDNF gene were selected from the human HapMap Han Chinese from Beijing (CHB) data set, and associations with moderate-to-severe AR were assessed in 2 independent cohorts of Chinese patients (2216 from Shandong province and 1239 living in Singapore). The functional effects of the BDNF genetic variants were determined by using both inxa0vitro and exxa0vivo assays.nnnRESULTSnThe tagging SNP rs10767664 was significantly associated with the risk of moderate-to-severe AR in both Singapore Chinese (Pxa0= .0017; odds ratio, 1.324) and Shandongxa0Chinese populations (Pxa0= .039; odds ratio, 1.180). The coding nonsynonymous SNP rs6265 was in perfect linkage with rs10767664 and conferred increased BDNF protein secretion by a human cell line inxa0vitro. Subjects bearing the AA genotype of rs10767664 exhibited increased risk of moderate-to-severe AR and displayed increased BDNF protein and total IgE levels in plasma. Using a large-scale expression quantitative trait locus study, we demonstrated that BDNF SNPs are significantly associated with altered BDNF concentrations in peripheral blood.nnnCONCLUSIONnA common genetic variant of the BDNF gene is associated with increased risk of moderate-to-severe AR, andxa0the AA genotype is associated with increased BDNF mRNAxa0levels in peripheral blood. Together, these data indicate that functional BDNF gene variants increase the risk of moderate-to-severe AR.

Germline variation in TP53 regulatory network genes associates with breast cancer survival and treatment outcome

Germline variation in the TP53 network genes PRKAG2, PPP2R2B, CCNG1, PIAS1 and YWHAQ was previously suggested to have an impact on drug response in vitro. Here, we investigated the effect on breast cancer survival of germline variation in these genes in 925 Finnish breast cancer patients and further analyzed five single nucleotide polymorphisms (SNPs) in PRKAG2 (rs1029946, rs4726050, rs6464153, rs7789699) and PPP2R2B (rs10477313) for 10‐year survival in breast cancer patients, interaction with TP53 R72P and MDM2‐SNP309, outcome after specific adjuvant therapy and correlation to tumor characteristics in 4,701 invasive cases from four data sets. We found evidence for carriers of PRKAG2‐rs1029946 and PRKAG2‐rs4726050 having improved survival in the pooled data (HR 0.53, 95% CI 0.3–0.9; p = 0.023 for homozygous carriers of the rare G‐allele and HR 0.85, 95% CI 0.7–0.9; p = 0.049 for carriers of the rare G allele, respectively). PRKAG2‐rs4726050 showed a significant interaction with MDM2‐SNP309, with PRKAG2‐rs4726050 rare G‐allele having a dose‐dependent effect for better breast cancer survival confined only to MDM2 SNP309 rare G‐allele carriers (HR 0.45, 95% CI 0.2–0.7; p = 0.001). This interaction also emerged as an independent predictor of better survival (p = 0.047). PPP2R2B‐rs10477313 rare A‐allele was found to predict better survival (HR 0.82, 95% CI 0.6–0.9; p = 0.018), especially after hormonal therapy (HR 0.66, 95% CI 0.5–0.9; p = 0.048). These findings warrant further studies and suggest that genetic markers in TP53 network genes such as PRKAG2 and PPP2R2B might affect prognosis and treatment outcome in breast cancer patients.

Genome-Wide Analysis of Protein-Coding Variants in Leprosy

Although genome-wide association studies have greatly advanced our understanding of the contribution of common noncoding variants to leprosy susceptibility, protein-coding variants have not been systematically investigated. We carried out a three-stage genome-wide association study of protein-coding variants in Hanxa0Chinese, of whom were 7,048 leprosy patients and 14,398 were healthy control subjects. Seven coding variants of exome-wide significance were discovered, including two rare variants: rs145562243 in NCKIPSD (Pxa0=xa01.71xa0× 10-9, odds ratio [OR]xa0= 4.35) and rs149308743 in CARD9 (Pxa0=xa02.09xa0× 10-8, ORxa0= 4.75); three low-frequency variants: rs76418789 in IL23R (Pxa0= 1.03xa0× 10-10, ORxa0= 1.36), rs146466242 in FLG (Pxa0= 3.39xa0× 10-12, ORxa0= 1.45), and rs55882956 in TYK2 (Pxa0= 1.04xa0× 10-6, ORxa0= 1.30); and two common variants: rs780668 in SLC29A3 (Pxa0= 2.17xa0× 10-9, ORxa0= 1.14) and rs181206 in IL27 (Pxa0= 1.08xa0× 10-7, ORxa0= 0.83). Discovered protein-coding variants, particularly low-frequency and rare ones, showed involvement of skin barrier and endocytosis/phagocytosis/autophagy, in addition to known innate and adaptive immunity, in the pathogenesis of leprosy, highlighting the merits of protein-coding variant studies for complex diseases.

7q21-rs6964587 and breast cancer risk: An extended case-control study by the Breast Cancer Association Consortium

Background Using the Breast Cancer Association Consortium, the authors previously reported that the single nucleotide polymorphism 7q21-rs6964587 (AKAP9-M463I) is associated with breast cancer risk. The authors have now assessed this association more comprehensively using 16 independent case–control studies. Methods The authors genotyped 14u2008843 invasive case patients and 19u2008852 control subjects with white European ancestry and 2595 invasive case patients and 2192 control subjects with Asian ancestry. ORs were estimated by logistic regression, adjusted for study. Heterogeneity in ORs was assessed by fitting interaction terms or by subclassifying case patients and applying polytomous logistic regression. Results For white European women, the minor T allele of 7q21-rs6964587 was associated with breast cancer risk under a recessive model (OR 1.07, 95% CI 1.00 to 1.13, p=0.04). Results were inconclusive for Asian women. From a combined analysis of 24u2008154 case patients and 33u2008376 control subjects of white European ancestry from the present and previous series, the best-fitting model was recessive, with an estimated OR of 1.08 (95% CI 1.03 to 1.13, p=0.001). The OR was greater at younger ages (p trend=0.01). Conclusion This may be the first common susceptibility allele for breast cancer to be identified with a recessive mode of inheritance.

Investigating the genetic relationship between Alzheimer’s disease and cancer using GWAS summary statistics

Growing evidence from both epidemiology and basic science suggest an inverse association between Alzheimer’s disease (AD) and cancer. We examined the genetic relationship between AD and various cancer types using GWAS summary statistics from the IGAP and GAME-ON consortia. Sample size ranged from 9931 to 54,162; SNPs were imputed to the 1000 Genomes European panel. Our results based on cross-trait LD Score regression showed a significant positive genetic correlation between AD and five cancers combined (colon, breast, prostate, ovarian, lung; rgxa0=xa00.17, Pxa0=xa00.04), and specifically with breast cancer (ER-negative and overall; rgxa0=xa00.21 and 0.18, Pxa0=xa00.035 and 0.034) and lung cancer (adenocarcinoma, squamous cell carcinoma and overall; rgxa0=xa00.31, 0.38 and 0.30, Pxa0=xa00.029, 0.016, and 0.006). Estimating the genetic correlation in specific functional categories revealed mixed positive and negative signals, notably stronger at annotations associated with increased enhancer activity. This suggests a role of gene expression regulators in the shared genetic etiology between AD and cancer, and that some shared variants modulate disease risk concordantly while others have effects in opposite directions. Due to power issues, we did not detect cross-phenotype associations at individual SNPs. This genetic overlap is not likely driven by a handful of major loci. Our study is the first to examine the co-heritability of AD and cancer leveraging large-scale GWAS results. The functional categories highlighted in this study need further investigation to illustrate the details of the genetic sharing and to bridge between different levels of associations.