https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:44999 Wed 26 Oct 2022 10:12:59 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42701 Wed 22 Mar 2023 15:07:38 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:19379 Wed 11 Apr 2018 14:19:24 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:37129 via the integration of genomics and proteomics data. In the Breast Cancer Association Consortium (BCAC), with 122,977 cases and 105,974 controls of European descendants, we evaluated the associations of the genetically predicted concentrations of >1,400 circulating proteins with breast cancer risk. We used data from a large-scale protein quantitative trait loci (pQTL) analysis as our study instrument. Summary statistics for these pQTL variants related to breast cancer risk were obtained from the BCAC and used to estimate odds ratios (OR) for each protein using the inverse-variance weighted method. We identified 56 proteins significantly associated with breast cancer risk by instrumental analysis (false discovery rate <0.05). Of these, the concentrations of 32 were influenced by variants close to a breast cancer susceptibility locus (ABO, 9q34.2). Many of these proteins, such as insulin receptor, insulin-like growth factor receptor 1 and other membrane receptors (OR: 0.82-1.18, p values: 6.96 × 10^-43.28 × 10^-8), are linked to insulin resistance and estrogen receptor signaling pathways. Proteins identified at other loci include those involved in biological processes such as alcohol and lipid metabolism, proteolysis, apoptosis, immune regulation and cell motility and proliferation. Consistent associations were observed for 22 proteins in the UK Biobank data (p < 0.05). The study identifies potential novel biomarkers for breast cancer, but further investigation is needed to replicate our findings.]]> Wed 07 Apr 2021 20:21:39 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:47795 Tue 31 Jan 2023 15:32:49 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:41408 Tue 21 Mar 2023 18:03:04 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:54872 Tue 19 Mar 2024 16:38:34 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52761 Tue 14 Nov 2023 15:30:24 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:48335 Tue 14 Mar 2023 17:16:01 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42894 Tue 06 Sep 2022 14:32:21 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:45124 Thu 27 Oct 2022 10:53:06 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49307 Thu 11 May 2023 14:39:42 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46914 Thu 08 Dec 2022 08:47:20 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20582 Sat 24 Mar 2018 07:55:36 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:44579 Mon 17 Oct 2022 14:17:20 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:24831 -8) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ~11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.]]> Mon 11 Mar 2019 12:13:11 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:45355 loss-of-function (LoF) variants in the base excision repair (BER) gene NTHL1 cause a high-risk hereditary multi-tumor syndrome that includes breast cancer, but the contribution of heterozygous variants to hereditary breast cancer is unknown. An analysis of 4985 women with breast cancer, enriched for familial features, and 4786 cancer-free women revealed significant enrichment for NTHL1 LoF variants. Immunohistochemistry confirmed reduced NTHL1 expression in tumors from heterozygous carriers but the NTHL1 bi-allelic loss characteristic mutational signature (SBS 30) was not present. The analysis was extended to 27,421 breast cancer cases and 19,759 controls from 10 international studies revealing 138 cases and 93 controls with a heterozygous LoF variant (OR 1.06, 95% CI: 0.82-1.39) and 316 cases and 179 controls with a missense variant (OR 1.31, 95% CI: 1.09-1.57). Missense variants selected for deleterious features by a number of in silico bioinformatic prediction tools or located within the endonuclease III functional domain showed a stronger association with breast cancer. Somatic sequencing of breast cancers from carriers indicated that the risk associated with NTHL1 appears to operate through haploinsufficiency, consistent with other described low-penetrance breast cancer genes. Data from this very large international multicenter study suggests that heterozygous pathogenic germline coding variants in NTHL1 may be associated with low- to moderate- increased risk of breast cancer.]]> Mon 01 May 2023 14:42:02 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46399 313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS₃₁₃ odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS₃₁₃ and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS₃₁₃ and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.]]> Fri 18 Nov 2022 14:15:23 AEDT ]]>