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| 2. |
- Hollestelle, Antoinette, et al.
(författare)
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No clinical utility of KRAS variant rs61764370 for ovarian or breast cancer
- 2016
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Ingår i: Gynecologic Oncology. - : Elsevier BV. - 0090-8258 .- 1095-6859. ; 141:2, s. 386-401
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Tidskriftsartikel (refereegranskat)abstract
- Objective Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3′ UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370. Methods Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers). Results We found no association with risk of ovarian cancer (OR = 0.99, 95% CI 0.94-1.04, p = 0.74) or breast cancer (OR = 0.98, 95% CI 0.94-1.01, p = 0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR = 1.09, 95% CI 0.97-1.23, p = 0.14, breast cancer HR = 1.04, 95% CI 0.97-1.12, p = 0.27; BRCA2, ovarian cancer HR = 0.89, 95% CI 0.71-1.13, p = 0.34, breast cancer HR = 1.06, 95% CI 0.94-1.19, p = 0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR = 0.94, 95% CI 0.83-1.07, p = 0.38), breast cancer (HR = 0.96, 95% CI 0.87-1.06, p = 0.38), and all other previously-reported associations. Conclusions rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.
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| 3. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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| 4. |
- Hamdi, Yosr, et al.
(författare)
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Association of breast cancer risk in BRCA1 and BRCA2 mutation carriers with genetic variants showing differential allelic expression : identification of a modifier of breast cancer risk at locus 11q22.3
- 2017
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Ingår i: Breast Cancer Research and Treatment. - : Springer Science and Business Media LLC. - 0167-6806 .- 1573-7217. ; 161:1, s. 117-134
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Cis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways. Methods: Using data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of ~320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2. Results: We identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 × 10−6). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance. Conclusion: We identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk.
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| 5. |
- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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| 6. |
- Augustin, Livia S. A., et al.
(författare)
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Dietary Fibre Consensus from the International Carbohydrate Quality Consortium (ICQC)
- 2020
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Ingår i: Nutrients. - : MDPI. - 2072-6643. ; 12:9
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Tidskriftsartikel (refereegranskat)abstract
- Dietary fibre is a generic term describing non-absorbed plant carbohydrates and small amounts of associated non-carbohydrate components. The main contributors of fibre to the diet are the cell walls of plant tissues, which are supramolecular polymer networks containing variable proportions of cellulose, hemicelluloses, pectic substances, and non-carbohydrate components, such as lignin. Other contributors of fibre are the intracellular storage oligosaccharides, such as fructans. A distinction needs to be made between intrinsic sources of dietary fibre and purified forms of fibre, given that the three-dimensional matrix of the plant cell wall confers benefits beyond fibre isolates. Movement through the digestive tract modifies the cell wall structure and may affect the interactions with the colonic microbes (e.g., small intestinally non-absorbed carbohydrates are broken down by bacteria to short-chain fatty acids, absorbed by colonocytes). These aspects, combined with the fibre associated components (e.g., micronutrients, polyphenols, phytosterols, and phytoestrogens), may contribute to the health outcomes seen with the consumption of dietary fibre. Therefore, where possible, processing should minimise the degradation of the plant cell wall structures to preserve some of its benefits. Food labelling should include dietary fibre values and distinguish between intrinsic and added fibre. Labelling may also help achieve the recommended intake of 14 g/1000 kcal/day.
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| 7. |
- Couch, Fergus J., et al.
(författare)
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Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer
- 2016
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 7:11375, s. 1-13
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Tidskriftsartikel (refereegranskat)abstract
- Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 x 10(-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 similar to 11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.
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| 8. |
- Jansen, Willemijn J, et al.
(författare)
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Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum.
- 2022
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Ingår i: JAMA neurology. - : American Medical Association (AMA). - 2168-6157 .- 2168-6149. ; 79:3, s. 228-243
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Tidskriftsartikel (refereegranskat)abstract
- One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.Alzheimer disease biomarkers detected on PET or in CSF.Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.Among the 19097 participants (mean [SD] age, 69.1 [9.8] years; 10148 women [53.1%]) included, 10139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P=.04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P=.004), subjective cognitive decline (9%; 95% CI, 3%-15%; P=.005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P=.004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P=.18).This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.
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| 9. |
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| 10. |
- Mavaddat, Nasim, et al.
(författare)
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Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants
- 2015
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 1460-2105 .- 0027-8874. ; 107:5, s. 036-036
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Tidskriftsartikel (refereegranskat)abstract
- Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.
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