Biology subjects

Bojesen, S. E.

Publications and source records attributed to Bojesen, S. E..

6 recordsLinked to original sources

bioRxiv2021

Rare copy number variants (CNVs) and breast cancer risk

BackgroundCopy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. ResultsGene burden tests detected the strongest association for deletions in BRCA1 (P= 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P= 0.0008), ATM (P= 0.002) and BRCA2 (P= 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. ConclusionsThis is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

genetics↗

bioRxiv2019

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. To identify novel loci, we performed a genome-wide association study (GWAS) including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status and tumor grade. We identified 32 novel susceptibility loci (P<5.0x10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate <0.05). Five loci showed associations (P<0.05) in opposite directions between luminal- and non-luminal subtypes. In-silico analyses showed these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 37.6% for triple-negative and 54.2% for luminal A-like disease. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

genetics↗

bioRxiv2019

Common breast cancer risk loci predispose to distinct tumor subtypes

BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER), but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate <5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at P<0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. ConclusionThis report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

genetics↗

bioRxiv2019

Immune-mediated genetic pathways resulting in pulmonary function impairment increase lung cancer susceptibility

Impaired lung function is often caused by cigarette smoking, making it challenging to disentangle its role in lung cancer susceptibility. Investigation of the shared genetic basis of these phenotypes in the UK Biobank and International Lung Cancer Consortium (29,266 cases, 56,450 controls) shows that lung cancer is genetically correlated with reduced forced expiratory volume in one second (FEV1: rg=0.098, p=2.3x10-8) and the ratio of FEV1 to forced vital capacity (FEV1/FVC: rg=0.137, p=2.0x10-12). Mendelian randomization analyses demonstrate that reduced FEV1 increases squamous cell carcinoma risk (odds ratio (OR)=1.51, 95% confidence intervals: 1.21-1.88), while reduced FEV1/FVC increases the risk of adenocarcinoma (OR=1.17, 1.01-1.35) and lung cancer in never smokers (OR=1.56, 1.05-2.30). These findings support a causal role of pulmonary impairment in lung cancer etiology. Integrative analyses reveal that pulmonary function instruments, including 73 novel variants, influence lung tissue gene expression and implicate immune-related pathways in mediating the observed effects on lung carcinogenesis.

genetics↗

bioRxiv2018

Epigenetic regulation of PAR4-related platelet activation: mechanistic links between environmental exposure and cardiovascular disease

Protease-activated receptor 4 (PAR4) is a potent thrombin receptor. Epigenetic control of the F2RL3 locus (which encodes for PAR4) via DNA methylation is associated with both smoking and cardiovascular disease. We examined the association between DNA hypomethylation at F2RL3 and risk of cardiovascular disease, focusing on acute myocardial infarction (AMI) (n=853 cases / 2,352 controls). We used in vitro cell models to dissect the role of DNA methylation in regulating expression of F2RL3. We investigated the interplay between F2RL3 DNA methylation and platelet function in human (n=41). Lastly, we used Mendelian randomization to unify observational and functional work by assessing evidence for causal relationships using data from UK Biobank (n=407,141) and CARDIoGRAMplusC4D (n=184,305). Observationally, one standard deviation (SD) decrease in DNA methylation at F2RL3 was associated with a 25% increase in the odds of AMI. In vitro, short-term exposure of cells to cigarette smoke reduced F2RL3 DNA methylation and increased gene expression. Transcriptional assays flagged a role for a CEBP recognition sequence in modulating the enhancer activity of F2RL3 exon 2. Lower DNA methylation at F2RL3 was associated with increased platelet reactivity in human. The estimated casual odds ratio of ischaemic heart disease was 1.03 (95% CI: 1.00, 1.07) per 1 SD decrease in F2RL3 DNA. In conclusion, we show that DNA methylation-dependent platelet activation is part of a complex system of features contributing to cardiovascular health. Tailoring therapeutic intervention to new knowledge of F2RL3/PAR4 function should be explored to ameliorate the detrimental effects of this risk factor on cardiovascular health.\n\nOne sentence summaryDNA methylation-dependent platelet activation is a likely causal contributor to cardiovascular health.

epidemiology↗

bioRxiv2018

Biomarker de-Mendelization: principles, potentials and limitations of a strategy to improve biomarker prediction by reducing the component of variance explained by genotype

In observational studies, the Mendelian randomization approach can be used to circumvent confounding, bias and reverse causation, and to assess a potential causal association between a biomarker and risk of disease. If, on the other hand, a substantial component of variance of a non-causal biomarker is explained by genotype, then genotype could potentially attenuate the observational association and the strength of the prediction. In order to reduce the component of variance explained by genotype, an approach that can be seen as the inverse of Mendelian randomization - biomarker de-Mendelization - appears plausible.Plasma YKL-40 is a good candidate for demonstrating principles of biomarker de-Mendelization because it is a non-causal biomarker with a substantial component of variance explained by genotype. This approach is an attempt to improve the observational association and the strength of a predictive biomarker; it is explicitly not aimed at detection of causal effects.\n\nWe studied 21 161 individuals form the Danish general population with measurements of YKL-40 concentration and rs4950928 genotype. Four different methods for biomarker de-Mendelization are explored for alcoholic liver cirrhosis and lung cancer.\n\nDe-Mendelization methods only improved predictive ability slighly. We observed an interaction between genotype and markers of developing disease with respect to YKL-40 concentration.\n\nEven when genotype explains 14% of the variance in a non-causal biomarker, we found no useful empirical improvement in risk prediction by biomarker de-Mendelization. This could reflect the predictive interaction between genotype and disease development being removed which counterbalanced any beneficial properties of the method in this situation.

epidemiology↗