A5005824105- Cancer Genomics and Diagnostics
- BRCA gene mutations in cancer
- Genetic Associations and Epidemiology
- Genomics and Rare Diseases
- Genetic factors in colorectal cancer
- Molecular Biology Techniques and Applications
- Nutrition, Genetics, and Disease
- Lung Cancer Treatments and Mutations
- Global Cancer Incidence and Screening
- Prostate Cancer Treatment and Research
- Cancer-related molecular mechanisms research
- Colorectal Cancer Screening and Detection
- Genomics and Chromatin Dynamics
- Ovarian cancer diagnosis and treatment
- Epigenetics and DNA Methylation
University of Cambridge
2022-2025
ABSTRACT In large cohort studies the number of unaffected individuals outnumbers affected individuals, and power can be low to detect associations for outcomes with prevalence. We consider how including recorded family history in regression models increases between genetic variants disease risk. show theoretically using Monte‐Carlo simulations that a disease, weighting 0.5 compared true cases, associations. This is powerful approach detecting moderate effects, but larger effect sizes >...
Prostate cancer (PCa) is highly heritable. No validated PCa risk model currently exists. We therefore sought to develop a genetic that can provide personalized predicted risks on the basis of known moderate- high-risk pathogenic variants, low-risk common and explicit family history, externally validate in an independent prospective cohort.
Deleterious germline variants in
The BOADICEA model predicts breast cancer risk using family history, epidemiological and genetic data. We evaluated its validity in a large prospective cohort.
Abstract In large cohort studies the number of unaffected individuals outnumbers affected individuals, and power can be low to detect associations for outcomes with prevalence. We consider how including recorded family history in regression models increases between genetic variants disease risk. show theoretically using Monte-Carlo simulations that disease, a weighting 0.5 compared true cases, associations. This is powerful approach detecting moderate effects, but larger effect sizes >0.5...
Abstract Recent exome-wide association studies have explored the role of coding variants in breast cancer risk, highlighting rare multiple genes including BRCA1, BRCA2, CHEK2, ATM and PALB2 , as well new susceptibility e.g., MAP3K1 . These genes, however, explain a small proportion missing heritability disease. Much likely lies non-coding genome. We evaluated 5’ 3’ untranslated regions (UTRs) 18,676 35,201 putative promoter regions, using whole-genome sequencing data from UK Biobank on 8,001...
Summary Background Deleterious germline variants in ATM and CHEK2 have been associated with a moderately increased risk of breast cancer. Risks for other cancers remain unclear, require further investigation. Methods Cancer associations coding were evaluated using whole-exome sequenced data from UK Biobank linked to cancer registration (348,488 participants), analysed both as retrospective case-control prospective cohort study. Odds ratios, hazard combined relative risks (RRs) estimated by...
Abstract Background The clinical validity of the multifactorial BOADICEA model for epithelial tubo-ovarian cancer (EOC) risk prediction has not been assessed in a large sample size or over longer term. Methods We evaluated discrimination and calibration UK Biobank cohort comprising 199,429 women (733 incident EOCs) European ancestry without previous history. predicted 10-year EOC incorporating data on questionnaire-based factors (QRFs), family history, 36-SNP polygenic score pathogenic...
Genome-wide association studies have been highly successful at identifying common variants associated with cancer, however, they do not explain all the inherited risk of cancer. Family-based studies, targeted sequencing and, more recently, exome-wide identified rare coding in some genes cancer risk, but overall contribution these to heritability is less clear. Here we describe a method estimate genome-wide that fits models burden effect sizes using an empirical Bayesian approach. We apply...
Introductory paragraph Linkage and candidate gene studies have identified several breast cancer susceptibility genes, but the overall contribution of coding variation to is unclear. To evaluate role rare variants more comprehensively, we performed a meta-analysis across three large whole-exome sequencing datasets, containing 16,498 cases 182,142 controls. Burden tests were for protein-truncating missense in 16,562 18,681 genes respectively. Associations between 7 at exome-wide significance (...