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1.
Biostatistics ; 2020 Feb 29.
Artigo em Inglês | MEDLINE | ID: mdl-32112086

RESUMO

Cancers are routinely classified into subtypes according to various features, including histopathological characteristics and molecular markers. Previous genome-wide association studies have reported heterogeneous associations between loci and cancer subtypes. However, it is not evident what is the optimal modeling strategy for handling correlated tumor features, missing data, and increased degrees-of-freedom in the underlying tests of associations. We propose to test for genetic associations using a mixed-effect two-stage polytomous model score test (MTOP). In the first stage, a standard polytomous model is used to specify all possible subtypes defined by the cross-classification of the tumor characteristics. In the second stage, the subtype-specific case-control odds ratios are specified using a more parsimonious model based on the case-control odds ratio for a baseline subtype, and the case-case parameters associated with tumor markers. Further, to reduce the degrees-of-freedom, we specify case-case parameters for additional exploratory markers using a random-effect model. We use the Expectation-Maximization algorithm to account for missing data on tumor markers. Through simulations across a range of realistic scenarios and data from the Polish Breast Cancer Study (PBCS), we show MTOP outperforms alternative methods for identifying heterogeneous associations between risk loci and tumor subtypes. The proposed methods have been implemented in a user-friendly and high-speed R statistical package called TOP (https://github.com/andrewhaoyu/TOP).

2.
Nat Commun ; 11(1): 1122, 2020 Feb 28.
Artigo em Inglês | MEDLINE | ID: mdl-32111823

RESUMO

Heart failure is a major public health problem affecting over 23 million people worldwide. In this study, we present the results of a large scale meta-analysis of heart failure GWAS and replication in a comparable sized cohort to identify one known and two novel loci associated with heart failure. Heart failure sub-phenotyping shows that a new locus in chromosome 1 is associated with left ventricular adverse remodeling and clinical heart failure, in response to different initial cardiac muscle insults. Functional characterization and fine-mapping of that locus reveal a putative causal variant in a cardiac muscle specific regulatory region activated during cardiomyocyte differentiation that binds to the ACTN2 gene, a crucial structural protein inside the cardiac sarcolemma (Hi-C interaction p-value = 0.00002). Genome-editing in human embryonic stem cell-derived cardiomyocytes confirms the influence of the identified regulatory region in the expression of ACTN2. Our findings extend our understanding of biological mechanisms underlying heart failure.

3.
Int J Cancer ; 2020 Mar 06.
Artigo em Inglês | MEDLINE | ID: mdl-32142159

RESUMO

The current study aimed to investigate the role of cooking with mustard oil and other dietary factors in relation to gallbladder cancer (GBC) in high- and low-incidence regions of India. A case-control study was conducted including 1,170 histologically confirmed cases and 2,525 group-matched visitor controls from the largest cancer hospital in India. Dietary data were collected through a food frequency questionnaire. For oil consumption we enquired about monthly consumption of 11 different types of cooking oil per family and the number of individuals usually sharing the meal to estimate per-individual consumption of oil. Information about method of cooking was also requested. Odds Ratios (OR) and 95% confidence intervals (CI) quantifying the association of GBC risk consumption of different types of oil, method of cooking, and dietary food items, were estimated using logistic regression models, after adjusting for potential confounders. High consumption of mustard oil was associated with GBC risk in both high- and low-risk regions (OR = 1.33, 95%CI = 0.99-1.78; OR = 3.01, 95%CI = 1.66-5.45) respectively. An increased risk of GBC was observed with deep frying of fresh fish in mustard oil (OR=1.57, 95% CI=0.99-2.47, P-value=0.052). A protective association was observed with consumption of leafy vegetables, fruits, onion and garlic. No association was observed between consumption of meat, spicy food, turmeric, pulses or with any other oil as a cooking medium. The effect of high consumption of mustard oil on GBC risk, if confirmed, has implications for the primary prevention of GBC, via a reduced consumption. This article is protected by copyright. All rights reserved.

4.
PLoS One ; 15(2): e0228198, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32023287

RESUMO

This report describes an R package, called the Individualized Coherent Absolute Risk Estimator (iCARE) tool, that allows researchers to build and evaluate models for absolute risk and apply them to estimate an individual's risk of developing disease during a specified time interval based on a set of user defined input parameters. An attractive feature of the software is that it gives users flexibility to update models rapidly based on new knowledge on risk factors and tailor models to different populations by specifying three input arguments: a model for relative risk, an age-specific disease incidence rate and the distribution of risk factors for the population of interest. The tool can handle missing information on risk factors for individuals for whom risks are to be predicted using a coherent approach where all estimates are derived from a single model after appropriate model averaging. The software allows single nucleotide polymorphisms (SNPs) to be incorporated into the model using published odds ratios and allele frequencies. The validation component of the software implements the methods for evaluation of model calibration, discrimination and risk-stratification based on independent validation datasets. We provide an illustration of the utility of iCARE for building, validating and applying absolute risk models using breast cancer as an example.

5.
Eur J Hum Genet ; 28(3): 300-312, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-31582815

RESUMO

Many complex human diseases, such as type 2 diabetes, are characterized by multiple underlying traits/phenotypes that have substantially shared genetic architecture. Multivariate analysis of correlated traits has the potential to increase the power of detecting underlying common genetic loci. Several cross-phenotype association methods have been proposed-some require individual-level data on traits and genotypes, while the others require only summary-level data. In this article, we explore whether non-normality of multivariate trait distribution affects the inference from some of the existing multi-trait methods and how that effect is dependent on the allele count of the genetic variant being tested. We find that most of these tests are susceptible to biases that lead to spurious association signals. Even after controlling for confounders that may contribute to non-normality and then applying inverse normal transformation on the residuals of each trait, these tests may have inflated type I errors for variants with low minor allele counts (MACs). A likelihood ratio test of association based on the ordinal regression of individual-level genotype conditional on the traits seems to be the least biased and can maintain type I error when the MAC is reasonably large (e.g., MAC > 30). Application of these methods to publicly available summary statistics of eight amino acid traits on European samples seem to exhibit systematic inflation (especially for variants with low MAC), which is consistent with our findings from simulation experiments.

6.
Genomics ; 112(2): 1223-1232, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-31306748

RESUMO

We investigated whether genetic susceptibility to tuberculosis (TB) influences lung adenocarcinoma development among never-smokers using TB genome-wide association study (GWAS) results within the Female Lung Cancer Consortium in Asia. Pathway analysis with the adaptive rank truncated product method was used to assess the association between a TB-related gene-set and lung adenocarcinoma using GWAS data from 5512 lung adenocarcinoma cases and 6277 controls. The gene-set consisted of 31 genes containing known/suggestive associations with genetic variants from previous TB-GWAS. Subsequently, we followed-up with Mendelian Randomization to evaluate the association between TB and lung adenocarcinoma using three genome-wide significant variants from previous TB-GWAS in East Asians. The TB-related gene-set was associated with lung adenocarcinoma (p = 0.016). Additionally, the Mendelian Randomization showed an association between TB and lung adenocarcinoma (OR = 1.31, 95% CI: 1.03, 1.66, p = 0.027). Our findings support TB as a causal risk factor for lung cancer development among never-smoking Asian women.

7.
Cancer Epidemiol Biomarkers Prev ; 29(2): 452-459, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31848206

RESUMO

BACKGROUND: High disease burden suggests the desirability to identify high-risk Asian never-smoking females (NSF) who may benefit from low-dose CT (LDCT) screening. In North America, one is eligible for LDCT screening if one satisfies the U.S. Preventive Services Task Force (USPSTF) criteria or has model-estimated 6-year risk greater than 0.0151. According to two U.S. reports, only 36.6% female patients with lung cancer met the USPSTF criteria, while 38% of the ever-smokers ages 55 to 74 years met the USPSTF criteria. METHODS: Using data on NSFs in the Taiwan Genetic Epidemiology Study of Lung Adenocarcinoma and the Taiwan Biobank before August 2016, we formed an age-matched case-control study consisting of 1,748 patients with lung cancer and 6,535 controls. Using these and an estimated age-specific lung cancer 6-year incidence rate among Taiwanese NSFs, we developed the Taiwanese NSF Lung Cancer Risk Models using genetic information and simplified questionnaire (TNSF-SQ). Performance evaluation was based on the newer independent datasets: Taiwan Lung Cancer Pharmacogenomics Study (LCPG) and Taiwan Biobank data after August 2016 (TWB2). RESULTS: The AUC based on the NSFs ages 55 to 70 years in LCPG and TWB2 was 0.714 [95% confidence intervals (CI), 0.660-0.768]. For women in TWB2 ages 55 to 70 years, 3.94% (95% CI, 2.95-5.13) had risk higher than 0.0151. For women in LCPG ages 55 to 74 years, 27.03% (95% CI, 19.04-36.28) had risk higher than 0.0151. CONCLUSIONS: TNSF-SQ demonstrated good discriminative power. The ability to identify 27.03% of high-risk Asian NSFs ages 55 to 74 years deserves attention. IMPACT: TNSF-SQ seems potentially useful in selecting Asian NSFs for LDCT screening.

8.
Environ Int ; 135: 105346, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31864026

RESUMO

BACKGROUND: The International Agency for Research on Cancer (IARC) classifies diesel engine exhaust as carcinogenic to humans based on sufficient evidence for lung cancer. IARC noted, however, an increased risk of bladder cancer (based on limited evidence). OBJECTIVE: To evaluate the association between quantitative, lifetime occupational diesel exhaust exposure and risk of urothelial cell carcinoma of the bladder (UBC) overall and according to pathological subtypes. METHODS: Data from personal interviews with 1944 UBC cases, as well as formalin-fixed paraffin-embedded tumor tissue blocks, and 2135 controls were pooled from two case-control studies conducted in the U.S. and Spain. Lifetime occupational histories combined with exposure-oriented questions were used to estimate cumulative exposure to respirable elemental carbon (REC), a primary surrogate for diesel exhaust. Unconditional logistic regression and two-stage polytomous logistic regression were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for smoking and other risk factors. RESULTS: Exposure to cumulative REC was associated with an increased risk of UBC; workers with cumulative REC >396 µg/m3-years had an OR of 1.61 (95% CI, 1.08-2.40). At this level of cumulative exposure, similar results were observed in the U.S. and Spain, OR = 1.75 (95% CI, 0.97-3.15) and OR = 1.54 (95% CI, 0.89-2.68), respectively. In lagged analysis, we also observed a consistent increased risk among workers with cumulative REC >396 µg/m3-years (range of ORs = 1.52-1.93) for all lag intervals evaluated (5-40 years). When we accounted for tumor subtypes defined by stage and grade, a significant association between diesel exhaust exposure and UBC was apparent (global test for association p = 0.0019). CONCLUSIONS: Combining data from two large epidemiologic studies, our results provide further evidence that diesel exhaust exposure increases the risk of UBC.

9.
Sci Rep ; 9(1): 11627, 2019 Aug 12.
Artigo em Inglês | MEDLINE | ID: mdl-31406220

RESUMO

Great Indian Bustard (GIB) is listed as Critically Endangered, with less than 250 individuals surviving in three fragmented populations. The species is under tremendous threat due to various anthropogenic pressures. Effective management and conservation of GIB requires a proper monitoring protocol, which we propose using an occupancy framework approach to detect changes in the species' population. We used occupancy estimates from various landscape level surveys and simulated scenarios to evaluate the effectiveness of the proposed protocol. Our result showed there is >70% chance of detecting 100% change in the occupancy with 100 sampling sites and 10 temporal replicates. While with double sampling sites, the same change can be detected with 4-6 temporal replicates. In absence of a robust population estimation method, we argue for the use of occupancy as a surrogate to detect change in population as it provides better insights for rare elusive species such as GIB. Our proposed methodological framework is more precise than previous methods, which will help in evaluating efficacy of management interventions proposed and the implementation of species recovery plans.

10.
Biometrika ; 106(3): 567-585, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31427822

RESUMO

Meta-analysis is widely popular for synthesizing information on common parameters of interest across multiple studies because of its logistical convenience and statistical efficiency. We develop a generalized meta-analysis approach to combining information on multivariate regression parameters across multiple studies that have varying levels of covariate information. Using algebraic relationships among regression parameters in different dimensions, we specify a set of moment equations for estimating parameters of a maximal model through information available from sets of parameter estimates for a series of reduced models from the different studies. The specification of the equations requires a reference dataset for estimating the joint distribution of the covariates. We propose to solve these equations using the generalized method of moments approach, with the optimal weighting of the equations taking into account uncertainty associated with estimates of the parameters of the reduced models. We describe extensions of the iterated reweighted least-squares algorithm for fitting generalized linear regression models using the proposed framework. Based on the same moment equations, we also develop a diagnostic test for detecting violations of underlying model assumptions, such as those arising from heterogeneity in the underlying study populations. The proposed methods are illustrated with extensive simulation studies and a real-data example involving the development of a breast cancer risk prediction model using disparate risk factor information from multiple studies.

11.
Am J Epidemiol ; 188(11): 2013-2020, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31429870

RESUMO

Investigations of gene (G)-environment (E) interactions have led to limited findings to date, possibly due to weak effects of individual genetic variants. Polygenic risk scores (PRS), which capture the genetic susceptibility associated with a set of variants, can be a powerful tool for detecting global patterns of interaction. Motivated by the case-only method for evaluating interactions with a single variant, we propose a case-only method for the analysis of interactions with a PRS in case-control studies. Assuming the PRS and E are independent, we show how a linear regression of the PRS on E in a sample of cases can be used to efficiently estimate the interaction parameter. Furthermore, if an estimate of the mean of the PRS in the underlying population is available, the proposed method can estimate the PRS main effect. Extensions allow for PRS-E dependence due to associations between variants in the PRS and E. Simulation studies indicate the proposed method offers appreciable gains in efficiency over logistic regression and can recover much of the efficiency of a cohort study. We applied the proposed method to investigate interactions between a PRS and epidemiologic factors on breast cancer risk in the UK Biobank (United Kingdom, recruited 2006-2010).

12.
J Natl Cancer Inst ; 2019 Jun 04.
Artigo em Inglês | MEDLINE | ID: mdl-31165158

RESUMO

BACKGROUND: External validation of risk models is critical for risk stratified breast cancer prevention. We used the Individualized Coherent Absolute Risk Estimation (iCARE) as a flexible tool for risk model development, comparative model validation, and to make projections for population risk stratification. METHODS: Performance of two recently developed models, iCARE-BPC3 and iCARE-Lit, were compared with two established models (BCRAT, IBIS) based on classical risk factors in a UK-based cohort of 64,874 White non-Hispanic women (863 cases) aged 35-74 years. Risk projections in a target population of US White non-Hispanic women aged 50-70 years assessed potential improvements in risk stratification by adding mammographic breast density (MD) and polygenic risk score (PRS). RESULTS: The best calibrated models were iCARE-Lit (expected to observed number of cases (E/O)=0.98 (95% confidence interval [CI]=0.87 to 1.11)) for women younger than 50 years; and iCARE-BPC3 (E/O=1.00 (0.93 to 1.09)) for women 50 years or older. Risk projections using iCARE-BPC3 indicated classical risk factors can identify ∼500,000 women at moderate to high risk (>3% five-year risk) in the target population. Addition of MD and a 313-variant PRS is expected to increase this to approximately 3.5 million, and among them, approximately 153,000 invasive breast cancer cases are expected within five years. CONCLUSIONS: iCARE models based on classical risk factors perform similarly or better than BCRAT or IBIS in White non-Hispanic women. Addition of MD and PRS can lead to substantial improvements in risk stratification. However, these integrated models require independent prospective validation before broad clinical applications.

13.
Breast Cancer Res ; 21(1): 68, 2019 05 22.
Artigo em Inglês | MEDLINE | ID: mdl-31118087

RESUMO

BACKGROUND: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. METHODS: Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. RESULTS: Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. CONCLUSIONS: The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.


Assuntos
Biomarcadores Tumorais , Densidade da Mama/genética , Neoplasias da Mama/genética , Neoplasias da Mama/patologia , Herança Multifatorial , Adulto , Idoso , Algoritmos , Índice de Massa Corporal , Estudos de Casos e Controles , Feminino , Humanos , Pessoa de Meia-Idade , Modelos Biológicos , Razão de Chances , Polimorfismo de Nucleotídeo Único , Medição de Risco , Fatores de Risco
14.
Nat Genet ; 51(6): 1067, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-31068672

RESUMO

In the version of this article initially published, in Supplementary Data 5, the logFC, FC, P value and adjusted P value for advanced AMD versus control (DE 4/1) without age correction did not correspond to the correct gene IDs. The errors have been corrected in the HTML version of the article.

15.
Cancer Causes Control ; 30(8): 799-811, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31069578

RESUMO

An important premise of epidemiology is that individuals with the same disease share similar underlying etiologies and clinical outcomes. In the past few decades, our knowledge of disease pathogenesis has improved, and disease classification systems have evolved to the point where no complex disease processes are considered homogenous. As a result, pathology and epidemiology have been integrated into the single, unified field of molecular pathological epidemiology (MPE). Advancing integrative molecular and population-level health sciences and addressing the unique research challenges specific to the field of MPE necessitates assembling experts in diverse fields, including epidemiology, pathology, biostatistics, computational biology, bioinformatics, genomics, immunology, and nutritional and environmental sciences. Integrating these seemingly divergent fields can lead to a greater understanding of pathogenic processes. The International MPE Meeting Series fosters discussion that addresses the specific research questions and challenges in this emerging field. The purpose of the meeting series is to: discuss novel methods to integrate pathology and epidemiology; discuss studies that provide pathogenic insights into population impact; and educate next-generation scientists. Herein, we share the proceedings of the Fourth International MPE Meeting, held in Boston, MA, USA, on 30 May-1 June, 2018. Major themes of this meeting included 'integrated genetic and molecular pathologic epidemiology', 'immunology-MPE', and 'novel disease phenotyping'. The key priority areas for future research identified by meeting attendees included integration of tumor immunology and cancer disparities into epidemiologic studies, further collaboration between computational and population-level scientists to gain new insight on exposure-disease associations, and future pooling projects of studies with comparable data.


Assuntos
Epidemiologia , Patologia Molecular , Humanos , Neoplasias/epidemiologia , Neoplasias/genética , Neoplasias/imunologia , Neoplasias/patologia
16.
Nat Commun ; 10(1): 1941, 2019 04 26.
Artigo em Inglês | MEDLINE | ID: mdl-31028273

RESUMO

Mendelian randomization (MR) has emerged as a major tool for the investigation of causal relationship among traits, utilizing results from large-scale genome-wide association studies. Bias due to horizontal pleiotropy, however, remains a major concern. We propose a novel approach for robust and efficient MR analysis using large number of genetic instruments, based on a novel spike-detection algorithm under a normal-mixture model for underlying effect-size distributions. Simulations show that the new method, MRMix, provides nearly unbiased or/and less biased estimates of causal effects compared to alternative methods and can achieve higher efficiency than comparably robust estimators. Application of MRMix to publicly available datasets leads to notable observations, including identification of causal effects of BMI and age-at-menarche on the risk of breast cancer; no causal effect of HDL and triglycerides on the risk of coronary artery disease; a strong detrimental effect of BMI on the risk of major depressive disorder.


Assuntos
Algoritmos , Neoplasias da Mama/genética , Doença da Artéria Coronariana/genética , Transtorno Depressivo Maior/genética , Genoma Humano , Análise da Randomização Mendeliana/estatística & dados numéricos , Fatores Etários , Índice de Massa Corporal , Neoplasias da Mama/sangue , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/etiologia , HDL-Colesterol/sangue , Doença da Artéria Coronariana/sangue , Doença da Artéria Coronariana/diagnóstico , Doença da Artéria Coronariana/etiologia , Conjuntos de Dados como Assunto , Transtorno Depressivo Maior/sangue , Transtorno Depressivo Maior/diagnóstico , Transtorno Depressivo Maior/etiologia , Feminino , Estudo de Associação Genômica Ampla , Humanos , Menarca/sangue , Menarca/genética , Característica Quantitativa Herdável , Fatores de Risco , Triglicerídeos/sangue
17.
Lancet Oncol ; 20(4): 463-464, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30799258
18.
Nat Genet ; 51(4): 606-610, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30742112

RESUMO

Genome-wide association studies (GWAS) have identified genetic variants at 34 loci contributing to age-related macular degeneration (AMD)1-3. We generated transcriptional profiles of postmortem retinas from 453 controls and cases at distinct stages of AMD and integrated retinal transcriptomes, covering 13,662 protein-coding and 1,462 noncoding genes, with genotypes at more than 9 million common SNPs for expression quantitative trait loci (eQTL) analysis of a tissue not included in Genotype-Tissue Expression (GTEx) and other large datasets4,5. Cis-eQTL analysis identified 10,474 genes under genetic regulation, including 4,541 eQTLs detected only in the retina. Integrated analysis of AMD-GWAS with eQTLs ascertained likely target genes at six reported loci. Using transcriptome-wide association analysis (TWAS), we identified three additional genes, RLBP1, HIC1 and PARP12, after Bonferroni correction. Our studies expand the genetic landscape of AMD and establish the Eye Genotype Expression (EyeGEx) database as a resource for post-GWAS interpretation of multifactorial ocular traits.


Assuntos
Predisposição Genética para Doença/genética , Degeneração Macular/genética , Locos de Características Quantitativas/genética , Transcriptoma/genética , Estudos de Casos e Controles , Perfilação da Expressão Gênica/métodos , Regulação da Expressão Gênica/genética , Estudo de Associação Genômica Ampla/métodos , Genótipo , Humanos , Fenótipo , Polimorfismo de Nucleotídeo Único/genética , Retina/fisiopatologia
20.
Genet Med ; 21(8): 1708-1718, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-30643217

RESUMO

PURPOSE: Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs). METHODS: BOADICEA incorporates the effects of truncating variants in BRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information. RESULTS: Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with 14.7% of women predicted to have a lifetime risk of ≥17-<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of ≥30% (high risk). CONCLUSION: This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.


Assuntos
Neoplasias da Mama/epidemiologia , Neoplasias da Mama/genética , Predisposição Genética para Doença , Testes Genéticos , Proteínas Mutadas de Ataxia Telangiectasia/genética , Proteína BRCA1/genética , Proteína BRCA2/genética , Neoplasias da Mama/patologia , Quinase do Ponto de Checagem 2/genética , Proteína do Grupo de Complementação N da Anemia de Fanconi/genética , Feminino , Humanos , Herança Multifatorial/genética , Mutação/genética , Neoplasias Ovarianas/epidemiologia , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/patologia , Polimorfismo de Nucleotídeo Único/genética , Medição de Risco , Fatores de Risco
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