Showing papers by "Shuai Li published in 2019"

A Cost-effectiveness Analysis of Multigene Testing for All Patients With Breast Cancer.

Abstract: Importance Moving to multigene testing for all women with breast cancer (BC) could identify many more mutation carriers who can benefit from precision prevention. However, the cost-effectiveness of this approach remains unaddressed. Objective To estimate incremental lifetime effects, costs, and cost-effectiveness of multigene testing of all patients with BC compared with the current practice of genetic testing (BRCA) based on family history (FH) or clinical criteria. Design, Setting, and Participants This cost-effectiveness microsimulation modeling study compared lifetime costs and effects of high-riskBRCA1/BRCA2/PALB2(multigene) testing of all unselected patients with BC (strategy A) withBRCA1/BRCA2testing based on FH or clinical criteria (strategy B) in United Kingdom (UK) and US populations. Data were obtained from 11 836 patients in population-based BC cohorts (regardless of FH) recruited to 4 large research studies. Data were collected and analyzed from January 1, 2018, through June 8, 2019. The time horizon is lifetime. Payer and societal perspectives are presented. Probabilistic and 1-way sensitivity analyses evaluate model uncertainty. Interventions In strategy A, all women with BC underwentBRCA1/BRCA2/PALB2testing. In strategy B, only women with BC fulfilling FH or clinical criteria underwentBRCAtesting. AffectedBRCA/PALB2carriers could undertake contralateral preventive mastectomy;BRCAcarriers could choose risk-reducing salpingo-oophorectomy (RRSO). Relatives of mutation carriers underwent cascade testing. Unaffected relative carriers could undergo magnetic resonance imaging or mammography screening, chemoprevention, or risk-reducing mastectomy for BC risk and RRSO for ovarian cancer (OC) risk. Main Outcomes and Measures Incremental cost-effectiveness ratio (ICER) was calculated as incremental cost per quality-adjusted life-year (QALY) gained and compared with standard £30 000/QALY and $100 000/QALY UK and US thresholds, respectively. Incidence of OC, BC, excess deaths due to heart disease, and the overall population effects were estimated. Results BRCA1/BRCA2/PALB2multigene testing for all patients detected with BC annually would cost £10 464/QALY (payer perspective) or £7216/QALY (societal perspective) in the United Kingdom or $65 661/QALY (payer perspective) or $61 618/QALY (societal perspective) in the United States compared with currentBRCAtesting based on clinical criteria or FH. This is well below UK and US cost-effectiveness thresholds. In probabilistic sensitivity analysis, unselected multigene testing remained cost-effective for 98% to 99% of UK and 64% to 68% of US health system simulations. One year’s unselected multigene testing could prevent 2101 cases of BC and OC and 633 deaths in the United Kingdom and 9733 cases of BC and OC and 2406 deaths in the United States. Correspondingly, 8 excess deaths due to heart disease occurred in the United Kingdom and 35 in the United States annually. Conclusions and Relevance This study found unselected, high-risk multigene testing for all patients with BC to be extremely cost-effective compared with testing based on FH or clinical criteria for UK and US health systems. These findings support changing current policy to expand genetic testing to all women with BC.

Within-family studies for Mendelian randomization: avoiding dynastic, assortative mating, and population stratification biases

Abstract: Mendelian randomization (MR) is a widely-used method for causal inference using genetic data. Mendelian randomization studies of unrelated individuals may be susceptible to bias from family structure, for example, through dynastic effects which occur when parental genotypes directly affect offspring phenotypes. Here we describe methods for within-family Mendelian randomization and through simulations show that family-based methods can overcome bias due to dynastic effects. We illustrate these issues empirically using data from 62,470 siblings from the UK Biobank and Nord-Trondelag Health Study. Both within-family and population-based Mendelian randomization analyses reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while MR estimates from population-based samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects largely disappeared in within-family MR analyses. We found differences between population-based and within-family based estimates, indicating the importance of controlling for family effects and population structure in Mendelian randomization studies.

Inference about causation between body mass index and DNA methylation in blood from a twin family study

Abstract: Several studies have reported DNA methylation in blood to be associated with body mass index (BMI), but few have investigated causal aspects of the association. We used a twin family design to assess this association at two life points and applied a novel analytical approach to appraise the evidence for causality. The methylation profile of DNA from peripheral blood was measured for 479 Australian women from 130 twin families. Linear regression was used to estimate the associations of DNA methylation at ~410,000 cytosine-guanine dinucleotides (CpGs), and of the average DNA methylation at ~20,000 genes, with current BMI, BMI at age 18–21 years, and the change between the two (BMI change). A novel regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess causation. At a 5% false discovery rate, nine, six and 12 CpGs at 24 loci were associated with current BMI, BMI at age 18–21 years and BMI change, respectively. The average DNA methylation of the BHLHE40 and SOCS3 loci was associated with current BMI, and of the PHGDH locus with BMI change. From the ICE FALCON analyses with BMI as the predictor and DNA methylation as the outcome, a woman’s DNA methylation level was associated with her co-twin’s BMI, and the association disappeared after conditioning on her own BMI, consistent with BMI causing DNA methylation. To the contrary, using DNA methylation as the predictor and BMI as the outcome, a woman’s BMI was not associated with her co-twin’s DNA methylation level, consistent with DNA methylation not causing BMI. For middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with current BMI, BMI at age 18–21 years and BMI change. Our study suggests that BMI has a causal effect on peripheral blood DNA methylation.

DNA methylation-based biological age, genome-wide average DNA methylation, and conventional breast cancer risk factors.

Abstract: DNA methylation-based biological age (DNAm age), as well as genome-wide average DNA methylation, have been reported to predict breast cancer risk. We aimed to investigate the associations between these DNA methylation-based risk factors and 18 conventional breast cancer risk factors for disease-free women. A sample of 479 individuals from the Australian Mammographic Density Twins and Sisters was used for discovery, a sample of 3354 individuals from the Melbourne Collaborative Cohort Study was used for replication, and meta-analyses pooling results from the two studies were conducted. DNAm age based on three epigenetic clocks (Hannum, Horvath and Levine) and genome-wide average DNA methylation were calculated using the HumanMethylation 450 K BeadChip assay data. The DNAm age measures were positively associated with body mass index (BMI), smoking, alcohol drinking and age at menarche (all nominal P < 0.05). Genome-wide average DNA methylation was negatively associated with smoking and number of live births, and positively associated with age at first live birth (all nominal P < 0.05). The association of DNAm age with BMI was also evident in within-twin-pair analyses that control for familial factors. This study suggests that some lifestyle and hormonal risk factors are associated with these DNA methylation-based breast cancer risk factors, and the observed associations are unlikely to be due to familial confounding but are likely causal. DNA methylation-based risk factors could interplay with conventional risk factors in modifying breast cancer risk.

Twins Research Australia: A New Paradigm for Driving Twin Research.

Abstract: Twins Research Australia (TRA) is a community of twins and researchers working on health research to benefit everyone, including twins. TRA leads multidisciplinary research through the application of twin and family study designs, with the aim of sustaining long-term twin research that, both now and in the future, gives back to the community. This article summarizes TRA's recent achievements and future directions, including new methodologies addressing causation, linkage to health, economic and educational administrative datasets and to geospatial data to provide insight into health and disease. We also explain how TRA's knowledge translation and exchange activities are key to communicating the impact of twin studies to twins and the wider community. Building researcher capability, providing registry resources and partnering with all key stakeholders, particularly the participants, are important for how TRA is advancing twin research to improve health outcomes for society. TRA provides researchers with open access to its vibrant volunteer membership of twins, higher order multiples (multiples) and families who are willing to consider participation in research. Established four decades ago, this resource facilitates and supports research across multiple stages and a breadth of health domains.

Genome-wide association study of peripheral blood DNA methylation and conventional mammographic density measures.

Abstract: Age- and body mass index (BMI)-adjusted mammographic density is one of the strongest breast cancer risk factors. DNA methylation is a molecular mechanism that could underlie inter-individual variation in mammographic density. We aimed to investigate the association between breast cancer risk-predicting mammographic density measures and blood DNA methylation. For 436 women from the Australian Mammographic Density Twins and Sisters Study and 591 women from the Melbourne Collaborative Cohort Study, mammographic density (dense area, nondense area and percentage dense area) defined by the conventional brightness threshold was measured using the CUMULUS software, and peripheral blood DNA methylation was measured using the HumanMethylation450 (HM450) BeadChip assay. Associations between DNA methylation at >400,000 sites and mammographic density measures adjusted for age and BMI were assessed within each cohort and pooled using fixed-effect meta-analysis. Associations with methylation at genetic loci known to be associated with mammographic density were also examined. We found no genome-wide significant (p 0.05/299 = 1.7 × 10-4 ). In summary, our study did not find evidence for associations between blood DNA methylation, as measured by the HM450 assay, and conventional mammographic density measures that predict breast cancer risk.

Measurement challenge : protocol for international case–control comparison of mammographic measures that predict breast cancer risk

Abstract: INTRODUCTION: For women of the same age and body mass index, increased mammographic density is one of the strongest predictors of breast cancer risk. There are multiple methods of measuring mammographic density and other features in a mammogram that could potentially be used in a screening setting to identify and target women at high risk of developing breast cancer. However, it is unclear which measurement method provides the strongest predictor of breast cancer risk. METHODS AND ANALYSIS: The measurement challenge has been established as an international resource to offer a common set of anonymised mammogram images for measurement and analysis. To date, full field digital mammogram images and core data from 1650 cases and 1929 controls from five countries have been collated. The measurement challenge is an ongoing collaboration and we are continuing to expand the resource to include additional image sets across different populations (from contributors) and to compare additional measurement methods (by challengers). The intended use of the measurement challenge resource is for refinement and validation of new and existing mammographic measurement methods. The measurement challenge resource provides a standardised dataset of mammographic images and core data that enables investigators to directly compare methods of measuring mammographic density or other mammographic features in case/control sets of both raw and processed images, for the purposes of the comparing their predictions of breast cancer risk. ETHICS AND DISSEMINATION: Challengers and contributors are required to enter a Research Collaboration Agreement with the University of Melbourne prior to participation in the measurement challenge. The Challenge database of collated data and images are stored in a secure data repository at the University of Melbourne. Ethics approval for the measurement challenge is held at University of Melbourne (HREC ID 0931343.3).

Should we offer multi-gene testing to all patients with breast cancer: a cost-effectiveness analysis

Abstract: Introduction/Background Currently breast cancer (BC) patients are offered genetic-testing only if they have a ≥10% risk of being a BRCA carrier based on family history and clinical criteria. However, this approach misses a large proportion (∼50%) of overall mutation carriers as they fall below this 10% threshold. Mutation identification enables primary prevention for ovarian cancer (OC) in BC-patients and BC-&-OC in unaffected relatives. We estimate incremental lifetime-effects, costs, cost-effectiveness and population impact of multigene-testing all BC patients compared to current practice of family-history/clinical-criteria based genetic (BRCA)-testing. Methodology Cost-effectiveness microsimulation modelling study comparing lifetime costs-&-effects of BRCA1/BRCA2/PALB2 (multigene) testing all unselected BC-cases (Strategy-A) with family-history/clinical-criteria based BRCA1/BRCA2-testing (Strategy-B) in both UK and US populations. Data obtained from 11,836 population-based BC-patients (regardless of family-history) recruited to four large research studies in the UK (Predicting-Risk-of-Breast-Cancer-at-Screening (PROCAS: 1389 out of 57,000 women) & Prospective-Outcomes-in-Sporadic-versus-Hereditary-breast-cancer (POSH: 2885) studies); US (Kaiser-Permanente Washington Breast-Cancer-Surveillance-Consortium (BCSC) registry: 5892 out of 132,139 women) and Australia (Population-based BC-cases of the Australian-Breast-Cancer-Family-Study (ABCFS: 1670 women)). The main outcome measure was the incremental cost per quality-adjusted life-year (QALY) gained with a 3.5% annual discount. Parameter uncertainty was explored using one-way and probabilistic sensitivity analyses. Results Compared with current clinical-criteria/family-history-based BRCA-testing, (BRCA1/BRCA2/PALB2) multigene-testing for all BC-patients would cost £10,470/QALY (UK) or $58,702/QALY (US) gained, well below UK/NICE and US cost-effectiveness thresholds of £30,000/QALY & $100,000/QALY. Probabilistic sensitivity-analysis shows unselected multigene-testing remains cost-effective for 98% UK/77% US health-system simulations. One year’s unselected panel-genetic testing can prevent 1,776 BC/OC-cases and 557 deaths in the UK; and 8,258 BC/OC-cases and 2,143 deaths in the US. Correspondingly, 7 UK/32 US excess heart-disease deaths occur annually. Conclusion Unselected panel genetic-testing for all BC patients compared to current clinical-criteria restricted testing is extremely cost-effective. We recommend changing the current policy to expand genetic testing to all BC patients. Disclosure RM declares research funding from The Eve Appeal and Cancer Research UK into population testing and from Barts & the London Charity and Rosetree Charity outside this work, as well as an honorarium for grant review from Israel National Institute for Health Policy Research and honorarium for advisory board meeting for MSD and Astrazeneca. DGE declares travel grants paid by Astrazeneca. The other authors declare no conflict of interest.