111 research outputs found

    Efficacy of group exercise–based cancer rehabilitation delivered via telehealth (TeleCaRe) : protocol for a randomized controlled trial

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    Background: Access to rehabilitation to support cancer survivors to exercise is poor. Group exercise–based rehabilitation may be delivered remotely, but no trials have currently evaluated their efficacy. Objective: We aimed to evaluate the efficacy of a group exercise–based cancer rehabilitation program delivered via telehealth compared to usual care for improving the quality of life of cancer survivors. Methods: A parallel, assessor-blinded, pragmatic randomized controlled trial with embedded cost and qualitative analysis will be completed. In total, 116 cancer survivors will be recruited from a metropolitan health network in Melbourne, Victoria, Australia. The experimental group will attend an 8-week, twice-weekly, 60-minute exercise group session supervised via videoconferencing supplemented by a web-based home exercise program and information portal. The comparison group will receive usual care including standardized exercise advice and written information. Assessments will be completed at weeks 0 (baseline), 9 (post intervention), and 26 (follow-up). The primary outcome will be health-related quality of life measured using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire at week 9. Secondary measures include walking capacity (6-minute walk test), physical activity (activPAL accelerometer), self-efficacy (Health Action Process Approach Questionnaire), and adverse events. Health service data including hospital length of stay, hospital readmissions, and emergency department presentations will be recorded. Semistructured interviews will be completed within an interpretive description framework to explore the patient experience. The primary outcome will be analyzed using linear mixed effects models. A cost-effectiveness analysis will also be performed. Results: The trial commenced in April 2022. As of June 2022, we enrolled 14 participants. Conclusions: This trial will inform the future implementation of cancer rehabilitation by providing important data about efficacy, safety, cost, and patient experience. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12621001417875; https://tinyurl.com/yc5crwtr International Registered Report Identifier (IRRID): PRR1-10.2196/3855

    Healthy weight regulation and eating disorder prevention in high school students: a universal and targeted web-based intervention

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    Background: Given the rising rates of obesity in children and adolescents, developing evidence-based weight loss or weight maintenance interventions that can be widely disseminated, well implemented, and are highly scalable is a public health necessity. Such interventions should ensure that adolescents establish healthy weight regulation practices while also reducing eating disorder risk.Objective: This study describes an online program, StayingFit, which has two tracks for universal and targeted delivery and was designed to enhance healthy living skills, encourage healthy weight regulation, and improve weight/shape concerns among high school adolescents.Methods: Ninth grade students in two high schools in the San Francisco Bay area and in St Louis were invited to participate. Students who were overweight (body mass index [BMI] >85th percentile) were offered the weight management track of StayingFit; students who were normal weight were offered the healthy habits track. The 12-session program included a monitored discussion group and interactive self-monitoring logs. Measures completed pre- and post-intervention included self-report height and weight, used to calculate BMI percentile for age and sex and standardized BMI (zBMI), Youth Risk Behavior Survey (YRBS) nutrition data, the Weight Concerns Scale, and the Center for Epidemiological Studies Depression Scale.Results: A total of 336 students provided informed consent and were included in the analyses. The racial breakdown of the sample was as follows: 46.7% (157/336) multiracial/other, 31.0% (104/336) Caucasian, 16.7% (56/336) African American, and 5.7% (19/336) did not specify; 43.5% (146/336) of students identified as Hispanic/Latino. BMI percentile and zBMI significantly decreased among students in the weight management track. BMI percentile and zBMI did not significantly change among students in the healthy habits track, demonstrating that these students maintained their weight. Weight/shape concerns significantly decreased among participants in both tracks who had elevated weight/shape concerns at baseline. Fruit and vegetable consumption increased for both tracks. Physical activity increased among participants in the weight management track, while soda consumption and television time decreased.Conclusions: Results suggest that an Internet-based, universally delivered, targeted intervention may support healthy weight regulation, improve weight/shape concerns among participants with eating disorders risk, and increase physical activity in high school students. Tailored content and interactive features to encourage behavior change may lead to sustainable improvements in adolescent health

    Improving access for community health and sub-acute outpatient services: protocol for a stepped wedge cluster randomised controlled trial

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    BACKGROUND: Waiting lists for treatment are common in outpatient and community services, Existing methods for managing access and triage to these services can lead to inequities in service delivery, inefficiencies and divert resources from frontline care. Evidence from two controlled studies indicates that an alternative to the traditional &quot;waitlist and triage&quot; model known as STAT (Specific Timely Appointments for Triage) may be successful in reducing waiting times without adversely affecting other aspects of patient care. This trial aims to test whether the model is cost effective in reducing waiting time across multiple services, and to measure the impact on service provision, health-related quality of life and patient satisfaction. METHODS/DESIGN: A stepped wedge cluster randomised controlled trial has been designed to evaluate the impact of the STAT model in 8 community health and outpatient services. The primary outcome will be waiting time from referral to first appointment. Secondary outcomes will be nature and quantity of service received (collected from all patients attending the service during the study period and health-related quality of life (AQOL-8D), patient satisfaction, health care utilisation and cost data (collected from a subgroup of patients at initial assessment and after 12&nbsp;weeks). Data will be analysed with a multiple multi-level random-effects regression model that allows for cluster effects. An economic evaluation will be undertaken alongside the clinical trial. DISCUSSION: This paper outlines the study protocol for a fully powered prospective stepped wedge cluster randomised controlled trial (SWCRCT) to establish whether the STAT model of access and triage can reduce waiting times applied across multiple settings, without increasing health service costs or adversely impacting on other aspects of patient care. If successful, it will provide evidence for the effectiveness of a practical model of access that can substantially reduce waiting time for outpatient and community services with subsequent benefits for both efficiency of health systems and patient care.<br /

    Intra-tumor heterogeneity of MLH1 promoter methylation revealed by deep single molecule bisulfite sequencing

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    A single tumor may contain cells with different somatic mutations. By characterizing this genetic heterogeneity within tumors, advances have been made in the prognosis, treatment and understanding of tumorigenesis. In contrast, the extent of epigenetic intra-tumor heterogeneity and how it influences tumor biology is under-explored. We have characterized epigenetic heterogeneity within individual tumors using next-generation sequencing. We used deep single molecule bisulfite sequencing and sample-specific DNA barcodes to determine the spectrum of MLH1 promoter methylation across an average of 1000 molecules in each of 33 individual samples in parallel, including endometrial cancer, matched blood and normal endometrium. This first glimpse, deep into each tumor, revealed unexpectedly heterogeneous patterns of methylation at the MLH1 promoter within a subset of endometrial tumors. This high-resolution analysis allowed us to measure the clonality of methylation in individual tumors and gain insight into the accumulation of aberrant promoter methylation on both alleles during tumorigenesis

    Canvass: a crowd-sourced, natural-product screening library for exploring biological space

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    NCATS thanks Dingyin Tao for assistance with compound characterization. This research was supported by the Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health (NIH). R.B.A. acknowledges support from NSF (CHE-1665145) and NIH (GM126221). M.K.B. acknowledges support from NIH (5R01GM110131). N.Z.B. thanks support from NIGMS, NIH (R01GM114061). J.K.C. acknowledges support from NSF (CHE-1665331). J.C. acknowledges support from the Fogarty International Center, NIH (TW009872). P.A.C. acknowledges support from the National Cancer Institute (NCI), NIH (R01 CA158275), and the NIH/National Institute of Aging (P01 AG012411). N.K.G. acknowledges support from NSF (CHE-1464898). B.C.G. thanks the support of NSF (RUI: 213569), the Camille and Henry Dreyfus Foundation, and the Arnold and Mabel Beckman Foundation. C.C.H. thanks the start-up funds from the Scripps Institution of Oceanography for support. J.N.J. acknowledges support from NIH (GM 063557, GM 084333). A.D.K. thanks the support from NCI, NIH (P01CA125066). D.G.I.K. acknowledges support from the National Center for Complementary and Integrative Health (1 R01 AT008088) and the Fogarty International Center, NIH (U01 TW00313), and gratefully acknowledges courtesies extended by the Government of Madagascar (Ministere des Eaux et Forets). O.K. thanks NIH (R01GM071779) for financial support. T.J.M. acknowledges support from NIH (GM116952). S.M. acknowledges support from NIH (DA045884-01, DA046487-01, AA026949-01), the Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program (W81XWH-17-1-0256), and NCI, NIH, through a Cancer Center Support Grant (P30 CA008748). K.N.M. thanks the California Department of Food and Agriculture Pierce's Disease and Glassy Winged Sharpshooter Board for support. B.T.M. thanks Michael Mullowney for his contribution in the isolation, elucidation, and submission of the compounds in this work. P.N. acknowledges support from NIH (R01 GM111476). L.E.O. acknowledges support from NIH (R01-HL25854, R01-GM30859, R0-1-NS-12389). L.E.B., J.K.S., and J.A.P. thank the NIH (R35 GM-118173, R24 GM-111625) for research support. F.R. thanks the American Lebanese Syrian Associated Charities (ALSAC) for financial support. I.S. thanks the University of Oklahoma Startup funds for support. J.T.S. acknowledges support from ACS PRF (53767-ND1) and NSF (CHE-1414298), and thanks Drs. Kellan N. Lamb and Michael J. Di Maso for their synthetic contribution. B.S. acknowledges support from NIH (CA78747, CA106150, GM114353, GM115575). W.S. acknowledges support from NIGMS, NIH (R15GM116032, P30 GM103450), and thanks the University of Arkansas for startup funds and the Arkansas Biosciences Institute (ABI) for seed money. C.R.J.S. acknowledges support from NIH (R01GM121656). D.S.T. thanks the support of NIH (T32 CA062948-Gudas) and PhRMA Foundation to A.L.V., NIH (P41 GM076267) to D.S.T., and CCSG NIH (P30 CA008748) to C.B. Thompson. R.E.T. acknowledges support from NIGMS, NIH (GM129465). R.J.T. thanks the American Cancer Society (RSG-12-253-01-CDD) and NSF (CHE1361173) for support. D.A.V. thanks the Camille and Henry Dreyfus Foundation, the National Science Foundation (CHE-0353662, CHE-1005253, and CHE-1725142), the Beckman Foundation, the Sherman Fairchild Foundation, the John Stauffer Charitable Trust, and the Christian Scholars Foundation for support. J.W. acknowledges support from the American Cancer Society through the Research Scholar Grant (RSG-13-011-01-CDD). W.M.W.acknowledges support from NIGMS, NIH (GM119426), and NSF (CHE1755698). A.Z. acknowledges support from NSF (CHE-1463819). (Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health (NIH); CHE-1665145 - NSF; CHE-1665331 - NSF; CHE-1464898 - NSF; RUI: 213569 - NSF; CHE-1414298 - NSF; CHE1361173 - NSF; CHE1755698 - NSF; CHE-1463819 - NSF; GM126221 - NIH; 5R01GM110131 - NIH; GM 063557 - NIH; GM 084333 - NIH; R01GM071779 - NIH; GM116952 - NIH; DA045884-01 - NIH; DA046487-01 - NIH; AA026949-01 - NIH; R01 GM111476 - NIH; R01-HL25854 - NIH; R01-GM30859 - NIH; R0-1-NS-12389 - NIH; R35 GM-118173 - NIH; R24 GM-111625 - NIH; CA78747 - NIH; CA106150 - NIH; GM114353 - NIH; GM115575 - NIH; R01GM121656 - NIH; T32 CA062948-Gudas - NIH; P41 GM076267 - NIH; R01GM114061 - NIGMS, NIH; R15GM116032 - NIGMS, NIH; P30 GM103450 - NIGMS, NIH; GM129465 - NIGMS, NIH; GM119426 - NIGMS, NIH; TW009872 - Fogarty International Center, NIH; U01 TW00313 - Fogarty International Center, NIH; R01 CA158275 - National Cancer Institute (NCI), NIH; P01 AG012411 - NIH/National Institute of Aging; Camille and Henry Dreyfus Foundation; Arnold and Mabel Beckman Foundation; Scripps Institution of Oceanography; P01CA125066 - NCI, NIH; 1 R01 AT008088 - National Center for Complementary and Integrative Health; W81XWH-17-1-0256 - Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program; P30 CA008748 - NCI, NIH, through a Cancer Center Support Grant; California Department of Food and Agriculture Pierce's Disease and Glassy Winged Sharpshooter Board; American Lebanese Syrian Associated Charities (ALSAC); University of Oklahoma Startup funds; 53767-ND1 - ACS PRF; PhRMA Foundation; P30 CA008748 - CCSG NIH; RSG-12-253-01-CDD - American Cancer Society; RSG-13-011-01-CDD - American Cancer Society; CHE-0353662 - National Science Foundation; CHE-1005253 - National Science Foundation; CHE-1725142 - National Science Foundation; Beckman Foundation; Sherman Fairchild Foundation; John Stauffer Charitable Trust; Christian Scholars Foundation)Published versionSupporting documentatio

    Prioritization of knowledge-needs to achieve best practices for bottom trawling in relation to seabed habitats

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    Management and technical approaches that achieve a sustainable level of fish production while at the same time minimizing or limiting the wider ecological effects caused through fishing gear contact with the seabed might be considered to be ‘best practice’. To identify future knowledge-needs that would help to support a transition towards the adoption of best practices for trawling, a prioritization exercise was undertaken with a group of 39 practitioners from the seafood industry and management, and 13 research scientists who have an active research interest in bottom-trawl and dredge fisheries. A list of 108 knowledge-needs related to trawl and dredge fisheries was developed in conjunction with an ‘expert task force’. The long list was further refined through a three stage process of voting and scoring, including discussions of each knowledge-need. The top 25 knowledge-needs are presented, as scored separately by practitioners and scientists. There was considerable consistency in the priorities identified by these two groups. The top priority knowledge-need to improve current understanding on the distribution and extent of different habitat types also reinforced the concomitant need for the provision and access to data on the spatial and temporal distribution of all forms of towed bottom-fishing activities. Many of the other top 25 knowledge-needs concerned the evaluation of different management approaches or implementation of different fishing practices, particularly those that explore trade-offs between effects of bottom trawling on biodiversity and ecosystem services and the benefits of fish production as food.Fil: Kaiser, Michel J.. Bangor University; Reino UnidoFil: Hilborn, Ray. University of Washington; Estados UnidosFil: Jennings, Simon. Fisheries and Aquaculture Science; Reino UnidoFil: Amaroso, Ricky. University of Washington; Estados UnidosFil: Andersen, Michael. Danish Fishermen; DinamarcaFil: Balliet, Kris. Sustainable Fisheries Partnership; Estados UnidosFil: Barratt, Eric. Sanford Limited; Nueva ZelandaFil: Bergstad, Odd A. Institute of Marine Research; NoruegaFil: Bishop, Stephen. Independent Fisheries Ltd; Nueva ZelandaFil: Bostrom, Jodi L. Marine Stewardship Council; Reino UnidoFil: Boyd, Catherine. Clearwater Seafoods; CanadáFil: Bruce, Eduardo A. Friosur S.A.; ChileFil: Burden, Merrick. Marine Conservation Alliance; Estados UnidosFil: Carey, Chris. Independent Fisheries Ltd.; Estados UnidosFil: Clermont, Jason. New England Aquarium; Estados UnidosFil: Collie, Jeremy S. University of Rhode Island,; Estados UnidosFil: Delahunty, Antony. National Federation of Fishermen; Reino UnidoFil: Dixon, Jacqui. Pacific Andes International Holdings Limited; ChinaFil: Eayrs, Steve. Gulf of Maine Research Institute; Estados UnidosFil: Edwards, Nigel. Seachill Ltd.; Reino UnidoFil: Fujita, Rod. Environmental Defense Fund; Reino UnidoFil: Gauvin, John. Alaska Seafood Cooperative; Estados UnidosFil: Gleason, Mary. The Nature Conservancy; Estados UnidosFil: Harris, Brad. Alaska Pacific University; Estados UnidosFil: He, Pingguo. University of Massachusetts Dartmouth; Estados UnidosFil: Hiddink, Jan G. Bangor University; Reino UnidoFil: Hughes, Kathryn M. Bangor University; Reino UnidoFil: Inostroza, Mario. EMDEPES; ChileFil: Kenny, Andrew. Fisheries and Aquaculture Science; Reino UnidoFil: Kritzer, Jake. Environmental Defense Fund; Estados UnidosFil: Kuntzsch, Volker. Sanford Limited; Estados UnidosFil: Lasta, Mario. Diag. Montegrande N° 7078. Mar del Plata; ArgentinaFil: Lopez, Ivan. Confederacion Española de Pesca; EspañaFil: Loveridge, Craig. South Pacific Regional Fisheries Management Organisation; Nueva ZelandaFil: Lynch, Don. Gorton; Estados UnidosFil: Masters, Jim. Marine Conservation Society; Reino UnidoFil: Mazor, Tessa. CSIRO Marine and Atmospheric Research; AustraliaFil: McConnaughey, Robert A. US National Marine Fisheries Service; Estados UnidosFil: Moenne, Marcel. Pacificblu; ChileFil: Francis. Marine Scotland Science; Reino UnidoFil: Nimick, Aileen M. Alaska Pacific University; Estados UnidosFil: Olsen, Alex. A. Espersen; DinamarcaFil: Parker, David. Young; Reino UnidoFil: Parma, Ana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; ArgentinaFil: Penney, Christine. Clearwater Seafoods; CanadáFil: Pierce, David. Massachusetts Division of Marine Fisheries; Estados UnidosFil: Pitcher, Roland. CSIRO Marine and Atmospheric Research; AustraliaFil: Pol, Michael. Massachusetts Division of Marine Fisheries; Estados UnidosFil: Richardson, Ed. Pollock Conservation Cooperative; Estados UnidosFil: Rijnsdorp, Adriaan D. Wageningen IMARES; Países BajosFil: Rilatt, Simon. A. Espersen; DinamarcaFil: Rodmell, Dale P. National Federation of Fishermen's Organisations; Reino UnidoFil: Rose, Craig. FishNext Research; Estados UnidosFil: Sethi, Suresh A. Alaska Pacific University; Estados UnidosFil: Short, Katherine. F.L.O.W. Collaborative; Nueva ZelandaFil: Suuronen, Petri. Fisheries and Aquaculture Department; ItaliaFil: Taylor, Erin. New England Aquarium; Estados UnidosFil: Wallace, Scott. The David Suzuki Foundation; CanadáFil: Webb, Lisa. Gorton's Inc.; Estados UnidosFil: Wickham, Eric. Unit four –1957 McNicoll Avenue; CanadáFil: Wilding, Sam R. Monterey Bay Aquarium; Estados UnidosFil: Wilson, Ashley. Department for Environment; Reino UnidoFil: Winger, Paul. Memorial University Of Newfoundland; CanadáFil: Sutherland, William J. University of Cambridge; Reino Unid

    A model of access combining triage with initial management reduced waiting time for community outpatient services: a stepped wedge cluster randomised controlled trial

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    BACKGROUND: Long waiting times are associated with public community outpatient health services. This trial aimed to determine if a new model of care based on evidence-based strategies that improved patient flow in two small pilot trials could be used to reduce waiting time across a variety of services. The key principle of the Specific Timely Appointments for Triage (STAT) model is that patients are booked directly into protected assessment appointments and triage is combined with initial management as an alternative to a waiting list and triage system. METHODS: A stepped wedge cluster randomised controlled trial was conducted between October 2015 and March 2017, involving 3116 patients at eight sites across a major Australian metropolitan health network. RESULTS: The intervention reduced waiting time to first appointment by 33.8% (IRR&thinsp;=&thinsp;0.663, 95% CI 0.516 to 0.852, P&thinsp;=&thinsp;0.001). Median waiting time decreased from a median of 42&nbsp;days (IQR 19 to 86) in the control period to a median of 24&nbsp;days (IQR 13 to 48) in the intervention period. A substantial reduction in variability was also noted. The model did not impact on most secondary outcomes, including time to second appointment, likelihood of discharge by 12&nbsp;weeks and number of appointments provided, but was associated with a small increase in the rate of missed appointments. CONCLUSIONS: Broad-scale implementation of a model of access and triage that combined triage with initial management and actively managed the relationship between supply and demand achieved substantial reductions in waiting time without adversely impacting on other aspects of care. The reductions in waiting time are likely to have been driven, primarily, by substantial reductions for those patients previously considered low priority. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12615001016527 registration date: 29/09/2015

    Prevalence and architecture of de novo mutations in developmental disorders.

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    The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year

    Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

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    Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

    Identification of a BRCA2-Specific modifier locus at 6p24 related to breast cancer risk

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    Common genetic variants contribute to the observed variation in breast cancer risk for BRCA2 mutation carriers; those known to date have all been found through population-based genome-wide association studies (GWAS). To comprehensively identify breast cancer risk modifying loci for BRCA2 mutation carriers, we conducted a deep replication of an ongoing GWAS discovery study. Using the ranked P-values of the breast cancer associations with the imputed genotype of 1.4 M SNPs, 19,029 SNPs were selected and designed for inclusion on a custom Illumina array that included a total of 211,155 SNPs as part of a multi-consortial project. DNA samples from 3,881 breast cancer affected and 4,330 unaffected BRCA2 mutation carriers from 47 studies belonging to the Consortium of Investigators of Modifiers of BRCA1/2 were genotyped and available for analysis. We replicated previously reported breast cancer susceptibility alleles in these BRCA2 mutation carriers and for several regions (including FGFR2, MAP3K1, CDKN2A/B, and PTHLH) identified SNPs that have stronger evidence of association than those previously published. We also identified a novel susceptibility allele at 6p24 that was inversely associated with risk in BRCA2 mutation carriers (rs9348512; per allele HR = 0.85, 95% CI 0.80-0.90, P = 3.9×10−8). This SNP was not associated with breast cancer risk either in the general population or in BRCA1 mutation carriers. The locus lies within a region containing TFAP2A, which encodes a transcriptional activation protein that interacts with several tumor suppressor genes. This report identifies the first breast cancer risk locus specific to a BRCA2 mutation background. This comprehensive update of novel and previously reported breast cancer susceptibility loci contributes to the establishment of a panel of SNPs that modify breast cancer risk in BRCA2 mutation carriers. This panel may have clinical utility for women with BRCA2 mutations weighing options for medical prevention of breast cancer
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