Review of non-clinical risk models to aid prevention of breast cancer.

A disease risk model is a statistical method which assesses the probability that an individual will develop one or more diseases within a stated period of time. Such models take into account the presence or absence of specific epidemiological risk factors associated with the disease and thereby potentially identify individuals at higher risk. Such models are currently used clinically to identify people at higher risk, including identifying women who are at increased risk of developing breast cancer. Many genetic and non-genetic breast cancer risk models have been developed previously. We have evaluated existing non-genetic/non-clinical models for breast cancer that incorporate modifiable risk factors. This review focuses on risk models that can be used by women themselves in the community in the absence of clinical risk factors characterization. The inclusion of modifiable factors in these models means that they can be used to improve primary prevention and health education pertinent for breast cancer. Literature searches were conducted using PubMed, ScienceDirect and the Cochrane Database of Systematic Reviews. Fourteen studies were eligible for review with sample sizes ranging from 654 to 248,407 participants. All models reviewed had acceptable calibration measures, with expected/observed (E/O) ratios ranging from 0.79 to 1.17. However, discrimination measures were variable across studies with concordance statistics (C-statistics) ranging from 0.56 to 0.89. We conclude that breast cancer risk models that include modifiable risk factors have been well calibrated but have less ability to discriminate. The latter may be a consequence of the omission of some significant risk factors in the models or from applying models to studies with limited sample sizes. More importantly, external validation is missing for most of the models. Generalization across models is also problematic as some variables may not be considered applicable to some populations and each model performance is conditioned by particular population characteristics. In conclusion, it is clear that there is still a need to develop a more reliable model for estimating breast cancer risk which has a good calibration, ability to accurately discriminate high risk and with better generalizability across populations.

Risk biomarkers enable precision in public health.

Precision medicine uses biomarkers to diagnose disease. However, they can also be used to measure risk of disease. Thus, biomarkers herald a new addition to public health - Precision Public Health. We examine the implications. Risk biomarkers are identified by analyzing population cohorts. They constitute risk factors in mathematical 'Disease Risk Models'. The risk may be fixed as in a genetic biomarker or variable as in some protein biomarkers. They help monitor current risk of disease in an individual, thereby aiding efforts to reduce risk. In the UK, the NHS Health Check system is a universal system for assessing risk and for risk reduction. The system can now make use of modern biomarkers once appropriate infrastructure and governance are in place.

Biobank Finances: A Socio-Economic Analysis and Review.

This socio-economic study is based on the widely held view that there is an inadequate supply of human biological samples that is hampering biomedical research development and innovation (RDI). The potential value of samples and the associated data are thus not being realized. We aimed to examine whether the financing of biobanks contributes to this problem and then to propose a national solution. We combined three methods: a qualitative case study; literature analysis; and informal consultations with experts. The case study enabled an examination of the complex institutional arrangements for biobanks, with a particular focus on cost models. For the purposes of comparison, a typology for biobanks was developed using the three methods. We found that it is not possible to apply a standard cost model across the diversity of biobanks, and there is a deficit in coordination and sustainability and an excess of complexity. We propose that coordination across this diversity requires dedicated resources for a national biobanking distributed research infrastructure. A coordination center would establish and improve standards and support a national portal for access. This should be financed centrally by public funds, possibly supplemented by industrial funding. We propose that: a) sample acquisition continues to be costed into projects and project proposals to ensure biobanking is driven by research needs; b) core biobanking activities and facilities be supported by central public funds distributed directly to host public institutions; and c) marginal costs for access be paid for by the user.

Public biobanks: calculation and recovery of costs.

A calculation grid developed by an international expert group was tested across biobanks in six countries to evaluate costs for collections of various types of biospecimens. The assessment yielded a tool for setting specimen-access prices that were transparently related to biobank costs, and the tool was applied across three models of collaborative partnership.

Course fees and academic ranking: insights from the IMI EMTRAIN on-course® database.

The Innovative Medicines Initiative (IMI) funded project on-course® (http://www.on-course.eu/) lists postgraduate biomedical courses in Europe and is comprehensive for all taught and research master's courses. Using on-course®, new insights into education and training in Europe can be delivered; and here we investigate the relationship between master's course fees and university ranking. We hypothesise that higher master's course fees would be associated with higher university ranking. This was indeed the case for research master's courses and for taught master's courses for non-EU students. However, we observed no correlation between taught master's course fees for EU students and university ranking, meaning EU students are paying on average as much for courses at lower ranked universities as they are for courses at higher ranked universities.

Toward a roadmap in global biobanking for health.

Biobanks can have a pivotal role in elucidating disease etiology, translation, and advancing public health. However, meeting these challenges hinges on a critical shift in the way science is conducted and requires biobank harmonization. There is growing recognition that a common strategy is imperative to develop biobanking globally and effectively. To help guide this strategy, we articulate key principles, goals, and priorities underpinning a roadmap for global biobanking to accelerate health science, patient care, and public health. The need to manage and share very large amounts of data has driven innovations on many fronts. Although technological solutions are allowing biobanks to reach new levels of integration, increasingly powerful data-collection tools, analytical techniques, and the results they generate raise new ethical and legal issues and challenges, necessitating a reconsideration of previous policies, practices, and ethical norms. These manifold advances and the investments that support them are also fueling opportunities for biobanks to ultimately become integral parts of health-care systems in many countries. International harmonization to increase interoperability and sustainability are two strategic priorities for biobanking. Tackling these issues requires an environment favorably inclined toward scientific funding and equipped to address socio-ethical challenges. Cooperation and collaboration must extend beyond systems to enable the exchange of data and samples to strategic alliances between many organizations, including governmental bodies, funding agencies, public and private science enterprises, and other stakeholders, including patients. A common vision is required and we articulate the essential basis of such a vision herein.

Selection and Implementation of the ISO9001 Standard to Support Biobanking Research Infrastructure Development.

The UK DNA Banking Network (UDBN) undertakes biobanking for genetic epidemiology research projects. A task assigned to it is the addition of scientific value to the resources under its management. This task is implemented by enabling appropriate access to the resources. We reasoned that access requires not only a fair access policy but also a quality policy implemented via a Quality Management System (QMS). UDBN decided to achieve consistency in sample management by identifying and implementing a suitable QMS with external certification. UDBN selected ISO9001 as a QMS. It was soon recognized that the QMS needed to encompass not only UDBN but also the academic department in which UDBN sits. An external certification body was selected and a post was dedicated to the role of QMS-Management Representative. Specialized software was acquired. A Quality Manual, individual training files and Standard Operating Procedures (SOPs) were prepared. QMS training was provided. These actions led to the approval of the ISO9001:2000 standard. This is the first report of an academic genetic epidemiology research laboratory receiving approval of the ISO9001 standard to validate the consistency of its operations. ISO9001 was selected because of its greater breadth of scope compared with other QMSs. We found that while laboratory protocols are transferable between labs, QMS SOPs are not transferable. This has consequences for efforts to ensure consistency across a biobank network: joint adoption of one multiparty QMS is probably required. We found that it was not possible to implement a QMS for biobanking in isolation: its host university department needed to be included. We have found that ISO9001 helps enable longitudinal accrual of data on the use of biobanking methods. Thus ISO9001 is not only a management tool to improve access to a biobanking research infrastructure but also a research tool for research infrastructure development.

Sources of variability between biobanks in the estimation of DNA concentration.

In biobank networks, accrual, aggregation, and retrieval of samples and data are impeded if minimal standards are not agreed in advance by the network members. The critical requirement is that outputs be standardized between biobanks. To start to address this problem of minimal standards, we undertook a pilot study and now report a follow-up study with 79 centers to identify sources of variability in a common measurement-the estimation of DNA concentration. Our main findings include confirmation of the results of the pilot study on overall variability between centers; fluorescence spectroscopy yields lower estimates of concentration and has less accuracy than absorption spectroscopy; and the 2 technologies differ in their sensitivity to mixing of the samples before measurement. We found that more recent servicing of liquid handling devices contributes to accuracy (at least when deploying absorption spectroscopy). We conclude that, while further study is required, there is a need to promote the development of complete Standard Operating Procedures in academic and commercial laboratories with the implementation of management systems that ensure full adherence to those procedures. There also needs to be a consensus on how much variability in measurements is acceptable for each downstream platform for technologies, including genotyping, sequencing, and epigenetics.

Impaired glucose tolerance and insulin resistance in heart failure: underrecognized and undertreated?

BACKGROUND: A link between diabetes mellitus (DM) and heart failure (HF) has been well-recognized for more than a century. HF is also closely linked to abnormal glucose regulation (AGR) and insulin resistance (IR) in patients without DM and, similarly, these conditions commonly coexist. In epidemiological studies, each condition appears to predict the other. The prevalence of AGR/IR in HF patients without DM is significantly underrecognized and, as yet, the optimal method for screening for these abnormalities in the outpatient setting is unclear. METHODS AND RESULTS: The purpose of this review is to overview the prevalence and prognostic impact of AGR and IR in HF patients without DM and discuss potential pathophysiological pathways that link these conditions with HF. The severity of glucose intolerance in patients with HF correlates with functional and clinical severity of HF and is an independent predictor of an adverse outcome. It is thought that changes in cardiac metabolism, including a switch from glucose metabolism toward fatty acid metabolism, may in part contribute to the pathophysiological processes associated with HF patients with AGR/IR. CONCLUSIONS: We discuss how pharmacological targeting of metabolic pathways in the myocardium of these patients with HF may represent novel therapeutic strategies in these at-risk patients.

Familial chronic lymphocytic leukemia in Norway and Denmark. Comments on pleiotropy and birth order.

AIM: To investigate the genetics of chronic lymphocytic leukemia (CLL). MATERIALS AND METHODS: In 56 (7%) out of 800 CLL patients with concomitant malignant hematological disease, 51 families and 141 cases were ascertained. RESULT: 106 cases (75%) of CLL, 27 cases (19%) of nonCLL and 8 cases (6%) of myeloproliferative disorders. Paternal disease was transmitted primarily to the youngest sons in the sibship while maternal disease was transmitted equally to all sibs, demonstrated by means of matrix conjugation and confirmed with Cox regression on parity and birth order (maternal-offspring combination: relative risk (RR), 95% confidence interval (CI)=1.47 (0.89 - 2.43), p=0.12, compared with paternal-offspring combination: RR=3.25, 95% CI=(1.57-6.72), p<0.001). The B-cell expression in familial and sporadic CLL was indistinguishable. CONCLUSION: Parental genomic imprinting is pointed out as one possible mechanism behind this non-Mendelian genomic output.

The UK DNA banking network: a "fair access" biobank.

The UK DNA Banking Network (UDBN) is a secondary biobank: it aggregates and manages resources (samples and data) originated by others. The network comprises, on the one hand, investigator groups led by clinicians each with a distinct disease specialism and, on the other hand, a research infrastructure to manage samples and data. The infrastructure addresses the problem of providing secure quality-assured accrual, storage, replenishment and distribution capacities for samples and of facilitating access to DNA aliquots and data for new peer-reviewed studies in genetic epidemiology. 'Fair access' principles and practices have been pragmatically developed that, unlike open access policies in this area, are not cumbersome but, rather, are fit for the purpose of expediting new study designs and their implementation. UDBN has so far distributed >60,000 samples for major genotyping studies yielding >10 billion genotypes. It provides a working model that can inform progress in biobanking nationally, across Europe and internationally.

Observational study on variability between biobanks in the estimation of DNA concentration.

BACKGROUND: There is little confidence in the consistency of estimation of DNA concentrations when samples move between laboratories. Evidence on this consistency is largely anecdotal. Therefore there is a need first to measure this consistency among different laboratories and then identify and implement remedies. A pilot experiment to test logistics and provide initial data on consistency was therefore conceived. METHODS: DNA aliquots at nominal concentrations between 10 and 300 ng/mul were dispensed into the wells of 96-well plates by one participant - the coordinating centre. Participants estimated the concentration in each well and returned estimates to the coordinating centre. RESULTS: Considerable overall variability was observed among estimates. There were statistically significant differences between participants' measurements and between fluorescence emission and absorption spectroscopy. CONCLUSION: Anecdotal evidence of variability in DNA concentration estimation has been substantiated. Reduction in variability between participants will require the identification of major sources of variation, specification of effective remedies and their implementation.