Targeted genetic testing for familial hypercholesterolaemia using next generation sequencing:a population-based study

Background<p></p> Familial hypercholesterolaemia (FH) is a common Mendelian condition which, untreated, results in premature coronary heart disease. An estimated 88% of FH cases are undiagnosed in the UK. We previously validated a method for FH mutation detection in a lipid clinic population using next generation sequencing (NGS), but this did not address the challenge of identifying index cases in primary care where most undiagnosed patients receive healthcare. Here, we evaluate the targeted use of NGS as a potential route to diagnosis of FH in a primary care population subset selected for hypercholesterolaemia.<p></p> Methods<p></p> We used microfluidics-based PCR amplification coupled with NGS and multiplex ligation-dependent probe amplification (MLPA) to detect mutations in LDLR, APOB and PCSK9 in three phenotypic groups within the Generation Scotland: Scottish Family Health Study including 193 individuals with high total cholesterol, 232 with moderately high total cholesterol despite cholesterol-lowering therapy, and 192 normocholesterolaemic controls.<p></p> Results<p></p> Pathogenic mutations were found in 2.1% of hypercholesterolaemic individuals, in 2.2% of subjects on cholesterol-lowering therapy and in 42% of their available first-degree relatives. In addition, variants of uncertain clinical significance (VUCS) were detected in 1.4% of the hypercholesterolaemic and cholesterol-lowering therapy groups. No pathogenic variants or VUCS were detected in controls.<p></p> Conclusions<p></p> We demonstrated that population-based genetic testing using these protocols is able to deliver definitive molecular diagnoses of FH in individuals with high cholesterol or on cholesterol-lowering therapy. The lower cost and labour associated with NGS-based testing may increase the attractiveness of a population-based approach to FH detection compared to genetic testing with conventional sequencing. This could provide one route to increasing the present low percentage of FH cases with a genetic diagnosis

Barriers and opportunities for evidence-based health service planning: the example of developing a Decision Analytic Model to plan services for sexually transmitted infections in the UK

Decision Analytic Models (DAMs) are established means of evidence-synthesis to differentiate between health interventions. They have mainly been used to inform clinical decisions and health technology assessment at the national level, yet could also inform local health service planning. For this, a DAM must take into account the needs of the local population, but also the needs of those planning its services. Drawing on our experiences from stakeholder consultations, where we presented the potential utility of a DAM for planning local health services for sexually transmitted infections (STIs) in the UK, and the evidence it could use to inform decisions regarding different combinations of service provision, in terms of their costs, cost-effectiveness, and public health outcomes, we discuss the barriers perceived by stakeholders to the use of DAMs to inform service planning for local populations, including (1) a tension between individual and population perspectives; (2) reductionism; and (3) a lack of transparency regarding models, their assumptions, and the motivations of those generating models

Aquatic food security:insights into challenges and solutions from an analysis of interactions between fisheries, aquaculture, food safety, human health, fish and human welfare, economy and environment

Fisheries and aquaculture production, imports, exports and equitability of distribution determine the supply of aquatic food to people. Aquatic food security is achieved when a food supply is sufficient, safe, sustainable, shockproof and sound: sufficient, to meet needs and preferences of people; safe, to provide nutritional benefit while posing minimal health risks; sustainable, to provide food now and for future generations; shock-proof, to provide resilience to shocks in production systems and supply chains; and sound, to meet legal and ethical standards for welfare of animals, people and environment. Here, we present an integrated assessment of these elements of the aquatic food system in the United Kingdom, a system linked to dynamic global networks of producers, processors and markets. Our assessment addresses sufficiency of supply from aquaculture, fisheries and trade; safety of supply given biological, chemical and radiation hazards; social, economic and environmental sustainability of production systems and supply chains; system resilience to social, economic and environmental shocks; welfare of fish, people and environment; and the authenticity of food. Conventionally, these aspects of the food system are not assessed collectively, so information supporting our assessment is widely dispersed. Our assessment reveals trade-offs and challenges in the food system that are easily overlooked in sectoral analyses of fisheries, aquaculture, health, medicine, human and fish welfare, safety and environment. We highlight potential benefits of an integrated, systematic and ongoing process to assess security of the aquatic food system and to predict impacts of social, economic and environmental change on food supply and demand

Improving identification of familial hypercholesterolaemia in primary care: Derivation and validation of the familial hypercholesterolaemia case ascertainment tool (FAMCAT)

Objective: Heterozygous familial hypercholesterolaemia (FH) is a common autosomal dominant disorder. The vast majority of affected individuals remain undiagnosed, resulting in lost opportunities for preventing premature heart disease. Better use of routine primary care data offers an opportunity to enhance detection. We sought to develop a new predictive algorithm for improving identification of individuals in primary care who could be prioritised for further clinical assessment using established diagnostic criteria. Methods: Data were analysed for 2,975,281 patients with total or LDL-cholesterol measurement from 1 Jan 1999 to 31 August 2013 using the Clinical Practice Research Datalink (CPRD). Included in this cohort study were 5050 documented cases of FH. Stepwise logistic regression was used to derive optimal multivariate prediction models. Model performance was assessed by its discriminatory accuracy (area under receiver operating curve [AUC]). Results: The FH prediction model (FAMCAT), consisting of nine diagnostic variables, showed high discrimination (AUC 0.860, 95% CI 0.848–0.871) for distinguishing cases from non-cases. Sensitivity analysis demonstrated no significant drop in discrimination (AUC 0.858, 95% CI 0.845–0.869) after excluding secondary causes of hypercholesterolaemia. Removing family history variables reduced discrimination (AUC 0.820, 95% CI 0.807–0.834), while incorporating more comprehensive family history recording of myocardial infraction significantly improved discrimination (AUC 0.894, 95% CI 0.884–0.904). Conclusion: This approach offers the opportunity to enhance detection of FH in primary care by identifying individuals with greatest probability of having the condition. Such cases can be prioritised for further clinical assessment, appropriate referral and treatment to prevent premature heart disease

Towards an Economy of Higher Education

This paper draws a distinction between ways thinking and acting, and hence of policy and practice in higher education, in terms of different kinds of economy: economies of exchange and economies of excess. Crucial features of economies of exchange are outlined and their presence in prevailing conceptions of teaching and learning is illustrated. These are contrasted with other possible forms of practice, which in turn bring to light the nature of an economy of excess. In more philosophical terms, and to expand on the picture, economies of excess are elaborated with reference, first, to the understanding of alterity in the work of Emmanuel Levinas and, second, to the idea of Dionysian intensity that is to be found in Nietzsche. In the light of critical comment on some current directions in policy and practice, the implications of these ways of thinking for the administrator, the teacher and the student in higher education are explored

Effect of primary care physicians' use of estimated glomerular filtration rate on the timing of their subspecialty referral decisions

<p>Abstract</p> <p>Background</p> <p>Primary care providers' suboptimal recognition of the severity of chronic kidney disease (CKD) may contribute to untimely referrals of patients with CKD to subspecialty care. It is unknown whether U.S. primary care physicians' use of estimated glomerular filtration rate (eGFR) rather than serum creatinine to estimate CKD severity could improve the timeliness of their subspecialty referral decisions.</p> <p>Methods</p> <p>We conducted a cross-sectional study of 154 United States primary care physicians to assess the effect of use of eGFR (versus creatinine) on the timing of their subspecialty referrals. Primary care physicians completed a questionnaire featuring questions regarding a hypothetical White or African American patient with progressing CKD. We asked primary care physicians to identify the serum creatinine and eGFR levels at which they would recommend patients like the hypothetical patient be referred for subspecialty evaluation. We assessed significant improvement in the timing [from eGFR < 30 to ≥ 30 mL/min/1.73m²) of their recommended referrals based on their use of creatinine versus eGFR.</p> <p>Results</p> <p>Primary care physicians recommended subspecialty referrals later (CKD more advanced) when using creatinine versus eGFR to assess kidney function [median eGFR 32 versus 55 mL/min/1.73m², p < 0.001]. Forty percent of primary care physicians significantly improved the timing of their referrals when basing their recommendations on eGFR. Improved timing occurred more frequently among primary care physicians practicing in academic (versus non-academic) practices or presented with White (versus African American) hypothetical patients [adjusted percentage(95% CI): 70% (45-87) versus 37% (reference) and 57% (39-73) versus 25% (reference), respectively, both p ≤ 0.01).</p> <p>Conclusions</p> <p>Primary care physicians recommended subspecialty referrals earlier when using eGFR (versus creatinine) to assess kidney function. Enhanced use of eGFR by primary care physicians' could lead to more timely subspecialty care and improved clinical outcomes for patients with CKD.</p

Focus on environmental risks and migration: causes and consequences

Environmental change poses risks to societies, including disrupting social and economic systems such as migration. At the same time, migration is an effective adaptation to environmental and other risks. We review novel science on interactions between migration, environmental risks and climate change. We highlight emergent findings, including how dominant flows of rural to urban migration mean that populations are exposed to new risks within destination areas and the requirement for urban sustainability. We highlight the issue of lack of mobility as a major issue limiting the effectiveness of migration as an adaptation strategy and leading to potentially trapped populations. The paper presents scenarios of future migration that show both displacement and trapped populations over the incoming decades. Papers in the special issue bring new insights from demography, human geography, political science and environmental science to this emerging field

Born in Bradford's Better Start: an experimental birth cohort study to evaluate the impact of early life interventions.

BACKGROUND: Early interventions are recognised as key to improving life chances for children and reducing inequalities in health and well-being, however there is a paucity of high quality research into the effectiveness of interventions to address childhood health and development outcomes. Planning and implementing standalone RCTs for multiple, individual interventions would be slow, cumbersome and expensive. This paper describes the protocol for an innovative experimental birth cohort: Born in Bradford's Better Start (BiBBS) that will simultaneously evaluate the impact of multiple early life interventions using efficient study designs. Better Start Bradford (BSB) has been allocated £49 million from the Big Lottery Fund to implement 22 interventions to improve outcomes for children aged 0-3 in three key areas: social and emotional development; communication and language development; and nutrition and obesity. The interventions will be implemented in three deprived and ethnically diverse inner city areas of Bradford. METHOD: The BiBBS study aims to recruit 5000 babies, their mothers and their mothers' partners over 5 years from January 2016-December 2020. Demographic and socioeconomic information, physical and mental health, lifestyle factors and biological samples will be collected during pregnancy. Parents and children will be linked to their routine health and local authority (including education) data throughout the children's lives. Their participation in BSB interventions will also be tracked. BiBBS will test interventions using the Trials within Cohorts (TwiCs) approach and other quasi-experimental designs where TwiCs are neither feasible nor ethical, to evaluate these early life interventions. The effects of single interventions, and the cumulative effects of stacked (multiple) interventions on health and social outcomes during the critical early years will be measured. DISCUSSION: The focus of the BiBBS cohort is on intervention impact rather than observation. As far as we are aware BiBBS is the world's first such experimental birth cohort study. While some risk factors for adverse health and social outcomes are increasingly well described, the solutions to tackling them remain elusive. The novel design of BiBBS can contribute much needed evidence to inform policy makers and practitioners about effective approaches to improve health and well-being for future generations

Text Mining for Literature Review and Knowledge Discovery in Cancer Risk Assessment and Research

Research in biomedical text mining is starting to produce technology which can make information in biomedical literature more accessible for bio-scientists. One of the current challenges is to integrate and refine this technology to support real-life scientific tasks in biomedicine, and to evaluate its usefulness in the context of such tasks. We describe CRAB – a fully integrated text mining tool designed to support chemical health risk assessment. This task is complex and time-consuming, requiring a thorough review of existing scientific data on a particular chemical. Covering human, animal, cellular and other mechanistic data from various fields of biomedicine, this is highly varied and therefore difficult to harvest from literature databases via manual means. Our tool automates the process by extracting relevant scientific data in published literature and classifying it according to multiple qualitative dimensions. Developed in close collaboration with risk assessors, the tool allows navigating the classified dataset in various ways and sharing the data with other users. We present a direct and user-based evaluation which shows that the technology integrated in the tool is highly accurate, and report a number of case studies which demonstrate how the tool can be used to support scientific discovery in cancer risk assessment and research. Our work demonstrates the usefulness of a text mining pipeline in facilitating complex research tasks in biomedicine. We discuss further development and application of our technology to other types of chemical risk assessment in the future