Population Genetics Identifies Challenges in Analyzing Rare Variants

Geneticists have, for years, understood the nature of genome‐wide association studies using common genomic variants. Recently, however, focus has shifted to the analysis of rare variants. This presents potential problems for researchers, as rare variants do not always behave in the same way common variants do, sometimes rendering decades of solid intuition moot. In this paper, we present examples of the differences between common and rare variants. We show why one must be significantly more careful about the origin of rare variants, and how failing to do so can lead to highly inflated type I error. We then explain how to best avoid such concerns with careful understanding and study design. Additionally, we demonstrate that a seemingly low error rate in next‐generation sequencing can dramatically impact the false‐positive rate for rare variants. This is due to the fact that rare variants are, by definition, seen infrequently, making it hard to distinguish between errors and real variants. Compounding this problem is the fact that the proportion of errors is likely to get worse, not better, with increasing sample size. One cannot simply scale their way up in order to solve this problem. Understanding these potential pitfalls is a key step in successfully identifying true associations between rare variants and diseases.     

Exploring the impacts of organisational structure,policy and practice on the health inequalities of marginalised communities: Illustrative cases from the UK healthcare system

This paper explores how organisational structure, policies and practices in healthcare can inadvertently disadvantage marginalised populations (e.g. individuals from ethnic minority backgrounds) and reinforce health inequalities. We draw upon three diverse UK healthcare settings (long term care institutions, high security hospitals and community pharmacies) to illustrate how systemic injustices negatively impact on access to care, treatment and health outcomes. The first case study considers the care of older people within nursing homes; specifically the disempowering effects of this service structure and impacts of choice reduction upon health and their access to health provision. The second case study explores the impact of security restrictions upon patients within high security hospitals, focusing particularly on the maintenance of relationships and support networks outside of the hospital. The third and final case study, draws upon a national community pharmacy medicine management service to illustrate ways in which policies and guidelines inadvertently obstruct patients' engagement with the service within a community setting. We draw upon these settings to highlight inequalities within different contexts and to illustrate the ways in which well intended services can inadvertently disadvantage marginalised communities in multiple ways.     

In Vitro-In Vivo Extrapolation and Hepatic Clearance-Dependent Underprediction

Accurately predicting the hepatic clearance of compounds using in vitro to in vivo extrapolation (IVIVE) is crucial within the pharmaceutical industry. However, several groups have recently highlighted the serious error in the process. Although empirical or regression-based scaling factors may be used to mitigate the common underprediction, they provide unsatisfying solutions because the reasoning behind the underlying error has yet to be determined. One previously noted trend was intrinsic clearance-dependent underprediction, highlighting the limitations of current in vitro systems. When applying these generated in vitro intrinsic clearance values during drug development and making first-in-human dose predictions for new chemical entities though, hepatic clearance is the parameter that must be estimated using a model of hepatic disposition, such as the well-stirred model. Here, we examine error across hepatic clearance ranges and find a similar hepatic clearance-dependent trend, with high clearance compounds not predicted to be so, demonstrating another gap in the field.