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.     

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.     

Caution! Overestimation of treatment effects of corticosteroid therapy for community-acquired pneumonia in a meta-analysis of randomized controlled trials

It is well known that a meta-analysis of randomized controlled trials aims to increase the power and precision of the estimated intervention effects. However, when a meta-analysis includes a limited number of patients and a small number of events, overestimation of intervention effect estimates may occur and could cause spurious results. Although many biases can cause the overestimation, random error may be the most common cause. Trial sequential analysis (TSA) can explore the independent effect of random error on intervention effect estimates in meta-analyses and protect meta-analyses against overestimation due to random error.     

Epidemiology of acute diarrhea in children living in Sicily

A longitudinal survey (February 1984 - January 1985) on the incidence of acute diarrhea episodes in a sample of 8,164 children (aged 0–12 years) living in southeastern Sicily was carried out by means of weekly telephone interviews with doctors practising in the territory. The incidence rate was 0.479 (0.472–0.485 95% C.I.) per child per year and the frequency of episodes was significantly higher (p < 0.001) in children aged 0–4 years (0.86). Diarrhea was more frequent in industrial areas than in rural ones, and almost half (45.1%) of the total episodes had a mild course. No death from diarrhea occurred and admission to hospital was reported for 8.4% of all cases.Corresponding author.     

Fluconazole dosing in continuous veno-venous haemofiltration (CVVHF): need for a high daily dose of 800 mg

To cover intermediate sensitive Candida glabrata in ICU patients,fluconazole plasma peak levels at least in the range of 16–32µg/ml appear necessary for treatment. Previous studiesdid not reach these fluconazole levels under continuous veno-venoushaemofiltration (CVVHF) with dosages of 200–600 mg fluconzoledaily. In the present study, nine patients simultaneously requiringCVVHF for treatment of acute oligoanuric renal failure and antimycotictherapy of Candida septicemia received fluconazole 800 mg/day.Fluconazole plasma levels were determined to evaluate whetherthis dosage is adequate to reach the advised fluconazole levels.Patients were dialysed on two consecutive days with an ultrafiltrationrate (UF) of 1000 ml/h or 2000 ml/h, respectively, in a randomizedorder. The predilution was 800 ml/h and 1800 ml/h, respectively.The treatment was tolerated without adverse effects. All patientsreached plasma fluconazole concentrations between 16 and 32µg/ml, remaining in this range for a minimum of 1 up to24 h with a mean of 9.6 h and a UF rate of 2000 ml/h, and 15.7h with a UF rate of 1000 ml/h. So far, there are no in vivodata on the fluconazole plasma concentrations required for effectivetreatment. However, our data demonstrate, that at least thefluconazole concentrations desirable on the basis of in vitrosusceptibility testing can be reached in critically ill patientson CVVHF in an ICU setting. However, in these patients, 800mg fluconazole/day are necessary to achieve fungicidal drugconcentrations.     

Developing Organ Offer and Acceptance Measures: When 'Good' Organs Are Turned Down

Turndowns of offers of deceased donor kidneys for transplantation can contribute to inefficiencies in the organ distribution system and inequality in access to donated organs. Match run data were obtained for 4967 'good' kidneys placed and transplanted in 2005 after fewer than 50 offers. These kidneys were not recovered from donation after cardiac death or expanded criteria donors, or from donors with a history of substance abuse. On average, these good kidneys were not accepted until after seven offers to candidates and after offers to 2.4 programs. Models for the likelihood of acceptance found several donor and candidate characteristics to be significantly related to acceptance rates (p < 0.05). After accounting for these variables, there remained 2- to 3-fold differences among transplant programs in acceptance rates. These models could be used to identify kidney transplant centers with exceptional acceptance practices. Several strategies might be employed to increase acceptance rates for good organs.     

ITERATIVE DYNAMIC PROGRAMMING FOR MINIMUM ENERGY CONTROL PROBLEMS WITH TIME DELAY

This paper presents the use of iterative dynamic programming employing exact penalty functions for minimum energy control problems. We show that exact continuously non-differentiable penalty functions are superior to continuously differentiable penalty functions in terms of satisfying final state constraints. We also demonstrate that the choice of an appropriate penalty function factor depends on the relative size of the time delay with respect to the final time and on the expected value of the energy consumption. A quadratic approximation (QA) of the delayed variables is much better than a linear approximation (LA) of the same for relatively large time delays. The QA improves the rate of convergence and avoids the formation of ‘kinks‘. A more general way of selecting appropriate penalty function factors is given and the results obtained using four illustrative examples of varying complexity corroborate the efficacy of the method.