Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs

There is heightened interest in using next-generation sequencing technologies to identify rare variants that influence complex human diseases and traits. Meta-analysis is essential to this endeavor because large sample sizes are required for detecting associations with rare variants. In this article, we provide a comprehensive overview of statistical methods for meta-analysis of sequencing studies for discovering rare-variant associations. Specifically, we discuss the calculation of relevant summary statistics from participating studies, the construction of gene-level association tests, the choice of transformation for quantitative traits, the use of fixed-effects versus random-effects models, and the removal of shadow association signals through conditional analysis. We also show that meta-analysis based on properly calculated summary statistics is as powerful as joint analysis of individual-participant data. In addition, we demonstrate the performance of different meta-analysis methods by using both simulated and empirical data. We then compare four major software packages for meta-analysis of rare-variant associations—MASS, RAREMETAL, MetaSKAT, and seqMeta—in terms of the underlying statistical methodology, analysis pipeline, and software interface. Finally, we present PreMeta, a software interface that integrates the four meta-analysis packages and allows a consortium to combine otherwise incompatible summary statistics.     

Review and Evaluation of Lantana Biocontrol Programs

This paper provides a review of lantana (Lantana camara L.) biological control programs worldwide. Tables on the origins of the agents introduced for the biocontrol of lantana, are presented, including references to the biology and/or host-tests for each species. Establishment and control rates of the introduced agents and cases leading to partial control of lantana are discussed. From the review, feeding groups and species contributing to control were identified. Leaf-, flower-, and fruit-feeding species were the most successful feeding groups, and the leaf-mining chrysomelid, Uroplata girardi Pic, was the most successful control agent. The main factor preventing establishment was the number of individuals released, while cultivar preferences, parasitism and predation, and climate reduced control. The implication of these results for lantana biocontrol programs is discussed, and future research requirements are identified.     

Methods for Fitting the Right-Truncated Weibull Distribution to Life-Test and Survival Data

This paper develops mathematical and computational methods for fitting, by the method of maximum likelihood (ML), the two-parameter, right-truncated Weibull distribution (RTWD) to life-test or survival data. Some important statistical properties of the RTWD are derived and ML estimating equations for the scale and shape parameters of the RTWD are developed. The ML equations are used to express the scale parameter as an analytic function of the shape parameter and to establish a computationally useful lower bound on the ML estimate of the shape parameter. This bound is a function only of the sample observations and the (known) truncation point T. The ML equations are reducible to a single nonlinear, transcendental equation in the shape parameter, and a computationally efficient algorithm is described for solving this equation. The practical use of the methods is illustrated in two numerical examples.     

Systematic Review of Screening and Surveillance Programs to Protect Workers from Nanomaterials

BackgroundScreening and surveillance approaches for workers exposed to nanomaterials could aid in early detection of health effects, provide data for epidemiological studies and inform action to decrease exposure. The aim of this review is to identify such screening and surveillance approaches, in order to extract available data regarding (i) the studies that have successfully been implemented in present day, (ii) identification of the most common and/or toxic nano-related health hazards for workers and (iii) possible exposure surveillance markers. This review contributes to the current understanding of the risk associated with nanomaterials by determining the knowledge gap and making recommendations based on current findings.MethodsA systematic review was conducted. PubMed and Embase were searched to identify articles reporting on any surveillance-related study that described both exposure to nanomaterials and the health indicators that were measured. Four reviewers worked in pairs to independently assess the eligibility of studies and risk of bias before extraction of data. Studies were categorised according to the type of study and the medical surveillance performed, which included the type of nanomaterial, any exposure details provided, as well as health indicators and biomarkers tested.ResultsInitially 92 studies were identified, from which 84 full texts were assessed for eligibility. Seven studies met all the inclusion criteria, i.e. those performed in Taiwan, Korea, Czech Republic and the US. Of these, six compared health indicators between exposed and unexposed workers and one study described a surveillance program. All studies were at a high risk of bias. Workers were exposed to a mix of nanomaterials in three studies, carbon-based nanomaterials in two studies, nano-silver in one study and nano-titanium oxide in the other study. Two studies did not find a difference in biomarkers between exposed and unexposed workers. In addition, differences in early effects on pulmonary function or neurobehavioral tests were not observed. One study found an increased prevalence of allergic dermatitis and “sneezing” in the exposed group.ConclusionsThis review of recently published data on surveillance studies proves that there is a gap in the current knowledge, where most of the surveillance-related studies reported do not follow a set format that provides the required information on ENM characterisation, the type of exposure and the measured indicators/biomarkers. Hence, there is very low quality evidence that screening and surveillance might detect adverse health effects associated with workplace exposure. This systematic review is relevant because it proves that, although surveillance programs have been initiated and preliminary results are being published, the current studies are actually not answering the important questions or solving the overall problem regarding what the potential health hazards are among workers either handling or potentially exposed to ENMs. The recommendations, thus proposed, are based on an obvious need for (i) exposure registries, where longitudinal follow-up studies should inform surveillance, (ii) known exposure measurements or summary indices for ENMs as a reference (iii) validation of candidate biomarkers and (iv) studies that compare the effects of these surveillance approaches to usual care, e.g. those commonly followed for bulk-size hazardous materials.     

Replantation versus Prosthetic Fitting in Traumatic Arm Amputations: A Systematic Review

Background

Traumatic arm amputations can be treated with replantation or surgical formalization of the stump with or without subsequent prosthetic fitting. In the literature, many authors suggest the superiority of replantation. This systematic review compared available literature to analyze whether replantation is functionally and psychologically more profitable than formalization and prosthetic fitting in patients with traumatic arm amputation.

Methods

Functional outcome and satisfaction levels were recorded of patients with amputation levels below elbow, through elbow, and above elbow.

Results

Functional outcomes of 301 replantation patients and 172 prosthesis patients were obtained. In the replantation group, good or excellent functional scores were reported in 39% of above elbow, 55% of through elbow, and 50% of below elbow amputation cases. Nearly 100% of patients were satisfied with the replanted limb. In the prosthesis group, full use of the prosthesis was attained in 48% of above elbow and in 89% of below elbow amputation patients. Here, 29% of patients elected not to use the prosthesis for reasons including pain and functional superfluity. In both replantation patients and prosthesis wearers, a below elbow amputation yielded better functional results than higher amputation levels.

Conclusions

Replantation of a traumatically amputated arm leads to good function and higher satisfaction rates than a prosthesis, regardless of the objective functional outcome. Sensation and psychological well-being seem the two major advantages of replantation over a prosthesis. The current review of the available literature shows that in carefully selected cases replantation could be the preferred option of treatment.     

Software Review of Analytica 1.2

Analytica is an easy-to-learn, easy-to-use modeling tool that allows modelers to represent what they know through influence diagrams. These diagrams show which model quantities are derived from which others and indicate by shape and color the roles that different nodes play in the model, e.g., decision variables, chance variables, outcome variables, deterministic functions, or abstractions of sub-models. A wide variety of built-in probability distributions allow uncertainties about input values to be painlessly specified and propagated through the model via a fast, professional Monte-Carlo simulation engine. Resulting uncertainties and sensitivities about any quantity in the model can be viewed with admirable ease and flexibility by selecting among probability density, cumulative distribution, confidence band, sensitivity analysis, and other displays. Analytica features clever hierarchical model management and navigation features that serious model-builders will appreciate and that novice modelers will learn from as they are led to develop well-structured, well-documented models. Simple continuous (compartmental-flow) and Markov chain dynamic simulation models can be built by paying some detailed attention to arrays and indices, although Analytica does not support true discrete-event simulation. Within its chosen domain—uncertainty propagation through influence diagram models—Analytica is by far the easiest and best tool that we have seen.     

植物含晶细胞的结构与功能

文章就植物含晶细胞的组分、分布、形态、存在形式和功能的研究进展作了介绍。     

The Efficacy of Resiliency Training Programs: A Systematic Review and Meta-Analysis of Randomized Trials

Importance

Poor mental health places a burden on individuals and populations. Resilient persons are able to adapt to life’s challenges and maintain high quality of life and function. Finding effective strategies to bolster resilience in individuals and populations is of interest to many stakeholders.

Objectives

To synthesize the evidence for resiliency training programs in improving mental health and capacity in 1) diverse adult populations and 2) persons with chronic diseases.

Data Sources

Electronic databases, clinical trial registries, and bibliographies. We also contacted study authors and field experts.

Study Selection

Randomized trials assessing the efficacy of any program intended to enhance resilience in adults and published after 1990. No restrictions were made based on outcome measured or comparator used.

Data Extraction and Synthesis

Reviewers worked independently and in duplicate to extract study characteristics and data. These were confirmed with authors. We conducted a random effects meta-analysis on available data and tested for interaction in planned subgroups.

Main Outcomes

The standardized mean difference (SMD) effect of resiliency training programs on 1) resilience/hardiness, 2) quality of life/well-being, 3) self-efficacy/activation, 4) depression, 5) stress, and 6) anxiety.

Results

We found 25 small trials at moderate to high risk of bias. Interventions varied in format and theoretical approach. Random effects meta-analysis showed a moderate effect of generalized stress-directed programs on enhancing resilience [pooled SMD 0.37 (95% CI 0.18, 0.57) p = .0002; I² = 41%] within 3 months of follow up. Improvement in other outcomes was favorable to the interventions and reached statistical significance after removing two studies at high risk of bias. Trauma-induced stress-directed programs significantly improved stress [−0.53 (−1.04, −0.03) p = .03; I² = 73%] and depression [−0.51 (−0.92, −0.10) p = .04; I² = 61%].

Conclusions

We found evidence warranting low confidence that resiliency training programs have a small to moderate effect at improving resilience and other mental health outcomes. Further study is needed to better define the resilience construct and to design interventions specific to it.

Registration Number

PROSPERO #CRD42014007185     

Particle Sizing of Liposomal Dispersions: A Critical Evaluation of Some Quasi-Elastic Light-Scattering Data-Analysis Software Programs

Abstract

The particle size of four liposomal dispersions was estimated by quasi-elastic light scattering. The data were analyzed by three different software programs. Comparing the estimated values for the average particle size and the particle size distribution, some differences became obvious. First, it was observed that the average values obtained by different calculation methods were hardly comparable, since some systematic deviations occurred. Comparing the estimated particle size distributions, the Malvern Automeasure software was shown to produce overly smoothed, broad monomodal distributions. On the other hand, the results of both the CONTIN and the Brookhaven ISDA package agreed much better with the particle size distributions estimated by image analysis of electron microscopic photographs, revealing that all samples studied were bimodal, containing small liposomes with a rather constant diameter as well as much bigger aggregates that were gradually broken down during sonication. Concerning the ISDA software in detail, more accurate results were obtained by the NNLS-based histogram method compared to the exponential sampling method. Overall, CONTIN seemed to yield the most reliable distributions, since the smaller liposomes were detected even in the unsonicated sample.     

Beyond Eyeballing: Fitting Models to Experimental Data

Abstract

As we learn more about the biology of the Toll-like receptors (TLRs), a wide range of molecules that can activate this fascinating family of pattern recognition receptors emerges. In addition to conserved pathogenic components, endogenous danger signals created upon tissue damage are also sensed by TLRs. Detection of these types of stimuli results in TLR mediated inflammation that is vital to fight pathogenic invasion and drive tissue repair. Aberrant activation of TLRs by pathogenic and endogenous ligands has also been linked with the pathogenesis of an increasing number of infectious and autoimmune diseases, respectively. Most recently, allergen activation of TLRs has also been described, creating a third broad class of TLR stimulus that has helped to shed light on the pathogenesis of allergic disease. To date, microbial activation of TLRs remains best characterized. Each member of the TLR family senses a specific subset of pathogenic ligands, pathogen associated molecular patterns (PAMPS), and a wealth of structural and biochemical data continues to reveal the molecular mechanisms of TLR activation by PAMPs, and to demonstrate how receptor specificity is achieved. In contrast, the mechanisms by which endogenous molecules and allergens activate TLRs remain much more mysterious. Here, we provide an overview of our current knowledge of how very diverse stimuli activate the same TLRs and the structural basis of these modes of immunity.     

Curve Fitting of the Corporate Recovery Rates: The Comparison of Beta Distribution Estimation and Kernel Density Estimation

Recovery rate is essential to the estimation of the portfolio’s loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody’s. However, it has a fatal defect that it can’t fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody’s new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management.     

基于@RISK番茄潜叶蛾对我国番茄产业造成的经济损失评估

[目的]新发恶性外来入侵物种番茄潜叶蛾的入侵对我国番茄产业的安全生产造成了极大威胁。本文利用@RISK模型对化学防治、生物防治和理化诱控3种不同防治场景下我国番茄产业的潜在经济损失和投入防治后可挽回的经济损失进行综合评估,结果可为我国番茄潜叶蛾综合防治体系的构建提供参考。[方法]基于国内外文献收集到的番茄潜叶蛾危害数据（危害率、番茄产量损失率、防治成本和防治效果）,结合全国农产品商务信息公共服务平台、FAO获得我国番茄的种植面积、产量及价格等相关数据,利用@RISK模型对不防治场景和3种不同防治场景下的番茄产业的经济损失进行评估。[结果]番茄潜叶蛾在不防治场景下每年给我国番茄产业造成的经济损失总量在（8226165.67~41903398.26）万元,在化学防治（使用合成杀虫剂）、生物防治（释放天敌昆虫和微生物制剂）和理化诱控（基于灯光和合成性信息素的诱杀产品）3种不同防治场景下能有效挽回经济损失,分别为89.83%、87.90%和89.19%。[结论]基于不同的防治场景能够有效挽回番茄潜叶蛾造成的经济损失,面对该害虫在我国的严峻扩散形势,建议各级政府和行业部门应高度重视并进一步加强番茄潜叶蛾的防控,保障我国番茄产业的安全生产。