Application of family-based tests of association for rare variants to pathways

Pathway analysis approaches for sequence data typically either operate in a single stage (all variants within all genes in the pathway are combined into a single, very large set of variants that can then be analyzed using standard gene-based test statistics) or in 2-stages (gene-based p values are computed for all genes in the pathway, and then the gene-based p values are combined into a single pathway p value). To date, little consideration has been given to the performance of gene-based tests (typically designed for a smaller number of single-nucleotide variants [SNVs]) when the number of SNVs in the gene or in the pathway is very large and the genotypes come from sequence data organized in large pedigrees. We consider recently proposed gene-based tests for rare variants from complex pedigrees that test for association between a large set of SNVs and a qualitative phenotype of interest (1-stage analyses) as well as 2-stage approaches. We find that many of these methods show inflated type I errors when the number of SNVs in the gene or the pathway is large (\u3e200 SNVs) and when using standard approaches to estimate the genotype covariance matrix. Alternative methods are needed when testing very large sets of SNVs in 1-stage approaches

Evaluation of the Power and Type 1 Error of Recently Proposed Family-based Tests of Assocations for Rare Variants

Until very recently, few methods existed to analyze rare-variant association with binary phenotypes in complex pedigrees. We consider a set of recently proposed methods applied to the simulated and real hypertension phenotype as part of the Genetic Analysis Workshop 18. Minimal power of the methods is observed for genes containing variants with weak effects on the phenotype. Application of the methods to the real hypertension phenotype yielded no genes meeting a strict Bonferroni cutoff of significance. Some prior literature connects 3 of the 5 most associated genes (p \u3c1 × 10−4) to hypertension or related phenotypes. Further methodological development is needed to extend these methods to handle covariates, and to explore more powerful test alternatives

Application of Family-based Tests of Association for Rare Variants to Pathways

Pathway analysis approaches for sequence data typically either operate in a single stage (all variants within all genes in the pathway are combined into a single, very large set of variants that can then be analyzed using standard “gene-based” test statistics) or in 2-stages (gene-based p values are computed for all genes in the pathway, and then the gene-based p values are combined into a single pathway p value). To date, little consideration has been given to the performance of gene-based tests (typically designed for a smaller number of single-nucleotide variants [SNVs]) when the number of SNVs in the gene or in the pathway is very large and the genotypes come from sequence data organized in large pedigrees. We consider recently proposed gene-based tests for rare variants from complex pedigrees that test for association between a large set of SNVs and a qualitative phenotype of interest (1-stage analyses) as well as 2-stage approaches. We find that many of these methods show inflated type I errors when the number of SNVs in the gene or the pathway is large (\u3e200 SNVs) and when using standard approaches to estimate the genotype covariance matrix. Alternative methods are needed when testing very large sets of SNVs in 1-stage approaches

General Approaches for Combining Multiple Rare Variant Associate Tests Provide Improved Power Across a Wider Range of Genetic Architecture

In the wake of the widespread availability of genome sequencing data made possible by way of nextgeneration technologies, a flood of gene‐based rare variant tests have been proposed. Most methods claim superior power against particular genetic architectures. However, an important practical issue remains for the applied researcher—namely, which test should be used for a particular association study which may consider multiple genes and/or multiple phenotypes. Recently, tests have been proposed which combine individual tests to minimize power loss while improving the robustness to a wide range of genetic architectures. In our analysis, we propose an expansion of these approaches, by providing a general method that works for combining an arbitrarily large number of any gene‐based rare variant test—a flexibility typically not available in other combined testing methods. We provide a theoretical framework for evaluating our combined test to provide direct insights into the relationship between test‐test correlation, test power and the combined test power relative to individual testing approaches and other combined testing approaches. We demonstrate that our flexible combined testing method can provide improved power and robustness against a wide range of genetic architectures. We further demonstrate the performance of our combined test on simulated genotypes, as well as on a dataset of real genotypes with simulated phenotypes. We support the increased use of flexible combined tests in practice to maximize robustness of rare‐variant testing strategies against a wide‐range of genetic architectures

Analgesic Management of Pain in Elite Athletes: A Systematic Review

Objective: To identify the prevalence, frequency of use, and effects of analgesic pain management strategies used in elite athletes. Design: Systematic literature review. Data Sources: Six databases: Ovid/Medline, SPORTDiscus, CINAHL, Embase, Cochrane Library, and Scopus. Eligibility Criteria for Selecting Studies: Empirical studies involving elite athletes and focused on the use or effects of medications used for pain or painful injury. Studies involving recreational sportspeople or those that undertake general exercise were excluded. Main Results: Of 70 articles found, the majority examined the frequency with which elite athletes use pain medications, including nonsteroidal anti-inflammatory drugs (NSAIDs), corticosteroids, anesthetics, and opioids. A smaller set of studies assessed the effect of medications on outcomes such as pain, function, and adverse effects. Oral NSAIDs are reported to be the most common medication, being used in some international sporting events by over 50% of athletes. Studies examining the effects of pain medications on elite athletes typically involved small samples and lacked control groups against which treated athletes were compared. Conclusions: Existing empirical research does not provide a sufficient body of evidence to guide athletes and healthcare professionals in making analgesic medication treatment decisions. Based on the relatively robust evidence regarding the widespread use of NSAIDs, clinicians and policymakers should carefully assess their current recommendations for NSAID use and adhere to a more unified consensus-based strategy for multidisciplinary pain management in elite athletes. In the future, we hope to see more rigorous, prospective studies of various pain management strategies in elite athletes, thus enabling a shift from consensus-based recommendations to evidence-based recommendations

A National Study on the Effects of Concussion in Collegiate Athletes and US Military Service Academy Members: The NCAA-DoD Concussion Assessment, Research and Education (CARE) Consortium Structure and Methods

BACKGROUND: The natural history of mild traumatic brain injury (TBI) or concussion remains poorly defined and no objective biomarker of physiological recovery exists for clinical use. The National Collegiate Athletic Association (NCAA) and the US Department of Defense (DoD) established the Concussion Assessment, Research and Education (CARE) Consortium to study the natural history of clinical and neurobiological recovery after concussion in the service of improved injury prevention, safety and medical care for student-athletes and military personnel. OBJECTIVES: The objectives of this paper were to (i) describe the background and driving rationale for the CARE Consortium; (ii) outline the infrastructure of the Consortium policies, procedures, and governance; (iii) describe the longitudinal 6-month clinical and neurobiological study methodology; and (iv) characterize special considerations in the design and implementation of a multicenter trial. METHODS: Beginning Fall 2014, CARE Consortium institutions have recruited and enrolled 23,533 student-athletes and military service academy students (approximately 90% of eligible student-athletes and cadets; 64.6% male, 35.4% female). A total of 1174 concussions have been diagnosed in participating subjects, with both concussion and baseline cases deposited in the Federal Interagency Traumatic Brain Injury Research (FITBIR) database. CONCLUSIONS: Challenges have included coordinating regulatory issues across civilian and military institutions, operationalizing study procedures, neuroimaging protocol harmonization across sites and platforms, construction and maintenance of a relational database, and data quality and integrity monitoring. The NCAA-DoD CARE Consortium represents a comprehensive investigation of concussion in student-athletes and military service academy students. The richly characterized study sample and multidimensional approach provide an opportunity to advance the field of concussion science, not only among student athletes but in all populations at risk for mild TBI

Interassociation Consensus Statement on Cardiovascular Care of College Student-Athletes

Cardiovascular evaluation and care of college student-athletes is gaining increasing attention from both the public and medical communities. Emerging strategies include screening of the general athlete population, recommendations of permissible levels of participation by athletes with identified cardiovascular conditions, and preparation for responding to unanticipated cardiac events in athletic venues. The primary focus has been sudden cardiac death and the utility of screening with or without advanced cardiac screening. The National Collegiate Athletic Association convened a multidisciplinary task force to address cardiovascular concerns in collegiate student-athletes and to develop consensus for an interassociation statement. This document summarizes the task force deliberations and follow-up discussions, and includes available evidence on cardiovascular risk, pre-participation evaluation, and the recognition of and response to cardiac arrest. Future recommendations for cardiac research initiatives, education, and collaboration are also provided

Developing mental health literacy and cultural competence in elite sport

Mental well-being, and mental health symptoms and disorders amongst elite athletes, have attracted a great deal of discussion recently. Current epidemiological evidence illustrates that mental health symptoms and disorders in elite athletes are prevalent and a concern for athletes, coaches, and sport organizations. Within the last two years, five consensus, expert, and position statements have been written on the topic of mental health in elite sport. A strategy suggested by each of the five statements and aimed at preventing and treating mental health symptoms and disorders in elite athletes, both individually and systemically, is, to employ education interventions, specifically those based on increasing mental health literacy. Mental health literacy has come to include concepts related to knowledge of effective self help and self-management strategies, challenging mental disorder stigma, awareness and use of mental health first aid to assist others, and the facilitation of help seeking behaviors. In elite sport, questions remain about how mental health literacy can address the unique needs of the individual athlete, but also factor in their culture and their environment in an effort to prevent and treat mental health symptoms and disorders. The purpose of this commentary is twofold: 1) to explore the evolving concept of mental health literacy within elite sport which addresses individuals, their culture, and their environment, and 2) to propose strategies for best practice and research in mental health literacy within elite sport relying on collaboration between sports psychiatry, sport psychology, and clinical psychology

General Approach for Combining Diverse Rare Variant Association Tests Provides Improved Robustness Across a Wider Range of Genetic Architectures

The widespread availability of genome sequencing data made possible by way of next-generation technologies has yielded a flood of different gene-based rare variant association tests. Most of these tests have been published because they have superior power for particular genetic architectures. However, for applied researchers it is challenging to know which test to choose in practice when little is known a priori about genetic architecture. Recently, tests have been proposed which combine two particular individual tests (one burden and one variance components) to minimize power loss while improving robustness to a wider range of genetic architectures. In our analysis we propose an expansion of these approaches, yielding a general method that works for combining any number of individual tests. We demonstrate that running multiple different tests on the same dataset and using a Bonferroni correction for multiple testing is never better than combining tests using our general method. We also find that using a test statistic that is highly robust to the inclusion of non-causal variants (Joint-infinity) together with a previously published combined test (SKAT-O) provides improved robustness to a wide range of genetic architectures and should be considered for use in practice. Software for this approach is supplied. We support the increased use of combined tests in practice-- as well as further exploration of novel combined testing approaches using the general framework provided here--to maximize robustness of rare-variant testing strategies against a wide range of genetic architectures