Mendelian randomization: concepts and scope

Mendelian randomization (MR) is a method of studying the causal effects of modifiable exposures (i.e., potential risk factors) on health, social, and economic outcomes using genetic variants associated with the specific exposures of interest. MR provides a more robust understanding of the influence of these exposures on outcomes because germline genetic variants are randomly inherited from parents to offspring and, as a result, should not be related to potential confounding factors that influence exposure–outcome associations. The genetic variant can therefore be used as a tool to link the proposed risk factor and outcome, and to estimate this effect with less confounding and bias than conventional epidemiological approaches. We describe the scope of MR, highlighting the range of applications being made possible as genetic data sets and resources become larger and more freely available. We outline the MR approach in detail, covering concepts, assumptions, and estimation methods. We cover some common misconceptions, provide strategies for overcoming violation of assumptions, and discuss future prospects for extending the clinical applicability, methodological innovations, robustness, and generalizability of MR findings

Causal Inference with Genetic Data:Past, Present, and Future

The set of methods discussed in this collection has emerged from the convergence of two scientific fields-genetics and causal inference. In this introduction, we discuss relevant aspects of each field and show how their convergence arises from the natural experiments that genetics offer. We present introductory concepts useful to readers unfamiliar with genetically informed methods for causal inference. We conclude that existing applications and foreseeable developments should ensure that we rapidly reap the rewards of this relatively new field, not only in terms of our understanding of human disease and development, but also in terms of tangible translational applications

What is orthopaedic triage? A systematic review

RATIONALE, AIMS AND OBJECTIVES: Complex and chronic disease is placing significant pressure on hospital outpatient departments. Novel ways of delivering care have been developed recently and are often described as ‘triage’ services. This paper reviews the literature pertaining to definitions and descriptions of orthopaedic/musculoskeletal triage processes, in order to provide information on ‘best practice’ to assist health care facilities. METHOD: A comprehensive open-ended search was conducted using electronic databases to identify studies describing models of triage clinics for patients with a musculoskeletal/orthopaedic complaint, who have been referred to hospital outpatient clinics for a surgical consultation. Studies were critically appraised using the McMaster quality appraisal tool and ranked using the National Health and Medical Research Council hierarchy of evidence. A thematic analysis of the definitions, processes and procedures of triage described within the literature was undertaken. RESULTS: 1930 studies were identified and 45 were included in the review (including diagnostic and evaluative research). The hierarchy of evidence ranged from I to IV; however, the majority were at low levels of evidence and scored poorly on the critical appraisal tool. Three broad themes of triage were identified: presence of a referral, configuration of the triage (who, how and where) and the aim of triage. However, there were significant inconsistencies across these themes. CONCLUSIONS: This systematic review highlighted the need for standardization of the definition of triage, the procedures of assessment and management and measures of outcome used in orthopaedic/musculoskeletal triage to ensure best-practice processes, procedures and outcomes for triage clinics

Effect of the excitation energy, type, and amount of defects

We present a detailed Raman study of defective graphene samples containing specific types of defects. In particular, we compared sp3 sites, vacancies, and substitutional Boron atoms. We find that the ratio between the D and G peak intensities, I(D)/I(G), does not depend on the geometry of the defect (within the Raman spectrometer resolution). In contrast, in the limit of low defect concentration, the ratio between the D′ and G peak intensities is higher for vacancies than sp3 sites. By using the local activation model, we attribute this difference to the term CS,x, representing the Raman cross section of I(x)/I(G) associated with the distortion of the crystal lattice after defect introduction per unit of damaged area, where x = D or D′. We observed that CS,D=0 for all the defects analyzed, while CS,D′ of vacancies is 2.5 times larger than CS,D′ of sp3 sites. This makes I(D)/I(D′) strongly sensitive to the nature of the defect. We also show that the exact dependence of I(D)/I(D′) on the excitation energy may be affected by the nature of the defect. These results can be used to obtain further insights into the Raman scattering process (in particular for the D′ peak) in order to improve our understanding and modeling of defects in graphene

Challenges and novel approaches for investigating molecular mediation

Understanding mediation is useful for identifying intermediates lying between an exposure and an outcome which, when intervened upon, will block (some or all of) the causal pathway between the exposure and outcome. Mediation approaches used in conventional epidemiology have been adapted to understanding the role of molecular intermediates in situations of high-dimensional omics data with varying degrees of success. In particular, the limitations of observational epidemiological study including confounding, reverse causation and measurement error can afflict conventional mediation approaches and may lead to incorrect conclusions regarding causal effects. Solutions to analysing mediation which overcome these problems include the use of instrumental variable methods such as Mendelian randomization, which may be applied to evaluate causality in increasingly complex networks of omics data

Functional brain imaging studies of youth depression: A systematic review

AbstractBackgroundThere is growing interest in understanding the neurobiology of major depressive disorder (MDD) in youth, particularly in the context of neuroimaging studies. This systematic review provides a timely comprehensive account of the available functional magnetic resonance imaging (fMRI) literature in youth MDD.MethodsA literature search was conducted using PubMED, PsycINFO and Science Direct databases, to identify fMRI studies in younger and older youth with MDD, spanning 13–18 and 19–25years of age, respectively.ResultsTwenty-eight studies focusing on 5 functional imaging domains were identified, namely emotion processing, cognitive control, affective cognition, reward processing and resting-state functional connectivity. Elevated activity in “extended medial network” regions including the anterior cingulate, ventromedial and orbitofrontal cortices, as well as the amygdala was most consistently implicated across these five domains. For the most part, findings in younger adolescents did not differ from those in older youth; however a general comparison of findings in both groups compared to adults indicated differences in the domains of cognitive control and affective cognition.ConclusionsYouth MDD is characterized by abnormal activations in ventromedial frontal regions, the anterior cingulate and amygdala, which are broadly consistent with the implicated role of medial network regions in the pathophysiology of depression. Future longitudinal studies examining the effects of neurodevelopmental changes and pubertal maturation on brain systems implicated in youth MDD will provide a more comprehensive neurobiological model of youth depression

Using Mendelian randomization to determine causal effects of maternal pregnancy (intrauterine) exposures on offspring outcomes:Sources of bias and methods for assessing them

Mendelian randomization (MR), the use of genetic variants as instrumental variables (IVs) to test causal effects, is increasingly used in aetiological epidemiology. Few of the methodological developments in MR have considered the specific situation of using genetic IVs to test the causal effect of exposures in pregnant women on postnatal offspring outcomes. In this paper, we describe specific ways in which the IV assumptions might be violated when MR is used to test such intrauterine effects. We highlight the importance of considering the extent to which there is overlap between genetic variants in offspring that influence their outcome with genetic variants used as IVs in their mothers. Where there is overlap, and particularly if it generates a strong association of maternal genetic IVs with offspring outcome via the offspring genotype, the exclusion restriction assumption of IV analyses will be violated. We recommend a set of analyses that ought to be considered when MR is used to address research questions concerned with intrauterine effects on post-natal offspring outcomes, and provide details of how these can be undertaken and interpreted. These additional analyses include the use of genetic data from offspring and fathers, examining associations using maternal non-transmitted alleles, and using simulated data in sensitivity analyses (for which we provide code). We explore the extent to which new methods that have been developed for exploring violation of the exclusion restriction assumption in the two-sample setting (MR-Egger and median based methods) might be used when exploring intrauterine effects in one-sample MR. We provide a list of recommendations that researchers should use when applying MR to test the effects of intrauterine exposures on postnatal offspring outcomes and use an illustrative example with real data to demonstrate how our recommendations can be applied and subsequent results appropriately interpreted