Background Mendelian randomization (MR) has developed into an established method for strengthening causal inference and estimating causal effects, largely due to the proliferation of genome-wide association studies. However, genetic instruments remain controversial, as horizontal pleiotropic effects can introduce bias into causal estimates. Recent work has highlighted the potential of gene–environment interactions in detecting and correcting for pleiotropic bias in MR analyses. Methods We introduce MR using Gene-by-Environment interactions (MRGxE) as a framework capable of identifying and correcting for pleiotropic bias. If an instrument–covariate interaction induces variation in the association between a genetic instrument and exposure, it is possible to identify and correct for pleiotropic effects. The interpretation of MRGxE is similar to conventional summary MR approaches, with a particular advantage of MRGxE being the ability to assess the validity of an individual instrument. Results We investigate the effect of adiposity, measured using body mass index (BMI), upon systolic blood pressure (SBP) using data from the UK Biobank and a single weighted allelic score informed by data from the GIANT consortium. We find MRGxE produces findings in agreement with two-sample summary MR approaches. Further, we perform simulations highlighting the utility of the approach even when the MRGxE assumptions are violated. Conclusions By utilizing instrument–covariate interactions in MR analyses implemented within a linear-regression framework, it is possible to identify and correct for horizontal pleiotropic bias, provided the average magnitude of pleiotropy is constant across interaction-covariate subgroups.

a equal supervisory contribution AbstractBackground: Mendelian randomization has developed into an established method for strengthening causal inference and estimating causal effects, largely due to the proliferation of genome-wide association studies. However, genetic instruments remain controversial as pleiotropic effects can introduce bias into causal estimates. Recent work has highlighted the potential of gene-environment interactions in detecting and correcting for pleiotropic bias in Mendelian randomization analyses. Methods:We introduce MR using Gene-by-Environment interactions (MRGxE) as a framework capable of identifying and correcting for pleiotropic bias, drawing upon developments in econometrics and epidemiology. If an instrument-covariate interaction induces variation in the association between a genetic instrument and exposure, it is possible to identify and correct for pleiotropic effects. The interpretation of MRGxE is similar to conventional summary Mendelian randomization approaches, with a particular advantage of MRGxE being the ability to assess the validity of an individual instrument. Results:We investigate the effect of BMI upon systolic blood pressure (SBP) using data from the UK Biobank and the GIANT consortium using a single instrument (a weighted allelic score). We find MRGxE produces findings in agreement with MR Egger regression in a two-sample summary MR setting, however, association estimates obtained across all methods differ considerably when excluding related participants or individuals of non-European ancestry. This could be a consequence of selection bias, though there is also potential for introducing bias by using a mixed ancestry population. Further, we assess the performance of MRGxE with respect to identifying and correcting for horizontal pleiotropy in a simulation setting, highlighting the utility of the approach even when the MRGxE assumptions are violated. Conclusions:By utilising instrument-covariate interactions within a linear regression framework, it is possible to identify and correct for pleiotropic bias, provided the average magnitude of pleiotropy is constant across interaction covariate subgroups.

BackgroundRotavirus infection is responsible for about 500,000 deaths annually, and the disease burden is disproportionately borne by children in low-income countries. Recently the World Health Organization (WHO) has released a global recommendation that all countries include infant rotavirus vaccination in their national immunization programs. Our objective was to provide information on the expected health, economic and financial consequences of rotavirus vaccines in the 72 GAVI support-eligible countries.MethodsWe synthesized population-level data from various sources (primarily from global-level databases) for the 72 countries eligible for the support by the GAVI Alliance (GAVI-eligible countries) in order to estimate the health and economic impact associated with rotavirus vaccination programs. The primary outcome measure was incremental cost (in 2005 international dollars [I$]) per disability-adjusted life year (DALY) averted. We also projected the expected reduction in rotavirus disease burden and financial resources required associated with a variety of scale-up scenarios.ResultsUnder the base-case assumptions (70% coverage), vaccinating one single birth cohort would prevent about 55% of rotavirus associated deaths in the 72 GAVI-eligible countries. Assuming I$25 per vaccinated child (~$5 per dose), the number of countries with the incremental cost per DALY averted less than I$200 was 47. Using the WHO's cost-effectiveness threshold based on per capita GDP, the vaccines were considered cost-effective in 68 of the 72 countries (~94%). A 10-year routine rotavirus vaccination would prevent 0.9-2.8 million rotavirus associated deaths among children under age 5 in the poorest parts of the world, depending on vaccine scale-up scenarios. Over the same intervention period, rotavirus vaccination programs would also prevent 4.5-13.3 million estimated cases of hospitalization and 41-107 million cases of outpatient clinic visits in the same population.ConclusionsOur findings suggest that rotavirus vaccination would be considered a worthwhile investment for improving general development as well as childhood health level in most low-income countries, with a favorable cost-effectiveness profile even under a vaccine price ($1.5-$5.0 per dose) higher than those of traditional childhood vaccines.

Visual stimuli fade from awareness under retinal stabilization or careful fixation, a phenomenon documented by Troxler more than 200 years ago. Research on visual fading during normal visual fixation typically has been restricted to discrete, simple, low-contrast shapes presented peripherally against a uniform or textured background. In four experiments, we document a striking new visual fading effect in which entire photographs of scenes fade to a uniform luminance and hue during normal visual fixation. Critically, this "scene fading" can be induced almost instantaneously by some types of visual transients but not by others. These induced fading effects are sufficiently robust that they can be experienced by most observers in a single trial. Taken as a whole, the effects are inconsistent with simple contrast adaptation, gradual Troxler fading, or transient-induced fading. They are, however, consistent with the idea that small contrast decrements can induce fading of entire scenes. The methods provide a robust tool for the exploration of visual fading, and the results could have important implications for the role of filling-in and neural adaptation in our visual awareness of natural scenes and other complex stimuli.