Replication of LDL SWAs hits in PROSPER/PHASE as validation for future (pharmaco)genetic analyses

<p><b>Background:</b> The PHArmacogenetic study of Statins in the Elderly at risk (PHASE) is a genome wide association study in the PROspective Study of Pravastatin in the Elderly at risk for vascular disease (PROSPER) that investigates the genetic variation responsible for the individual variation in drug response to pravastatin. Statins lower LDL-cholesterol in general by 30%, however not in all subjects. Moreover, clinical response is highly variable and adverse effects occur in a minority of patients. In this report we first describe the rationale of the PROSPER/PHASE project and second show that the PROSPER/PHASE study can be used to study pharmacogenetics in the elderly.</p> <p><b>Methods:</b> The genome wide association study (GWAS) was conducted using the Illumina 660K-Quad beadchips following manufacturer's instructions. After a stringent quality control 557,192 SNPs in 5,244 subjects were available for analysis. To maximize the availability of genetic data and coverage of the genome, imputation up to 2.5 million autosomal CEPH HapMap SNPs was performed with MACH imputation software. The GWAS for LDL-cholesterol is assessed with an additive linear regression model in PROBABEL software, adjusted for age, sex, and country of origin to account for population stratification.</p> <p><b>Results:</b> Forty-two SNPs reached the GWAS significant threshold of p = 5.0e-08 in 5 genomic loci (APOE/APOC1; LDLR; FADS2/FEN1; HMGCR; PSRC1/CELSR5). The top SNP (rs445925, chromosome 19) with a p-value of p = 2.8e-30 is located within the APOC1 gene and near the APOE gene. The second top SNP (rs6511720, chromosome 19) with a p-value of p = 5.22e-15 is located within the LDLR gene. All 5 genomic loci were previously associated with LDL-cholesterol levels, no novel loci were identified. Replication in WOSCOPS and CARE confirmed our results.</p> <p><b>Conclusion:</b> With the GWAS in the PROSPER/PHASE study we confirm the previously found genetic associations with LDL-cholesterol levels. With this proof-of-principle study we show that the PROSPER/PHASE study can be used to investigate genetic associations in a similar way to population based studies. The next step of the PROSPER/PHASE study is to identify the genetic variation responsible for the variation in LDL-cholesterol lowering in response to statin treatment in collaboration with other large trials.</p&gt

Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve

Engineering periplasmic ligand binding proteins as glucose nanosensors

Diabetes affects over 100 million people worldwide. Better methods for monitoring blood glucose levels are needed for improving disease management. Several labs have previously made glucose nanosensors by modifying members of the periplasmic ligand binding protein superfamily. This minireview summarizes recent developments in constructing new versions of these proteins that are responsive within the physiological range of blood glucose levels, employ new reporter groups, and/or are more robust. These experiments are important steps in the development of novel proteins that have the characteristics needed for an implantable glucose nanosensor for diabetes management: specificity for glucose, rapid response, sensitivity within the physiological range of glucose concentrations, reproducibility, and robustness

An experimental investigation into the dimensional error of powder-binder three-dimensional printing

This paper is an experimental investigation into the dimensional error of the rapid prototyping additive process of powder-binder three-dimensional printing. Ten replicates of a purpose-designed part were produced using a three-dimensional printer, and measurements of the internal and external features of all surfaces were made using a general purpose coordinate measuring machine. The results reveal that the bases of all replicates (nominally flat) have a concave curvature, producing a flatness error of the primary datum. This is in contrast to findings regarding other three-dimensional printing processes, widely reported in the literature, where a convex curvature was observed. All external surfaces investigated in this study showed positive deviation from nominal values, especially in the z-axis. The z-axis error consisted of a consistent positive cumulative error and a different constant error in different replicates. By compensating for datum surface error, the average total height error of the test parts can be reduced by 25.52 %. All the dimensional errors are hypothesised to be explained by expansion and the subsequent distortion caused by layer interaction during and after the printing process

Value of Laboratory Tests in Employer-Sponsored Health Risk Assessments for Newly Identifying Health Conditions: Analysis of 52,270 Participants

Employer-sponsored health risk assessments (HRA) may include laboratory tests to provide evidence of disease and disease risks for common medical conditions. We evaluated the ability of HRA-laboratory testing to provide new disease-risk information to participants.We performed a cross-sectional analysis of HRA-laboratory results for participating adult employees and their eligible spouses or their domestic partners, focusing on three common health conditions: hyperlipidemia, diabetes mellitus, and chronic kidney disease. HRA with laboratory results of 52,270 first-time participants were analyzed. Nearly all participants had access to health insurance coverage. Twenty-four percent (12,392) self-reported one or more of these medical conditions: 21.1% (11,017) self-identified as having hyperlipidemia, 4.7% (2,479) self-identified as having diabetes, and 0.7% (352) self-identified as having chronic kidney disease. Overall, 36% (n = 18,540) of participants had laboratory evidence of at least one medical condition newly identified: 30.7% (16,032) had laboratory evidence of hyperlipidemia identified, 1.9% (984) had laboratory evidence of diabetes identified, and 5.5% (2,866) had laboratory evidence of chronic kidney disease identified. Of all participants with evidence of hyperlipidemia 59% (16,030 of 27,047), were newly identified through the HRA. Among those with evidence of diabetes 28% (984 of 3,463) were newly identified. The highest rate of newly identified disease risk was for chronic kidney disease: 89% (2,866 of 3,218) of participants with evidence of this condition had not self-reported it. Men (39%) were more likely than women (33%) to have at least one newly identified condition (p<0.0001). Among men, lower levels of educational achievement were associated with modestly higher rates of newly identified disease risk (p<0.0001); the association with educational achievement among women was unclear. Even among the youngest age range (20 to 29 year olds), nearly 1 in 4 participants (24%) had a newly identified risk for disease.These results support the important role of employer-sponsored laboratory testing as an integral element of HRA for identifying evidence of previously undiagnosed common medical conditions in individuals of all working age ranges, regardless of educational level and gender

The Myocardial Ischemia Reduction with Acute Cholesterol Lowering trial: MIRACuLous or not, it's time to change current practice

The Myocardial Ischemia Reduction with Aggressive Cholesterol Lowering (MIRACL) study was the first trial to assess whether statins might be of clinical benefit in those with recently unstable coronary disease. MIRACL found that high-dose atorvastatin was safe and reduced the incidence of the composite endpoint, death, non-fatal myocardial infarction, resuscitated sudden cardiac death or emergent rehospitalization for recurrent ischemia at 16 weeks when compared with placebo. Despite a number of important study limitations, MIRACL's findings and the prior observation that inpatient initiation of lipid-lowering therapy is associated with higher rates of subsequent utilization, suggest that it is prudent to begin statin therapy when patients present with an acute coronary syndrome

Climate-carbon cycle uncertainties and the Paris Agreement

The Paris Agreement aims to address the gap between existing climate policies and policies consistent with ‘holding the increase in global average temperature to well below 2C’. The feasibility of meeting the target has been questioned both in terms of the possible requirement for negative emissions, and ongoing debate on the sensitivity of the climate-carbon cycle system. Using a sequence of ensembles of a fully dynamic three-dimensional climate-carbon cycle model, forced by emissions from an integrated assessment model of regional-level climate policy, economy, and technological transformation, we show that a reasonable interpretation of the Paris Agreement is still technically achievable. Specifically, limiting peak (decadal) warming to less than 1.7°C, or end-century warming to less than 1.54°C, occurs in 50% of our simulations in a policy scenario without net negative emissions or excessive stringency in any policy domain. We evaluate two mitigation scenarios, with 200 GTC and 307 GTC post-2017 emissions, quantifying spatio-temporal variability of warming, precipitation, ocean acidification and marine productivity. Under rapid decarbonisation decadal variability dominates the mean response in critical regions, with significant implications for decision making, demanding impact methodologies that address non-linear spatio-temporal responses. Ignoring carbon-cycle feedback uncertainties (explaining 47% of peak warming uncertainty) becomes unreasonable under strong mitigation conditions.We acknowledge C-EERNG and Cambridge Econometrics for support, and funding from EPSRC (to J.-F.M., fellowship number EP/ K007254/1); the Newton Fund (to J.-F.M., P.S. and J.E.V., EPSRC grant number EP/N002504/1 and ESRC grant number ES/N013174/1), NERC (to N.R.E., P.H. and H.P., grant number NE/P015093/1), CONICYT (to P.S.), the Philomathia Foundation (to J.E.V.) and Horizon 2020 (to H.E.P. and J.-F.M., the Sim4Nexus project)