Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: A pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk ofmajor cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regressionmodels to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10-8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genom

A new in vivo screening model for posterior spinal bone formation: comparison of ten calcium phosphate ceramic material treatments

This study presents a new screening model for evaluating the influence of multiple conditions on the initial process of bone formation in the posterior lumbar spine of a large animal. This model uses cages designed for placement on the decorticated transverse process of the goat lumbar spine. Five conduction channels per cage, each be defined by a different material treatment, are open to both the underlying bone and overlying soft tissue. The model was validated in ten adult Dutch milk goats, with each animal implanted with two cages containing a total of ten calcium phosphate material treatments according to a randomized complete block design. The ten calcium phosphate ceramic materials were created through a combination of material chemistry (BCP, TCP, HA), sintering temperature (low, medium, high), calcination and surface roughness treatments. To monitor the bone formation over time, fluorochrome markers were administered at 3, 5 and 7 weeks and the animals were sacrificed at 9 weeks after implantation. Bone formation in the conduction channels was investigated by histology and histomorphometry of non-decalcified sections using traditional light and epifluorescent microscopy. According to both observed and measured bone formation parameters, materials were ranked in order of increasing magnitude as follows: low sintering temperature BCP (rough and smooth)≈medium sintering temperature BCP≈TCP>calcined low sintering temperature HA>non-calcined low sintering temperature HA>high sintering temperature BCP (rough and smooth)>high sintering temperature HA (calcined and non-calcined). These results agree closely with those obtained in previous studies of osteoconduction and bioactivity of ceramics thereby validating the screening model presented in this study

Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity

Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents' survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan

Designing a hybrid thin-film/wafer silicon triple photovoltaic junction for solar water splitting

Solar fuels are a promising way to store solar energy seasonally. This paper proposes an earth-abundant heterostructure to split water using a photovoltaic-electrochemical device (PV-EC). The heterostructure is based on a hybrid architecture of a thin-film (TF) silicon tandem on top of a c-Si wafer (W) heterojunction solar cell (a-Si:H (TF)/nc-Si:H (TF)/c-Si(W)) The multijunction approach allows to reach enough photovoltage for water splitting, while maximizing the spectrum utilization. However, this unique approach also poses challenges, including the design of effective tunneling recombination junctions (TRJ) and the light management of the cell. Regarding the TRJs, the solar cell performance is improved by increasing the n-layer doping of the middle cell. The light management can be improved by using hydrogenated indium oxide (IOH) as transparent conductive oxide (TCO). Finally, other light management techniques such as substrate texturing or absorber bandgap engineering were applied to enhance the current density. A correlation was observed between improvements in light management by conventional surface texturing and a reduced nc-Si:H absorber material quality. The final cell developed in this work is a flat structure, using a top absorber layer consisting of a high bandgap a-Si:H. This triple junction cell achieved a PV efficiency of 10.57%, with a fill factor of 0.60, an open-circuit voltage of 2.03 V and a short-circuit current density of 8.65 mA/cm2. When this cell was connected to an IrOx/Pt electrolyser, a stable solar-to-hydrogen (STH) efficiency of 8.3% was achieved and maintained for 10 hours.</p

Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function

In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10−9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10−4-2.2 × 10−7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in genera

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation

Proceeding toward the maximum of solar cycle 25 with a radiation environment similar to the previous cycle

The Sun exhibited lower-than-average activity levels, including a weak maximum and a prolonged minimum in the solar cycle (SC) 24. Thiswas following a 60-year trend of weakening solar activity, leading to speculations that we could be moving into another secular minimum scenario like the Dalton or the Gleissberg periods. During such periods, the fluxes of galactic cosmic rays (GCRs) increase significantly, introducing radiation hazards for long-term crewed space explorations. In our previous work, we predicted the level of solar activity, and thus, the radiation environment for SC25 will be similar to SC24. In this paper, we show that, to date, the radiation environment observed by CRaTER has been similar to SC24, as we predicted. Furthermore, we predict that if the radiation environment remains similar to SC24, the maximum value for permissible mission duration (PMD) for SC25 will be 917-230+234 days based on NASA\u27s latest permissible exposure limit (PEL)

Measurement of the forward Z boson production cross-section in pp collisions at s=13\sqrt{s} = 13 TeV

A measurement of the production cross-section of Z bosons in pp collisions at $\sqrt{s} = 13$ TeV is presented using dimuon and dielectron final states in LHCb data. The cross-section is measured for leptons with pseudorapidities in the range $2.0 \eta 4.5$, transverse momenta $p_\text{T} 20$ GeV and dilepton invariant mass in the range $60 m(\ell\ell) 120$ GeV. The integrated cross-section from averaging the two final states is \begin{equation*}\sigma_{\text{Z}}^{\ell\ell} = 194.3 \pm 0.9 \pm 3.3 \pm 7.6\text{ pb,}\end{equation*} where the first uncertainty is statistical, the second is due to systematic effects, and the third is due to the luminosity determination. In addition, differential cross-sections are measured as functions of the Z boson rapidity, transverse momentum and the angular variable $\phi^*_\eta$

Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing