Genetically determined height and coronary artery disease.

BACKGROUND: The nature and underlying mechanisms of an inverse association between adult height and the risk of coronary artery disease (CAD) are unclear. METHODS: We used a genetic approach to investigate the association between height and CAD, using 180 height-associated genetic variants. We tested the association between a change in genetically determined height of 1 SD (6.5 cm) with the risk of CAD in 65,066 cases and 128,383 controls. Using individual-level genotype data from 18,249 persons, we also examined the risk of CAD associated with the presence of various numbers of height-associated alleles. To identify putative mechanisms, we analyzed whether genetically determined height was associated with known cardiovascular risk factors and performed a pathway analysis of the height-associated genes. RESULTS: We observed a relative increase of 13.5% (95% confidence interval [CI], 5.4 to 22.1; P<0.001) in the risk of CAD per 1-SD decrease in genetically determined height. There was a graded relationship between the presence of an increased number of height-raising variants and a reduced risk of CAD (odds ratio for height quartile 4 versus quartile 1, 0.74; 95% CI, 0.68 to 0.84; P<0.001). Of the 12 risk factors that we studied, we observed significant associations only with levels of low-density lipoprotein cholesterol and triglycerides (accounting for approximately 30% of the association). We identified several overlapping pathways involving genes associated with both development and atherosclerosis. CONCLUSIONS: There is a primary association between a genetically determined shorter height and an increased risk of CAD, a link that is partly explained by the association between shorter height and an adverse lipid profile. Shared biologic processes that determine achieved height and the development of atherosclerosis may explain some of the association. (Funded by the British Heart Foundation and others.)

Quantifying Privacy: A Novel Entropy-Based Measure of Disclosure Risk

It is well recognised that data mining and statistical analysis pose a serious treat to privacy. This is true for financial, medical, criminal and marketing research. Numerous techniques have been proposed to protect privacy, including restriction and data modification. Recently proposed privacy models such as differential privacy and k-anonymity received a lot of attention and for the latter there are now several improvements of the original scheme, each removing some security shortcomings of the previous one. However, the challenge lies in evaluating and comparing privacy provided by various techniques. In this paper we propose a novel entropy based security measure that can be applied to any generalisation, restriction or data modification technique. We use our measure to empirically evaluate and compare a few popular methods, namely query restriction, sampling and noise addition.Comment: 20 pages, 4 figure

The complex TIE between macrophages and angiogenesis

Macrophages are primarily known as phagocytic immune cells, but they also play a role in diverse processes, such as morphogenesis, homeostasis and regeneration. In this review, we discuss the influence of macrophages on angiogenesis, the process of new blood vessel formation from the pre-existing vasculature. Macrophages play crucial roles at each step of the angiogenic cascade, starting from new blood vessel sprouting to the remodelling of the vascular plexus and vessel maturation. Macrophages form promising targets for both pro- and anti-angiogenic treatments. However, to target macrophages, we will first need to understand the mechanisms that control the functional plasticity of macrophages during each of the steps of the angiogenic cascade. Here, we review recent insights in this topic. Special attention will be given to the TIE2-expressing macrophage (TEM), which is a subtype of highly angiogenic macrophages that is able to influence angiogenesis via the angiopoietin-TIE pathway

Passive experimental autoimmune encephalomyelitis in C57BL/6 with MOG: evidence of involvement of B cells

Experimental autoimmune encephalomyelitis (EAE) is the most relevant animal model to study demyelinating diseases such as multiple sclerosis. EAE can be induced by active (active EAE) or passive (at-EAE) transfer of activated T cells in several species and strains of rodents. However, histological features of at-EAE model in C57BL/6 are poorly described. The aim of this study was to characterize the neuroinflammatory and neurodegenerative responses of at-EAE in C57BL/6 mice by histological techniques and compare them with that observed in the active EAE model. To develop the at-EAE, splenocytes from active EAE female mice were harvested and cultured in presence of MOG 35-55 and IL-12, and then injected intraperitoneally in recipient female C57BL6/J mice. In both models, the development of EAE was similar except for starting before the onset of symptoms and presenting a higher EAE cumulative score in the at-EAE model. Spinal cord histological examination revealed an increased glial activation as well as more extensive demyelinating areas in the at-EAE than in the active EAE model. Although inflammatory infiltrates composed by macrophages and T lymphocytes were found in the spinal cord and brain of both models, B lymphocytes were significantly increased in the at-EAE model. The co-localization of these B cells with IgG and their predominant distribution in areas of demyelination would suggest that IgG-secreting B cells are involved in the neurodegenerative processes associated with at-EAE

A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association studies (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185 thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7 million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most known CAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidate genes that newly implicate biological processes in vessel walls. We observed intra-locus allelic heterogeneity but little evidence of low frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect siz

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

Can tillage and agronomy be integrated with herbicide application to control resistant weeds?

Non-Peer ReviewedThe prevalence of group 2 resistant broadleaved weeds threatens successful lentil production on the Canadian Great Plains. The objective of this study was to develop an integrated weed management strategy combining physical, cultural and chemical weed control methods for lentil producers dealing with group 2 resistant wild mustard. The study was conducted for 3 years between 2011 and 2013 at 2 locations at Saskatoon and Scott, Saskatchewan. It was a randomized two way factorial with weed control method and seeding rate as the main effects. Weed control treatments tested consisted of a control treated with a glyphosate burnoff, saflufenacil (Heat ™) herbicide, rotary hoeing, half rate metribuzin (Sencor ™) herbicide, a fully integrated treatment, and a full herbicide treatment. Three seeding rates representing 1, 2, and 4 times the recommended seeding rate were tested (130, 260, and 520 plants m-2). Increasing seeding rate consistently lowered mustard biomass at both locations. The full herbicide treatment provided the greatest reduction in mustard biomass followed by the integrated treatment. The integrated treatment relied more on increased seeding rate to reduce mustard biomass and produce yield, and at the highest seeding rate it was able to provide equivalent yield to the full herbicide system. The results of this study show that an integrated system utilizing an increased seeding rate can control resistant weeds and maintain yields to a similar level as a strategy that relies only on herbicides for weed control

Evaluation of harvest aids application timing for lentil dry down

Non-Peer ReviewedHarvesting stage is a critical step for lentil producers to maintain high seed yield and good quality. Desiccating lentil with desiccants/harvest aids can dry down lentil evenly and quickly, and control late-growing green weeds, which enhances lentil harvest efficiency and allows early harvesting. Since the harvest aids are applied at a late growth stage, high herbicide residue in seeds may cause commercial issues with marketing lentil. Application timing of harvest aids is critical for producers. Improper application timing may reduce yield and thousand seed weight, but increase herbicide residue in seeds. Therefore, the objective of the harvest aids application timing (% seed moisture) trial was to evaluate the responses of lentil to different herbicide application timings at Saskatoon and Scott, Saskatchewan, over 2 years (2012 and 2013). For this trial, glyphosate (900 g a.e. ha-1), saflufenacil (50 g a.i. ha-1), and the combination of glyphosate plus saflufenacil (900 g a.e. ha-1 and 36 g a.i. ha-1) were applied when seed moisture content was 60%, 50%, 40%, 30% and 20%. Apart from these herbicide treatments, there was also an untreated control, which is desiccated naturally. Significant relationships between evaluated variables and application timing on the basis of seed moisture content were detected. Also, this trial indicated that early application timing (60% application seed moisture) could result in reductions in lentil yield and thousand seed weight. Glyphosate residue in seeds was less than 4 mg kg-1 when glyphosate was applied alone at 30% and 20% average seed moisture. Glyphosate residue decreased when adding saflufenacil to glyphosate. Saflufenacil residue consistently increased with earlier application timing of the harvest aids

Evaluation of new and existing desiccants in lentil

Non-Peer ReviewedGlobally, herbicide resistance has become a major challenge for many producers. In western Canada, many lentil (Lens culinaris L.) producers have great difficulty controlling Group 2 resistant biotypes. Two of these problematic weeds, wild mustard (Sinapis arvensis L.) and kochia (Kochia scoparia), are particularly challenging for lentil growers and can cause extensive yield loss when not adequately controlled. Desiccation is primarily used to dry down lentil for harvest ease and efficiency but can also be used as a late season control for actively growing weeds. The objective of this project is to evaluate the response of wild mustard and kochia to different herbicides, tank mixed with two different rates of glyphosate (450 g a.e. ha-1 and 900 g a.e. ha-1) at Saskatoon and Scott, Saskatchewan over a 2 year period. Desiccation occurred when the lentil seed moisture content was approximately 30%. Preliminary results are under investigation. Evaluation of seed and plant moisture of the treated plots is ongoing, along with an evaluation of the effects of the treatments on viability and vigour of affected weed seeds

Image based machine learning for identification of macrophage subsets

Macrophages play a crucial rule in orchestrating immune responses against pathogens and foreign materials. Macrophages have remarkable plasticity in response to environmental cues and are able to acquire a spectrum of activation status, best exemplified by pro-inflammatory (M1) and anti-inflammatory (M2) phenotypes at the two ends of the spectrum. Characterisation of M1 and M2 subsets is usually carried out by quantification of multiple cell surface markers, transcription factors and cytokine profiles. These approaches are time consuming, require large numbers of cells and are resource intensive. In this study, we used machine learning algorithms to develop a simple and fast imaging-based approach that enables automated identification of different macrophage functional phenotypes using their cell size and morphology. Fluorescent microscopy was used to assess cell morphology of different cell types which were stained for nucleus and actin distribution using DAPI and phalloidin respectively. By only analysing their morphology we were able to identify M1 and M2 phenotypes effectively and could distinguish them from naïve macrophages and monocytes with an average accuracy of 90%. Thus we suggest high-content and automated image analysis can be used for fast phenotyping of functionally diverse cell populations with reasonable accuracy and without the need for using multiple markers