Comparison of the McGrath® Series 5 and GlideScope® Ranger with the Macintosh laryngoscope by paramedics

<p>Abstract</p> <p>Background</p> <p>Out-of-hospital endotracheal intubation performed by paramedics using the Macintosh blade for direct laryngoscopy is associated with a high incidence of complications. The novel technique of video laryngoscopy has been shown to improve glottic view and intubation success in the operating room. The aim of this study was to compare glottic view, time of intubation and success rate of the McGrath^®Series 5 and GlideScope^®Ranger video laryngoscopes with the Macintosh laryngoscope by paramedics.</p> <p>Methods</p> <p>Thirty paramedics performed six intubations in a randomised order with all three laryngoscopes in an airway simulator with a normal airway. Subsequently, every participant performed one intubation attempt with each device in the same manikin with simulated cervical spine rigidity using a cervical collar. Glottic view, time until visualisation of the glottis and time until first ventilation were evaluated.</p> <p>Results</p> <p>Time until first ventilation was equivalent after three intubations in the first scenario. In the scenario with decreased cervical motion, the time until first ventilation was longer using the McGrath^®compared to the GlideScope^®and AMacintosh (p < 0.01). The success rate for endotracheal intubation was similar for all three devices. Glottic view was only improved using the McGrath^®device (p < 0.001) compared to using the Macintosh blade.</p> <p>Conclusions</p> <p>The learning curve for video laryngoscopy in paramedics was steep in this study. However, these data do not support prehospital use of the McGrath^®and GlideScope^®devices by paramedics.</p

EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data

Summary: The R package EasyStrata facilitates the evaluation and visualization of stratified genome-wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test and account for between-strata difference as a means to tackle gene-strata interaction effects and (ii) extended graphical features tailored for stratified GWAMA results. The software provides further features also suitable for general GWAMAs including functions to annotate, exclude or highlight specific loci in plots or to extract independent subsets of loci from genome-wide datasets. It is freely available and includes a user-friendly scripting interface that simplifies data handling and allows for combining statistical and graphical functions in a flexible fashion. Availability: EasyStrata is available for free (under the GNU General Public License v3) from our Web site www.genepi-regensburg.de/easystrata and from the CRAN R package repository cran.r-project.org/web/packages/EasyStrata/. Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Approaches to detect genetic effects that differ between two strata in genome-wide meta-analyses: Recommendations based on a systematic evaluation.

Genome-wide association meta-analyses (GWAMAs) conducted separately by two strata have identified differences in genetic effects between strata, such as sex-differences for body fat distribution. However, there are several approaches to identify such differences and an uncertainty which approach to use. Assuming the availability of stratified GWAMA results, we compare various approaches to identify between-strata differences in genetic effects. We evaluate type I error and power via simulations and analytical comparisons for different scenarios of strata designs and for different types of between-strata differences. For strata of equal size, we find that the genome-wide test for difference without any filtering is the best approach to detect stratum-specific genetic effects with opposite directions, while filtering for overall association followed by the difference test is best to identify effects that are predominant in one stratum. When there is no a priori hypothesis on the type of difference, a combination of both approaches can be recommended. Some approaches violate type I error control when conducted in the same data set. For strata of unequal size, the best approach depends on whether the genetic effect is predominant in the larger or in the smaller stratum. Based on real data from GIANT (&gt;175 000 individuals), we exemplify the impact of the approaches on the detection of sex-differences for body fat distribution (identifying up to 10 loci). Our recommendations provide tangible guidelines for future GWAMAs that aim at identifying between-strata differences. A better understanding of such effects will help pinpoint the underlying mechanisms

Nocturnal hypoxemic burden and micro- and macrovascular disease in patients with type 2 diabetes

Background Micro- and macrovascular diseases are common in patients with type 2 diabetes mellitus (T2D) and may be partly caused by nocturnal hypoxemia. The study aimed to characterize the composition of nocturnal hypoxemic burden and to assess its association with micro- and macrovascular disease in patients with T2D. Methods This cross-sectional analysis includes overnight oximetry from 1247 patients with T2D enrolled in the DIACORE (DIAbetes COhoRtE) study. Night-time spent below a peripheral oxygen saturation of 90% (T90) as well as T90 associated with non-specific drifts in oxygen saturation (T90non − specific), T90 associated with acute oxygen desaturation (T90desaturation) and desaturation depths were assessed. Binary logistic regression analyses adjusted for known risk factors (age, sex, smoking status, waist-hip ratio, duration of T2D, HbA1c, pulse pressure, low-density lipoprotein, use of statins, and use of renin-angiotensin-aldosterone system inhibitors) were used to assess the associations of such parameters of hypoxemic burden with chronic kidney disease (CKD) as a manifestation of microvascular disease and a composite of cardiovascular diseases (CVD) reflecting macrovascular disease. Results Patients with long T90 were significantly more often affected by CKD and CVD than patients with a lower hypoxemic burden (CKD 38% vs. 28%, p < 0.001; CVD 30% vs. 21%, p < 0.001). Continuous T90desaturation and desaturation depth were associated with CKD (adjusted OR 1.01 per unit, 95% CI [1.00; 1.01], p = 0.008 and OR 1.30, 95% CI [1.06; 1.61], p = 0.013, respectively) independently of other known risk factors for CKD. For CVD there was a thresholdeffect, and only severly and very severly increased T90non−specific was associated with CVD ([Q3;Q4] versus [Q1;Q2], adjusted OR 1.51, 95% CI [1.12; 2.05], p = 0.008) independently of other known risk factors for CVD. Conclusion While hypoxemic burden due to oxygen desaturations and the magnitude of desaturation depth were significantly associated with CKD, only severe hypoxemic burden due to non-specific drifts was associated with CVD. Specific types of hypoxemic burden may be related to micro- and macrovascular disease

KidneyGPS: a user-friendly web application to help prioritize kidney function genes and variants based on evidence from genome-wide association studies

Background Genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with kidney function. By combining these findings with post-GWAS information (e.g., statistical fine-mapping to identify independent association signals and to narrow down signals to causal variants; or different sources of annotation data), new hypotheses regarding physiology and disease aetiology can be obtained. These hypotheses need to be tested in laboratory experiments, for example, to identify new therapeutic targets. For this purpose, the evidence obtained from GWAS and post-GWAS analyses must be processed and presented in a way that they are easily accessible to kidney researchers without specific GWAS expertise. Main Here we present KidneyGPS, a user-friendly web-application that combines genetic variant association for estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics consortium with annotation of (i) genetic variants with functional or regulatory effects (“SNP-to-gene” mapping), (ii) genes with kidney phenotypes in mice or human (“gene-to-phenotype”), and (iii) drugability of genes (to support re-purposing). KidneyGPS adopts a comprehensive approach summarizing evidence for all 5906 genes in the 424 GWAS loci for eGFR identified previously and the 35,885 variants in the 99% credible sets of 594 independent signals. KidneyGPS enables user-friendly access to the abundance of information by search functions for genes, variants, and regions. KidneyGPS also provides a function (“GPS tab”) to generate lists of genes with specific characteristics thus enabling customizable Gene Prioritisation (GPS). These specific characteristics can be as broad as any gene in the 424 loci with a known kidney phenotype in mice or human; or they can be highly focussed on genes mapping to genetic variants or signals with particularly with high statistical support. KidneyGPS is implemented with RShiny in a modularized fashion to facilitate update of input data (https://kidneygps.ur.de/gps/). Conclusion With the focus on kidney function related evidence, KidneyGPS fills a gap between large general platforms for accessing GWAS and post-GWAS results and the specific needs of the kidney research community. This makes KidneyGPS an important platform for kidney researchers to help translate in silico research results into in vitro or in vivo researc

KidneyGPS: a user-friendly web application to help prioritize kidney function genes and variants based on evidence from genome-wide association studies

Background Genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with kidney function. By combining these findings with post-GWAS information (e.g., statistical fine-mapping to identify independent association signals and to narrow down signals to causal variants; or different sources of annotation data), new hypotheses regarding physiology and disease aetiology can be obtained. These hypotheses need to be tested in laboratory experiments, for example, to identify new therapeutic targets. For this purpose, the evidence obtained from GWAS and post-GWAS analyses must be processed and presented in a way that they are easily accessible to kidney researchers without specific GWAS expertise. Main Here we present KidneyGPS, a user-friendly web-application that combines genetic variant association for estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics consortium with annotation of (i) genetic variants with functional or regulatory effects (“SNP-to-gene” mapping), (ii) genes with kidney phenotypes in mice or human (“gene-to-phenotype”), and (iii) drugability of genes (to support re-purposing). KidneyGPS adopts a comprehensive approach summarizing evidence for all 5906 genes in the 424 GWAS loci for eGFR identified previously and the 35,885 variants in the 99% credible sets of 594 independent signals. KidneyGPS enables user-friendly access to the abundance of information by search functions for genes, variants, and regions. KidneyGPS also provides a function (“GPS tab”) to generate lists of genes with specific characteristics thus enabling customizable Gene Prioritisation (GPS). These specific characteristics can be as broad as any gene in the 424 loci with a known kidney phenotype in mice or human; or they can be highly focussed on genes mapping to genetic variants or signals with particularly with high statistical support. KidneyGPS is implemented with RShiny in a modularized fashion to facilitate update of input data (https://kidneygps.ur.de/gps/). Conclusion With the focus on kidney function related evidence, KidneyGPS fills a gap between large general platforms for accessing GWAS and post-GWAS results and the specific needs of the kidney research community. This makes KidneyGPS an important platform for kidney researchers to help translate in silico research results into in vitro or in vivo research

Genetic evidence for a role of adiponutrin in the metabolism of apolipoprotein B-containing lipoproteins

Adiponutrin (PNPLA3) is a predominantly liver-expressed transmembrane protein with phospholipase activity that is regulated by fasting and feeding. Recent genome-wide association studies identified PNPLA3 to be associated with hepatic fat content and liver function, thus pointing to a possible involvement in the hepatic lipoprotein metabolism. The aim of this study was to examine the association between two common variants in the adiponutrin gene and parameters of lipoprotein metabolism in 23 274 participants from eight independent West-Eurasian study populations including six population-based studies [Bruneck (n = 800), KORA S3/F3 (n = 1644), KORA S4/F4 (n = 1814), CoLaus (n = 5435), SHIP (n = 4012), Rotterdam (n = 5967)], the SAPHIR Study as a healthy working population (n = 1738) and the Utah Obesity Case-Control Study including a group of 1037 severely obese individuals (average BMI 46 kg/m2) and 827 controls from the same geographical region of Utah. We observed a strong additive association of a common non-synonymous variant within adiponutrin (rs738409) with age-, gender-, and alanine-aminotransferase-adjusted lipoprotein concentrations: each copy of the minor allele decreased levels of total cholesterol on average by 2.43 mg/dl (P = 8.87 × 10−7), non-HDL cholesterol levels by 2.35 mg/dl (P = 2.27 × 10−6) and LDL cholesterol levels by 1.48 mg/dl (P = 7.99 × 10−4). These associations remained significant after correction for multiple testing. We did not observe clear evidence for associations with HDL cholesterol or triglyceride concentrations. In conclusion, our study suggests that adiponutrin is involved in the metabolism of apoB-containing lipoprotein

On the impact of different approaches to classify age-related macular degeneration: Results from the German AugUR study

While age-related macular degeneration (AMD) poses an important personal and public health burden, comparing epidemiological studies on AMD is hampered by differing approaches to classify AMD. In our AugUR study survey, recruiting residents from in/around Regensburg, Germany, aged 70+, we analyzed the AMD status derived from color fundus images applying two different classification systems. Based on 1,040 participants with gradable fundus images for at least one eye, we show that including individuals with only one gradable eye (n = 155) underestimates AMD prevalence and we provide a correction procedure. Bias-corrected and standardized to the Bavarian population, late AMD prevalence is 7.3% (95% confidence interval = [5.4; 9.4]). We find substantially different prevalence estimates for "early/intermediate AMD" depending on the classification system: 45.3% (95%-CI = [41.8; 48.7]) applying the Clinical Classification (early/intermediate AMD) or 17.1% (95%-CI = [14.6; 19.7]) applying the Three Continent AMD Consortium Severity Scale (mild/moderate/severe early AMD). We thus provide a first effort to grade AMD in a complete study with different classification systems, a first approach for bias-correction from individuals with only one gradable eye, and the first AMD prevalence estimates from a German elderly population. Our results underscore substantial differences for early/intermediate AMD prevalence estimates between classification systems and an urgent need for harmonization

The German AugUR study: study protocol of a prospective study to investigate chronic diseases in the elderly

Background The majority of patients suffering from chronic health disabilities is beyond 70 years of age. Typical late-onset chronic diseases include those affecting the heart, the kidney, cancer, and conditions of the eye such as age-related macular degeneration. These diseases disable patients for many years and largely compromise autonomy in daily life. Due to challenges in recruiting the elderly, the collection of population-based epidemiological data as a prerequisite to understand associated risk factors and mechanisms is commonly done in the general population within an age-range of 20 to 70 years. Methods/Design We establish the German AugUR study (Age-related diseases: understanding genetic and non-genetic influences - a study at the University of Regensburg), a prospective study in the mobile elderly general population in and around Regensburg in eastern Bavaria. In the long term, we aim to recruit 3,000 persons of Caucasian ethnicity with at least 70 years of age via residents’ registration offices and conduct 3-year follow-ups. The study protocol includes a standardized interview regarding social and life-style factors, medication history, quality-of-life, and existing diagnoses of common diseases. The participants undergo medical examinations for ophthalmological, cardiovascular or diabetes-related conditions, and general measurements of body shape and fitness. The program is particularly tailored for the elderly. Biobanking of whole blood, serum, plasma, and urine is conducted and standard laboratory measurements are performed in fresh samples. Discussion AugUR is specifically designed as a research platform to host studies of late onset diseases. Consequently, this platform will help (1) to unravel the genetic and non-genetic etiology of disease development and progression, (2) to serve as control group of elderly individuals for comparisons with various patient groups, (3) to derive prevalence and incidence data on chronic diseases, and (4) to provide clinical reference parameters for the elderly mobile general population. This data will foster our understanding of disease mechanisms, which may ultimately help to improve prevention, diagnosis, and therapy for frequent chronic diseases. Here we present the baseline study protocol of AugUR

Genetics Meets Metabolomics: A Genome-Wide Association Study of Metabolite Profiles in Human Serum

The rapidly evolving field of metabolomics aims at a comprehensive measurement of ideally all endogenous metabolites in a cell or body fluid. It thereby provides a functional readout of the physiological state of the human body. Genetic variants that associate with changes in the homeostasis of key lipids, carbohydrates, or amino acids are not only expected to display much larger effect sizes due to their direct involvement in metabolite conversion modification, but should also provide access to the biochemical context of such variations, in particular when enzyme coding genes are concerned. To test this hypothesis, we conducted what is, to the best of our knowledge, the first GWA study with metabolomics based on the quantitative measurement of 363 metabolites in serum of 284 male participants of the KORA study. We found associations of frequent single nucleotide polymorphisms (SNPs) with considerable differences in the metabolic homeostasis of the human body, explaining up to 12% of the observed variance. Using ratios of certain metabolite concentrations as a proxy for enzymatic activity, up to 28% of the variance can be explained (p-values 10−16 to 10−21). We identified four genetic variants in genes coding for enzymes (FADS1, LIPC, SCAD, MCAD) where the corresponding metabolic phenotype (metabotype) clearly matches the biochemical pathways in which these enzymes are active. Our results suggest that common genetic polymorphisms induce major differentiations in the metabolic make-up of the human population. This may lead to a novel approach to personalized health care based on a combination of genotyping and metabolic characterization. These genetically determined metabotypes may subscribe the risk for a certain medical phenotype, the response to a given drug treatment, or the reaction to a nutritional intervention or environmental challenge