A ventricular-vascular coupling model in presence of aortic stenosis

In patients with aortic stenosis, the left ventricular afterload is determined by the degree of valvular obstruction and the systemic arterial system. We developed an explicit mathematical model formulated with a limited number of independent parameters that describes the interaction among the left ventricle, an aortic stenosis, and the arterial system. This ventricular-valvular-vascular (V(3)) model consists of the combination of the time-varying elastance model for the left ventricle, the instantaneous transvalvular pressure-flow relationship for the aortic valve, and the three-element windkessel representation of the vascular system. The objective of this study was to validate the V(3) model by using pressure-volume loop data obtained in six patients with severe aortic stenosis before and after aortic valve replacement. There was very good agreement between the estimated and the measured left ventricular and aortic pressure waveforms. The total relative error between estimated and measured pressures was on average (standard deviation) 7.5% (SD 2.3) and the equation of the corresponding regression line was y = 0.99x - 2.36 with a coefficient of determination r(2) = 0.98. There was also very good agreement between estimated and measured stroke volumes (y = 1.03x + 2.2, r(2) = 0.96, SEE = 2.8 ml). Hence, this mathematical V(3) model can be used to describe the hemodynamic interaction among the left ventricle, the aortic valve, and the systemic arterial system

Maternal plasma folate impacts differential DNA methylation in an epigenome-wide meta-analysis of newborns

Folate is vital for fetal development. Periconceptional folic acid supplementation and food fortification are recommended to prevent neural tube defects. Mechanisms whereby periconceptional folate influences normal development and disease are poorly understood: epigenetics may be involved. We examine the association between maternal plasma folate during pregnancy and epigenome-wide DNA methylation using Illumina" s HumanMethyl450 Beadchip in 1,988 newborns from two European cohorts. Here we report the combined covariate-adjusted results using meta-analysis and employ pathway and gene expression analyses. Four-hundred forty-three CpGs (320 genes) are significantly associated with maternal plasma folate levels during pregnancy (false discovery rate 5%); 48 are significant after Bonferroni correction. Most genes are not known for folate biology, including APC2, GRM8, SLC16A12, OPCML, PRPH, LHX1, KLK4 and PRSS21. Some relate to birth defects other than neural tube defects, neurological functions or varied aspects of embryonic development. These findings may inform how maternal folate impacts the developing epigenome and health outcomes in offspring

The Rotterdam Study: 2010 objectives and design update

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in close to a 1,000 research articles and reports (see www.epib.nl/rotterdamstudy). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods

Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis

Genetic association studies have identified 21 loci associated with atopic dermatitis risk predominantly in populations of European ancestry. To identify further susceptibility loci for this common, complex skin disease, we performed a meta-analysis of >15 million genetic variants in 21,399 cases and 95,464 controls from populations of European, African, Japanese and Latino ancestry, followed by replication in 32,059 cases and 228,628 controls from 18 studies. We identified ten new risk loci, bringing the total number of known atopic dermatitis risk loci to 31 (with new secondary signals at four of these loci). Notably, the new loci include candidate genes with roles in the regulation of innate host defenses and T cell function, underscoring the important contribution of (auto)immune mechanisms to atopic dermatitis pathogenesis

Identification of a Sudden Cardiac Death Susceptibility Locus at 2q24.2 through Genome-Wide Association in European Ancestry Individuals

Sudden cardiac death (SCD) continues to be one of the leading causes of mortality worldwide, with an annual incidence estimated at 250,000–300,000 in the United States and with the vast majority occurring in the setting of coronary disease. We performed a genome-wide association meta-analysis in 1,283 SCD cases and >20,000 control individuals of European ancestry from 5 studies, with follow-up genotyping in up to 3,119 SCD cases and 11,146 controls from 11 European ancestry studies, and identify the BAZ2B locus as associated with SCD (P = 1.8×10−10). The risk allele, while ancestral, has a frequency of ∼1.4%, suggesting strong negative selection and increases risk for SCD by 1.92–fold per allele (95% CI 1.57–2.34). We also tested the role of 49 SNPs previously implicated in modulating electrocardiographic traits (QRS, QT, and RR intervals). Consistent with epidemiological studies showing increased risk of SCD with prolonged QRS/QT intervals, the interval-prolonging alleles are in aggregate associated with increased risk for SCD (P = 0.006)

Taxonomy based on science is necessary for global conservation

Peer reviewe

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons. A cross-ancestry genome-wide association meta-analysis of amyotrophic lateral sclerosis (ALS) including 29,612 patients with ALS and 122,656 controls identifies 15 risk loci with distinct genetic architectures and neuron-specific biology

The Rotterdam Study: 2012 objectives and design update

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, oncological, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in over a 1,000 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods

T-staging pulmonary oncology from radiological reports using natural language processing: translating into a multi-language setting

Abstract Background In the era of datafication, it is important that medical data are accurate and structured for multiple applications. Especially data for oncological staging need to be accurate to stage and treat a patient, as well as population-level surveillance and outcome assessment. To support data extraction from free-text radiological reports, Dutch natural language processing (NLP) algorithm was built to quantify T-stage of pulmonary tumors according to the tumor node metastasis (TNM) classification. This structuring tool was translated and validated on English radiological free-text reports. A rule-based algorithm to classify T-stage was trained and validated on, respectively, 200 and 225 English free-text radiological reports from diagnostic computed tomography (CT) obtained for staging of patients with lung cancer. The automated T-stage extracted by the algorithm from the report was compared to manual staging. A graphical user interface was built for training purposes to visualize the results of the algorithm by highlighting the extracted concepts and its modifying context. Results Accuracy of the T-stage classifier was 0.89 in the validation set, 0.84 when considering the T-substages, and 0.76 when only considering tumor size. Results were comparable with the Dutch results (respectively, 0.88, 0.89 and 0.79). Most errors were made due to ambiguity issues that could not be solved by the rule-based nature of the algorithm. Conclusions NLP can be successfully applied for staging lung cancer from free-text radiological reports in different languages. Focused introduction of machine learning should be introduced in a hybrid approach to improve performance

[¹⁸F]fluorodeoxyglucose uptake patterns in lung before radiotherapy identify areas more susceptible to radiation-induced lung toxicity in non-small-cell lung cancer patients

PURPOSE: Our hypothesis was that pretreatment inflammation in the lung makes pulmonary tissue more susceptible to radiation damage. The relationship between pretreatment [(18)F]fluorodeoxyglucose ([(18)F]FDG) uptake in the lungs (as a surrogate for inflammation) and the delivered radiation dose and radiation-induced lung toxicity (RILT) was investigated. METHODS AND MATERIALS: We retrospectively studied a prospectively obtained cohort of 101 non-small-cell lung cancer patients treated with (chemo)radiation therapy (RT). [(18)F]FDG-positron emission tomography-computed tomography (PET-CT) scans used for treatment planning were studied. Different parameters were used to describe [(18)F]FDG uptake patterns in the lungs, excluding clinical target volumes, and the interaction with radiation dose. An increase in the dyspnea grade of 1 (Common Terminology Criteria for Adverse Events version 3.0) or more points compared to the pre-RT score was used as an endpoint for analysis of RILT. The effect of [(18)F]FDG and CT-based variables, dose, and other patient or treatment characteristics that effected RILT was studied using logistic regression. RESULTS: Increased lung density and pretreatment [(18)F]FDG uptake were related to RILT after RT with univariable logistic regression. The 95th percentile of the [(18)F]FDG uptake in the lungs remained significant in multivariable logistic regression (p = 0.016; odds ratio [OR] = 4.3), together with age (p = 0.029; OR = 1.06), and a pre-RT dyspnea score of ≥1 (p = 0.005; OR = 0.20). Significant interaction effects were demonstrated among the 80th, 90th, and 95th percentiles and the relative lung volume receiving more than 2 and 5 Gy. CONCLUSIONS: The risk of RILT increased with the 95th percentile of the [(18)F]FDG uptake in the lungs, excluding clinical tumor volume (OR = 4.3). The effect became more pronounced as the fraction of the 5%, 10%, and 20% highest standardized uptake value voxels that received more than 2 Gy to 5 Gy increased. Therefore, the risk of RILT may be decreased by applying sophisticated radiotherapy techniques to avoid areas in the lung with high [(18)F]FDG uptake