10 results found
Zhou B, Danaei G, Stevens GA, et al., 2019, Long-term and recent trends in hypertension awareness, treatment, and control in 12 high-income countries: an analysis of 123 nationally representative surveys, Lancet, Vol: 394, Pages: 639-651, ISSN: 0140-6736
Background: Antihypertensive medicines are effective in reducing adverse cardiovascular events. Our aim was to compare hypertension awareness, treatment and control, and how they have changed over time, in high-income countries. Methods: We used data on 526,336 participants aged 40-79 years in 123 national health examination surveys from 1976 to 2017 in twelve high-income countries: Australia, Canada, Finland, Germany, Ireland, Italy, Japan, New Zealand, South Korea, Spain, the UK, and the USA. We calculated the percent of participants with hypertension – defined as systolic blood pressure ≥140mmHg or diastolic blood pressure ≥90mmHg or being on pharmacological treatment for hypertension – who were aware of their condition, who were treated, and whose hypertension was controlled (i.e. lower than 140/90 mmHg). Findings: Canada, South Korea, Australia and the UK have the lowest prevalence of hypertension, and Finland the highest. In the 1980s and early 1990s, treatment rates were at most 40% and control rates were below 25% in most countries and age-sex groups. Over time, hypertension awareness and treatment increased and control rate improved in all twelve countries, with South Korea and Germany experiencing the largest improvements. Most of the increase occurred in the 1990s and early-mid 2000s, having plateaued since in most countries.Canada, Germany, South Korea and the USA have the highest rates of awareness, treatment and control, while Finland, Ireland, Japan and Spain the lowest. Even in the best performing countries, treatment coverage was at most 80% and control rates were below 70%. Interpretation: Hypertension awareness, treatment and control have improved substantially in high-income countries since the 1980s and 1990s. However, control rates have plateaued in the past decade, at levels lower than those in high-quality hypertension
Rodriguez-Martinez A, Ayala R, Posma JM, et al., 2019, pJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra, Bioinformatics, Vol: 35, Pages: 1916-1922, ISSN: 1367-4803
Motivation: Data processing is a key bottleneck for 1H NMR-based metabolic profiling of complex biological mixtures, such as biofluids. These spectra typically contain several thousands of signals, corresponding to possibly few hundreds of metabolites. A number of binning-based methods have been proposed to reduce the dimensionality of 1D 1H NMR datasets, including statistical recoupling of variables (SRV). Here, we introduce a new binning method, named JBA ("pJRES Binning Algorithm"), which aims to extend the applicability of SRV to pJRES spectra. Results: The performance of JBA is comprehensively evaluated using 617 plasma 1H NMR spectra from the FGENTCARD cohort. The results presented here show that JBA exhibits higher sensitivity than SRV to detect peaks from low-abundance metabolites. In addition, JBA allows a more efficient removal of spectral variables corresponding to pure electronic noise, and this has a positive impact on multivariate model building. Availability: The algorithm is implemented using the MWASTools R/Bioconductor package. Supplementary information: Supplementary data are available at Bioinformatics online.
Bixby H, Bentham J, Zhou B, et al., 2019, Rising rural body-mass index is the main driver of the global obesity epidemic, Nature, Vol: 569, Pages: 260-264, ISSN: 0028-0836
Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities1,2. This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity3,4,5,6. Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017—and more than 80% in some low- and middle-income regions—was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing—and in some countries reversal—of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.
Rodriguez-Martinez A, Ayala R, Posma J, et al., 2018, Exploring the Genetic Landscape of Metabolic Phenotypes with MetaboSignal, Current protocols in bioinformatics / editoral board, Andreas D. Baxevanis ... [et al.], ISSN: 1934-3396
Ebbels TMD, Rodriguez-Martinez A, Dumas M-E, et al., 2018, Advances in Computational Analysis of Metabolomic NMR Data, NMR-based Metabolomics
Rodriguez-Martinez A, Posma JM, Ayala R, et al., 2017, J-Resolved (1)H NMR 1D-Projections for Large-Scale Metabolic Phenotyping Studies: Application to Blood Plasma Analysis., Analytical Chemistry, Vol: 89, Pages: 11405-11412, ISSN: 0003-2700
(1)H nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping is now widely used for large-scale epidemiological applications. To minimize signal overlap present in 1D (1)H NMR spectra, we have investigated the use of 2D J-resolved (JRES) (1)H NMR spectroscopy for large-scale phenotyping studies. In particular, we have evaluated the use of the 1D projections of the 2D JRES spectra (pJRES), which provide single peaks for each of the J-coupled multiplets, using 705 human plasma samples from the FGENTCARD cohort. On the basis of the assessment of several objective analytical criteria (spectral dispersion, attenuation of macromolecular signals, cross-spectral correlation with GC-MS metabolites, analytical reproducibility and biomarker discovery potential), we concluded that the pJRES approach exhibits suitable properties for implementation in large-scale molecular epidemiology workflows.
Rodriguez Martinez A, Posma JM, Ayala R, et al., 2017, MWASTools: an R/Bioconductor package for metabolome-wide association studies, Bioinformatics, Vol: 34, Pages: 890-892, ISSN: 1367-4803
Summary: MWASTools is an R package designed to provide an integrated pipeline to analyze metabonomic data in large-scale epidemiological studies. Key functionalities of our package include: quality control analysis; metabolome-wide association analysis using various models (partial correlations, generalized linear models); visualization of statistical outcomes; metabolite assignment using statistical total correlation spectroscopy (STOCSY); and biological interpretation of MWAS results.Availability: The MWASTools R package is implemented in R (version > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/
Rodriguez Martinez A, Ayala R, Posma JM, et al., 2016, MetaboSignal, a network-based approach for topological analysis of metabotype regulation via metabolic and signaling pathways, Bioinformatics, Vol: 33, Pages: 773-775, ISSN: 1367-4803
MetaboSignal is an R package that allows merging metabolic and signaling pathways reported in the Kyoto Encyclopaedia of Genes and Genomes (KEGG). It is a network-based approach designed to navigate through topological relationships between genes (signaling- or metabolic-genes) and metabolites, representing a powerful tool to investigate the genetic landscape of metabolic phenotypes.
Alton EW, Beekman JM, Boyd AC, et al., 2016, Preparation for a first-in-man lentivirus trial in patients with cystic fibrosis, Thorax, Vol: 72, Pages: 137-147, ISSN: 0040-6376
We have recently shown that non-viral gene therapy can stabilise the decline of lung function in patients with cystic fibrosis (CF). However, the effect was modest, and more potent gene transfer agents are still required. Fuson protein (F)/Hemagglutinin/Neuraminidase protein (HN)-pseudotyped lentiviral vectors are more efficient for lung gene transfer than non-viral vectors in preclinical models. In preparation for a first-in-man CF trial using the lentiviral vector, we have undertaken key translational preclinical studies. Regulatory-compliant vectors carrying a range of promoter/enhancer elements were assessed in mice and human air-liquid interface (ALI) cultures to select the lead candidate; cystic fibrosis transmembrane conductance receptor (CFTR) expression and function were assessed in CF models using this lead candidate vector. Toxicity was assessed and 'benchmarked' against the leading non-viral formulation recently used in a Phase IIb clinical trial. Integration site profiles were mapped and transduction efficiency determined to inform clinical trial dose-ranging. The impact of pre-existing and acquired immunity against the vector and vector stability in several clinically relevant delivery devices was assessed. A hybrid promoter hybrid cytosine guanine dinucleotide (CpG)- free CMV enhancer/elongation factor 1 alpha promoter (hCEF) consisting of the elongation factor 1α promoter and the cytomegalovirus enhancer was most efficacious in both murine lungs and human ALI cultures (both at least 2-log orders above background). The efficacy (at least 14% of airway cells transduced), toxicity and integration site profile supports further progression towards clinical trial and pre-existing and acquired immune responses do not interfere with vector efficacy. The lead rSIV.F/HN candidate expresses functional CFTR and the vector retains 90-100% transduction efficiency in clinically relevant delivery devices. The data support the progression of the F/HN-pseudotype
Dumas ME, Domange C, Calderari S, et al., 2016, Topological Analysis of Metabolic Networks Integrating Co-Segregating Transcriptomes and Metabolomes in Type 2 Diabetic Rat Congenic Series, Genome Medicine, Vol: 8, ISSN: 1756-994X
Background: The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus is caused by complex organ-specific cellular mechanisms contributing to impaired insulin secretion and insulin resistance. Methods: We used systematic metabotyping by 1H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualise shortest paths between metabolites and genes significantly associated with each genomic block.Results: Despite strong genomic similarities (95-99%) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific metabotypes (mQTL) and genome-wide expression traits (eQTL). Variation in key metabolites like glucose, succinate, lactate or 3-hydroxybutyrate, and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing shortest path length drove prioritization of biological validations by gene silencing. Conclusions: These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulations and to characterize novel f
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