Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.Peer reviewe

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of 'leaving no one behind', it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. METHODS: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator

Etude structurale et fonctionnelle de la protéine HasB, impliquée dans l'acquisition de l'hème chez Serratia marcescens

Chez les bactéries à Gram négatif, certaines molécules comme les sidérophores ou l hème doivent être activement transportées à travers la membrane externe via des récepteurs membranaires qui permettent la fixation et l internalisation du ligand. Ce type de transport nécessite la protéine de membrane interne TonB qui interagit avec ces récepteurs via un domaine globulaire appelé domaine périplasmique. En plus de la protéine TonB, la bactérie Serratia marcescens possède une protéine homologue, appelée HasB, impliquée dans le système d acquisition de l hème via les hémophores. Ce système est basé sur la sécrétion d une protéine extracellulaire qui capture l hème libre ou lié à des hémoprotéines et qui le délivre ensuite à un récepteur spécifique de la membrane externe (HasR). Chez S. marcescens, les deux protéines HasB et TonB sont actives pour le transport de l hème via le récepteur HasR. Cependant, HasB ne peut pas remplacer TonB pour les autres fonctions TonB-dépendantes. La protéine HasB se comporte donc comme une protéine TonB spécifique de l acquisition de l hème via le récepteur HasR. Afin de comprendre les bases de cette spécificité, l étude structurale par RMN du domaine périplasmique de HasB a été entreprise. Pour cela, les étapes de clonage, d expression et de purification d un échantillon isotopiquement marqué ont été mises au point. L analyse des spectres 3D hétéronucléaires correspondants a permis l attribution des signaux de la protéine ainsi que l identification des éléments de structures secondaires. L interaction entre le domaine périplasmique de HasB et HasR a aussi été étudiée par ITC afin de mieux comprendre la spécificité de cette interaction.In Gram negative bacteria, some molecules such as siderophores or heme must be actively transported through the outer membrane. This transport requires outer membrane receptors which interact and internalize the ligand through the membrane. This transport requires the inner membrane protein TonB, which interacts with these receptors through a globular domain named periplasmic domain. In addition to the TonB protein, the Gram negative bacteria Serratia marcescens possesses a supplementary TonB-like protein called HasB. This protein is a component of the hemophore-dependent heme acquisition system of S. marcescens. This system involves a soluble extracellular protein that acquires free or hemoprotein-bound heme and delivers it to a specific outer membrane receptor (HasR). In S. marcescens both HasB and TonB are active for heme uptake via the HasR receptor. However, HasB can not replace TonB for the others TonB-dependent processes. There is a great deal of evidence that HasB behaves as a specific TonB-like protein dedicated to heme uptake through the HasR receptor. In order to understand the basis of this specificity, NMR structural study of the periplasmic domain of HasB was carried out. Cloning, expression and purification steps of an isotopically labeled sample were optimized. Heteronuclear 3D spectra analysis enabled us to assign backbone and side chain resonances and to localize secondary structure elements. Additionally, the HasB-HasR interaction was studied by ITC microcalorimetry in order to characterize the specificity of this interaction.PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF

Etude structurale et fonctionnelle de la protéine HasS, un facteur anti-sigma impliqué dans la régulation de l'acquisition de l'hème chez Serratia marcescens

Chez les bactéries Gram-négatif, les systèmes d acquisition des différentes sources de fer sont généralement soumis à une régulation très fine. Ils sont régulés en fonction de la concentration intracellulaire en fer. Pour certains, il existe un niveau de régulation supplémentaire qui s effectue par une signalisation transmembranaire. Cette signalisation nécessite l interactions entre trois protéines spécifiques d un système donné : le récepteur membranaire et le facteur sigma de type ECF (extracytoplasmic fonction) et son anti-sigma qui une protéine de membrane interne. Les mécanismes moléculaires de ce processus de signalisation sont inconnus. Durant cette étude, nous nous sommes intéressés à la voie de signalisation régulant l acquisition de l hème via le système Has (heme acquisistion system) de Serratia marcescens. Nous nous sommes focalisés sur la première étape de cette signalisation transmembranaire à savoir, l interaction entre le domaine périplasmique du récepteur HasR et le facteur anti-sigma HasS. Nous avons étudié les aspects structuraux et fonctionnels de ces deux protéines. Nous avons déterminé par RMN la structure 3D du domaine périplasmique de HasR et identifié les résidus impliqués dans la voie de signalisation. De plus, nous avons produit pour la première fois le domaine périplasmique de HasS. Nous avons ensuite déterminé son état de repliement et étudié son interaction avec le domaine périplasmique de HasRIron uptake systems in gram-negative bacteria are generally tightly regulated by iron intracellular concentration. Some of them are also controlled by a transmembrane signaling. Three specific proteins are involved in the latter process : the outer membrane receptor and the ECF (extracytoplasmic function) sigma and antisigma factors. The data about these proteins and of their molecular interactions are sparse and the mechanisms governing this transmembrane signalisation are not understood. We present here the results of the study of the transmembrane signaling in the Has system (heme acquisition system) of Serratia marcescens. We focused on the interaction between the periplasmic domain of the receptor HasR and the ECF anti-sigma factor HasS, two proteins controlling the first step of this signaling process. We carried out structural and functional studies of these protiens. We solved the structure of the periplasmic domain of HasR by NMR and determined which of its residues were involved in the transmembrane signaling. We produced, for the fisrt time, the periplasmic domain of HasS and carried out its characterized regarding its structural features and its interaction with the periplasmic domain of HasRPARIS-BIUSJ-Biologie recherche (751052107) / SudocSudocFranceF

Mutagenesis and Molecular Modeling Reveal Three Key Extracellular Loops of the Membrane Receptor HasR That Are Involved in Hemophore HasA Binding▿ †

On the basis of the three-dimensional model of the heme/hemophore TonB-dependent outer membrane receptor HasR, mutants with six-residue deletions in the 11 putative extracellular loops were generated. Although all mutants continued to be active TonB-dependent heme transporters, mutations in three loops abolished hemophore HasA binding both in vivo and in vitro

Structural Analysis of Proteins from Bacterial Secretion Systems and Their Assemblies by NMR Spectroscopy

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Modulation by substrates of the interaction between the HasR outer membrane receptor and its specific TonB-like protein, HasB.

International audienceTonB is a cytoplasmic membrane protein required for active transport of various essential substrates such as heme and iron siderophores through the outer membrane receptors of Gram-negative bacteria. This protein spans the periplasm, contacts outer membrane transporters by its C-terminal domain, and transduces energy from the protonmotive force to the transporters. The TonB box, a relatively conserved sequence localized on the periplasmic side of the transporters, has been shown to directly contact TonB. While Serratia marcescens TonB functions with various transporters, HasB, a TonB-like protein, is dedicated to the HasR transporter. HasR acquires heme either freely or via an extracellular heme carrier, the hemophore HasA, that binds to HasR and delivers heme to the transporter. Here, we study the interaction of HasR with a HasB C-terminal domain and compare it with that obtained with a TonB C-terminal fragment. Analysis of the thermodynamic parameters reveals that the interaction mode of HasR with HasB differs from that with TonB, the difference explaining the functional specificity of HasB for HasR. We also demonstrate that the presence of the substrate on the extracellular face of the transporter modifies, via enthalpy-entropy compensation, the interaction with HasB on the periplasmic face. The transmitted signal depends on the nature of the substrate. While the presence of heme on the transporter modifies only slightly the nature of interactions involved between HasR and HasB, hemophore binding on the transporter dramatically changes the interactions and seems to locally stabilize some structural motifs. In both cases, the HasR TonB box is the target for those modifications