Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Therapeutic perspectives of PPAR-gamma modulation in acute myeloid leukemia

La leucémie aiguë myéloïde (LAM) représente la forme la plus fréquente de leucémie aiguë chez l'adulte. Le pronostic global des LAM reste souvent médiocre en raison de la fréquence élevée des rechutes, causées par la persistance des cellules souches leucémiques (CSL) peu ou insensibles à la chimiothérapie conventionnelle. L'activation de PPAR-gamma implique la diminution transcriptionnelle de STAT5A/B, deux facteurs de transcription essentiels à la maintenance des CSL. Cette modulation du niveau de STAT5 constitue un mécanisme d'action potentiel des agonistes de PPAR-gamma dans les LAM, car la voie STAT5 est activée de manière constitutive dans 70% des cas et associée à un pronostic péjoratif ainsi qu'à une survie globale médiocre. La pioglitazone, agoniste de PPAR-gamma présente un profil de toxicité bien établi après des années d'utilisation en clinique comme anti-diabétique, faisant de ce dernier un candidat de choix pour envisager un repositionnement thérapeutique. Nous avons confirmé le potentiel thérapeutique de la pioglitazone en monothérapie, celle-ci exerce in vitro un effet antiprolifératif sur les lignées de LAM et les cellules primaires de patients en culture liquide à court terme et en test clonogénique. Ces résultats n'ayant pas pu être confirmés in vivo dans des modèles murins de xénogreffe de cellules primaires, nous avons démembré un mécanisme de résistance in vivo aux agonistes de PPAR-gamma médié par le microenvironnement médullaire. Ce mécanisme passe par la suractivation de l'axe Gas6/AXL sous l'action de la pioglitazone. AXL est un récepteur à activité tyrosine kinase de la famille des récepteurs TAM (TYRO-3, AXL, MER) dont la liaison à son ligand Gas6 recrute un certain nombre de voies de signalisation en aval, impliquées dans la prolifération et la survie. L'association avec un inhibiteur spécifique d'AXL, le bemcentinib, a permis de restaurer l'effet anti-leucémique de la pioglitazone in vitro sur un système de co-culture sur cellules stromales MS-5, mimant l'effet du microenvironnement. Outre cet effet antiprolifératif, l'activation de PPAR-gamma possède également des propriétés anti-inflammatoires, anti-fibrotiques ainsi que de modulation du phénotype MDR (Multidrug resistance) qui pourraient bénéficier aux patients atteints de LAM. Dans ce contexte, nous avons pu mettre en évidence sur une cohorte de 53 patients atteints de LAM au diagnostic, la dérégulation d'un ensemble de cytokines et facteurs de croissance, caractérisée en particulier par une augmentation des cytokines pro-inflammatoires (IL-6, IL-8, S100A8/A9 et TNF-α) justifiant le rationnel à utiliser la pioglitazone dans les LAM. En revanche, nous n'avons pas pu mettre en évidence d'activité de modulation de la pompe d'efflux glycoprotéine-P (phénotype MDR) par les ligands de PPAR-gamma aux doses thérapeutiques.L'ensemble de ces résultats est en cours d'évaluation dans un modèle in vivo de xénogreffe de cellules primaires dans des souris NOD/SCID/IL2Rgamma-/-, ces modèles murins permettront de confirmer le potentiel thérapeutique de la combinaison pioglitazone + inhibiteur d'AXL à cibler et éliminer les CSL au sein de leur microenvironnement, tout en évaluant le rôle régulateur de PPAR-gamma sur l'inflammation et la fibrose.Acute myeloid leukemia (AML) is the most common type of acute leukemia in adults. The overall prognosis of AML remains generally poor due to the high rate of relapse, often due to the persistence of leukemic stem cells (LSC) which are unresponsive or insensitive to conventional chemotherapy. Activation of PPAR-gamma involves transcriptional downregulation of STAT5A/B, two essential transcription factors for LSC maintenance. This modulation of STAT5 levels is a potential mechanism of action for PPAR-gamma agonists in AML, as the STAT5 pathway is constitutively activated in 70% of cases and associated with poor prognosis and shortened overall survival. The PPAR-gamma agonist pioglitazone has a well-established safety profile after years of clinical use as an antidiabetic drug, making it a promising candidate for therapeutic repositioning. Our study confirms the therapeutic potential of pioglitazone as a monotherapy, exerting an antiproliferative effect on AML cell lines and primary patient cells in vitro in short-term liquid culture and in clonogenic assays. We have unraveled an in vivo resistance mechanism to PPAR-gamma agonists mediated by the bone marrow microenvironment which involved overactivation of the Gas6/AXL axis under the influence of pioglitazone. AXL is a tyrosine kinase receptor of the TAM receptor family (TYRO-3, AXL, MER) whose binding to its Gas6 ligand recruits several downstream signaling pathways involved in leukemia cell proliferation and survival.Combination with the specific AXL inhibitor bemcentinib restores pioglitazone efficacy in vitro, in a co-culture system with MS-5 stromal cells, mimicking the effect of the microenvironment. In addition to this antiproliferative effect, PPAR-gamma activation also implies anti-inflammatory and anti-fibrotic properties, as well as modulation of the MDR (Multidrug resistance) phenotype, which could be beneficial to AML patients. In this study, we analyzed a cohort of 53 patients with AML at diagnosis and found a deregulation of numerous of cytokines and growth factors. Specifically, we observed an increase in pro-inflammatory cytokines (IL-6, IL-8, S100A8/A9 et TNF-α), supporting the rationale of using pioglitazone in the treatment of AML. However, we were unable to demonstrate any modulation of the P-glycoprotein efflux pump by PPAR-gamma ligands at therapeutic doses. All these findings are currently being evaluated in an in vivo primary cell xenograft model using NOD/SCID/IL2Rgamma-/- mice. These murine models will confirm the therapeutic potential of the pioglitazone + AXL inhibitor combination, targeting and eliminating LSC within their microenvironment, and further explore the regulatory role of PPAR-gamma on inflammation and fibrosis

Automated Detection of Dysplasia: Data Mining from Our Hematology Analyzers

Myelodysplastic syndromes (MDSs) are clonal hematopoietic diseases of the elderly, characterized by chronic cytopenia, ineffective and dysplastic hematopoiesis, recurrent genetic abnormalities and increased risk of progression to acute myeloid leukemia. Diagnosis on a complete blood count (CBC) can be challenging due to numerous other non-neoplastic causes of cytopenias. New generations of hematology analyzers provide cell population data (CPD) that can be exploited to reliably detect MDSs from a routine CBC. In this review, we first describe the different technologies used to obtain CPD. We then give an overview of the currently available data regarding the performance of CPD for each lineage in the diagnostic workup of MDSs. Adequate exploitation of CPD can yield very strong diagnostic performances allowing for faster diagnosis and reduction of time-consuming slide reviews in the hematology laboratory

Automated Detection of Dysplasia: Data Mining from Our Hematology Analyzers

International audienceMyelodysplastic syndromes (MDSs) are clonal hematopoietic diseases of the elderly, charac-terized by chronic cytopenia, ineffective and dysplastic hematopoiesis, recurrent genetic abnormalities and increased risk of progression to acute myeloid leukemia. Diagnosis on a complete blood count (CBC) can be challenging due to numerous other non-neoplastic causes of cytopenias. New genera-tions of hematology analyzers provide cell population data (CPD) that can be exploited to reliably detect MDSs from a routine CBC. In this review, we first describe the different technologies used to obtain CPD. We then give an overview of the currently available data regarding the performance of CPD for each lineage in the diagnostic workup of MDSs. Adequate exploitation of CPD can yield very strong diagnostic performances allowing for faster diagnosis and reduction of time-consuming slide reviews in the hematology laboratory

HIV-Sheltering Platelets From Immunological Non-Responders Induce a Dysfunctional Glycolytic CD4+ T-Cell Profile

International audienceImmunological non-responders (InRs) are HIV-infected individuals in whom the administration of combination antiretroviral therapy (cART), although successful in suppressing viral replication, cannot properly reconstitute patient circulating CD4+ T-cell number to immunocompetent levels. The causes for this immunological failure remain elusive, and no therapeutic strategy is available to restore a proper CD4+ T-cell immune response in these individuals. We have recently demonstrated that platelets harboring infectious HIV are a hallmark of InR, and we now report on a causal connection between HIV-containing platelets and T-cell dysfunctions. We show here that in vivo, platelet–T-cell conjugates are more frequent among CD4+ T cells in InRs displaying HIV-containing platelets (<350 CD4+ T cells/μl blood for >1 year) as compared with healthy donors or immunological responders (IRs; >350 CD4+ T cells/μl). This contact between platelet containing HIV and T cell in the conjugates is not infectious for CD4+ T cells, as coculture of platelets from InRs containing HIV with healthy donor CD4+ T cells fails to propagate infection to CD4+ T cells. In contrast, when macrophages are the target of platelets containing HIV from InRs, macrophages become infected. Differential transcriptomic analyses comparing InR and IR CD4+ T cells reveal an upregulation of genes involved in both aerobic and anaerobic glycolysis in CD4+ T cells from InR vs. IR individuals. Accordingly, InR platelets containing HIV induce a dysfunctional increase in glycolysis-mediated energy production in CD4+ T cells as compared with T cells cocultured with IR platelets devoid of virus. In contrast, macrophage metabolism is not affected by platelet contact. Altogether, this brief report demonstrates a direct causal link between presence of HIV in platelets and T-cell dysfunctions typical of InR, contributing to devise a platelet-targeted therapy for improving immune reconstitution in these individuals. Copyrigh

Machine learning-based improvement of MDS-CBC score brings platelets into the limelight to optimize smear review in the hematology laboratory

International audienceBackground: Myelodysplastic syndromes (MDS) are clonal hematopoietic diseases of the elderly characterized by chronic cytopenias, ineffective and dysplastic haematopoiesis, recurrent genetic abnormalities and increased risk of progression to acute myeloid leukemia. A challenge of routine laboratory Complete Blood Counts (CBC) is to correctly identify MDS patients while simultaneously avoiding excess smear reviews. To optimize smear review, the latest generations of hematology analyzers provide new cell population data (CPD) parameters with an increased ability to screen MDS, among which the previously described MDS-CBC Score, based on Absolute Neutrophil Count (ANC), structural neutrophil dispersion (Ne-WX) and mean corpuscular volume (MCV). Ne-WX is increased in the presence of hypogranulated/degranulated neutrophils, a hallmark of dysplasia in the context of MDS or chronic myelomonocytic leukemia. Ne-WX and MCV are CPD derived from leukocytes and red blood cells, therefore the MDS-CBC score does not include any platelet-derived CPD. We asked whether this score could be improved by adding the immature platelet fraction (IPF), a CPD used as a surrogate marker of dysplastic thrombopoiesis. Methods: Here, we studied a cohort of more than 500 individuals with cytopenias, including 168 MDS patients. In a first step, we used Breiman’s random forests algorithm, a machine-learning approach, to identify the most relevant parameters for MDS prediction. We then designed Classification And Regression Trees (CART) to evaluate, using resampling, the effect of model tuning parameters on performance and choose the “optimal” model across these parameters. Results: Using random forests algorithm, we identified Ne-WX and IPF as the strongest discriminatory predictors, explaining 37 and 33% of diagnoses respectively. To obtain “simplified” trees, which could be easily implemented into laboratory middlewares, we designed CART combining MDS-CBC score and IPF. Optimal results were obtained using a MDS-CBC score threshold equal to 0.23, and an IPF threshold equal to 3%. Conclusions: We propose an extended MDS-CBC score, including CPD from the three myeloid lineages, to improve MDS diagnosis on routine laboratory CBCs and optimize smear reviews

Artificial intelligence to empower diagnosis of myelodysplastic syndromes by multiparametric flow cytometry

International audienceThe diagnosis of myelodysplastic syndromes (MDS) might be challenging and relies on the convergence of cytological, cytogenetic, and molecular arguments. Multiparametric flow cytometry (MFC) helps diagnose MDS, especially when other features are non-contributory, but remains underestimated mostly due to a lack of standardization of cytometers. We present here an innovative model integrating artificial intelligence (AI) with MFC to improve the diagnosis and the classification of MDS. We develop a machine learning model by elasticnet algorithm trained on a cohort of 191 patients and only based on flow cytometry parameters selected by Boruta algorithm, to build a simple but reliable prediction score with 5 parameters. Our MDS prediction score assisted by AI greatly improves the sensitivity of Ogata score while keeping an excellent specificity validated on an external cohort of 89 patients with an AUC = 0.935. This model allows the diagnosis of both high and low risk MDS with 91.8% sensitivity and 92.5% specificity. Interestingly, it highlights a progressive evolution of the score from clonal hematopoiesis of indeterminate potential (CHIP) to highrisk MDS, suggesting a linear evolution between these different stages. By significantly decreasing the overall misclassification of 52% for patients with MDS and of 31.3% for those without MDS (p=0.02), our AI-assisted prediction score outperforms the Ogata score and positions itself as a reliable tool to help diagnose myelodysplastic syndromes

Effects of Cyanobacterial Lipopolysaccharides from Microcystis on Glutathione-Based Detoxification Pathways in the Zebrafish (Danio rerio) Embryo

Cyanobacteria (“blue-green algae”) are recognized producers of a diverse array of toxic secondary metabolites. Of these, the lipopolysaccharides (LPS), produced by all cyanobacteria, remain to be well investigated. In the current study, we specifically employed the zebrafish (Danio rerio) embryo to investigate the effects of LPS from geographically diverse strains of the widespread cyanobacterial genus, Microcystis, on several detoxifying enzymes/pathways, including glutathione-S-transferase (GST), glutathione peroxidase (GPx)/glutathione reductase (GR), superoxide dismutase (SOD), and catalase (CAT), and compared observed effects to those of heterotrophic bacterial (i.e., E. coli) LPS. In agreement with previous studies, cyanobacterial LPS significantly reduced GST in embryos exposed to LPS in all treatments. In contrast, GPx moderately increased in embryos exposed to LPS, with no effect on reciprocal GR activity. Interestingly, total glutathione levels were elevated in embryos exposed to Microcystis LPS, but the relative levels of reduced and oxidized glutathione (i.e., GSH/GSSG) were, likewise, elevated suggesting that oxidative stress is not involved in the observed effects as typical of heterotrophic bacterial LPS in mammalian systems. In further support of this, no effect was observed with respect to CAT or SOD activity. These findings demonstrate that Microcystis LPS affects glutathione-based detoxification pathways in the zebrafish embryo, and more generally, that this model is well suited for investigating the apparent toxicophore of cyanobacterial LPS, including possible differences in structure-activity relationships between heterotrophic and cyanobacterial LPS, and teleost fish versus mammalian systems