33 research outputs found
Assessment of Anti-cancerous properties of Nyctanthes arbor-tristis Linn natural compounds
Purpose: Nyctanthes arbor-tristis Linn., the lovely and fragrant flowering tree, sometimes called night-blooming jasmine or parijat, is native to Southeast and South Asia. For ages, this has been utilized in traditional medicine. There are claims that its leaves and blossoms have anti-inflammatory, antimicrobial, and anti-diabetic qualities. Plants contain anti-cancer capabilities; however, this has not yet been investigated. Therefore, we propose to explore mechanistic interaction with different cancer targets and active chemicals of this plant through computational methods, which will be further subjected to in vitro/in vivo experimental validation to show its anti-cancerous potentialities.
Description: Nyctanthes arbor-tristis Linn. plant contains several natural compounds like flavonoids, lignans, saponins, and napthoquinones. Nyctanthes arbor-tristis Linn. has been used for generations to treat various illnesses, including certain malignancies, in ancient medical systems like Ayurveda. These uses, however, require substantial scientific support as they are predicated on anecdotal evidence. One of the most important factors in carcinogenesis and the success of anticancer treatments is inflammation. Our latest research on anti-inflammatory activities reveals that natural chemicals from Nyctanthes arbor-tristis Linn. can interact with cyclooxygenase-2 (COX-2) and prostaglandin E2 (PGE2).Cyclooxygenase-2, or COX-2, is a multifunctional and intricate protein that frequently aids in the growth and metastasis of cancer. COX-2 catalyzes arachidonic acid to produce prostaglandins, the main by-product of which is PGE2.
PGE2 is a signaling molecule that affects the behavior of tumor cells in several ways. PGE2 promotes cell division in cancer cells and prevents apoptosis or programmed cell death. PGE2 encourages the creation of new blood vessels, which gives tumors the oxygen and nourishment they require for survival. PGE2 facilitates metastasis, or the spread of cancer cells to other organs, by improving their capacity to move and infiltrate surrounding tissues. PGE2 inhibits the immune system\u27s ability to fight cancer, which makes it easier for cancer cells to avoid being found and destroyed. The overexpression of COX-2 stimulates many signaling pathways in cancer cells, augmenting their proliferation and endurance. COX-2 can become constitutively activated in cancer cells due to mutations in the genes controlling its expression. Natural chemicals derived from this plant may target cancer genes such as TP53 (tumor suppressor), KRAS (oncogene), BRCA1, BRCA2, and HER2 (breast cancer) to express their anti-cancer capabilities. Thus, the explored interaction of active chemicals of this plant with cyclooxygenase and other cancer targets will help to suggest alternative anticancer molecules from this plant.
Looking Ahead: The proposed computational analysis led by molecular interaction and molecular dynamics simulation will provide new insight into alternative anticancer potentialities of natural resources, which could prevent life-threatening diseases and avoid the initiation of tumors
XAI Implementation on Preliminary Data Analysis Phase: Explainable Output Application with Prediction of Diabetes Mellitus at Early Stage
Background: This study aims to create a machine learning model that produces explainable, interpretable, andtrustable predictions for diabetes using an XAI approach. Objective: In the study, we have utilized an earlier approach toimplementing explainable Machine Learning. Methods: In order to apply XAI technique, we follow a brief version of CRISPDM.(i) Data Understanding, (ii) Data Preparation, (iii) Model Planning and Building (iv) SHAP Implementation forInterpretability. Results: Global interpretability shows us that two major contributors are symptoms of Polydipsia and Polyuria.An algorithm doesn't "know" prior information, which is highly specific domain knowledge. Local interpretability-basedsingle-instance explanation showed decent multivariate reasoning capability. If the reasoning was based on a simple univariateapproach, positive polyuria alone should result in a high probability of positive model output, considering the positive SHAPvalue of polyuria. Conclusion: The model output results 99.7% confidence to be classified as negative makes much sense sincepolyuria is also a common symptom of many different situations, such as diabetes insipidus, Kidney disease, Liver failure,Medications that include diuretics, Chronic diarrhea, Cushing’s syndrome, Psychogenic polydipsia, Hypercalcemia,Pregnancy
Comparative Molecular Docking Studies with ABCC1 and Aquaporin 9 in the Arsenite Complex Efflux
Arsenic is the most toxic metalloid present in the natural environment in both organic and inorganic arsenic forms. Inorganic arsenic is often more hazardous than the organic form. Arsenite and arsenate compounds are the major inorganic forms which are toxic causing severe human health dysfunction including cancer. Excretion of arsenic from the system is found elusive. Therefore, it is of interest to screen channel proteins with the arsenic complex in the different combination of arsenic, GSH (glutathione) and arsenic, selenium using docking methods. The mode of arsenic removal. The complex structure revealed the mode of arsenic binding efficiency with the receptor aquaporine 9 and ABCC1 channel protein. This provides insights to understand the mechanism of arsenic efflux. These inferences find application in the design, identification and development of novel nutracetucal or any other formulation useful in the balance of arsenic efflux
Molecular Docking of Known Carcinogen 4- (Methyl-nitrosamino)-1-(3-pyridyl)-1-butanone (NNK) with Cyclin Dependent Kinases towards Its Potential Role in Cell Cycle Perturbation
Cell cycle is maintained almost all the times and is controlled by various regulatory proteins and their complexes (Cdk+Cyclin) in different phases of interphase (G1, S and G2) and mitosis of cell cycle. A number of mechanisms have been proposed for the initiation and progression of carcinogenesis by abruption in cell cycle process. One of the important features of cancer/carcinogenesis is functional loss of these cell cycle regulatory proteins particularly in CDKs and cyclins. We hypothesize that there is a direct involvement of these cell cycle regulatory proteins not only at the genetic level but also proteins level, during the initiation of carcinogenesis. Therefore, it becomes significant to determine inconsistency in the functioning of regulatory proteins due to interaction with carcinogen 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). Hence, we investigated the interaction efficiency of NNK, against cell cycle regulatory proteins. We found a different value of ΔG (free energy of binding) among the studied proteins ranging between -3.29 to -7.25 kcal/mol was observed. To validate the results, we considered Human Oxy-Hemoglobin at 1.25 Å Resolution, [PDB_ID:1HHO] as a +ve control, (binding energy -6.06 kcal/mol). Finally, the CDK8 (PDB_ID:3RGF) and CDK2 (PDB_ID:3DDP) regulatory proteins showing significantly strong molecular interaction with NNK -7.25 kcal/mol, -6.19 kcal/mol respectively were analyzed in details. In this study we predicted that CDK8 protein fails to form functional complex with its complementary partner cyclin C in presence of NNK. Consequently, inconsistency of functioning in regulatory proteins might lead to the abruption in cell cycle progression; contribute to the loss of cell cycle control and subsequently increasing the possibility of carcinogenesis
Binding Pattern Elucidation of NNK and NNAL Cigarette Smoke Carcinogens with NER Pathway Enzymes: an Onco- Informatics Study
Cigarette smoke derivatives like NNK (4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone) and NNAL (4-(methylnitrosamino)-1-(3-pyridyl)-1-butan-1-ol) are well-known carcinogens. We analyzed the interaction of enzymes involved in the NER (nucleotide excision repair) pathway with ligands (NNK and NNAL). Binding was characterized for the enzymes sharing equivalent or better interaction as compared to +Ve control. The highest obtained docking energy between NNK and enzymes RAD23A, CCNH, CDK7, and CETN2 were -7.13 kcal/mol, -7.27 kcal/mol, -8.05 kcal/mol and -7.58 kcal/mol respectively. Similarly the highest obtained docking energy between NNAL and enzymes RAD23A, CCNH, CDK7, and CETN2 were -7.46 kcal/mol, -7.94 kcal/mol, -7.83 kcal/mol and -7.67 kcal/mol respectively. In order to find out the effect of NNK and NNAL on enzymes involved in the NER pathway applying protein-protein interaction and protein-complex (i.e. enzymes docked with NNK/ NNAL) interaction analysis. It was found that carcinogens are well capable to reduce the normal functioning of genes like RAD23A (HR23A), CCNH, CDK7 and CETN2. In silico analysis indicated loss of functions of these genes and their corresponding enzymes, which possibly might be a cause for alteration of DNA repair pathways leading to damage buildup and finally contributing to cancer formation
Interaction pattern for the complex of B-DNAFullerene compounds with a set of known replication proteins using docking study
Fullerenes have attracted considerable attention due to their unique chemical structure and potential applications which has opened wide venues for possible human exposure to various fullerene types. Therefore, in depth knowledge of how fullerene may interfere with various cellular processes becomes quite imperative. The present study was designed to investigate how the presence of fullerene affect the binding of DNA with different enzymes involved in replication process. Different fullerenes were first docked with DNA and then binding scores of different enzymes was analyzed with fullerene docked DNA. C30, C40 & C50 once docked with DNA, reduced the binding score of primase, whereas no significant change in the binding score was observed with the helicase, ssb protein, dna pol δ, dna pol ɛ, ligase, DNA clamp, and topoisomerases. On the contrast, the binding score of RPA14 decreases in fluctuating manner while interacting with increasing molecular weight of fullerene bound single-stranded DNA complex. The study revealed the affect of fullerene family interacting with DNA on the binding pattern of enzymes involved in replication process. Study suggests that the presence of most of fullerenes may not affect the activity of these enzymes necessary for replication process whereas C30, C40 & C50 may disrupt the activity of primase, (strating point for DNA polymerase) its docking score decreases from 13820 to 10702
Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions
Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021
Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions
Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill & Melinda Gates Foundation