Renaler Phänotyp von Mäusen mit induzierbarer Deletion von mTORC1 und mTORC2 im Tubulusepithel

Bei unklarer Rolle von mTOR im Tubulussystem und bei zunehmendem Einsatz von mTOR-Inhibitoren hat sich diese Arbeit zum Ziel gesetzt, die physiologische Funktion von mTOR und die damit verbundene Pathophysiologie im proximalen Tubulus zu untersuchen. Dazu wurde ein Mausmodell mit einem induzierbaren gewebespezifischen Knockout der beiden mTOR-Komplexen mTORC1 und mTORC2 herangezogen. Es konnte nachgewiesen werden, dass eine Deletion von mTORC1 und mTORC2 zu einer Resorptionsstörung im proximalen Tubulus führt, die sich durch eine erhöhte Natriurese, Kaliurese, Phosphaturie, Glucosurie und eine globale Aminoazidurie äußert. Zudem verursachte diese Deletion eine Niereninsuffizienz mit verminderter GFR, erhöhten Harnstoffwerten und verringertem Nierengewicht. Weil sich der Knockout ausschließlich auf den proximalen Tubulus beschränkte und im Glomerulus somit keine Deletion vorlag, ist davon auszugehen, dass die nachgewiesene Niereninsuffizienz am ehesten nicht auf einer glomerulär bedingten Störung beruht, sondern eher als Antwort der Niere auf die Störung des proximalen Tubulus zu betrachten ist. Darüber hinaus zeigte sich eine Reduktion des Körpergewichtes, die am ehesten auf einen insgesamt gestörten Energiehaushalt zurückzuführen ist. Diese Befunde untermauern die zu Beginn gestellte Hypothese, dass mTOR als ein intrazelluläres Schlüsselprotein eine große Bedeutung im Haushalt der proximal-tubulären Zelle zukommt. Diese Bedeutung wird umso deutlicher, wenn man berücksichtigt, dass im proximalen Tubulus verschiedenste Transportvorgänge von beispielsweise Proteinen, Glucose, Elektrolyten ablaufen, die nahezu alle durch mTOR reguliert werden. Dieser enge Zusammenhang spielt eine große Rolle, wenn es beispielsweise um Nebenwirkungen von mTOR-Inhibitoren geht. Nichtdestotrotz bleiben die genauen molekularen Mechanismen, die für die erhobenen Befunde ursächlich sind, durch diese Arbeit ungeklärt

MTOR regulates endocytosis and nutrient transport in proximal tubular cells

Renal proximal tubular cells constantly recycle nutrients to ensure minimal loss of vital substrates into the urine. Although most of the transport mechanisms have been discovered at the molecular level, little is known about the factors regulating these processes. Here, we show that mTORC1 and mTORC2 specifically and synergistically regulate PTC endocytosis and transport processes. Using a conditional mouse genetic approach to disable nonredundant subunits of mTORC1, mTORC2, or both, we showed that mice lacking mTORC1 or mTORC1/mTORC2 but not mTORC2 alone develop a Fanconi-like syndrome of glucosuria, phosphaturia, aminoaciduria, low molecular weight proteinuria, and albuminuria. Interestingly, proteomics and phosphoproteomics of freshly isolated kidney cortex identified either reduced expression or loss of phosphorylation at critical residues of different classes of specific transport proteins. Functionally, this resulted in reduced nutrient transport and a profound perturbation of the endocytic machinery, despite preserved absolute expression of the main scavenger receptors, MEGALIN and CUBILIN. Our findings highlight a novel mTOR–dependent regulatory network for nutrient transport in renal proximal tubular cells

Definition of bulky disease in early stage diffuse large B-cell lymphoma in computed tomography on coronal and transverse planes

BackgroundIn early stage diffuse large B-cell lymphoma (ESDLBL), tumor bulkiness is an important determinant of treatment and prognosis. Tumor bulk is usually measured on transverse computed tomography (CT) plane and variably defined from 5 to 10 cm.ObjectivesOur study aims to investigate the prognostic significance of bulky disease measured on CT coronal and transverse planes and to evaluate the outcome of patients with bulky disease.MethodsPatients with ESDLBL and treated with rituximab, cyclophosphamide, doxorubicin, and prednisolone (RCHOP) with or without radiotherapy were included. Receiver Operating Characteristic (ROC) analysis was used to identify the optimal tumor dimension that correlated with progression, relapse, or death. Correlation between different variables and progression-free survival (PFS) and overall survival (OS) were analyzed using log-rank (Mantel–Cox) test and Cox proportional hazard models.ResultsA total of 127 patients with a median age of 47 (range: 18–90) years were included. Eighty-two (64.6%) patients treated with combined modality treatment (CMT) [RCHOP + radiotherapy]. After a median follow-up of 40 (range: 2–114) months, 3-year PFS and OS were 83.9% (95% CI: 76.759%–89.981%), and 80.6% (95% CI: 72.499%–87.531%), respectively. Tumor dimension of >7.5 cm measured on either CT plane was the optimal cutoff point to define bulky disease. Three-year PFS and OS were inferior in the group of patients with no bulky disease on transvers plane (n = 84) but had bulky disease on coronal plane (n = 9,10.7%); (94.2% vs. 75%, p = 0.017 and 90.5% vs. 56.3%, p = 0.002), as well as in patients with no bulky disease on coronal plane (n = 89), but had bulky disease on transverse plane (n = 14, 15.7%); (94.1% vs. 62.3%, p < 0.001, and 90.4% vs. 63.5%, p = 0.002). Compared to RCHOP alone, 3-year PFS and OS were better in patients with bulky disease treated with CMT (78% vs. 52.5%, p = 0.018 and 81.8% vs. 38.7%, p = 0.003) but not in patients with non-bulky disease (96.2% vs. 93%, p = 0.691 and 87.6% vs. 91.5%, p = 0.477).ConclusionIn ESDLBL, measurement of tumor mass on transverse and coronal CT planes may help in better identification of patients with bulky disease. The use of CMT was associated with better survival outcomes in patients with bulky disease

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

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

BackgroundFuture 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.MethodsUsing 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.FindingsIn 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]).InterpretationGlobally, 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.FundingBill & Melinda Gates Foundation.</p