Krox-20 inhibits Jun-NH2-terminal kinase/c-Jun to control Schwann cell proliferation and death

The transcription factor Krox-20 controls Schwann cell myelination. Schwann cells in Krox-20 null mice fail to myelinate, and unlike myelinating Schwann cells, continue to proliferate and are susceptible to death. We find that enforced Krox-20 expression in Schwann cells cell-autonomously inactivates the proliferative response of Schwann cells to the major axonal mitogen β–neuregulin-1 and the death response to TGFβ or serum deprivation. Even in 3T3 fibroblasts, Krox-20 not only blocks proliferation and death but also activates the myelin genes periaxin and protein zero, showing properties in common with master regulatory genes in other cell types. Significantly, a major function of Krox-20 is to suppress the c-Jun NH2-terminal protein kinase (JNK)–c-Jun pathway, activation of which is required for both proliferation and death. Thus, Krox-20 can coordinately control suppression of mitogenic and death responses. Krox-20 also up-regulates the scaffold protein JNK-interacting protein 1 (JIP-1). We propose this as a possible component of the mechanism by which Krox-20 regulates JNK activity during Schwann cell development

c-Jun is a negative regulator of myelination

Schwann cell myelination depends on Krox-20/Egr2 and other promyelin transcription factors that are activated by axonal signals and control the generation of myelin-forming cells. Myelin-forming cells remain remarkably plastic and can revert to the immature phenotype, a process which is seen in injured nerves and demyelinating neuropathies. We report that c-Jun is an important regulator of this plasticity. At physiological levels, c-Jun inhibits myelin gene activation by Krox-20 or cyclic adenosine monophosphate. c-Jun also drives myelinating cells back to the immature state in transected nerves in vivo. Enforced c-Jun expression inhibits myelination in cocultures. Furthermore, c-Jun and Krox-20 show a cross-antagonistic functional relationship. c-Jun therefore negatively regulates the myelinating Schwann cell phenotype, representing a signal that functionally stands in opposition to the promyelin transcription factors. Negative regulation of myelination is likely to have significant implications for three areas of Schwann cell biology: the molecular analysis of plasticity, demyelinating pathologies, and the response of peripheral nerves to injury

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

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

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

(A) Western blot showing that c-Jun is absent from cells infected with CRE-expressing adenovirus

The blot also compares periaxin in control (Con) and –null cells (CRE) infected with GFP control adenovirus (GFP) or a Krox-20/GFP virus (K20). Note high periaxin levels in Krox-20–infected –null cells (CRE). (B–E) control ( con) and –null mouse Schwann cells 2 d after infection with Krox-20/GFP adenovirus. Note that Krox-20 induces much higher levels of P protein in –null cells (D and E) than in control cells (B and C). The reason why P levels in the Krox-20–expressing control cells appear low in this picture (C) compared with other comparable experiments (e.g., ) is that exposure had to be reduced (equally for C and E) to avoid overexposure in E. (F and G) P protein expression in control cells P ( con) and c–null mouse Schwann cells after 3 d of exposure to db-cAMP/NRG-1. Note that cAMP/NRG-1 induces substantially higher P levels in cells without c-Jun. Bars, 15 μm.<p><b>Copyright information:</b></p><p>Taken from "c-Jun is a negative regulator of myelination"</p><p></p><p>The Journal of Cell Biology 2008;181(4):625-637.</p><p>Published online 19 May 2008</p><p>PMCID:PMC2386103.</p><p></p

(A and B) Cotransfection of Krox-20/GFP with Jun(Asp) or with Jun(Ala) inhibits Krox-20–mediated induction of periaxin and P

K20/EV represents cells cotransfected with Krox-20 and control vector. (C–F) P in situ experiment showing that cotransfection of Krox-20/GFP with Jun(Ala) inhibits Krox-20–mediated induction of mRNA. C and D are controls, and the arrows show a cell coexpressing Krox-20 and a control vector where Krox-20 has induced P mRNA. Arrows in E and F show a cell coexpressing Krox-20 and Jun(Ala) where Jun(Ala) has inhibited Krox-induced expression. Bar, 15 μm. (G) Percentages of GFP-positive cells that also express mRNA in cells cotransfected with the constructs indicated. Error bars show one standard deviation of the mean.<p><b>Copyright information:</b></p><p>Taken from "c-Jun is a negative regulator of myelination"</p><p></p><p>The Journal of Cell Biology 2008;181(4):625-637.</p><p>Published online 19 May 2008</p><p>PMCID:PMC2386103.</p><p></p

(A) MBP immunolabeling of sciatic nerve sections showing delayed loss of myelin in –null nerves compared with controls, 3 d after transection of nerves of 5-d-old mice

Bar, 10 μm. (B) Quantification of the delay in myelin disappearance by quantitative image analysis of MBP-immunolabeled sections (comparable to those shown in A) 2, 3, and 5 d after injury (expressed as percentage of MPB area in uncut P5 nerve). In every case, the difference between c-Jun–null and control nerves is significant (P < 0.01). (C) Electron micrographs showing –null and control nerves from 5-d-old mice, intact and 3 d after injury as indicated. Note preservation of rounded or partially collapsed myelin sheaths in –null nerves. Bar, 4 μm. (D) Counts of myelin sheaths (rounded or collapsed) in c–null and control nerves 3 and 5 d after injury (3 d, P < 0.05; 5 d, P < 0.01). Error bars show standard deviation of the mean.<p><b>Copyright information:</b></p><p>Taken from "c-Jun is a negative regulator of myelination"</p><p></p><p>The Journal of Cell Biology 2008;181(4):625-637.</p><p>Published online 19 May 2008</p><p>PMCID:PMC2386103.</p><p></p

(A) Western blot showing that MKK7, presumably by activating JNK, inhibits Krox-20–induced myelin protein expression

The cells were coinfected with adenoviruses expressing the constructs indicated. (B) Western blot of cells infected with adenoviruses expressing control LacZ or activated MKK7 to activate JNK. Note that periaxin induced by 2 d of exposure to 1 mM of db-cAMP in LacZ control cells is inhibited by MKK7 expression. (C–F) MKK7 activates c-Jun even in the presence of Krox-20. C and E show that Krox-20 coinfected with a control LacZ-expressing adenovirus suppresses c-Jun levels. D and F show that when Krox-20 is coexpressed with MKK7, high c-Jun levels are maintained. (G) MKK7-mediated suppression of myelin gene expression depends on c-Jun. In normal cells ( con), Krox-20–induced periaxin expression (K20/LacZ) is suppressed by MKK7 (K20/MKK7). This suppression does not occur when this experiment is repeated in cells without c-Jun ( null). Error bars show one standard deviation of the mean. (H–K) Reactivation of JNK/c-Jun in Krox-20–expressing cells that already synthesize P abolishes P protein expression. Retrovirally infected cells already expressing Krox-20 and P were infected with either LacZ control (H and I) or MKK7-expressing (J and K) adenoviruses. Cells were labeled with either LacZ and P (H and I) or MKK7 and P (J and K) antibodies. Note down-regulation of P protein in Krox-20–expressing cells infected with MKK7 adenovirus. Bars, 15 μm.<p><b>Copyright information:</b></p><p>Taken from "c-Jun is a negative regulator of myelination"</p><p></p><p>The Journal of Cell Biology 2008;181(4):625-637.</p><p>Published online 19 May 2008</p><p>PMCID:PMC2386103.</p><p></p