12 research outputs found
PolyGA targets the ER stress-adaptive response by impairing GRP75 function at the MAM in C9ORF72-ALS/FTD.
ER stress signaling is linked to the pathophysiological and clinical disease manifestations in amyotrophic lateral sclerosis (ALS). Here, we have investigated ER stress-induced adaptive mechanisms in C9ORF72-ALS/FTD, focusing on uncovering early endogenous neuroprotective mechanisms and the crosstalk between pathological and adaptive responses in disease onset and progression. We provide evidence for the early onset of ER stress-mediated adaptive response in C9ORF72 patient-derived motoneurons (MNs), reflected by the elevated increase in GRP75 expression. These transiently increased GRP75 levels enhance ER-mitochondrial association, boosting mitochondrial function and sustaining cellular bioenergetics during the initial stage of disease, thereby counteracting early mitochondrial deficits. In C9orf72 rodent neurons, an abrupt reduction in GRP75 expression coincided with the onset of UPR, mitochondrial dysfunction and the emergence of PolyGA aggregates, which co-localize with GRP75. Similarly, the overexpression of PolyGA in WT cortical neurons or C9ORF72 patient-derived MNs led to the sequestration of GRP75 within PolyGA inclusions, resulting in mitochondrial calcium (Ca2+) uptake impairments. Corroborating these findings, we found that PolyGA aggregate-bearing human post-mortem C9ORF72 hippocampal dentate gyrus neurons not only display reduced expression of GRP75 but also exhibit GRP75 sequestration within inclusions. Sustaining high GRP75 expression in spinal C9orf72 rodent MNs specifically prevented ER stress, normalized mitochondrial function, abrogated PolyGA accumulation in spinal MNs, and ameliorated ALS-associated behavioral phenotype. Taken together, our results are in line with the notion that neurons in C9ORF72-ALS/FTD are particularly susceptible to ER-mitochondrial dysfunction and that GRP75 serves as a critical endogenous neuroprotective factor. This neuroprotective pathway, is eventually targeted by PolyGA, leading to GRP75 sequestration, and its subsequent loss of function at the MAM, compromising mitochondrial function and promoting disease onset
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
In Vitro Modeling as a Tool for Testing Therapeutics for Spinal Muscular Atrophy and IGHMBP2-Related Disorders
Spinal Muscular Atrophy (SMA) is the leading genetic cause of infant mortality. The most common form of SMA is caused by mutations in the SMN1 gene, located on 5q (SMA). On the other hand, mutations in IGHMBP2 lead to a large disease spectrum with no clear genotype–phenotype correlation, which includes Spinal Muscular Atrophy with Muscular Distress type 1 (SMARD1), an extremely rare form of SMA, and Charcot–Marie–Tooth 2S (CMT2S). We optimized a patient-derived in vitro model system that allows us to expand research on disease pathogenesis and gene function, as well as test the response to the AAV gene therapies we have translated to the clinic. We generated and characterized induced neurons (iN) from SMA and SMARD1/CMT2S patient cell lines. After establishing the lines, we treated the generated neurons with AAV9-mediated gene therapy (AAV9.SMN (Zolgensma) for SMA and AAV9.IGHMBP2 for IGHMBP2 disorders (NCT05152823)) to evaluate the response to treatment. The iNs of both diseases show a characteristic short neurite length and defects in neuronal conversion, which have been reported in the literature before with iPSC modeling. SMA iNs respond to treatment with AAV9.SMN in vitro, showing a partial rescue of the morphology phenotype. For SMARD1/CMT2S iNs, we were able to observe an improvement in the neurite length of neurons after the restoration of IGHMBP2 in all disease cell lines, albeit to a variable extent, with some lines showing better responses to treatment than others. Moreover, this protocol allowed us to classify a variant of uncertain significance on IGHMBP2 on a suspected SMARD1/CMT2S patient. This study will further the understanding of SMA, and SMARD1/CMT2S disease in particular, in the context of variable patient mutations, and might further the development of new treatments, which are urgently needed
Loss of IRF2BPL impairs neuronal maintenance through excess Wnt signaling.
De novo truncations in Interferon Regulatory Factor 2 Binding Protein Like (IRF2BPL) lead to severe childhood-onset neurodegenerative disorders. To determine how loss of IRF2BPL causes neural dysfunction, we examined its function in Drosophila and zebrafish. Overexpression of either IRF2BPL or Pits, the Drosophila ortholog, represses Wnt transcription in flies. In contrast, neuronal depletion of Pits leads to increased wingless (wg) levels in the brain and is associated with axonal loss, whereas inhibition of Wg signaling is neuroprotective. Moreover, increased neuronal expression of wg in flies is sufficient to cause age-dependent axonal loss, similar to reduction of Pits. Loss of irf2bpl in zebrafish also causes neurological defects with an associated increase in wnt1 transcription and downstream signaling. WNT1 is also increased in patient-derived astrocytes, and pharmacological inhibition of Wnt suppresses the neurological phenotypes. Last, IRF2BPL and the Wnt antagonist, CKIα, physically and genetically interact, showing that IRF2BPL and CkIα antagonize Wnt transcription and signaling