Congenital myopathies: characteristic and subtypes in Hong Kong

This journal suppl. entitled: 20th International Congress of The World Muscle SocietyCongenital myopathies are a group of childhood onset neuromuscular disorder with the diagnosis mainly based on genetic and pathological features. This is a unique group with phenotypic, genotypic and pathological heterogeneity, so the confirmation of an underlying diagnosis is often challenging. This is the first congenital myopathy case series in Hong Kong. A total of 15 patients have been diagnosed to have congenital myopathies with 11 patients had the genetic mutations being identified (4 patients had RYR1 mutations, 3 patients had ACTA1 mutations, 2 patients had KLHL40 mutations, 1 patient had MTM1 mutation and 1 patient had DNM2 mutation).postprin

Associations between extreme temperatures and cardiovascular cause-specific mortality: results from 27 countries

BACKGROUND: Cardiovascular disease is the leading cause of death worldwide. Existing studies on the association between temperatures and cardiovascular deaths have been limited in geographic zones and have generally considered associations with total cardiovascular deaths rather than cause-speci fi c cardiovascular deaths. METHODS: We used uni fi ed data collection protocols within the Multi-Country Multi-City Collaborative Network to assemble a database of daily counts of speci fi c cardiovascular causes of death from 567 cities in 27 countries across 5 continents in overlapping periods ranging from 1979 to 2019. City-speci fi c daily ambient temperatures were obtained from weather stations and climate reanalysis models. To investigate cardiovascular mortality associations with extreme hot and cold temperatures, we fi t case-crossover models in each city and then used a mixed-effects meta-analytic framework to pool individual city estimates. Extreme temperature percentiles were compared with the minimum mortality temperature in each location. Excess deaths were calculated for a range of extreme temperature days. RESULTS: The analyses included deaths from any cardiovascular cause (32 154 935), ischemic heart disease (11 745 880), stroke (9 351 312), heart failure (3 673 723), and arrhythmia (670 859). At extreme temperature percentiles, heat (99th percentile) and cold (1st percentile) were associated with higher risk of dying from any cardiovascular cause, ischemic heart disease, stroke, and heart failure as compared to the minimum mortality temperature, which is the temperature associated with least mortality. Across a range of extreme temperatures, hot days (above 97.5th percentile) and cold days (below 2.5th percentile) accounted for 2.2 (95% empirical CI [eCI], 2.1-2.3) and 9.1 (95% eCI, 8.9-9.2) excess deaths for every 1000 cardiovascular deaths, respectively. Heart failure was associated with the highest excess deaths proportion from extreme hot and cold days with 2.6 (95% eCI, 2.4-2.8) and 12.8 (95% eCI, 12.2-13.1) for every 1000 heart failure deaths, respectively. CONCLUSIONS: Across a large, multinational sample, exposure to extreme hot and cold temperatures was associated with a greater risk of mortality from multiple common cardiovascular conditions. The intersections between extreme temperatures and cardiovascular health need to be thoroughly characterized in the present day-and especially under a changing climate

Joint effect of heat and air pollution on mortality in 620 cities of 36 countries

Background The epidemiological evidence on the interaction between heat and ambient air pollution on mortality is still inconsistent. Objectives To investigate the interaction between heat and ambient air pollution on daily mortality in a large dataset of 620 cities from 36 countries. Methods We used daily data on all-cause mortality, air temperature, particulate matter ≤ 10 μm (PM10), PM ≤ 2.5 μm (PM2.5), nitrogen dioxide (NO2), and ozone (O3) from 620 cities in 36 countries in the period 1995–2020. We restricted the analysis to the six consecutive warmest months in each city. City-specific data were analysed with over-dispersed Poisson regression models, followed by a multilevel random-effects meta-analysis. The joint association between air temperature and air pollutants was modelled with product terms between non-linear functions for air temperature and linear functions for air pollutants. Results We analyzed 22,630,598 deaths. An increase in mean temperature from the 75th to the 99th percentile of city-specific distributions was associated with an average 8.9 % (95 % confidence interval: 7.1 %, 10.7 %) mortality increment, ranging between 5.3 % (3.8 %, 6.9 %) and 12.8 % (8.7 %, 17.0 %), when daily PM10 was equal to 10 or 90 μg/m3, respectively. Corresponding estimates when daily O3 concentrations were 40 or 160 μg/m3 were 2.9 % (1.1 %, 4.7 %) and 12.5 % (6.9 %, 18.5 %), respectively. Similarly, a 10 μg/m3 increment in PM10 was associated with a 0.54 % (0.10 %, 0.98 %) and 1.21 % (0.69 %, 1.72 %) increase in mortality when daily air temperature was set to the 1st and 99th city-specific percentiles, respectively. Corresponding mortality estimate for O3 across these temperature percentiles were 0.00 % (-0.44 %, 0.44 %) and 0.53 % (0.38 %, 0.68 %). Similar effect modification results, although slightly weaker, were found for PM2.5 and NO2. Conclusions Suggestive evidence of effect modification between air temperature and air pollutants on mortality during the warm period was found in a global dataset of 620 cities.Massimo Stafoggia, Francesca K. de’ Donato, Masna Rai and Alexandra Schneider were partially supported by the European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655). Jan Kyselý and Aleš Urban were supported by the Czech Science Foundation project (22-24920S). Joana Madureira was supported by the Fundação para a Ciência e a Tecnologia (FCT) (grant SFRH/BPD/115112/2016). Masahiro Hashizume was supported by the Japan Science and Technology Agency (JST) as part of SICORP, Grant Number JPMJSC20E4. Noah Scovronick was supported by the NIEHS-funded HERCULES Center (P30ES019776). South African Data were provided by Statistics South Africa, which did not have any role in conducting the study. Antonio Gasparrini was supported by the Medical Research Council-UK (Grants ID: MR/V034162/1 and MR/R013349/1), the Natural Environment Research Council UK (Grant ID: NE/R009384/1), and the European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655)

Author Correction: Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition

Correction to: Nature Genetics https://doi.org/10.1038/s41588-019-0562-0, published online 05 February 2020

Comparison of weather station and climate reanalysis data for modelling temperature-related mortality

Epidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations that offer limited spatial and temporal coverage. Climate reanalysis represents an alternative option that provide complete spatio-temporal exposure coverage, and yet are to be systematically explored for their suitability in assessing temperature-related health risks at a global scale. Here we provide the first comprehensive analysis over multiple regions to assess the suitability of the most recent generation of reanalysis datasets for health impact assessments and evaluate their comparative performance against traditional station-based data. Our findings show that reanalysis temperature from the last ERA5 products generally compare well to station observations, with similar non-optimal temperature-related risk estimates. However, the analysis offers some indication of lower performance in tropical regions, with a likely underestimation of heat-related excess mortality. Reanalysis data represent a valid alternative source of exposure variables in epidemiological analyses of temperature-related risk. © 2022, The Author(s).The original version of this Article contained an error in Affiliation 25, which was incorrectly given as ‘Faculty of Medicine ArqFuturo INSPER, University of São Paulo, São Paulo, Brazil’. The correct affiliation is listed below. Faculty of Medicine, University of São Paulo, São Paulo, Brazil The original Article has been corrected. © The Author(s) 2022.The study was primarily supported by Grants from the European Commission’s Joint Research Centre Seville (Research Contract ID: JRC/SVQ/2020/MVP/1654), Medical Research Council-UK (Grant ID: MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655). The following individual Grants also supported this work: J.K and A.U were supported by the Czech Science Foundation, project 20-28560S. A.T was supported by MCIN/AEI/10.13039/501100011033, Grant CEX2018-000794-S. V.H was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant agreement No 101032087. This work was generated using Copernicus Climate Change Service (C3S) information [1985–2019]

Author Correction: Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing (Nature Genetics, (2020), 52, 3, (331-341), 10.1038/s41588-019-0576-7)

Correction to: Nature Genetics, published online 05 February 2020. In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium were listed in the Supplementary Information; however, these members should have been included in the main paper. The original Article has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper

Author Correction: Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer

Correction to: Nature Genetics https://doi.org/10.1038/s41588-019-0564-y, published online 05 February 2020

The burden of heat-related mortality attributable to recent human-induced climate change

Medical Research Council-UK (Grant ID: MR/M022625/1); Natural Environment Research Council UK (Grant ID: NE/R009384/1); European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655); N. Scovronick was supported by the NIEHS-funded HERCULES Center (P30ES019776); Y. Honda was supported by the Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, Japan (JPMEERF15S11412); J. Jaakkola was supported by Academy of Finland (Grant No. 310372); V. Huber was supported by the Spanish Ministry of Economy, Industry and Competitiveness (Grant ID: PCIN-2017-046) and the German Federal Ministry of Education and Research (Grant ID: 01LS1201A2); J Kysely and A. Urban were supported by the Czech Science Foundation (Grant ID: 20-28560S); J. Madureira was supported by the Fundação para a Ciência e a Tecnologia (FCT) (SFRH/BPD/115112/2016); S. Rao and F. di Ruscio were supported by European Union’s Horizon 2020 Project EXHAUSTION (Grant ID: 820655); M. Hashizume was supported by the Japan Science and Technology Agency (JST) as part of SICORP, Grant Number JPMJSC20E4; Y. Guo was supported by the Career Development Fellowship of the Australian National Health and Medical Research Council (#APP1163693); S. Lee was support by the Early Career Fellowship of the Australian National Health and Medical Research Council (#APP1109193)

Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study

© 2021 The Author(s). Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. Interpretation: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. Funding: Australian Research Council and the Australian National Health and Medical Research Council.Australian Research Council; Australian National Health and Medical Research Council