Plasma lutein and zeaxanthin concentrations associated with musculoskeletal health and incident frailty in The Irish Longitudinal Study on Ageing (TILDA)

peer-reviewedIntroduction Lutein and zeaxanthin are diet-derived carotenoids that are proposed to help mitigate frailty risk and age-related declines in musculoskeletal health via their anti-oxidant and anti-inflammatory properties. Therefore, this study aimed to investigate the association between lutein and zeaxanthin status and indices of musculoskeletal health and incident frailty among community-dwelling adults aged ≥50 years in the Irish Longitudinal Study on Ageing (TILDA). Methods Cross-sectional analyses (n = 4513) of plasma lutein and zeaxanthin concentrations and grip strength, usual gait speed, timed up-and-go (TUG), probable sarcopenia (defined as grip strength <27 kg in men, <16 kg in women), and bone mass (assessed using calcaneal broadband ultrasound stiffness index) were performed at Wave 1 (2009–2011; baseline). In the longitudinal analyses (n = 1425–3100), changes in usual gait speed (at Wave 3, 2014–2015), grip strength (Wave 4, 2016) and TUG (at Wave 5, 2018), incident probable sarcopenia (at Wave 4) and incident frailty (Fried's phenotype, Frailty Index, FRAIL Scale, Clinical Frailty Scale-classification tree, at Wave 5) were determined. Data were analysed using linear and ordinal logistic regression, adjusted for confounders. Results Cross-sectionally, plasma lutein and zeaxanthin concentrations were positively associated with usual gait speed (B [95 % CI] per 100-nmol/L higher concentration: Lutein 0.59 [0.18, 1.00], Zeaxanthin 1.46 [0.37, 2.55] cm/s) and inversely associated with TUG time (Lutein −0.07 [−0.11, −0.03], Zeaxanthin −0.14 [−0.25, −0.04] s; all p 0.05). Plasma lutein concentration was positively associated with bone stiffness index (0.54 [0.15, 0.93], p 0.05). Conclusion Higher plasma lutein and zeaxanthin concentrations at baseline were associated with a reduced likelihood of incident frailty after ~8 years of follow up. Baseline plasma lutein and zeaxanthin concentrations were also positively associated with several indices of musculoskeletal health cross-sectionally but were not predictive of longitudinal changes in these outcomes over 4–8 years.Horizon 2020 Marie Skłodowska-Curie ActionsThis work was supported by the Teagasc Research Leaders 2025 programme co-funded by Teagasc and the European Union's Horizon 2020 - Research and Innovation Framework Programme under the H2020 Marie Skłodowska-Curie Actions grant agreement number 754380. TILDA is funded by Atlantic Philanthropies, the Irish Department of Health and Irish Life. Roman Romero-Ortuno is funded by a grant from Science Foundation Ireland under grant number 18/FRL/6188

HEROIC: a 5-year observational cohort study aimed at identifying novel factors that drive diabetic kidney disease: rationale and study protocol

Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. INTRODUCTION: Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease worldwide and a major cause of premature mortality in diabetes mellitus (DM). While improvements in care have reduced the incidence of kidney disease among those with DM, the increasing prevalence of DM means that the number of patients worldwide with DKD is increasing. Improved understanding of the biology of DKD and identification of novel therapeutic targets may lead to new treatments. A major challenge to progress has been the heterogeneity of the DKD phenotype and renal progression. To investigate the heterogeneity of DKD we have set up The East and North London Diabetes Cohort (HEROIC) Study, a secondary care-based, multiethnic observational study of patients with biopsy-proven DKD. Our primary objective is to identify histological features of DKD associated with kidney endpoints in a cohort of patients diagnosed with type 1 and type 2 DM, proteinuria and kidney impairment. METHODS AND ANALYSIS: HEROIC is a longitudinal observational study that aims to recruit 500 patients with DKD at high-risk of renal and cardiovascular events. Demographic, clinical and laboratory data will be collected and assessed annually for 5 years. Renal biopsy tissue will be collected and archived at recruitment. Blood and urine samples will be collected at baseline and during annual follow-up visits. Measured glomerular filtration rate (GFR), echocardiography, retinal optical coherence tomography angiography and kidney and cardiac MRI will be performed at baseline and twice more during follow-up. The study is 90% powered to detect an association between key histological and imaging parameters and a composite of death, renal replacement therapy or a 30% decline in estimated GFR. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Bloomsbury Research Ethics Committee (REC 18-LO-1921). Any patient identifiable data will be stored on a password-protected National Health Services N3 network with full audit trail. Anonymised imaging data will be stored in a ISO27001-certificated data warehouse.Results will be reported through peer-reviewed manuscripts and conferences and disseminated to participants, patients and the public using web-based and social media engagement tools as well as through public events

Developing an automated VR cognitive treatment for psychosis: GameChange VR therapy

The automated delivery of psychological treatment using virtual reality (VR) has the potential to revolutionise patient access to evidence-based care. VR creates immersive, interactive computer simulations, which elicit responses similar to the real world. VR simulations provide an ideal opportunity for the experimentation and experiential learning that are key to successful cognitive therapy. If automated, and using the latest consumer kit, VR treatment can substantially scale-up the delivery of psychological therapy. However, the successful application of automated VR to mental health difficulties requires precise treatment targets linked to the right psychological theory and techniques. This paper describes the process of development of an automated VR cognitive therapy targeting anxious avoidance of everyday social situations by patients with psychosis. In the gameChange project, a person-centered design process was used involving people with lived experience of psychosis, clinical psychologists, designers, and software developers. The six-session gameChange VR therapy consists of six everyday scenarios: a street, a bus, a café, a pub, a doctor's waiting room, and a shop. Each scenario has five levels of difficulty. Every level provides an opportunity to test out fearful cognitions while limiting the use of safety-seeking behaviours, allowing patients to build confidence in their ability to cope. Learning is facilitated by a virtual coach and therapeutic gaming elements are included. Data from user testing indicates that the gameChange VR therapy is easy to use and engaging. The clinical effectiveness of gameChange VR therapy is now being tested in a randomised controlled trial with several hundred patients with psychosis

Antigen-driven EGR2 expression is required for exhausted CD8 + T cell stability and maintenance

Chronic stimulation of CD8 T cells triggers exhaustion, a distinct differentiation state with diminished effector function. Exhausted cells exist in multiple differentiation states, from stem-like progenitors that are the key mediators of the response to checkpoint blockade, through to terminally exhausted cells. Due to its clinical relevance, there is substantial interest in defining the pathways that control differentiation and maintenance of these subsets. Here, we show that chronic antigen induces the anergy-associated transcription factor EGR2 selectively within progenitor exhausted cells in both chronic LCMV and tumours. EGR2 enables terminal exhaustion and stabilizes the exhausted transcriptional state by both direct EGR2-dependent control of key exhaustion-associated genes, and indirect maintenance of the exhausted epigenetic state. We show that EGR2 is a regulator of exhaustion that epigenetically and transcriptionally maintains the differentiation competency of progenitor exhausted cells. +This work was funded by National Institutes of Health Grant U19-AI100627, the Swiss National Science Foundation and the Novartis Foundation for Medical-Biological Research (S.S.G.), the Australian Cancer Research Foundation (for the Peter Mac Flow Cytometry and Molecular Genomics facilities) and by the National Health and Medical Research Council (NHMRC) through Program Grants 1016953 & 1113904, Ideas Grant APP2001719, Australia Fellowship 585490 (C.C.G.), Senior Principal Research Fellowships (1081858, C.C.G., 1139607, A.K.), and CJ Martin Early Career Fellowship 585518 (I.A.P.)

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019 : a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p&lt;0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p&lt;0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

Phenotypic profiling of high throughput imaging screens with generic deep convolutional features

While deep learning has seen many recent applications to drug discovery, most have focused on predicting activity or toxicity directly from chemical structure. Phenotypic changes exhibited in cellular images are also indications of the mechanism of action (MoA) of chemical compounds. In this paper, we show how pre-trained convolutional image features can be used to assist scientists in discovering interesting chemical clusters for further investigation. Our method reduces the dimensionality of raw fluorescent stained images from a high throughput imaging (HTI) screen, producing an embedding space that groups together images with similar cellular phenotypes. Running standard unsupervised clustering on this embedding space yields a set of distinct phenotypic clusters. This allows scientists to further select and focus on interesting clusters for downstream analyses. We validate the consistency of our embedding space qualitatively with t-sne visualizations, and quantitatively by measuring embedding variance among images that are known to be similar. Results suggested the usefulness of our proposed workflow using deep learning and clustering and it can lead to robust HTI screening and compound triage