Environment and Obesity in the National Children\u27s Study

Objective: In this review we describe the approach taken by the National Children’s Study (NCS), a 21-year prospective study of 100,000 American children, to understanding the role of environmental factors in the development of obesity. Data sources and extraction: We review the literature with regard to the two core hypotheses in the NCS that relate to environmental origins of obesity and describe strategies that will be used to test each hypothesis. Data synthesis: Although it is clear that obesity in an individual results from an imbalance between energy intake and expenditure, control of the obesity epidemic will require understanding of factors in the modern built environment and chemical exposures that may have the capacity to disrupt the link between energy intake and expenditure. The NCS is the largest prospective birth cohort study ever undertaken in the United States that is explicitly designed to seek information on the environmental causes of pediatric disease. Conclusions: Through its embrace of the life-course approach to epidemiology, the NCS will be able to study the origins of obesity from preconception through late adolescence, including factors ranging from genetic inheritance to individual behaviors to the social, built, and natural environment and chemical exposures. It will have sufficient statistical power to examine interactions among these multiple influences, including gene–environment and gene–obesity interactions. A major secondary benefit will derive from the banking of specimens for future analysis

Macrophage metabolism in the intestine is compartment specific and regulated by the microbiota

Intestinal macrophages play a vital role in the maintenance of gut homeostasis through signals derived from the microbiota. We previously demonstrated that microbial-derived metabolites can shape the metabolic functions of macrophages. Here, we show that antibiotic-induced disruption of the intestinal microbiota dramatically alters both the local metabolite environment and the metabolic functions of macrophages in the colon. Broad-spectrum antibiotic administration in mice increased the expression of the large neutral amino acid transporter LAT1 and accordingly, amino acid uptake. Subsequently, antibiotic administration enhanced the metabolic functions of colonic macrophages, increasing phosphorylation of components of mammalian/mechanistic target of rapamycin signalling pathways, with increased expression of genes involved in glycolysis and oxidative phosphorylation (OXPHOS), increased mitochondrial function, increased rate of extracellular acidification (ECAR; measure of glycolysis) and increased rate of oxygen consumption (OCR; measure of OXPHOS). Small bowel macrophages were less metabolically active than their colonic counterparts, with macrophage metabolism in the small intestine being independent of the microbiota. Finally, we reveal tissue-resident Tim4+ CD4+ macrophages exhibit enhanced fatty acid uptake alongside reduced fatty acid synthesis compared to recruited macrophages. Thus, the microbiota shapes gut macrophage metabolism in a compartment-specific manner, with important implications for monocyte recruitment and macrophage differentiation

Antibiotics induce sustained dysregulation of intestinal T cell immunity by perturbing macrophage homeostasis

Macrophages in the healthy intestine are highly specialized and usually respond to the gut microbiota without provoking an inflammatory response. A breakdown in this tolerance leads to inflammatory bowel disease (IBD), but the mechanisms by which intestinal macrophages normally become conditioned to promote microbial tolerance are unclear. Strong epidemiological evidence linking disruption of the gut microbiota by antibiotic use early in life to IBD indicates an important role for the gut microbiota in modulating intestinal immunity. Here, we show that antibiotic use causes intestinal macrophages to become hyperresponsive to bacterial stimulation, producing excess inflammatory cytokines. Re-exposure of antibiotic-treated mice to conventional microbiota induced a long-term, macrophage-dependent increase in inflammatory T helper 1 (T 1) responses in the colon and sustained dysbiosis. The consequences of this dysregulated macrophage activity for T cell function were demonstrated by increased susceptibility to infections requiring T 17 and T 2 responses for clearance (bacterial and helminth infections), corresponding with increased inflammation. Short-chain fatty acids (SCFAs) were depleted during antibiotic administration; supplementation of antibiotics with the SCFA butyrate restored the characteristic hyporesponsiveness of intestinal macrophages and prevented T cell dysfunction. Butyrate altered the metabolic behavior of macrophages to increase oxidative phosphorylation and also promoted alternative macrophage activation. In summary, the gut microbiota is essential to maintain macrophage-dependent intestinal immune homeostasis, mediated by SCFA-dependent pathways. Oral antibiotics disrupt this process to promote sustained T cell-mediated dysfunction and increased susceptibility to infections, highlighting important implications of repeated broad-spectrum antibiotic use

Environment and Obesity in the National Children’s Study

Objective: In this review we describe the approach taken by the National Children’s Study (NCS), a 21-year prospective study of 100,000 American children, to understanding the role of environmental factors in the development of obesity. Data sources and extraction: We review the literature with regard to the two core hypotheses in the NCS that relate to environmental origins of obesity and describe strategies that will be used to test each hypothesis. Data synthesis: Although it is clear that obesity in an individual results from an imbalance between energy intake and expenditure, control of the obesity epidemic will require understanding of factors in the modern built environment and chemical exposures that may have the capacity to disrupt the link between energy intake and expenditure. The NCS is the largest prospective birth cohort study ever undertaken in the United States that is explicitly designed to seek information on the environmental causes of pediatric disease. Conclusions: Through its embrace of the life-course approach to epidemiology, the NCS will be able to study the origins of obesity from preconception through late adolescence, including factors ranging from genetic inheritance to individual behaviors to the social, built, and natural environment and chemical exposures. It will have sufficient statistical power to examine interactions among these multiple influences, including gene–environment and gene–obesity interactions. A major secondary benefit will derive from the banking of specimens for future analysis

HIV-1 Nef Targets MHC-I and CD4 for Degradation Via a Final Common β-COP–Dependent Pathway in T Cells

To facilitate viral infection and spread, HIV-1 Nef disrupts the surface expression of the viral receptor (CD4) and molecules capable of presenting HIV antigens to the immune system (MHC-I). To accomplish this, Nef binds to the cytoplasmic tails of both molecules and then, by mechanisms that are not well understood, disrupts the trafficking of each molecule in different ways. Specifically, Nef promotes CD4 internalization after it has been transported to the cell surface, whereas Nef uses the clathrin adaptor, AP-1, to disrupt normal transport of MHC-I from the TGN to the cell surface. Despite these differences in initial intracellular trafficking, we demonstrate that MHC-I and CD4 are ultimately found in the same Rab7+ vesicles and are both targeted for degradation via the activity of the Nef-interacting protein, β-COP. Moreover, we demonstrate that Nef contains two separable β-COP binding sites. One site, an arginine (RXR) motif in the N-terminal α helical domain of Nef, is necessary for maximal MHC-I degradation. The second site, composed of a di-acidic motif located in the C-terminal loop domain of Nef, is needed for efficient CD4 degradation. The requirement for redundant motifs with distinct roles supports a model in which Nef exists in multiple conformational states that allow access to different motifs, depending upon which cellular target is bound by Nef

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

The Global Burden of Diseases, Injuries and Risk Factors 2017 includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. METHODS: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting

Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2)

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017

Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning