58 research outputs found

    Genome-wide imputation identifies novel associations and localises signals in idiopathic inflammatory myopathies.

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    OBJECTIVES The idiopathic inflammatory myopathies (IIM) are heterogeneous diseases, thought to be initiated by immune activation in genetically predisposed individuals. In this study we imputed variants from the Immunochip array using a large reference panel to fine-map associations and identify novel associations in IIM. METHODS We analysed 2,565 Caucasian IIM samples collected through the Myositis Genetics Consortium (MYOGEN) and 10,260 ethnically-matched controls. We imputed 1,648,116 variants from the Immunochip array using the Haplotype Reference Consortium panel and conducted association analysis on IIM, and clinical and serological subgroups. RESULTS The human leukocyte antigen (HLA) locus was consistently the most significantly associated region. Four non-HLA regions reached genome-wide significance, three in the whole IIM cohort (SDK2 and LINC00924 - both novel, and STAT4), with evidence of independent variants in STAT4, and NAB1 in the polymyositis (PM) subgroup. We also found suggestive evidence of association with loci previously associated with other autoimmune rheumatic diseases (TEC and LTBR). We identified more significant associations than those previously reported in IIM, for STAT4 and DGKQ in the total cohort, for NAB1 and FAM167A-BLK loci in PM, and CCR5 in inclusion body myositis. We found enrichment of variants among DNase I hypersensitivity sites and histone marks associated with active transcription within blood cells. CONCLUSIONS We report novel and strong associations in IIM and PM, and localise signals to single genes and immune cell types. This article is protected by copyright. All rights reserved

    Identification of Novel Associations and Localization of Signals in Idiopathic Inflammatory Myopathies Using Genome-Wide Imputation

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    OBJECTIVES: The idiopathic inflammatory myopathies (IIM) are heterogeneous diseases, thought to be initiated by immune activation in genetically predisposed individuals. In this study we imputed variants from the Immunochip array using a large reference panel to fine-map associations and identify novel associations in IIM. METHODS: We analysed 2,565 Caucasian IIM samples collected through the Myositis Genetics Consortium (MYOGEN) and 10,260 ethnically-matched controls. We imputed 1,648,116 variants from the Immunochip array using the Haplotype Reference Consortium panel and conducted association analysis on IIM, and clinical and serological subgroups. RESULTS: The human leukocyte antigen (HLA) locus was consistently the most significantly associated region. Four non-HLA regions reached genome-wide significance, three in the whole IIM cohort (SDK2 and LINC00924 - both novel, and STAT4), with evidence of independent variants in STAT4, and NAB1 in the polymyositis (PM) subgroup. We also found suggestive evidence of association with loci previously associated with other autoimmune rheumatic diseases (TEC and LTBR). We identified more significant associations than those previously reported in IIM, for STAT4 and DGKQ in the total cohort, for NAB1 and FAM167A-BLK loci in PM, and CCR5 in inclusion body myositis. We found enrichment of variants among DNase I hypersensitivity sites and histone marks associated with active transcription within blood cells. CONCLUSIONS: We report novel and strong associations in IIM and PM, and localise signals to single genes and immune cell types

    Focused HLA analysis in Caucasians with myositis identifies significant associations with autoantibody subgroups

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    Objectives: Idiopathic inflammatory myopathies (IIM) are a spectrum of rare autoimmune diseases characterised clinically by muscle weakness and heterogeneous systemic organ involvement. The strongest genetic risk is within the major histocompatibility complex (MHC). Since autoantibody presence defines specific clinical subgroups of IIM, we aimed to correlate serotype and genotype, to identify novel risk variants in the MHC region that co-occur with IIM autoantibodies. Methods: We collected available autoantibody data in our cohort of 2582 Caucasian patients with IIM. High resolution human leucocyte antigen (HLA) alleles and corresponding amino acid sequences were imputed using SNP2HLA from existing genotyping data and tested for association with 12 autoantibody subgroups. Results: We report associations with eight autoantibodies reaching our study-wide significance level of p<2.9x10(-5). Associations with the 8.1 ancestral haplotype were found with anti-Jo-1 (HLA-B*08:01, p=2.28x10(-53) and HLA-DRB1*03:01, p=3.25x10(-9)), anti-PM/Scl (HLA-DQB1*02:01, p=1.47x10(-26)) and anti-cN1A autoantibodies (HLA-DRB1*03:01, p=1.40x10(-11)). Associations independent of this haplotype were found with anti-Mi-2 (HLA-DRB1*07:01, p=4.92x10(-13)) and anti-HMGCR autoantibodies (HLA-DRB1*11, p=5.09x10(-6)). Amino acid positions may be more strongly associated than classical HLA associations; for example with anti-Jo-1 autoantibodies and position 74 of HLA-DRB1 (p=3.47x10(-64)) and position 9 of HLA-B (p=7.03x10(-11)). We report novel genetic associations with HLA-DQB1 anti-TIF1 autoantibodies and identify haplotypes that may differ between adult-onset and juvenile-onset patients with these autoantibodies. Conclusions: These findings provide new insights regarding the functional consequences of genetic polymorphisms within the MHC. As autoantibodies in IIM correlate with specific clinical features of disease, understanding genetic risk underlying development of autoantibody profiles has implications for future research

    Multilocus genotyping reveals high heterogeneity and strong local population structure of the Plasmodium vivax population in the Peruvian Amazon

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    <p>Abstract</p> <p>Background</p> <p>Peru is one of the Latin American countries with the highest malaria burden, mainly due to <it>Plasmodium vivax </it>infections. However, little is known about <it>P. vivax </it>transmission dynamics in the Peruvian Amazon, where most malaria cases occur. The genetic diversity and population structure of <it>P. vivax </it>isolates collected in different communities around Iquitos city, the capital of the Peruvian Amazon, was determined.</p> <p>Methods</p> <p><it>Plasmodium vivax </it>population structure was determined by multilocus genotyping with 16 microsatellites on 159 <it>P. vivax </it>infected blood samples (mono-infections) collected in four sites around Iquitos city. The population characteristics were assessed only in samples with monoclonal infections (n = 94), and the genetic diversity was determined by calculating the expected heterozygosity and allelic richness. Both linkage disequilibrium and the genetic differentiation (<it>θ</it>) were estimated.</p> <p>Results</p> <p>The proportion of polyclonal infections varied substantially by site (11% - 70%), with the expected heterozygosity ranging between 0.44 and 0.69; no haplotypes were shared between the different populations. Linkage disequilibrium was present in all populations (<it>I</it><sub>A</sub><sup>S </sup>0.14 - 0.61) but was higher in those with fewer polyclonal infections, suggesting inbreeding and a clonal population structure. Strong population differentiation (<it>θ </it>= 0.45) was found and the Bayesian inference cluster analysis identified six clusters based on distinctive allele frequencies.</p> <p>Conclusion</p> <p>The <it>P. vivax </it>populations circulating in the Peruvian Amazon basin are genetically diverse, strongly differentiated and they have a low effective recombination rate. These results are in line with the low and clustered pattern of malaria transmission observed in the region around Iquitos city.</p

    Cross-cutting principles for planetary health education

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    Since the 2015 launch of the Rockefeller Foundation Lancet Commission on planetary health,1 an enormous groundswell of interest in planetary health education has emerged across many disciplines, institutions, and geographical regions. Advancing these global efforts in planetary health education will equip the next generation of scholars to address crucial questions in this emerging field and support the development of a community of practice. To provide a foundation for the growing interest and efforts in this field, the Planetary Health Alliance has facilitated the first attempt to create a set of principles for planetary health education that intersect education at all levels, across all scales, and in all regions of the world—ie, a set of cross-cutting principles

    Repositioning of the global epicentre of non-optimal cholesterol

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    High blood cholesterol is typically considered a feature of wealthy western countries(1,2). However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world(3) and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health(4,5). However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.Peer reviewe

    Rising rural body-mass index is the main driver of the global obesity epidemic in adults

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    Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

    Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

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    Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

    Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants

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    © The Author(s) 2018. Background: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure. Methods: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20-29 years to 70-79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probittransformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure. Results: In 2005-16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the highincome Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association. Conclusions: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups
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