8 research outputs found
Repositioning of the global epicentre of non-optimal cholesterol
High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 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 health4,5. 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 risk—changed 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.</p
Supplementary Material for: Trends in Costs of Thyroid Disease Treatment in Denmark during 1995–2015
<b><i>Background:</i></b> Iodine fortification (IF) may contribute to changes in costs of thyroid disease treatment through changes in disease patterns. From a health economic perspective, assessment of the development in costs of thyroid disease treatment in the population is pertinent. <b><i>Objectives:</i></b> To assess the trends in annual medicine and hospital costs of thyroid disease treatment during 1995–2015 in Denmark, i.e., before and after the introduction of mandatory IF in 2000. <b><i>Methods:</i></b> Information on treatments for thyroid disease (antithyroid medication, thyroid hormone therapy, thyroid surgery, and radioiodine treatment) was obtained from nationwide registers. Costs were valued at 2015 prices using sales prices for medicines and the Danish Diagnosis-Related Group (DRG) and Danish Ambulatory Grouping System (DAGS) tariffs of surgeries/radioiodine treatments. Results were adjusted for changes in population size and age and sex distribution. <b><i>Results:</i></b> The total direct medicine and hospital costs of thyroid disease treatment increased from EUR ∼190,000 per 100,000 persons in 1995 to EUR ∼270,000 per 100,000 persons in 2015. This was mainly due to linearly increased costs of thyroid hormone therapy and increased costs of thyroid surgery since 2008. Costs of antithyroid medication increased slightly and transiently after IF, while costs of radioiodine treatment remained constant. Costs of thyroid hormone therapy and thyroid surgery did not follow the development in the prevalence of hypothyroidism and structural thyroid diseases observed in concurrent studies. <b><i>Conclusion:</i></b> The costs of total direct medicine and hospital costs for thyroid disease treatment in Denmark increased from 1995 to 2015. This is possibly due to several factors, e.g., changes in treatment practices, and the direct effect of IF alone remains to be estimated
Uncarboxylated matrix Gla-protein: A biomarker of vitamin K status and cardiovascular risk
Association of alcohol consumption with allergic disease and asthma: A multi-centre Mendelian randomization analysis.
Aims To use the rs1229984 variant associated with alcohol consumption as an instrument for alcohol consumption to test the causality of the association of alcohol consumption with hay fever, asthma, allergic sensitization and serum total immunoglobulin (Ig) E. Design Observational and Mendelian randomization analyses using genetic variants as unbiased markers of exposure to estimate causal effects, subject to certain assumptions. Setting Europe. Participants We included a total of 466 434 people aged 15-82 years from 17 population-based studies conducted from 1997 to 2015. Measurements The rs1229984 (ADH1B) was genotyped; alcohol consumption, hay fever and asthma were selfreported. Specific and total IgE were measured from serum samples. Findings Observational analyses showed that ever-drinking versus non-drinking, but not amount of alcohol intake, was positively associatedwith hay fever and inversely associated with asthma but not with allergic sensitization or serum total immunoglobulin (Ig) E. However, Mendelian randomization analyses did not suggest that the observational associations are causal. The causal odds ratio (OR) per genetically assessed unit of alcohol/week was an OR = 0.907 [ 95% confidence interval (CI) = 0.806, 1.019; P = 0.101] for hay fever, an OR = 0.897 (95% CI = 0.790, 1.019; P = 0.095) for asthma, an OR = 0.971 (95% CI = 0.804, 1.174; P = 0.763) for allergic sensitization and a 4.7% change (95% CI = -5.5%, 14.9%; P = 0.366) for total IgE. Conclusions In observational analyses, ever-drinking versus not drinking was positively associated with hay fever and negatively associated with asthma. However, the Mendelian randomization results were not consistent with these associations being causal
Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk
A saturated map of common genetic variants associated with human height
Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries
Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight
From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions. © Copyright
A saturated map of common genetic variants associated with human height.
Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes <sup>1</sup> . Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel <sup>2</sup> ) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries