We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent)... Show moreWe assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 x 10(-9)), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations. Show less
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... Show moreCommon 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 sizes1. 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 panel2) 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. Show less
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here... Show moreGlycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets. Show less
Isolated systolic hypertension (ISH) is the most common form of hypertension and is highly prevalent in older people. We recently showed differences between upper-arm cuff and invasive blood... Show moreIsolated systolic hypertension (ISH) is the most common form of hypertension and is highly prevalent in older people. We recently showed differences between upper-arm cuff and invasive blood pressure (BP) become greater with increasing age, which could influence correct identification of ISH. This study sought to determine the difference between identification of ISH by cuff BP compared with invasive BP. Cuff BP and invasive aortic BP were measured in 1695 subjects (median 64 years, interquartile range [55-72], 68% male) from the INSPECT (Invasive Blood Pressure Consortium) database. Data were recorded during coronary angiography among 29 studies, using 21 different cuff BP devices. ISH was defined as >= 130/<80 mm Hg using cuff BP compared with invasive aortic BP as the reference. The prevalence of ISH was 24% (n=407) according to cuff BP but 38% (n=642) according to invasive aortic BP. There was fair agreement (Cohen kappa, 0.36) and 72% concordance between cuff and invasive aortic BP for identifying ISH. Among the 28% of subjects (n=471) with misclassification of ISH status by cuff BP, 20% (n=96) of the difference was due to lower cuff systolic BP compared with invasive aortic systolic BP (mean, -16.4 mm Hg [95% CI, -18.7 to -14.1]), whereas 49% (n=231) was from higher cuff diastolic BP compared with invasive aortic diastolic BP (+14.2 mm Hg [95% CI, 11.5-16.9]). In conclusion, compared with invasive BP, cuff BP fails to identify ISH in a sizeable portion of older people and demonstrates the need to improve cuff BP measurements. Show less
Blood pressure (BP) is a leading global risk factor. Increasing age is related to changes in cardiovascular physiology that could influence cuff BP measurement, but this has never been examined... Show moreBlood pressure (BP) is a leading global risk factor. Increasing age is related to changes in cardiovascular physiology that could influence cuff BP measurement, but this has never been examined systematically and was the aim of this study. Cuff BP was compared with invasive aortic BP across decades of age (from 40 to 89 years) using individual-level data from 31 studies (1674 patients undergoing coronary angiography) and 22 different cuff BP devices (19 oscillometric, 1 automated auscultation, 2 mercury sphygmomanometry) from the Invasive Blood Pressure Consortium. Subjects were aged 64 +/- 11 years, and 32% female. Cuff systolic BP overestimated invasive aortic systolic BP in those aged 40 to 49 years, but with each older decade of age, there was a progressive shift toward increasing underestimation of aortic systolic BP (P<0.0001). Conversely, cuff diastolic BP overestimated invasive aortic diastolic BP, and this progressively increased with increasing age (P<0.0001). Thus, there was a progressive increase in cuff pulse pressure underestimation of invasive aortic PP with increasing decades of age (P<0.0001). These age-related trends were observed across all categories of BP control. We conclude that cuff BP as an estimate of aortic BP was substantially influenced by increasing age, thus potentially exposing older people to greater chance for misdiagnosis of the true risk related to BP. Show less
Improvements in medical treatment have contributed to rising health spending. Yet there is relatively little evidence on whether the spending increase is "worth it" in the sense of producing better... Show moreImprovements in medical treatment have contributed to rising health spending. Yet there is relatively little evidence on whether the spending increase is "worth it" in the sense of producing better health outcomes of commensurate value-a critical question for understanding productivity in the health sector and, as that sector grows, for deriving an accurate quality-adjusted price index for an entire economy. We analyze individual-level panel data on medical spending and health outcomes for 123,548 patients with type 2 diabetes in four health systems: Japan, The Netherlands, Hong Kong and Taiwan. Using a "cost-of-living" method that measures value based on improved survival, we find a positive net value of diabetes care: the value of improved survival outweighs the added costs of care in each of the four health systems. This finding is robust to accounting for selective survival, end-of-life spending, and a range of values for a life-year or fraction of benefits attributable to medical care. Since the estimates do not include the value from improved quality of life, they are conservative. We, therefore, conclude that the increase in medical spending for management of diabetes is offset by an increase in quality. Show less
Purpose: Computed tomography angiography (CTA) is increasingly used for the diagnosis of coronary artery disease (CAD). However, CTA is not commonly used for the assessment of ventricular and... Show morePurpose: Computed tomography angiography (CTA) is increasingly used for the diagnosis of coronary artery disease (CAD). However, CTA is not commonly used for the assessment of ventricular and atrial function, although functional information extracted from CTA data is expected to improve the diagnostic value of the examination. In clinical practice, the extraction of ventricular and atrial functional information, such as stroke volume and ejection fraction, requires accurate delineation of cardiac chambers. In this paper, we investigated the accuracy and robustness of cardiac chamber delineation using a multiatlas based segmentation method on multicenter and multivendor CTA data. Methods: A fully automatic multiatlas based method for segmenting the whole heart (i.e., the outer surface of the pericardium) and cardiac chambers from CTA data is presented and evaluated. In the segmentation approach, eight atlas images are registered to a new patient's CTA scan. The eight corresponding manually labeled images are then propagated and combined using a per voxel majority voting procedure, to obtain a cardiac segmentation. Results: The method was evaluated on a multicenter/multivendor database, consisting of (1) a set of 1380 Siemens scans from 795 patients and (2) a set of 60 multivendor scans (Siemens, Philips, and GE) from different patients, acquired in six different institutions worldwide. A leave-one-out 3D quantitative validation was carried out on the eight atlas images; we obtained a mean surface-to-surface error of 0.94 +/- 1.12 mm and an average Dice coefficient of 0.93 was achieved. A 2D quantitative evaluation was performed on the 60 multivendor data sets. Here, we observed a mean surface-to-surface error of 1.26 +/- 1.25 mm and an average Dice coefficient of 0.91 was achieved. In addition to this quantitative evaluation, a large-scale 2D and 3D qualitative evaluation was performed on 1380 and 140 images, respectively. Experts evaluated that 49% of the 1380 images were very accurately segmented (below 1 mm error) and that 29% were accurately segmented (error between 1 and 3 mm), which demonstrates the robustness of the presented method. Conclusions: A fully automatic method for whole heart and cardiac chamber segmentation was presented and evaluated using multicenter/multivendor CTA data. The accuracy and robustness of the method were demonstrated by successfully applying the method to 1420 multicenter/multivendor data sets. (C) 2010 American Association of Physicists in Medicine. [DOI: 10.1118/1.3512795] Show less
