Utilization of statins and aspirin among patients with diabetes and hyperlipidemia: Taiwan, 1998–2006

AbstractBackgroundThe proper use of statins and aspirin decrease the risk of coronary heart disease (CHD) among patients with diabetes (DM) and hyperlipidemia. The purpose of this study was to analyze the time trends and determinants of prescribing statins and aspirin among patients with DM and hyperlipidemia in medical practice in Taiwan.MethodsA cohort of 21,667 patients with DM and hyperlipidemia during the period from 1998 to 2006 was identified by using data of ambulatory care claims from Taiwan's National Health Insurance Database. The dataset was categorized into two equal calendar periods: Period 1 (September 1998–June 2002) and Period 2 (July 2002–April 2006). Multivariate logistic regression analyses were used to determine the independent determinants associated with receipt of lipid-lowering agents and aspirin among these patients.ResultsThere were significant increases in the prescribing of statins (OR 1.78; 95% CI 1.66−1.91) and aspirin (OR 1.47, 95% CI 1.50−1.59) in Period 2 as compared with Period 1. Nevertheless, 30% of patients with coexisting CHD neither received statins nor aspirin. Only 15% to 25% of DM patients with hyperlipidemia and CHD received the combined treatment with aspirin and statin. In multivariate logistic regression, we found that women received aspirin less frequently than men. Old patients (>45 years) with concomitant CHD were more likely to receive statins and aspirin.ConclusionDespite the increasing trend in the use of statins and aspirin in DM patients with hyperlipidemia in Taiwan, the improvements were at best modest, particularly for secondary prevention. Our data indicate the need for continued efforts to improve the utilization of these drugs in daily practice

Urinary acrolein protein conjugates-tocreatinine ratio is positively associated with diabetic peripheral neuropathy in patients with type 2 diabetes mellitus

Acrolein, an unsaturated aldehyde, plays a pathological role in neurodegenerative diseases. However, less is known about its effects on peripheral neuropathy. The aim of this study was to investigate the association of acrolein and diabetic peripheral neuropathy in patients with type 2 diabetes. We recruited 148 ambulatory patients with type 2 diabetes. Each participant underwent an assessment of the Michigan Neuropathy Screening Instrument Physical Examination. Diabetic peripheral neuropathy was defined as Michigan Neuropathy Screening Instrument Physical Examination score ≥ 2.5. Serum levels and urinary levels of acrolein protein conjugates were measured. Urinary acrolein protein conjugates-to-creatinine ratios were determined. Patients with diabetic peripheral neuropathy had significantly higher urinary acrolein protein conjugates-to-creatinine ratios than those without diabetic peripheral neuropathy (7.91, 95% CI: 5.96–10.50 vs 5.31, 95% CI: 4.21–6.68, P = 0.029). Logarithmic transformation of urinary acrolein protein conjugates-to-creatinine ratios was positively associated with diabetic peripheral neuropathy in univariate logistic analysis, and the association remained significant in multivariate analysis (OR = 2.45, 95% CI: 1.12–5.34, P = 0.025). In conclusion, urinary acrolein protein conjugates-to-creatinine ratio may act as a new biomarker for diabetic peripheral neuropathy in type 2 diabetes. The involvement of acrolein in the pathogenesis of diabetic peripheral neuropathy warrants further investigation

Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci

Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies

A meta-analysis of genome-wide association studies for adiponectin levels in East Asians identifies a novel locus near WDR11-FGFR2

Blood levels of adiponectin, an adipocyte-secreted protein correlated with metabolic and cardiovascular risks, are highly heritable. Genome-wide association (GWA) studies for adiponectin levels have identified 14 loci harboring variants associated with blood levels of adiponectin. To identify novel adiponectin-associated loci, particularly those of importance in East Asians, we conducted a meta-analysis of GWA studies for adiponectin in 7827 individuals, followed by two stages of replications in 4298 and 5954 additional individuals. We identified a novel adiponectin-associated locus on chromosome 10 near WDR11-FGFR2 (P = 3.0 × 10−14) and provided suggestive evidence for a locus on chromosome 12 near OR8S1-LALBA (P = 1.2 × 10−7). Of the adiponectin-associated loci previously described, we confirmed the association at CDH13 (P = 6.8 × 10−165), ADIPOQ (P = 1.8 × 10−22), PEPD (P = 3.6 × 10−12), CMIP (P = 2.1 × 10−10), ZNF664 (P = 2.3 × 10−7) and GPR109A (P = 7.4 × 10−6). Conditional analysis at ADIPOQ revealed a second signal with suggestive evidence of association only after conditioning on the lead SNP (Pinitial = 0.020; Pconditional = 7.0 × 10−7). We further confirmed the independence of two pairs of closely located loci (<2 Mb) on chromosome 16 at CMIP and CDH13, and on chromosome 12 at GPR109A and ZNF664. In addition, the newly identified signal near WDR11-FGFR2 exhibited evidence of association with triglycerides (P = 3.3 × 10−4), high density lipoprotein cholesterol (HDL-C, P = 4.9 × 10−4) and body mass index (BMI)-adjusted waist–hip ratio (P = 9.8 × 10−3). These findings improve our knowledge of the genetic basis of adiponectin variation, demonstrate the shared allelic architecture for adiponectin with lipids and central obesity and motivate further studies of underlying mechanisms

Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets

Genome-Wide Association Study and Functional Characterization Identifies Candidate Genes for Insulin-Stimulated Glucose Uptake

Distinct tissue-specific mechanisms mediate insulin action in fasting and postprandial states. Previous genetic studies have largely focused on insulin resistance in the fasting state, where hepatic insulin action dominates. Here we studied genetic variants influencing insulin levels measured 2 h after a glucose challenge in \u3e55,000 participants from three ancestry groups. We identified ten new loci (P \u3c 5 × 10-8) not previously associated with postchallenge insulin resistance, eight of which were shown to share their genetic architecture with type 2 diabetes in colocalization analyses. We investigated candidate genes at a subset of associated loci in cultured cells and identified nine candidate genes newly implicated in the expression or trafficking of GLUT4, the key glucose transporter in postprandial glucose uptake in muscle and fat. By focusing on postprandial insulin resistance, we highlighted the mechanisms of action at type 2 diabetes loci that are not adequately captured by studies of fasting glycemic traits

Genetic diversity fuels gene discovery for tobacco and alcohol use

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury(1-4). These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries(5). Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.Peer reviewe

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p