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Träfflista för sökning "WFRF:(Rathmann Wolfgang) srt2:(2015-2018)"

Sökning: WFRF:(Rathmann Wolfgang) > (2015-2018)

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1.
  • Danaei, Goodarz, et al. (författare)
  • Effects of diabetes definition on global surveillance of diabetes prevalence and diagnosis: a pooled analysis of 96 population-based studies with 331288 participants
  • 2015
  • Ingår i: The Lancet Diabetes & Endocrinology. - : Elsevier. - 2213-8595 .- 2213-8587. ; 3:8, s. 624-637
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Diabetes has been defined on the basis of different biomarkers, including fasting plasma glucose (FPG), 2-h plasma glucose in an oral glucose tolerance test (2hOGTT), and HbA(1c). We assessed the effect of different diagnostic definitions on both the population prevalence of diabetes and the classification of previously undiagnosed individuals as having diabetes versus not having diabetes in a pooled analysis of data from population-based health examination surveys in different regions. Methods We used data from 96 population-based health examination surveys that had measured at least two of the biomarkers used for defining diabetes. Diabetes was defined using HbA(1c) (HbA(1c) >= 6 . 5% or history of diabetes diagnosis or using insulin or oral hypoglycaemic drugs) compared with either FPG only or FPG-or-2hOGTT definitions (FPG >= 7 . 0 mmol/L or 2hOGTT >= 11 . 1 mmol/L or history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated diabetes prevalence, taking into account complex survey design and survey sample weights. We compared the prevalences of diabetes using different definitions graphically and by regression analyses. We calculated sensitivity and specificity of diabetes diagnosis based on HbA1c compared with diagnosis based on glucose among previously undiagnosed individuals (ie, excluding those with history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated sensitivity and specificity in each survey, and then pooled results using a random-effects model. We assessed the sources of heterogeneity of sensitivity by meta-regressions for study characteristics selected a priori. Findings Population prevalence of diabetes based on FPG- or-2hOGTT was correlated with prevalence based on FPG alone (r= 0 . 98), but was higher by 2-6 percentage points at different prevalence levels. Prevalence based on HbA(1c) was lower than prevalence based on FPG in 42 . 8% of age-sex-survey groups and higher in another 41 . 6%; in the other 15 . 6%, the two definitions provided similar prevalence estimates. The variation across studies in the relation between glucose-based and HbA(1c)-based prevalences was partly related to participants' age, followed by natural logarithm of per person gross domestic product, the year of survey, mean BMI, and whether the survey population was national, subnational, or from specific communities. Diabetes defined as HbA(1c) 6 . 5% or more had a pooled sensitivity of 52 . 8% (95% CI 51 . 3-54 . 3%) and a pooled specificity of 99 . 74% (99 . 71-99 . 78%) compared with FPG 7 . 0 mmol/L or more for diagnosing previously undiagnosed participants; sensitivity compared with diabetes defined based on FPG-or-2hOGTT was 30 . 5% (28 . 7-32 . 3%). None of the preselected study-level characteristics explained the heterogeneity in the sensitivity of HbA(1c) versus FPG. Interpretation Different biomarkers and definitions for diabetes can provide different estimates of population prevalence of diabetes, and differentially identify people without previous diagnosis as having diabetes. Using an HbA(1c)-based definition alone in health surveys will not identify a substantial proportion of previously undiagnosed people who would be considered as having diabetes using a glucose-based test.
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3.
  • de las Heras Gala, Tonia, et al. (författare)
  • Association of changes in inflammation with variation in glycaemia, insulin resistance and secretion based on the KORA study
  • 2018
  • Ingår i: Diabetes/Metabolism Research and Reviews. - : John Wiley and Sons. - 1520-7552. ; 34:8
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims: Subclinical systemic inflammation may contribute to the development of type 2 diabetes, but its association with early progression of glycaemic deterioration in persons without diabetes has not been fully investigated. Our primary aim was to assess longitudinal associations of changes in pro-inflammatory (leukocytes, high-sensitivity C-reactive protein (hsCRP)) and anti-inflammatory (adiponectin) markers with changes in markers that assessed glycaemia, insulin resistance, and secretion (HbA1c, HOMA-IR, and HOMA-ß). Furthermore, we aimed to directly compare longitudinal with cross-sectional associations. Materials and methods: This study includes 819 initially nondiabetic individuals with repeated measurements from the Cooperative Health Research in the Region of Augsburg (KORA) S4/F4 cohort study (median follow-up: 7.1 years). Longitudinal and cross-sectional associations were simultaneously examined using linear mixed growth models. Changes in markers of inflammation were used as independent and changes in markers of glycaemia/insulin resistance/insulin secretion as dependent variables. Models were adjusted for age, sex, major lifestyle and metabolic risk factors for diabetes using time-varying variables in the final model. Results: Changes of leukocyte count were positively associated with changes in HbA1c and HOMA-ß while changes in adiponectin were inversely associated with changes in HbA1c. All examined cross-sectional associations were statistically significant; they were generally stronger and mostly directionally consistent to the longitudinal association estimates. Conclusions: Adverse changes in low-grade systemic inflammation go along with glycaemic deterioration and increased insulin secretion independently of changes in other risk factors, suggesting that low-grade inflammation may contribute to the development of hyperglycaemia and a compensatory increase in insulin secretion.
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4.
  • Fuchsberger, Christian, et al. (författare)
  • The genetic architecture of type 2 diabetes
  • 2016
  • Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 536:7614, s. 41-47
  • Tidskriftsartikel (refereegranskat)abstract
    • The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
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5.
  • Kilpeläinen, Tuomas O, et al. (författare)
  • Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.
  • 2016
  • Ingår i: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 7
  • Tidskriftsartikel (refereegranskat)abstract
    • Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.
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6.
  • Klueppelholz, Birgit, et al. (författare)
  • Association of subclinical inflammation with deterioration of glycaemia before the diagnosis of type 2 diabetes: the KORA S4/F4 study
  • 2015
  • Ingår i: Diabetologia. - : Springer. - 1432-0428 .- 0012-186X. ; 58:10, s. 2269-2277
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims/hypothesis The role of biomarkers of subclinical inflammation in the early deterioration of glycaemia before type 2 diabetes is largely unknown. We hypothesised that increased levels of circulating proinflammatory biomarkers and decreased circulating adiponectin would be associated with 7 year increases of HbA(1c) in non-diabetic individuals. Methods This study was based on individuals who participated in the prospective Cooperative Health Research in the Region of Augsburg (KORA) S4 survey (1999-2001) and the 7 year follow-up KORA F4 (2006-2008) survey. Individuals with type 2 diabetes at baseline or with a diagnosis of diabetes in the period between both surveys were excluded, which left a sample of 850 men and women. Multivariable linear regression analyses were performed to assess associations among baseline values of leucocyte count and levels of acute-phase proteins (high-sensitivity C-reactive protein [hsCRP], serum amyloid A [SAA] and fibrinogen), IL-6 and adiponectin with changes in HbA(1c) between baseline and follow-up. Results A high leucocyte count and high hsCRP, SAA and IL-6 levels were positively associated with changes in HbA(1c) after adjusting for age, sex, lifestyle factors and baseline HbA(1c). In contrast, the adiponectin level was inversely associated with changes in HbA(1c) (p value between < 0.0001 and 0.020). The associations of leucocyte count and levels of hsCRP and SAA with HbA(1c) changes remained significant after additional adjustment for waist circumference and circulating lipids at baseline and for the 7 year change in waist circumference (p value between 0.004 and 0.045). Conclusions/interpretation An elevated leucocyte count and elevated hsCRP and SAA were associated with early deterioration of glycaemia before the diagnosis of type 2 diabetes. These associations were largely independent of baseline abdominal adiposity and increases in waist circumference.
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7.
  • Wheeler, Eleanor, et al. (författare)
  • Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations : A transethnic genome-wide meta-analysis
  • 2017
  • Ingår i: PLoS Medicine. - : PUBLIC LIBRARY SCIENCE. - 1549-1277 .- 1549-1676. ; 14:9
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.Methods & findings: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 x 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI0.55-0.74) of African American adults with T2Dto remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.Conclusions: As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.
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8.
  • Flannick, Jason, et al. (författare)
  • Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
  • 2017
  • Ingår i: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 4
  • Tidskriftsartikel (refereegranskat)abstract
    • To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to ~82 K Europeans via the exome chip, and similar to ~90% of low-frequency non-coding variants in similar to ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
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9.
  • Flannick, Jason, et al. (författare)
  • Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
  • 2017
  • Ingår i: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 4
  • Tidskriftsartikel (refereegranskat)abstract
    • To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to 82 K Europeans via the exome chip, and similar to 90% of low-frequency non-coding variants in similar to 44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
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10.
  • Mahajan, Anubha, et al. (författare)
  • Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes
  • 2018
  • Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:4, s. 559-571
  • Tidskriftsartikel (refereegranskat)abstract
    • We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10−7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent ‘false leads’ with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
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