| 1. |
- de las Heras Gala, Tonia, et al.
(författare)
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Association of changes in inflammation with variation in glycaemia, insulin resistance and secretion based on the KORA study
- 2018
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Ingår i: Diabetes/Metabolism Research and Reviews. - : Wiley. - 1520-7552. ; 34:8
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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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| 2. |
- Klüppelholz, Birgit, et al.
(författare)
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Association of subclinical inflammation with deterioration of glycaemia before the diagnosis of type 2 diabetes : the KORA S4/F4 study
- 2015
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 58:10, s. 2269-2277
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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 HbA1c 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 HbA1c between baseline and follow-up.Results A high leucocyte count and high hsCRP, SAA and IL-6 levels were positively associated with changes in HbA1c after adjusting for age, sex, lifestyle factors and baseline HbA1c. In contrast, the adiponectin level was inversely associated with changes in HbA1c (p value between <0.0001 and 0.020). The associations of leucocyte count and levels of hsCRP and SAA with HbA1c 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).
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| 3. |
- Flannick, Jason, et al.
(författare)
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Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
- 2017
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 4
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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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| 4. |
- Fuchsberger, Christian, et al.
(författare)
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The genetic architecture of type 2 diabetes
- 2016
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 536:7614, s. 41-47
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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. |
- Mahajan, Anubha, et al.
(författare)
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Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes
- 2018
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:4, s. 559-571
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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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| 6. |
- Rauh, Simone P, et al.
(författare)
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Predicting glycated hemoglobin levels in the non-diabetic general population : development and validation of the DIRECT-DETECT prediction model - a DIRECT study
- 2017
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:2
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Tidskriftsartikel (refereegranskat)abstract
- AIMS/HYPOTHESIS: To develop a prediction model that can predict HbA1c levels after six years in the non-diabetic general population, including previously used readily available predictors.METHODS: Data from 5,762 initially non-diabetic subjects from three population-based cohorts (Hoorn Study, Inter99, KORA S4/F4) were combined to predict HbA1c levels at six year follow-up. Using backward selection, age, BMI, waist circumference, use of anti-hypertensive medication, current smoking and parental history of diabetes remained in sex-specific linear regression models. To minimize overfitting of coefficients, we performed internal validation using bootstrapping techniques. Explained variance, discrimination and calibration were assessed using R2, classification tables (comparing highest/lowest 50% HbA1c levels) and calibration graphs. The model was externally validated in 2,765 non-diabetic subjects of the population-based cohort METSIM.RESULTS: At baseline, mean HbA1c level was 5.6% (38 mmol/mol). After a mean follow-up of six years, mean HbA1c level was 5.7% (39 mmol/mol). Calibration graphs showed that predicted HbA1c levels were somewhat underestimated in the Inter99 cohort and overestimated in the Hoorn and KORA cohorts, indicating that the model's intercept should be adjusted for each cohort to improve predictions. Sensitivity and specificity (95% CI) were 55.7% (53.9, 57.5) and 56.9% (55.1, 58.7) respectively, for women, and 54.6% (52.7, 56.5) and 54.3% (52.4, 56.2) for men. External validation showed similar performance in the METSIM cohort.CONCLUSIONS/INTERPRETATION: In the non-diabetic population, our DIRECT-DETECT prediction model, including readily available predictors, has a relatively low explained variance and moderate discriminative performance, but can help to distinguish between future highest and lowest HbA1c levels. Absolute HbA1c values are cohort-dependent.
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| 7. |
- Wahl, Simone, et al.
(författare)
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Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity
- 2017
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Ingår i: Nature. - : NATURE PUBLISHING GROUP. - 0028-0836 .- 1476-4687. ; 541:7635, s. 81-
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Tidskriftsartikel (refereegranskat)abstract
- Approximately 1.5 billion people worldwide are overweight or affected by obesity, and are at risk of developing type (2) diabetes, cardiovascular disease and related metabolic and inflammatory disturbances(1,2). Although the mechanisms linking adiposity to associated clinical conditions are poorly understood, recent studies suggest that adiposity may influence DNA methylation(3-6), a key regulator of gene expression and molecular phenotype(7). Here we use epigenome-wide association to show that body mass index (BMI; a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci with P < 1 x 10(-7), range P = 9.2 x 10(-8) to 6.0 x 10(-46); n = 10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find that methylation loci are enriched for functional genomic features in multiple tissues (P < 0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci (P < 9.0 x 10(-6), range P = 5.5 x 10(-6) to 6.1 x 10(-35), n = 1,785 samples). The methylation loci identify genes involved in lipid and lipoprotein metabolism, substrate transport and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future development of type 2 diabetes (relative risk per 1 standard deviation increase in methylation risk score: 2.3 (2.07-2.56); P = 1.1 x 10(-54)). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type 2 diabetes and other adverse clinical consequences of obesity.
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