Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

22-year trends in dysglycemia and body mass index: A population-based cohort study in Savitaipale, Finland.

AIMS: We describe a 22-year prospective observational population-based study that determined the prevalence and incidence of type 2 diabetes (T2D) and intermediate hyperglycaemia (IH), obesity, hypertension, and disorders of lipid metabolism in a middle-age population in the Finnish municipality of Savitaipale. METHODS: 1151 people participated in the baseline survey in 1996-1999, following two follow-up examinations, in 2007-2008 and 2018-2019. Follow-up studies comprised clinical measurements, 2-h oral glucose tolerance test and other biochemistry, questionnaires, and registry data. RESULTS: The prevalence of T2D quadrupled to 27% and the proportion of normoglycemic people decreased from 73% to 44% while IH increased only slightly during the 22-year follow-up. A large proportion of people who died between the surveys were diabetic. The mean body mass index (BMI) did not, whereas mean waist circumference increased significantly, by 5-6 cm (P = 0.001) during the 22 years. Systolic blood pressure increased by 13-15 mmHg from baseline (P = 0.0001) but diastolic blood pressure did not. The mean plasma levels of total and LDL-cholesterol decreased 10.8% and 8.9% in women (P = 0.001), 21.5% and 22.2% in men (P = 0.001), respectively, while HDL-cholesterol and triglycerides remained stable. The proportion of those achieving targets in the treatment of dyslipidaemia increased significantly (P < 0.001). CONCLUSIONS: In this 22-year prospective follow-up study of in middle-aged Europeans with high participation rates, the progression of dysglycaemia to overt diabetes with aging was rapid, even without a significant change in BMI.

Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-Hour OGTT: An IMI DIRECT Study.

Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA1c indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). ß-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISRr), and insulin secretion potentiation (P < 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISRr (P < 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, P < 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.

Genome-Wide Association Analysis of Pancreatic Beta-Cell Glucose Sensitivity.

CONTEXT: Pancreatic beta-cell glucose sensitivity is the slope of the plasma glucose-insulin secretion relationship and is a key predictor of deteriorating glucose tolerance and development of type 2 diabetes. However, there are no large-scale studies looking at the genetic determinants of beta-cell glucose sensitivity. OBJECTIVE: To understand the genetic determinants of pancreatic beta-cell glucose sensitivity using genome-wide meta-analysis and candidate gene studies. DESIGN: We performed a genome-wide meta-analysis for beta-cell glucose sensitivity in subjects with type 2 diabetes and nondiabetic subjects from 6 independent cohorts (n = 5706). Beta-cell glucose sensitivity was calculated from mixed meal and oral glucose tolerance tests, and its associations between known glycemia-related single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) SNPs were estimated using linear regression models. RESULTS: Beta-cell glucose sensitivity was moderately heritable (h2 ranged from 34% to 55%) using SNP and family-based analyses. GWAS meta-analysis identified multiple correlated SNPs in the CDKAL1 gene and GIPR-QPCTL gene loci that reached genome-wide significance, with SNP rs2238691 in GIPR-QPCTL (P value = 2.64 × 10-9) and rs9368219 in the CDKAL1 (P value = 3.15 × 10-9) showing the strongest association with beta-cell glucose sensitivity. These loci surpassed genome-wide significance when the GWAS meta-analysis was repeated after exclusion of the diabetic subjects. After correction for multiple testing, glycemia-associated SNPs in or near the HHEX and IGF2B2 loci were also associated with beta-cell glucose sensitivity. CONCLUSION: We show that, variation at the GIPR-QPCTL and CDKAL1 loci are key determinants of pancreatic beta-cell glucose sensitivity.

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.

BACKGROUND: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. METHODS: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. RESULTS: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. CONCLUSIONS: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. METHODS AND FINDINGS: We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or ≥5%) rather than a continuous one. CONCLUSIONS: In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community. TRIAL REGISTRATION: ClinicalTrials.gov NCT03814915.

Future risk of metabolic syndrome in women with a previous LGA delivery stratified by gestational glucose tolerance: a prospective cohort study.

BACKGROUND: Whether the delivery of a large-for-gestational-age (LGA) infant predicts future maternal metabolic syndrome (MetS) is not known. To this aim, we investigated the incidence of MetS and its components in women with or without a history of gestational diabetes mellitus (GDM) with a view to the birth weight of the offspring. METHODS: Eight hundred seventy six women treated for their pregnancies in Kuopio University Hospital in 1989-2009 underwent a follow-up study (mean follow-up time 7.3 (SD 5.1) years), of whom 489 women with GDM and 385 normoglycemic controls. The women were stratified into two groups according to the newborn's birth weight: 10-90th percentile (appropriate-for-gestational-age; AGA) (n = 662) and > 90th percentile (LGA) (n = 116). MetS and its components were evaluated in the follow-up study according to the International Diabetes Federation criteria. RESULTS: LGA vs. AGA delivery was associated with a higher incidence of MetS at follow-up in women with a background of GDM (54.4% vs. 43.6%), but not in women without GDM. CONCLUSION: An LGA delivery in women with GDM is associated with a higher risk of future MetS and this group is optimal to study preventive measures for MetS. In contrast, an LGA delivery after a normoglycemic pregnancy was not associated with an increased future maternal MetS risk.

Delivery of an LGA infant and the maternal risk of diabetes: A prospective cohort study.

AIMS: Was to determine whether the birth weight of the infant predicts prediabetes (impaired fasting glucose, impaired glucose tolerance, or both) and type 2 diabetes (T2DM) during long-term follow-up of women with or without gestational diabetes mellitus (GDM). METHODS: The women with or without GDM during their pregnancies in Kuopio University Hospital in 1989-2009 (n=876) were contacted and invited for an evaluation. They were stratified into two groups according to the newborn's birth weight: 10-90th percentile (appropriate-for-gestational-age; AGA) (n=662) and >90th percentile (large-for-gestational-age; LGA) (n=116). Glucose tolerance was investigated with an oral glucose tolerance test after a mean follow-up time of 7.3 (SD 5.1) years. RESULTS: The incidence of T2DM was 11.8% and 0% in the women with and without GDM, respectively, after an LGA delivery. The incidence of prediabetes increased with offspring birth weight categories in the women with and without GDM: from 46.3% and 26.2% (AGA) to 52.9% and 29.2% (LGA), respectively. CONCLUSIONS: GDM women with LGA infants are at an increased risk for subsequent development of T2DM and therefore represent a target group for intervention to delay or prevent T2DM development. In contrast, an LGA delivery without GDM does not increase T2DM risk.

Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.

A correction to this article has been published and is linked from the HTML version of this article.

Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 × 10-8) or suggestively genome wide (p < 2.3 × 10-6). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass.Lean body mass is a highly heritable trait and is associated with various health conditions. Here, Kiel and colleagues perform a meta-analysis of genome-wide association studies for whole body lean body mass and find five novel genetic loci to be significantly associated.

Predicting glycated hemoglobin levels in the non-diabetic general population: Development and validation of the DIRECT-DETECT prediction model - a DIRECT study.

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.

The risk of metabolic syndrome in women with previous GDM in a long-term follow-up.

The aim of this study was to evaluate the incidence of metabolic syndrome (MetS) during long-term follow-up of women with gestational diabetes (GDM). Furthermore, we evaluated the glycemic measures from an oral glucose tolerance test (OGTT) during pregnancy as predictors of incident MetS. Women diagnosed with GDM were divided into two groups according to the results of OGTT: one abnormal value = GDM1 (n = 338) and two abnormal values = GDM2 (n = 151), while women with normal glucose tolerance (n = 385) served as controls. MetS and its components were evaluated in a follow-up study (mean follow-up time 7.3 ± 5.1 years) according to the International Diabetes Federation (IDF) criteria. Fasting plasma glucose in OGTT was the best predictor of incident MetS in ROC (area under the curve) analysis. The incidence of MetS during a <5-year follow-up was 22.2% in controls, 39.3% in GDM1 and 60.4% in GDM2; and >10-year follow-up 24.2%, 46.2% and 62.5%, respectively. In controls and GDM2, the incidence of MetS remained nearly constant during the follow-up, whereas in GDM1 it increased. In conclusion, already mild gestational glucose intolerance may progress to MetS and therefore merits intervention measures to prevent future cardiovascular disease.

Does Future Diabetes Risk Impair Current Quality of Life? A Cross-Sectional Study of Health-Related Quality of Life in Relation to the Finnish Diabetes Risk Score (FINDRISC).

OBJECTIVES: Present study examines the relationship between the estimated risk of developing type 2 diabetes (T2D) and health-related quality of life (HRQoL). We quantify the association between Finnish Diabetes Risk Score (FINDRISC) and HRQoL, and examine the potential use of FINDRISC as tool to evaluate HRQoL indirectly. METHODS: We conducted a cross-sectional study comprising 707 Finnish people without a diagnosis of T2D between the ages of 51 and 75 years. The risk of developing T2D was assessed using the validated and widely used FINDRISC (range 0-26 points), and quality of life was measured using two preference-based HRQoL instruments (15D and SF-6D) and one health profile instrument (SF-36). Effects of the individual FINDRISC items and demographic and clinical characteristics, such as co-morbidities, on HRQoL were studied using multivariable Tobit regression models. RESULTS: Low HRQoL was significantly and directly associated with the estimated risk of developing T2D. An approximate 4-5 point change in FINDRISC score was observed to be associated with clinically noticeable changes in the preference-based instrument HRQoL index scores. The association between HRQoL and the risk of developing T2D was also observed for most dimensions of HRQoL in all applied HRQoL instruments. Overall, old age, lack of physical activity, obesity, and history of high blood glucose were the FINDRISC factors most prominently associated with lower HRQoL. CONCLUSIONS: The findings may help the health care professionals to substantiate the possible improvement in glucose metabolism and HRQoL potentially achieved by lifestyle changes, and better convince people at high risk of T2D to take action towards healthier lifestyle habits. FINDRISC may also provide an accurate proxy for HRQoL, and thus by estimating the risk of T2D with the FINDRISC, information about patients' HRQoL may also be obtained indirectly, when it is not feasible to use HRQoL instruments.

Post-challenge glycemia during pregnancy as a marker of future risk of type 2 diabetes: a prospective cohort study.

The aim of this study was to evaluate the glycemic measures from an oral glucose tolerance test (OGTT) during pregnancy as predictors of incident type 2 diabetes mellitus (T2DM). Patients diagnosed with gestational diabetes mellitus (GDM) were divided into two groups according to the results of OGTT: one abnormal value = GDM1 (n = 338) and two abnormal values = GDM2 (n = 151), while women with normal glucose tolerance served as controls (n = 385). Glucose tolerance was re-evaluated with an OGTT in a follow-up study (average follow-up time 7.3 ± 5.1 years). The incidence of T2DM after 10 years follow-up increased progressively by the degree of the glycemic abnormality during pregnancy: 0.8% in controls, 3.8% in GDM1 (adjusted HR 17.6, 95% CI 1.9-162.3) and 25.0% in GDM2 (adjusted HR 72.9, 95% CI 9.6-553.7), respectively (p = <0.0001). The risk of T2DM is significantly increased in women with two or more abnormal values in OGTT during pregnancy. Post-challenge glucose levels in OGTT were the best predictors of the incident T2DM in ROC analysis and they therefore identify the greatest risk group for targeted prevention of T2DM after GDM.

Increased risk of diabetes with statin treatment is associated with impaired insulin sensitivity and insulin secretion: a 6 year follow-up study of the METSIM cohort.

AIMS/HYPOTHESIS: The aim of this work was to investigate the mechanisms underlying the risk of type 2 diabetes associated with statin treatment in the population-based Metabolic Syndrome in Men (METSIM) cohort. METHODS: A total of 8,749 non-diabetic participants, aged 45-73 years, were followed up for 5.9 years. New diabetes was diagnosed in 625 men by means of an OGTT, HbA1c ≥6.5% (48 mmol/mol) or glucose-lowering medication started during the follow-up. Insulin sensitivity and secretion were evaluated with OGTT-derived indices. RESULTS: Participants on statin treatment (N = 2,142) had a 46% increased risk of type 2 diabetes (adjusted HR 1.46 [95% CI 1.22, 1.74]). The risk was dose dependent for simvastatin and atorvastatin. Statin treatment significantly increased 2 h glucose (2hPG) and glucose AUC of an OGTT at follow-up, with a nominally significant increase in fasting plasma glucose (FPG). Insulin sensitivity was decreased by 24% and insulin secretion by 12% in individuals on statin treatment (at FPG and 2hPG <5.0 mmol/l) compared with individuals without statin treatment (p < 0.01). Decreases in insulin sensitivity and insulin secretion were dose dependent for simvastatin and atorvastatin. CONCLUSIONS/INTERPRETATION: Statin treatment increased the risk of type 2 diabetes by 46%, attributable to decreases in insulin sensitivity and insulin secretion.

Glycated hemoglobin levels are mostly dependent on nonglycemic parameters in 9398 Finnish men without diabetes.

CONTEXT: Determinants of the variance in glycated hemoglobin (HbA1c) among individuals without type 2 diabetes remain largely unknown. OBJECTIVE: We investigated the determinants of HbA1c, fasting plasma glucose, and 2-hour glucose in an oral glucose tolerance test and the associations of these glycemic markers with insulin sensitivity and insulin secretion in Finnish men without type 2 diabetes. DESIGN AND SETTING: The design and setting were the cross-sectional population-based Metabolic Syndrome in Men study including 10 197 Finnish men, aged 45-70 years, and randomly selected from the population register of Kuopio, Eastern Finland. PARTICIPANTS: Participants were a total of 9398 men without type 2 diabetes or with newly diagnosed type 2 diabetes at baseline (mean age 57 ± 7 y; body mass index 27.0 ± 4.0 kg/m(2), mean ± SD) in the Metabolic Syndrome in Men study cohort. INTERVENTIONS: The intervention included an oral glucose tolerance test. MAIN OUTCOME MEASURES: Glycemic and nonglycemic determinants of the variance in HbA1c among participants without type 2 diabetes and the association of HbA1c with insulin secretion and insulin sensitivity were measured. RESULTS: Age, fasting plasma glucose, and high-sensitivity C-reactive protein were the strongest determinants of HbA1c, explaining 12% of the variance in HbA1c levels in participants without type 2 diabetes. Disposition index (insulin secretion) and the Matsuda insulin sensitivity index (insulin sensitivity) explained only less than 2% of the variance in HbA1c in the participants without type 2 diabetes. CONCLUSIONS: The variance in HbA1c among men without type 2 diabetes was largely determined by nonglycemic factors and only weakly by impaired insulin sensitivity and insulin secretion.

Ketone body production is differentially altered in steatosis and non-alcoholic steatohepatitis in obese humans.

BACKGROUND & AIMS: Levels of ketone bodies have been reported to be both increased and decreased in individuals with non-alcoholic fatty liver disease. We investigated whether the metabolism of ketone bodies is different in simple steatosis and in non-alcoholic steatohepatitis (NASH). METHODS: Serum low molecular weight molecules including ketone bodies were measured using high-throughput proton (1H) nuclear magnetic resonance in 116 (76 categorized unequivocally to those with normal liver, simple steatosis or NASH) morbidly obese individuals [age 47.3 ± 8.7 (mean ± SD) years, body mass index 45.1 ± 6.1 kg/m(2) , 39 men and 77 women] with histological assessment of NASH and analysis of gene expression in the liver. Finally, we correlated ß-hydroxybutyrate (ß-OHB) levels with NASH predicting score in Metabolic Syndrome in Men Study (METSIM) population study (n = 8749 non-diabetic men). RESULTS: Levels of ketone bodies were lower in individuals with NASH compared to individuals with simple steatosis (P = 0.004 and P = 0.018 for ß-OHB and acetoacetate respectively). Lower levels of ß-OHB were associated with the NASH predicting score in the METSIM study (P = 0.001). Liver inflammation correlated with mRNA expression of genes regulating ketolysis in the liver (Spearman correlation 0.379-0.388, P < 0.0006 for ACAT1, ACSS2 and BDH1). CONCLUSION: Lower levels of ketone bodies in individuals with NASH compared to individuals with simple steatosis suggest a decrease in ketone body metabolism in NASH.

Markers of tissue-specific insulin resistance predict the worsening of hyperglycemia, incident type 2 diabetes and cardiovascular disease.

We investigated the ability of surrogate markers of tissue-specific insulin resistance (IR, Matsuda IR, Adipocyte IR, Liver IR) to predict deterioration of hyperglycemia, incident type 2 diabetes and cardiovascular events in the Metabolic Syndrome in Men (METSIM) Study. The METSIM Study includes 10,197 Finnish men, aged 45-73 years, and examined in 2005-2010. A total of 558 of 8,749 non-diabetic participants at baseline were diagnosed with new-onset diabetes and 239 with a new CVD event during a 5.9-year follow-up of this cohort (2010-2013). Compared to fasting plasma insulin level, Matsuda IR (IR in skeletal muscle) and Adipocyte IR were significantly better predictors of 2-hour plasma glucose and glucose area under the curve after adjustment for confounding factors. Liver IR was the strongest predictor of both incident type 2 diabetes (hazard ratio = 1.83, 95% confidence interval: 1.68-1.98) and cardiovascular events (hazard ratio = 1.31, 95% confidence interval: 1.15-1.48). Hazard ratios for fasting insulin were 1.37 (95% confidence interval: 1.32-1.42) and 1.11 (95% confidence interval: 1.00-1.24), respectively. Tissue-specific markers of IR, Matsuda IR and Adipocyte IR, were superior to fasting plasma insulin level in predicting worsening of hyperglycemia, and Liver IR was superior to fasting insulin level in predicting incident type 2 diabetes and cardiovascular events.

Long-term changes in glucose metabolism after gestational diabetes: a double cohort study.

BACKGROUND: Gestational diabetes (GDM) has been associated with an elevated risk of type 2 diabetes in women after the pregnancy. Recognition of the factors differentiating the women at highest risk of progression to overt disease from those who remain normoglycemic after gestational diabetes is of key importance for targeted prevention programmes. To this aim, we investigated the incidence and risk factors of prediabetes and type 2 diabetes with a view to the underlying pathophysiological mechanisms in a long-term follow-up of women with a history of gestational diabetes. METHODS: 489 women with GDM and 385 normoglycemic controls attended a follow-up study after pregnancy (mean follow-up time 7.3, SD 5.1 years) in Kuopio, Finland. Glucose tolerance was evaluated with an oral glucose tolerance test, insulin sensitivity by Matsuda insulin sensitivity index (ISI), and insulin secretion by Disposition Index 30 (DI30). RESULTS: GDM increased risk of pre-diabetes and diabetes (HR 3.7, 95% C.I. 2.8-4.7 and HR 40.7, 95% C.I. 5.3-310.1, respectively, after adjustment for confounding factors) and was associated with both increased fasting (P < 0.001) and 2-hour plasma glucose (P < 0.001) during OGTT at the follow-up study. This effect was attenuated when adjusted for Matsuda ISI but abolished after adjustments with DI30 suggesting insulin secretion is the key defect leading to type 2 diabetes after GDM pregnancy. Increase in waist circumference and weight after pregnancy predicted the development of hyperglycemic conditions in women with a history of GDM (P < 0.001, and P = 0.002, respectively). CONCLUSIONS: Pre-diabetic stages after GDM pregnancy are frequent and reflect the progressive risk of type 2 diabetes in long-term follow-up. Hyperglycemia after GDM pregnancy results from beta cell failure and inability to compensate the increased insulin resistance by insulin secretion. Importantly, increase in waist circumference and as well as weight gain during the follow-up is associated with progression to prediabetes and type 2 diabetes in women with a history GDM.