Per-Anders Jansson

Impact of an Exercise Intervention on DNA Methylation in Skeletal Muscle From First-Degree Relatives of Patients With Type 2 Diabetes

To identify epigenetic patterns, which may predispose to type 2 diabetes (T2D) due to a family history (FH) of the disease, we analyzed DNA methylation genome-wide in skeletal muscle from individuals with (FH+) or without (FH−) an FH of T2D. We found differential DNA methylation of genes in biological pathways including mitogen-activated protein kinase (MAPK), insulin, and calcium signaling (P ≤ 0.007) and of individual genes with known function in muscle, including MAPK1, MYO18B, HOXC6, and the AMP-activated protein kinase subunit PRKAB1 in skeletal muscle of FH+ compared with FH− men. We further validated our findings from FH+ men in monozygotic twin pairs discordant for T2D, and 40% of 65 analyzed genes exhibited differential DNA methylation in muscle of both FH+ men and diabetic twins. We further examined if a 6-month exercise intervention modifies the genome-wide DNA methylation pattern in skeletal muscle of the FH+ and FH− individuals. DNA methylation of genes in retinol metabolism and calcium signaling pathways (P < 3 × 10−6) and with known functions in muscle and T2D including MEF2A, RUNX1, NDUFC2, and THADA decreased after exercise. Methylation of these human promoter regions suppressed reporter gene expression in vitro. In addition, both expression and methylation of several genes, i.e., ADIPOR1, BDKRB2, and TRIB1, changed after exercise. These findings provide new insights into how genetic background and environment can alter the human epigenome.

Altered DNA methylation and differential expression of genes influencing metabolism and inflammation in adipose tissue from subjects with type 2 diabetes

Genetics, epigenetics, and environment may together affect the susceptibility for type 2 diabetes (T2D). Our aim was to dissect molecular mechanisms underlying T2D using genome-wide expression and DNA methylation data in adipose tissue from monozygotic twin pairs discordant for T2D and independent case-control cohorts. In adipose tissue from diabetic twins, we found decreased expression of genes involved in oxidative phosphorylation; carbohydrate, amino acid, and lipid metabolism; and increased expression of genes involved in inflammation and glycan degradation. The most differentially expressed genes included ELOVL6, GYS2, FADS1, SPP1 (OPN), CCL18, and IL1RN. We replicated these results in adipose tissue from an independent case-control cohort. Several candidate genes for obesity and T2D (e.g., IRS1 and VEGFA) were differentially expressed in discordant twins. We found a heritable contribution to the genome-wide DNA methylation variability in twins. Differences in methylation between monozygotic twin pairs discordant for T2D were subsequently modest. However, 15,627 sites, representing 7,046 genes including PPARG, KCNQ1, TCF7L2, and IRS1, showed differential DNA methylation in adipose tissue from unrelated subjects with T2D compared with control subjects. A total of 1,410 of these sites also showed differential DNA methylation in the twins discordant for T2D. For the differentially methylated sites, the heritability estimate was 0.28. We also identified copy number variants (CNVs) in monozygotic twin pairs discordant for T2D. Taken together, subjects with T2D exhibit multiple transcriptional and epigenetic changes in adipose tissue relevant to the development of the disease.

Endothelial dysfunction in insulin resistance and type 2 diabetes

Macrovascular disease is the number one killer in type 2 diabetes patients. The cluster of risk factors in the insulin resistance syndrome (IRS) partly explains this notion. Insulin action in muscle, liver or adipose tissue has been thoroughly described in the literature, whilst this has been less described for the endothelium. Insulin stimulates nitric oxide (NO) production in the endothelium and reduced bioavailability of NO is usually defined as endothelial dysfunction. This impairment might be related to defective insulin signalling in the endothelial cell. Therefore, insulin resistance mechanisms in the endothelial cell will be emphasized in this review.

Reduced expression of PGC-1 and insulin-signaling molecules in adipose tissue is associated with insulin resistance

Peroxisome proliferator-activated receptor gamma (PPAR gamma) co-activator 1 (PGC-1) regulates glucose metabolism and energy expenditure and, thus, potentially insulin sensitivity. We examined the expression of PGC-1, PPAR gamma, insulin receptor substrate-1 (IRS-1), glucose transporter isoform-4 (GLUT-4), and mitochondrial uncoupling protein-1 (UCP-1) in adipose tissue and skeletal muscle from non-obese, non-diabetic insulin-resistant, and insulin-sensitive individuals. PGC-1, both mRNA and protein, was expressed in human adipose tissue and the expression was significantly reduced in insulin-resistant subjects. The expression of PGC-1 correlated with the mRNA levels of IRS-1, GLUT-4, and UCP-1 in adipose tissue. Furthermore, the adipose tissue expression of PGC-1 and IRS-1 correlated with insulin action in vivo. In contrast, no differential expression of PGC-1, GLUT-4, or IRS-1 was found in the skeletal muscle of insulin-resistant vs insulin-sensitive subjects. The findings suggest that PGC-1 may be involved in the differential gene expression and regulation between adipose tissue and skeletal muscle. The combined reduction of PGC-1 and insulin signaling molecules in adipose tissue implicates adipose tissue dysfunction which, in turn, can impair the systemic insulin response in the insulin-resistant subjects.

Postprandial hypertriglyceridemia and insulin resistance in normoglycemic first-degree relatives of patients with type 2 diabetes.

Microangiopathy and, in particular, macroangiopathy contribute to excess morbidity and early death in patients with type 2 diabetes (1). At diagnosis, patients with type 2 diabetes have a three- to fourfold greater risk for cardiovascular disease than nondiabetic persons (2, 3); in addition, approximately 40% have evidence of macroangiopathy (4). Therefore, diabetes may be only one of the underlying risk factors for macroangiopathic complications. Several factors associated with type 2 diabetes can be noted years before diagnosis, including decreased first-phase insulin secretion (5, 6) and an impaired metabolic effect of insulin (insulin resistance) (5, 7-9). Risk factors for macroangiopathy in patients with type 2 diabetes include an elevated fasting triglyceride level; a low high-density lipoprotein (HDL) cholesterol level; and accumulation of small, dense, low-density lipoprotein (LDL) particles, which are atherogenic and easily oxidized (10). More researchers now recognize that postprandial handling of triglyceride-rich lipoproteins is important for the propensity for atherosclerosis (10-12). Elevated postprandial triglyceride levels have been seen in persons with fasting hypertriglyceridemia (10, 12), persons who smoke (13, 14), and persons with type 2 diabetes (10). Although genetic predisposition for type 2 diabetes is associated with insulin resistance and impaired glucose disposal, fasting lipid levels usually remain normal at this early stage (8, 15). We assessed insulin sensitivity and postprandial triglyceride response in healthy first-degree male relatives of patients with type 2 diabetes and a group of carefully matched controls who had no known genetic predisposition for diabetes. Methods Participants Participants were recruited by advertisements in a local newspaper. Criteria for inclusion in our study were both parents or one parent and a sibling with type 2 diabetes; male sex (to exclude variation in insulin sensitivity during the menstrual cycle); normal glucose tolerance (16); a fasting triglyceride concentration less than 1.7 mmol/L; no evidence of hypertension, endocrine disease, or metabolic disease; and not smoking. The control group consisted of persons who did not have a known family history of diabetes but fulfilled the remaining criteria. Relatives and controls were pairwise matched for the following variables, expressed as mean SD: age (34 5 years compared with 34 4 years), body mass index (24.5 2.4 kg/m2 compared with 24.6 2.6 kg/m2), waist-to-hip ratio (0.89 0.07 compared with 0.88 0.05), and degree of physical activity (as assessed by interview). Thirteen persons who had two first-degree relatives with type 2 diabetes and 13 persons with no known family history of type 2 diabetes were included in the study. All participants gave informed consent, and the protocol was approved by the ethical committee of Gteborg University. Oral Glucose Tolerance Test All participants had a 75-g oral glucose tolerance test. Insulin Sensitivity Insulin sensitivity was measured by using the euglycemic clamp technique and insulin infusion rates of 10 mU/m2 body surface min -1 and 60 mU/m2 body surface min -1, as described in detail elsewhere (17). Insulin sensitivity was measured by using the rate of glucose infusion during steady-state hyperinsulinemia; this rate is expressed as glucose utilization (mg/kg lean body mass min -1). The insulin sensitivity index represents sensitivity in relation to the prevailing plasma insulin concentration. Lean body mass was calculated from measurements of naturally occurring potassium 40 in a whole-body counter. Meal Tolerance Test The 6-hour postprandial response to a standardized, mixed-meal test was determined as previously described (13) after the participants had fasted overnight. The energy content of the meal was 919 kcal (3.8 MJ); 33 g (14% of energy) were derived from protein, 51 g (49% of energy) were derived from fat, and 83 g (36% of energy) were derived from carbohydrates. The meal contained 30 g of saturated fat, 15 g of monounsaturated fat, and 3 g of polyunsaturated fat. Arterialized venous blood samples were collected from a heated forearm at the times indicated in the Figure for assessment of glucose, insulin, free fatty acids, and triglycerides. Postprandial lipoprotein and hepatic lipase activities were determined 6 hours before and 15 minutes after an intravenous injection of heparin, 100 U/kg of body weight (Lvens, Ballerup, Denmark). Figure. Metabolic variables during a meal tolerance test in 13 first-degree relatives of patients with type 2 diabetes ( white circles ) and 13 controls ( black circles ). A. B. C. D. P Blood Chemistry Glucose, insulin, and free fatty acid levels were determined as previously reported (17); other lipid levels were determined with an automated Cobas Mira analyzer (Hoffman-LaRoche, Basel, Switzerland). High-density lipoprotein cholesterol levels were measured by using the phosphotungstic acid-magnesium chloride precipitation method. Lipoprotein and hepatic lipase activities were determined as previously reported (17). Statistical Analysis Data were analyzed as individual values and as the area under the curve above zero or as the incremental area under the curve above baseline. Two-tailed values of statistical significance were evaluated by using the Student paired t-test. A P value less than 0.050 was considered statistically significant. Correlations were determined by using the Spearman rank test. StatView 4.5 (Abacus Concepts, Inc., Berkeley, California) was used for all statistical calculations. Role of the Funding Sources The funding sources were not involved in the collection, analysis, or interpretation of the data or in the decision to submit the manuscript for publication. Results The detailed results of the metabolic tests are shown in the Table. Table. Metabolic Variables in First-Degree Relatives of Patients with Type 2 Diabetes and in Controls Oral Glucose Tolerance Test The glucose and insulin concentrations during the oral glucose tolerance test were similar in relatives and controls. All participants had normal glucose tolerance. Insulin Sensitivity At the low insulin infusion rate, relatives had lower insulin sensitivity than controls when the euglycemic clamp was used (P=0.006). The difference at the high insulin infusion rate, however, was of borderline significance (P=0.051). Meal Tolerance Test Glucose concentrations before the meal (P=0.036) and 1 hour after the meal (P=0.039) were slightly but significantly higher in relatives than in controls (Figure, part A). Relatives had higher postprandial insulin levels 3 and 4 hours after the meal (Figure, part B). However, because of the variations, differences in the total 6-hour area under the curve and the incremental area under the curve for glucose and insulin during the meal tolerance test were not statistically significant (Table). Fasting triglyceride concentrations before the meal tolerance test were similar in relatives and controls (Table). However, the postprandial response, expressed as the 6-hour incremental area under the curve for triglycerides, was significantly increased by 50% in relatives (P=0.037) (Figure, part C). Relatives and controls had similar fasting concentrations before the meal; however, free fatty acid levels were 50% higher in relatives 1 hour after the meal (P=0.030) (Figure, part D). Fasting total cholesterol levels and HDL cholesterol levels did not differ significantly between the groups. Basal and heparin-released plasma lipase activities, assessed in 11 matched participants, were also similar (Table). Insulin sensitivity was significantly and negatively correlated to the fasting triglyceride concentrations (r s =0.52 [95% CI, 0.76 to 0.15]; P=0.011) and the postprandial triglyceride response (r s =0.46 [95% CI, 0.72 to 0.07]; P=0.026). The fasting HDL cholesterol levels were also negatively correlated to the fasting triglyceride concentrations (r s =0.60 [95% CI, 0.80 to 0.28]; P=0.003) and the postprandial triglyceride response (r s =0.44 [95% CI, 0.71 to 0.07]; P=0.027). Discussion In our study, male normoglycemic first-degree relatives of patients with type 2 diabetes exhibited an increased postprandial triglyceride response to a mixed meal, despite having normal fasting triglyceride levels. Because the relatives were carefully matched to the control group for potential confounding factors, such as sex, age, body mass index, and waist-to-hip ratio, the data suggest that the differences in postprandial triglyceride metabolism were caused by an inherited defect. This defect is probably linked to insulin resistance in the relatives. An increased and prolonged postprandial triglyceride response represents an atherogenic profile that is therefore present long before fasting hypertriglyceridemia or glucose intolerance becomes evident. As insulin resistance becomes exacerbated and free fatty acid levels become elevated by obesity (7), smoking (17), or an inherent progression to impaired glucose tolerance, the dyslipidemic features of the insulin resistance syndrome (that is, elevated fasting triglyceride levels and decreased HDL cholesterol levels) are consistently seen. The relation between postprandial lipid intolerance and fasting hypertriglyceridemia is well established (10, 12). The idea that atherosclerosis is linked to postprandial lipid metabolism was introduced by Zilversmit (11) approximately 20 years ago. Postprandial lipemia consists of a heterogeneous group of triglyceride-rich particles of different compositions and origins. It is not yet clear which lipoprotein particle or particles are related to the type of postprandial hyperlipidemia that is the major risk factor for coronary artery disease. However, evidence is accumulating that small chylomicrons; remnants of very-low-density lipoprotein (VLDL) particles; and easily oxidized small dense LDL particles are atherogenic (10, 12). In addition, in o

Low cellular IRS 1 gene and protein expression predict insulin resistance and NIDDM.

We examined the gene and protein expression of IRS 1 (insulin receptor substrate 1) in adipocytes from two groups of healthy individuals with an increased propensity for non‐insulin‐dependent diabetes mellitus (NIDDM): those with two first‐degree relatives with diabetes and another group with massive obesity. A low expression of IRS 1(<50% of the matched control group) was seen in «30% of both groups and these individuals were characterized by insulin resistance and its hallmarks: higher levels of insulin, glucose, and triglycerides. Two individuals with previously unknown NIDDM were diagnosed and both had low IRS 1 expression. Low IRS 1 protein expression was associated with low mRNA levels but not with the common Gly972Arg polymorphism of the IRS 1 gene. Taken together, our present and previous findings show that a low expression of IRS 1 in fat cells predicts insulin resistance and NIDDM. Furthermore, they support the likelihood that an impaired transcriptional activation may play a key role in the pathogenesis of NIDDM.—Carvalho, E., Jansson, P.‐A., Axelsen, M., Eriksson, J. W., Huang, X., Groop, L., Rondinone, C., Sjostrom, L., Smith, U. Low cellular IRS 1 gene and protein expression predict insulin resistance and NIDDM. FASEB J. 13, 2173–2178 (1999)

Evidence for lactate production by human adipose tissue in vivo

SummaryMicrodialysis of the abdominal subcutaneous tissue was performed in seven healthy normal weight subjects after an overnight fast and also after oral ingestion of 100 g glucose. The lactate concentration in the interstitial water was compared with that in the venous and arterialized plasma from the cubital veins. In the postabsorptive state the lactate concentration in the subcutaneous tissue (1128±72 μmol/l, mean±SEM) was significantly higher (p<0.01) than that in both arterialized (722±72 μmol/l) and venous plasma (798±41 μmol/l). The oral glucose load further increased the lactate level in the subcutaneous tissue throughout the observation period of 2 h. The kinetics for the increase in the lactate concentration was not apparently different in blood or tissue. The highest lactate levels were 1798±173 umol/l in the subcutaneous tissue and 1199±150 μmol/l and 1275±123 μmol/l in arterialized and venous plasma, respectively. It is concluded that abdominal adipose tissue produces lactate both in the fasting state and after an oral glucose load. The data emphasize the importance of the adipose tissue as a significant source of lactate production in the body.

A novel cellular marker of insulin resistance and early atherosclerosis in humans is related to impaired fat cell differentiation and low adiponectin

The epidemic increase in type 2 diabetes can be prevented only if markers of risk can be identified and used for early intervention. We examined the clinical phenotype of individuals characterized by normal or low IRS‐1 protein expression in fat cells as well as the potential molecular mechanisms related to the adipose tissue. Twenty‐five non‐obese individuals with low or normal IRS‐1 expression in subcutaneous abdominal fat cells were extensively characterized and the results compared with 71 carefully matched subjects with or without a known genetic predisposition for type 2 diabetes. In contrast to the commonlyused risk marker, knownheredity for diabetes, low cellular IRS‐1 identified individuals who were markedly insulin resistant, had high proinsulin and insulin levels, and exhibited evidence of early atherosclerosis measured as increased intima media thickness in the carotid artery bulb. Circulating levels of adiponectin were also significantly reduced. Gene analyses of fat cells in a parallel study showed attenuated expression of several genes related to fat cell differentiation (adiponectin, aP2, PPARγ, and lipoprotein lipase) in the group of individuals characterized by a low IRS‐1 expression and insulin resistance. A low IRS‐1 expression in fat cells is a marker of insulin resistance and risk for type 2 diabetes and is associated with evidence of early vascular complications. Impaired adipocyte differentiation, including low gene expression and circulating levels of adiponectin, can provide a link between the cellular marker and the in vivo phenotype.—Jansson, P.‐A., Pellmé, F., Hammarstedt, A., Sandqvist, M., Brekke, H., Caidahl, K., Forsberg, M., Volkmann, R., Carvalho, E., Funahashi, T., Matsuzawa, Y., Wiklund, O., Yang, X., Taskinen, M.‐R., Smith, U. A novel cellular marker of insulin resistance and early atherosclerosis in humans is related to impaired fat cell differentiation and low adiponectin. FASEB J. 17, 1434–1440 (2003)

Hydrochlorothiazide, but not Candesartan, aggravates insulin resistance and causes visceral and hepatic fat accumulation : the mechanisms for the diabetes preventing effect of Candesartan (MEDICA) Study

Treatment with angiotensin II receptor blockers is associated with lower risk for the development of type 2 diabetes mellitus compared with thiazide diuretics. The Mechanisms for the Diabetes Preventing Effect of Candesartan Study addressed insulin action and secretion and body fat distribution after treatment with candesartan, hydrochlorothiazide, and placebo. Twenty-six nondiabetic, abdominally obese, hypertensive patients were included in a multicenter 3-way crossover trial, and 22 completers (by predefined criteria; 10 men and 12 women) were included in the analyses. They underwent 12-week treatment periods with candesartan (C; 16 to 32 mg), hydrochlorothiazide (H; 25 to 50 mg), and placebo (P), respectively, and the treatment order was randomly assigned and double blinded. Intravenous glucose tolerance tests and euglycemic hyperinsulinemic (56 mU/m2 per minute) clamps were performed. Intrahepatic and intramyocellular and extramyocellular lipid content and subcutaneous and visceral abdominal adipose tissue were measured using proton magnetic resonance spectroscopy and MRI. Insulin sensitivity (M-value) was reduced following H versus C and P (6.07±2.05, 6.63±2.04, and 6.90±2.10 mg/kg of body weight per minute, mean±SD; P≤0.01). Liver fat content was higher (P<0.05) following H than both P and C. The subcutaneous to visceral abdominal adipose tissue ratio was reduced following H versus C and P (P<0.01). Glycosylated hemoglobin, alanine aminotransferase, aspartate aminotransferase, and high-sensitivity C-reactive protein levels were higher (P<0.05) after H, but not C, versus P. There were no changes in body fat, intramyocellular lipid, extramyocellular lipid, or first-phase insulin secretion. Blood pressure was reduced similarly by C and H versus P. In conclusion, visceral fat redistribution, liver fat accumulation, low-grade inflammation, and aggravated insulin resistance were demonstrated after hydrochlorothiazide but not candesartan treatment. These findings can partly explain the diabetogenic potential of thiazides.

Impact of age, BMI and HbA1c levels on the genome-wide DNA methylation and mRNA expression patterns in human adipose tissue and identification of epigenetic biomarkers in blood

Increased age, BMI and HbA1c levels are risk factors for several non-communicable diseases. However, the impact of these factors on the genome-wide DNA methylation pattern in human adipose tissue remains unknown. We analyzed the DNA methylation of ∼480 000 sites in human adipose tissue from 96 males and 94 females and related methylation to age, BMI and HbA1c. We also compared epigenetic signatures in adipose tissue and blood. Age was significantly associated with both altered DNA methylation and expression of 1050 genes (e.g. FHL2, NOX4 and PLG). Interestingly, many reported epigenetic biomarkers of aging in blood, including ELOVL2, FHL2, KLF14 and GLRA1, also showed significant correlations between adipose tissue DNA methylation and age in our study. The most significant association between age and adipose tissue DNA methylation was found upstream of ELOVL2. We identified 2825 genes (e.g. FTO, ITIH5, CCL18, MTCH2, IRS1 and SPP1) where both DNA methylation and expression correlated with BMI. Methylation at previously reported HIF3A sites correlated significantly with BMI in females only. HbA1c (range 28-46 mmol/mol) correlated significantly with the methylation of 711 sites, annotated to, for example, RAB37, TICAM1 and HLA-DPB1. Pathway analyses demonstrated that methylation levels associated with age and BMI are overrepresented among genes involved in cancer, type 2 diabetes and cardiovascular disease. Our results highlight the impact of age, BMI and HbA1c on epigenetic variation of candidate genes for obesity, type 2 diabetes and cancer in human adipose tissue. Importantly, we demonstrate that epigenetic biomarkers in blood can mirror age-related epigenetic signatures in target tissues for metabolic diseases such as adipose tissue.