AJP - Endo Fuel your research with LabChart
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Am J Physiol Endocrinol Metab 291: E282-E290, 2006. First published February 14, 2006; doi:10.1152/ajpendo.00604.2005
0193-1849/06 $8.00
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
291/2/E282    most recent
00604.2005v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (8)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Lautamäki, R.
Right arrow Articles by Nuutila, P.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Lautamäki, R.
Right arrow Articles by Nuutila, P.

Liver steatosis coexists with myocardial insulin resistance and coronary dysfunction in patients with type 2 diabetes

Riikka Lautamäki,1 Ronald Borra,1,2 Patricia Iozzo,1,3 Markku Komu,2 Terho Lehtimäki,4 Marko Salmi,5 Sirpa Jalkanen,5 K. E. Juhani Airaksinen,6 Juhani Knuuti,1 Riitta Parkkola,2 and Pirjo Nuutila1,6

1Turku PET Centre, 2Department of Radiology, University of Turku, Turku, Finland; 3Institute of Clinical Physiology, National Research Council, Pisa, Italy; 4Department of Clinical Chemistry, University of Tampere and Tampere University Hospital, Tampere; 5Medicity Research Laboratory and Department of Medical Microbiology, University of Turku and Department of Bacterial and Inflammatory Diseases, National Public Health Institute, Turku; and 6Department of Medicine, University of Turku, Turku, Finland

Submitted 2 December 2005 ; accepted in final form 7 February 2006


   ABSTRACT
TOP
 ABSTRACT
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 DISCLOSURE
 REFERENCES
 
Nonalcoholic fatty liver (NAFL) is a common comorbidity in patients with type 2 diabetes and links to the risk of coronary syndromes. The aim was to determine the manifestations of metabolic syndrome in different organs in patients with liver steatosis. We studied 55 type 2 diabetic patients with coronary artery disease using positron emission tomography. Myocardial perfusion was measured with [15O]H2O and myocardial and skeletal muscle glucose uptake with 2-deoxy-2-[18F]fluoro-D-glucose during hyperinsulinemic euglycemia. Liver fat content was determined by magnetic resonance proton spectroscopy. Patients were divided on the basis of their median (8%) into two groups with low (4.6 ± 2.0%) and high (17.4 ± 8.0%) liver fat content. The groups were well matched for age, BMI, and fasting plasma glucose. In addition to insulin resistance at the whole body level (P = 0.012) and muscle (P = 0.002), the high liver fat group had lower insulin-stimulated myocardial glucose uptake (P = 0.040) and glucose extraction rate (P = 0.0006) compared with the low liver fat group. In multiple regression analysis, liver fat content was the most significant explanatory variable for myocardial insulin resistance. In addition, the high liver fat group had increased concentrations of high sensitivity C-reactive protein, soluble forms of E-selectin, vascular adhesion protein-1, and intercellular adhesion molecule-1 (P < 0.05) and lower coronary flow reserve (P = 0.02) compared with the low liver fat group. In conclusion, in patients with type 2 diabetes and coronary artery disease, liver fat content is a novel independent indicator of myocardial insulin resistance and reduced coronary functional capacity. Further studies will reveal the effect of hepatic fat reduction on myocardial metabolism and coronary function.

hepatic steatosis; coronary disease; positron emission tomography; magnetic resonance spectroscopy

INSULIN RESISTANCE characterizes over 80% of patients with type 2 diabetes (T2DM) (44). Impaired glucose uptake in several tissues and endothelial dysfunction are usual findings. Increased hepatic fat content has been found to affect ~50% of type 2 diabetic patients in the United States (6); thus nonalcoholic fatty liver (NAFL) often coexists with metabolic syndrome and insulin resistance. Futhermore, Hamaguchi et al. (20) have recently shown that metabolic syndrome may predict NAFL.

Fatty liver has been closely linked to insulin resistance at the whole body level irrespective of body weight, BMI, fat distribution, and glucose tolerance (35). Coronary risk factors tend to cluster in patients with high liver fat content, and patients with NAFL show more advanced carotid atherosclerosis compared with healthy controls (3, 8, 52). Recently, in a prospective study, it was shown that T2DM patients with NAFL had more cardiovascular related events during follow-up (53). In addition, Villanova et al. (57) have presented a significant relationship between peripheral endothelial dysfunction and NAFL. These findings show NAFL as a well-defined risk factor for coronary artery disease; however, direct evidence of the effect of hepatic steatosis on heart is lacking.

In T2DM, coronary function is significantly impaired, and there may exist abnormal substrate metabolism potentially contributing to their poor prognosis after myocardial infarction (7, 50). In addition, patients with T2DM often present low-grade inflammation, which is significantly related to the atherosclerotic processes (44). However, despite the significance of fatty liver as a coronary risk factor, until now the relationship between hepatic fat content and myocardial metabolism and coronary function in T2DM patients with ischemic coronary artery disease (CAD) has not been studied. Positron emission tomography (PET) combined with the euglycemic hyperinsulinemic clamp technique and 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) and 15O-labeled water ([15O]H2O) is a method of choice to quantify the tissue-specific insulin sensitivity and blood flow (40).

The aim of the present study was to evaluate whether NAFL is associated with more severe myocardial insulin resistance and impaired perfusion in patients with T2DM and CAD. Using proton magnetic resonance spectroscopy (1H-MRS), the euglycemic clamp technique, and PET, we were able to find a novel association between hepatic fat content and myocardial insulin resistance.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 DISCLOSURE
 REFERENCES
 
Subjects. A total of 55 patients with T2DM, as defined by World Health Organization criteria (4), and ischemic coronary heart disease were assigned to protocol. Inclusion criteria were that BMI was between 20 and 40 kg/m2 and that diabetes was treated with diet or with metformin and/or sulfonylurea and was in good or moderate glycemic control (Hb A1c <8.5%). All subjects had past or present angina pectoris symptoms under stress but no unstable angina pectoris, and they were on stable medical therapy. Ten patients had a history of previous myocardial infarction, and six patients had Q-waves on electrocardiogram. Patients with chronic insulin therapy, diabetes treated with thiazolidinediones, alcohol or drug abuse, or clinical signs of heart failure were excluded (left ventricular ejection fraction was measured in all patients by echocardiography). Characteristics of the patients are shown in Table 1. All patients gave written informed consent before participating in the study. The study was conducted according to the guidelines of the Declaration of Helsinki, and the study protocol was approved by the Ethics Committee of the Hospital District of Southwest Finland.


View this table:
[in this window]
[in a new window]
  		Table 1. Characteristics of study subjects

 
Study design. Before entering the study, all subjects had previously undergone single photon emission computed tomography (SPECT) imaging, in which exercise-induced ischemia of the myocardium had been diagnosed and ischemic score calculated as previously described (1). In the current study, coronary angiography was performed to determine the stenotic vessels. Liver fat content was measured using proton magnetic resonance spectroscopy (1H-MRS). Myocardial perfusion and metabolism were measured by PET during insulin stimulation. Angiography, PET, and MRS were performed on three separate days.

Before the PET study, patients refrained from caffeine-containing drinks, from smoking, and from all their medications with the exception of short-acting nitrates for 12 h. Two catheters were placed, one in an antecubital vein for infusion of adenosine, glucose, and insulin and for tracer injections and another in the contralateral arm for blood sampling. The euglycemic hyperinsulinemic clamp technique was used as previously described (14). The rate of insulin infusion was 1 mU·kg–1·min–1 (Actrapid; Novo Nordisk, Copenhagen, Denmark). During hyperinsulinemia, euglycemia was maintained by infusing 20% glucose. The rate of the glucose infusion was adjusted according to plasma glucose concentrations measured every 5–10 min from arterialized blood. At the time point of 60 min of euglycemic hyperinsulinemic clamp, myocardial perfusion measurements at rest and during adenosine-induced hyperemia were performed. At 90 min of insulin stimulation, [18F]FDG was injected, and dynamic PET study of myocardial region was started for 40 min; thereafter the femoral region was scanned for 20 min. The total duration of clamp was 180 min. Insulin and free fatty acid (FFA) concentrations were determined every 30 and 60 min. The electrocardiogram and heart rate were monitored throughout the study. Blood pressure was measured every 15 min throughout the study.

Determination of the nonischemic and nonstenotic region in myocardium. For the PET analysis, the region with no ischemic defects (determined previously in the SPECT study) and no stenotic lesions in the coronary angiography was identified in all subjects. PET analysis was based on the eight-segment heart phantom map, which is based on the segmental division described by Brunken and colleagues (9, 10) dividing the myocardium into anterobasilar, anteroseptal, anterior, lateral, posteroseptal, apical, posterobasilar, and inferior segments. The feasibility of this analysis has been tested in previous studies (26, 34).

Angiographic data were individually aligned to the eight segments of the heart phantom map. Typically left anterior descending artery was considered to supply the anterobasal, anterior septal, anterior, and apical regions, left circumflex artery, the lateral and posterobasal regions, and right coronary artery, the posteroseptal and inferior segments. The analyses of the SPECT and the coronary angiography were performed by different, independent, experienced observers, and after that the results were matched together. The nonischemic and nonstenotic region was determined individually in each patient. In patients with triple vessel disease, the localizations of stenosis and ischemia were in the remote region of the coronary vessel territory; thus the nonischemic region was determined as a region proximal to the ischemic and stenotic defect. Consequently, the myocardial region used for the analysis had no reversible perfusion deficit in the SPECT and was associated with nonstenotic coronary artery.

PET image acquisition, processing, and corrections. The positron-emitting tracers [15O]H2O and [18F]FDG were produced as previously described (19, 43). Patients were positioned supine in an eight-ring ECAT 931/08-12 tomograph (Siemens/CTI, Knoxville, TN). Photon attenuation was corrected by a transmission scan of 5 min with a removable ring source of 68Ge. Myocardial blood flow was measured by intravenous infusion of [15O]H2O (1.3–1.5 GBq) over 2 min. Dynamic imaging was performed at rest and after 60 s from the start of the adenosine infusion (140 µg·kg–1·min–1) with frames of 6 x 5 s, 6 x 15 s, and 8 x 30 s. [18F]FDG (220–260 MBq) was injected intravenously over 1 min, and dynamic imaging was performed with frames of 8 x 15 s, 2 x 30 s, 2 x 120 s, 1 x 180 s, and 6 x 300 s of the myocardial region followed by 5 x 240 s of the femoral region. An arterialized blood sample for measurement of plasma radioactivity was drawn once during each time frame. All data were corrected for dead time, decay, and photon attenuation and reconstructed in a 128 x 128 matrix.

Calculation of myocardial perfusion. Large regions of interest (ROI) were placed on representative transaxial slices in each study to cover the nonischemic and nonstenotic myocardial region. The ROIs drawn in the rest images were copied to the images obtained during adenosine-induced hyperemia. Myocardial blood flow was calculated using a single-compartment model as previously published (22). Arterial input function was obtained as previously described (21).

Measurement of myocardial and skeletal muscle and whole body glucose uptake. The three-compartmental model of [18F]FDG was used as previously described (45). Plasma time activity was measured with an automatic gamma-counter (Wizard 1480 3"; Wallac, Turku, Finland) from manually drawn samples. Myocardial and skeletal muscle glucose uptakes were calculated as previously published (18, 30), with lumped constant values of 1.0 and 1.2, respectively (38, 41). Myocardial regions associated with nonstenotic coronary artery and normal perfusion were included in the analysis. Myocardial glucose extraction rate was calculated as myocardial glucose uptake divided by myocardial blood flow at rest. Whole body glucose uptake was measured from 80 to 120 min of the clamp, as earlier described (14).

Liver fat content (1H-MRS). A 1.5 T MR imager (Signa Horizon LX, GE Medical Systems) with the general-purpose flex surface coil and body coil was used for MRI and MRS. A coronal scout image of the abdominal area was obtained followed by transverse T1W dual-echo fast-spoiled gradient echo (out-in-phase) imaging during breath hold for localization of the liver. A single voxel was positioned in the liver parenchyma outside the area of the great vessels by an experienced radiologist. Voxel dimensions were adjusted to avoid visible vascular structures, taking into account the chemical shift artifact. The mean volume of the voxel was 28.38 ± 6.61 cm3. A PRESS 1H-MRS sequence (PROBE-SV) was used with the following parameters: time of repetition = 3,000 ms, time of echo = 25 ms, number of excitations = 8, number of signals = 48, with a total duration of 2:36 min. During this sequence, data were acquired during two breath-hold intervals of 21 s. A typical location for the voxel is displayed in the T1W image with the corresponding spectrum (Fig. 1).


Figure 1
View larger version (43K):
[in this window]
[in a new window]
  		Fig. 1. Location for the voxel used in 1H magnetic resonsnce spectroscopy is displayed in the T1W image with the corresponding spectrum.

 
The time domain fitting of the signal was performed using the java Magnetic Resonance User Interface (jMRUI) v.2001 data analysis package (http://www.mrui.uab.es/mrui/). Fat signal amplitudes of the frames were calculated with water suppression, using the AMARES algorithm (56). The methylene and methyl peak amplitudes of the fat spectrum and amplitude of the water spectrum were corrected due to different T2 decay and molar concentrations of 1H nuclei in fat and water (49). Liver fat content was defined as fat in relation to the total weight of liver tissue (54). This measurement of liver fat content by proton spectroscopy has been validated against histologically determined lipid contents of liver biopsies in humans (54) and animals (49) and against estimates of fatty degeneration by X-ray computed assisted tomography (33). Patients were divided into two groups of low (<8%) and high (>8%) liver fat content according to the median of liver fat of the whole group (7.8%). The division was also based on previous findings that triglyceride content of liver >8% is a reliable sign of pathological fatty liver (15).

Intra-abdominal and subcutaneous fat (MRI). A single T1W FSE image was obtained at the level of the L2–L3 intervertebral disc for analysis of abdominal adipose tissue masses, as previously described (2). Adipose tissue density of 0.9196 g/ml was used for converting measured volumes into weight.

Coronary angiography. Coronary angiography was performed via the femoral artery with the Judkins technique after an intravenous injection of 3,750 IU of heparin and 0.5 mg of sublingual nitroglycerin. Angiography was performed with 5-Fr catheters (Cordis, Johnson & Johnson, Miami Lakes, FL). A single operator analyzed coronary artery diameters with QCA software (Quantcor stenosis evaluation software; Siemens, Munich, Germany).

Biochemical analysis. All laboratory samples, with the exception of the samples of inflammatory markers, were sent by courier to a central laboratory (Quest Diagnostics, London, UK). Standard methods and quality control used for the tests were performed. LDL cholesterol concentration was calculated with the Friedewald formula. The concentrations of fasting high sensitivity C-reative protein (hsCRP) and soluble adhesion molecules were measured as previously described (24, 42).

Statistical methods. All data are reported as means ± SD. An unpaired t-test was used to compare the variables between the groups in normally distributed data. In case of a skewed variable, log transformation or the nonparametric Mann-Whitney U-test was performed. The {chi}2 test was used for proportion analysis in groups. Pearson's correlation coefficient, in case of normally distributed variables, and Spearman's nonparametric rank correlation coefficients were calculated for the selected variables. Multiple linear regression analysis was performed to study the relation between the liver fat content and the metabolic variables. A P value of <0.05 was considered statistically significant. All statistical analyses were performed with SAS statistical analysis system v.8.2 (Cary, NC).


   RESULTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 DISCLOSURE
 REFERENCES
 
Physical characteristics. The groups of low (4.6 ± 2.0%; range 1.4–7.8%) and high liver fat (17.4 ± 8.0%; range 9.0–41.8%) were similar with respect to sex, age, BMI, and waist-to-hip ratio (Table 2). Abdominal subcutaneous fat masses were not significantly different between the groups, but the amount of intra-abdominal (visceral) fat was increased in the high liver fat group compared with the low liver fat group (P = 0.009).


View this table:
[in this window]
[in a new window]
  		Table 2. Characteristics of groups of high and low liver fat content

 
CAD and myocardial perfusion. The location of the coronary lesions is shown in Table 2. The median of the degree of the main stenotic lesion was 60% (range 9–100%) with no significant difference between the groups. There was no statistical difference between the groups in left ventricular ejection fraction (66 ± 6 vs. 62 ± 7%, low liver fat and high liver fat group, respectively). When coronary flow reserve (CFR) was used as an indicator of endothelial function, it was found to be 28% lower in patients with fatty liver, indicating more severe coronary dysfunction in these patients (Fig. 2). In the pooled population, liver fat content was negatively correlated with CFR (r = –0.38, P = 0.020).


Figure 2
View larger version (10K):
[in this window]
[in a new window]
  		Fig. 2. A: liver fat content, whole body insulin sensitivity, myocardial glucose uptake, and glucose extraction are significantly different in the 2 groups. B: coronary flow reserve is lower in patients with fatty liver. Open bars, patients with low liver fat content; filled bars, patients with high liver fat content. *P < 0.0001, {dagger}P = 0.012, {ddagger}P = 0.040, §P = 0.0006, ||P = 0.02.

 
Glucose and lipid metabolism. Fasting plasma glucose and insulin levels were similar between the groups (Table 2), but Hb A1c (P = 0.08) tended to be, and fasting serum C-peptide levels (P = 0.001) were, higher in the high liver fat group compared with the low liver fat group.

During intravenously maintained hyperinsulinemia, steady-state plasma glucose (5.1 ± 0.3 vs. 5.4 ± 0.5 mmol/l, P = NS) or serum insulin (426.3 ± 58.0 vs. 449.1 ± 67.3 pmol/l, P = NS) levels did not differ between the groups. Whole body insulin sensitivity was 24% (10.2 ± 3.8 vs. 13.4 ± 5.3 µmol·kg–1·min–1, P = 0.012) and skeletal muscle glucose uptake was 37% (15.2+7.4 vs. 24.3+11.9 µmol·kg–1·min–1, P = 0.002) lower in the high fat group compared with the low fat group. Furthermore, myocardial glucose uptake was significantly impaired in patients with fatty liver (P = 0.040; Fig. 2). In addition, myocardial glucose extraction rate was significantly impaired in the high-fat group compared with the low-fat group (P = 0.0006). In the whole population, there was a significant inverse correlation between myocardial glucose uptake and FFA concentration during clamp (r = –0.39, P = 0.003).

Serum total cholesterol, triglycerides, and LDL and HDL cholesterol did not differ between the groups (Table 2). Fasting FFA concentrations were similar in both groups, but patients with fatty liver showed a significantly higher level of circulating FFAs during clamp than patients with low liver fat content (0.12 ± 0.06 vs. 0.18 ± 0.07 mmol/l, P = 0.001).

Liver function tests and inflammation markers. In both groups, the liver enzymes were within normal range (serum alanine transaminase <42 U/liter and serum {gamma}-glutamyltransferase <65 U/liter); however, they were slightly but significantly higher in the high liver fat group compared with the low liver fat group (Table 2). Patients with high liver fat content had significantly increased hsCRP level compared with the patients with low liver fat content (Table 3). Homocysteine and plasminogen activator inhibitor-1 (PAI-1) tended to be higher in the high liver fat group. The levels of soluble intercellular adhesion molecule-1 (ICAM-1) and E-selectin, as well as soluble vascular adhesion protein-1 (VAP-1) molecules, were increased in patients with fatty liver.


View this table:
[in this window]
[in a new window]
  		Table 3. Inflammation markers

 
Relation between hepatic fat content and myocardial metabolic mediators. To examine the relation between liver fat, myocardial insulin resistance, and measurements of obesity, simple and multiple linear regression analyses were employed. In simple regression analyses, liver fat content was correlated with BMI (r = 0.38, P = 0.005), waist circumference (r = 0.38, P = 0.005), and visceral fat mass (r = 0.31, P = 0.021), but no association was found between liver fat and Hb A1c, fasting plasma glucose, subcutaneous fat mass, or waist-to-hip ratio. Liver fat content was inversely associated with whole body glucose uptake (r = –0.50, P < 0.0001), skeletal muscle glucose uptake (r = –0.36, P = 0.007), myocardial glucose uptake (r = –0.47, P = 0.0003) (Fig. 3) and positively correlated with FFA levels during clamp (r = 0.45, P = 0.0007).


Figure 3
View larger version (12K):
[in this window]
[in a new window]
  		Fig. 3. Hepatic fat content is strongly inversely correlated with myocardial glucose uptake.

 
To determine the role of liver fat content in myocardial metabolism, multiple regression analysis controlling for variables that showed significant correlation with myocardial metabolism was performed. Only liver fat content (P = 0.016) and whole body glucose uptake (P = 0.006) were significant determinants of myocardial glucose uptake. Whole body glucose uptake was significantly correlated with myocardial glucose uptake (r = 0.41, P = 0.002); however, when liver fat content was used as a covariate, the association was no longer significant (P = 0.06). In a more specific multiple regression analysis model, with independent variables that directly affect myocardial metabolism, only liver fat content remained a significant factor (Table 4).


View this table:
[in this window]
[in a new window]
  		Table 4. Multiple regression analyses

 

   DISCUSSION
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 DISCLOSURE
 REFERENCES
 
The present study reveals a novel finding that liver fat content is an independent, significant mediator of myocardial glucose uptake in T2DM patients with CAD. Furthermore, high hepatic fat content is related to an increased visceral fat mass, impaired whole body and skeletal muscle insulin sensitivity, and coronary dysfunction in addition to an increment in inflammation markers. To our knowledge, this study is the first to address the direct association between liver and heart by combining highly advanced noninvasive metabolic imaging techniques in a relatively large patient population.

The present study confirms previous findings that patients with high liver fat content show decreased insulin sensitivity at the whole body level and provides a novel finding of a relationship between an increased liver fat content and impaired myocardial metabolism. Moreover, this study further extends previous findings (3, 8, 52, 53, 57) suggesting a direct relationship between NAFL and coronary atherosclerosis by showing impaired coronary flow reserve and increment in markers of low-grade inflammation in patients with NAFL.

The pathogenesis of NAFL is still under investigation. Insulin resistance enhances adipocyte lipolysis and increases the amount of circulating FFAs, which are taken up at an increased rate in hepatocytes. The main part of the stored triglycerides arises from the circulating FFAs (16). Visceral adipose tissue releases FFAs, which are delivered via the portal vein into the liver. In the present study, visceral fat depots were 22% larger in patients with fatty liver, which may suggest enhanced delivery of FFAs into the liver. In liver, mitochondrial beta-oxidation soon becomes overloaded, causing an increased concentration of FFAs in hepatocytes, which induces enhanced lipid oxidation and, consequently, oxidative stress. On the other hand, FFA synthesis in hepatocytes is increased due to increased glycolysis caused by hyperinsulinemia (6). In the current study, we found that liver enzymes were normal or only mildly elevated in patients with high liver fat content, which is in agreement with previous observations (6). Thus many patients with NAFL remain undiagnosed until other significant manifestations of the disease have occurred. Because silent high liver fat content may contribute to low-grade inflammation and significant impairment in insulin sensitivity, coronary function, and myocardial glucose uptake, the latter ones being detrimental to the myocardium during ischemic conditions, asymptomatic fatty liver cannot be considered a benign side condition in these patients.

Lately, inflammation has been linked to coronary syndromes. A latent infection caused by several bacteria or viruses has been suggested to be the etiological factor; however, the causality still remains controversial (12). In insulin resistance, low-grade inflammation is common but the underlying mechanism is unknown. CRP is a strong predictive biomarker of cardiovascular events as well as a direct participant in atherosclerosis (58). In the current study, we found that hsCRP is significantly higher in patients with high liver fat content, suggesting low-grade inflammation in these patients. In addition, coronary dysfunction, as measured by coronary flow reserve, was more prominent in patients with high liver fat content. This is in agreement with a previous study in type 1 diabetic patients showing that higher hsCRP values were associated with reduced coronary vasoreactivity (48). Furthermore, in the current study, soluble forms of vascular adhesion molecules ICAM-1, VAP-1, and E-selectin were upregulated in patients with higher liver fat content, suggesting more dysfunctional endothelial cells and vascular injury. Soluble forms are markers of inflammation and may correlate with facilitated attachment of leucocytes on vascular wall and, consequently, promotion of the production of proinflammatory cytokines (37). Especially, increased levels of soluble VAP-1, which itself is produced in the liver (29), have been found in inflammatory liver diseases (28). Interestingly, the semicarbazide-sensitive amine oxidase activity of VAP-1 has been previously linked to increased oxidative stress and vascular injury (46). With respect to these previous findings, we may suggest that hepatic steatosis per se may cause low-grade inflammation, which may affect coronary vasculature as well as myocardial metabolism.

Whole body insulin sensitivity, skeletal muscle glucose uptake, myocardial glucose uptake, and myocardial glucose extraction rate were significantly higher in the low hepatic fat group. Because resting myocardial blood flow did not differ between the groups, the decreased glucose extraction rate suggests an intrinsic defect in myocardial glucose transport independent of blood flow in patients with fatty liver. As the signal transduction pathways may differ during insulin stimulation and during ischemia, the results of the present study do not confirm the impaired myocardial glucose uptake during ischemia in patients with hepatic steatosis (17). However, it has been suggested that whole body insulin sensitivity is directly associated with myocardial insulin sensitivity (23), which is in agreement with the present study. This shows a close relationship between whole body and myocardial glucose uptake; thus the high-risk profile for cardiovascular events related to whole body insulin resistance is in close association with myocardial insulin resistance. Previously, it has been suggested that the underlying factor for hepatic steatosis could be insulin resistance per se (11). According to the multiple regression analysis in the current study, the association between insulin resistance at the whole body level and myocardial glucose uptake (dependent variable) was abolished when liver fat content was taken into account as an additional independent variable, suggesting a more significant role of hepatic steatosis over the whole body insulin sensitivity. This supports the atherogenic role of NAFL beyond the insulin resistance as previously proposed (51). Still, the actual cellular mechanism for such action remains to be solved.

In patients with ischemic heart disease, glucose is considered an essential fuel source due to the fact that energy may be produced from glucose during anaerobic conditions also. It is well established that the primary fuel for myocardium is represented by FFAs in the fasting state and glucose in the fed state (13). Myocardial glucose uptake is inversely associated with serum FFAs in both healthy and insulin-resistant conditions, and such a relationship explains the bulk of the individual variation in myocardial metabolism (25, 39). However, myocardial insulin resistance has been found in patients with T2DM and CAD (23). In the present study, myocardial glucose uptake was measured in the nonischemic regions in these patients. Despite the fact that the regions may not be considered normal due to the underlying CAD, since the left ventricular function was normal, the compensatory work of nonischemic regions may be considered negligible. Furthermore, the measurements were performed during stable conditions; thus no significant ischemia was present. Additionally, it has been shown that insulin is capable of increasing glucose uptake both in the ischemic and in the nonischemic regions (34). This confirms our results of impaired myocardial glucose uptake in NAFL.

One of the underlying mechanisms explaining the relationship between fatty liver and impaired myocardial metabolism may be an excessive FFA input into the myocardium due to the shift to FFA metabolism (50). In the normal situation, FFAs are delivered into cells according to the requirement of fuel, and few or no unoxidized FFAs are left intracellularly (55). However, when the supply of FFAs exceeds the rate of mitochondrial beta-oxidation, oxidative stress is induced (32), and intracellular triglycerides and fatty acid intermediates, ceramides, start to build up, and activation of peroxisome proliferator-activated receptor-{alpha}-related genes occurs (59). The lipotoxicity of these accumulated elements has been shown to cause contractile dysfunction through cardiac apoptosis (60). In addition, it has been suggested that triglycerides, as relatively inert substances, could negatively affect muscular contractions (55). Furthermore, it has been found in animal studies that nonadipose tissue triglyceride content could also induce formation of fibrosis (60). In the current study, circulating FFAs were significantly increased during hyperinsulinemia in patients with higher hepatic fat content, which is typical for patients with whole body insulin resistance. However, in the current study, whole body glucose disposal and circulating FFAs could not explain the rate of myocardial glucose uptake, since the predominant direct determinant was liver fat content. This suggests that hepatic triglyceride storage may be directly associated with myocardial triglyceride storage and thus with an impairment in myocardial oxidative glucose metabolism. In addition, in T2DM patients increased levels of circulating FFA concentration are associated with an increment in PAI-1 level, partly contributing to the hypercoagulable state in these patients (27). This suggests that, in addition to the impaired myocardial metabolism, there is an increased risk for atherothrombotic incidents associated with impaired FFA suppressibility, which may partly contribute to the cardiovascular complications.

In the present study, the glucose disposal was measured under high physiological hyperinsulinemia (insulin infusion rate 1 mU·kg–1·min–1). Because hepatic glucose production is not fully suppressed in all patients with T2DM under these conditions (5), whole body glucose utilization may be underestimated. In contrast, when muscle glucose uptake is studied using FDG-PET, the direct tissue-specific metabolic rate is measured. Therefore, we reperformed the linear regression analysis with skeletal muscle glucose uptake replacing whole body glucose uptake (data not shown). This even strengthens the role of hepatic steatosis as an independent contributor of myocardial glucose uptake since it, as well, leaves hepatic steatosis as the only independent contributor. Consequently, although the measurement of whole body insulin sensitivity as such may possess some limitations in these patients, the skeletal muscle glucose uptake measurements confirm the findings of impaired insulin sensitivity in NAFL.

In the current study, myocardial glucose uptake measurements were performed after the adenosine-induced hyperemia. It has been published that adenosine infusion enhances the effects of insulin and increases myocardial glucose uptake (31). However, it has been shown with FDG-PET that the effects of adenosine after completion of infusion on myocardial glucose uptake is negligible (36); thus adenosine-induced hyperemia does not have an interfering effect in the current study. Here, the myocardial blood flow was measured during insulin infusion. Insulin has an increasing effect on the hyperemic blood flow as such (47); however, here the measurements were performed under the same conditions in both groups; consequently, the increasing effect of insulin does not affect the net result of the present study.

In contrast to previous studies focused on liver fat as a risk factor of metabolic syndrome, diabetes, and CAD, the aim in the present study was to evaluate whether patients who already have these clinical diseases differ from each other when divided into subgroups according to liver fat accumulation. In the current study, the patients were divided into two groups according to the median of the liver fat content. This division was also based on previous findings that liver triglyceride content greater than 8% is a reliable sign of pathological fatty liver (15). Here, NAFL is well associated with impaired myocardial metabolism and coronary dysfunction; however, the causality of this relationship needs more exploration. Inflammation as such may cause reduced coronary vasoreactivity, and impaired coronary vasoreactivity precedes clinical atherosclerosis and thus may be partly responsible for complications in these patients. In addition, impaired myocardial glucose uptake is detrimental to myocardium during ischemia; therefore, increased myocardial insulin resistance as seen here in patients with hepatic steatosis may be related to the abnormal substrate metabolism, which has been suggested as one of the reasons for poor prognosis (7). In addition to that, it is important to observe that from the multiple regression analysis liver steatosis is a more significant indicator of myocardial metabolism than FFA concentration, which has been thought to be one of the most important contributors of myocardial glucose uptake. The present study introduces hepatic steatosis as a more important contributor, which suggests other possible mechanisms of the regulation of glucose uptake than the Randle's cycle only. However, what effect this may have on myocardial triglyceride content remains open. Moreover, the cross-sectional nature of the present study does not allow conclusions regarding the future risks of cardiovascular events, and because patients in the present study had stable coronary heart disease, they do not represent the whole patient population. Yet 55 patients is a relatively large patient population with regard to the highly sensitive noninvasive metabolic techniques (PET, 1H-MRS, MRI, and insulin-glucose clamping) combined in this study; thus the result does fill a knowledge gap.

In conclusion, hepatic steatosis is a direct predictor of impaired myocardial metabolism and coronary dysfunction. The underlying mechanisms may be lipotoxicity due to FFA accumulation and low-grade inflammation. Further studies will reveal the effect of reduction in hepatic fat content on myocardial metabolism and coronary function in this high-risk patient group.


   GRANTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
DISCLOSURE
 REFERENCES
 
This study was financially supported by grants from Academy of Finland (Grant no. 203958), European Community Program QOL 1.1.1 (Marie Curie Fellowship, contract no. QKGA-1999-51330), Turku University Hospital, Aarne and Aili Turunen Foundation, Finnish Cultural Foundation, and Jalmari and Rauha Ahokas Foundation.


   DISCLOSURE
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 DISCLOSURE
REFERENCES
 
This study was financially supported by a grant from GlaxoSmithKline.


   ACKNOWLEDGMENTS
 
The MRUI software package was kindly provided by the participants of the European Union Network programmes: Human Capital and Mobility, CHRX-CT94-0432 and Training and Mobility of Researchers, ERB-FMRX-CT97-0160. We thank the staff of Turku PET Centre for their excellent technical assistance.


   FOOTNOTES
 

Address for reprint requests and other correspondence: P. Nuutila, Turku PET Centre, Turku University Hospital, Kiinamyllynkatu 4-8, PO Box 52, FIN-20521 Turku, Finland (e-mail: pirjo.nuutila{at}utu.fi)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 DISCLOSURE
 REFERENCES
 

  1. American Society of Nuclear Cardiology. Imaging guidelines for nuclear cardiology procedures, part 2. J Nucl Cardiol 6: G47–G84, 1999.[CrossRef][Medline]
  2. Abate N, Garg A, Coleman R, Grundy SM, and Peshock RM. Prediction of total subcutaneous abdominal, intraperitoneal, and retroperitoneal adipose tissue masses in men by a single axial magnetic resonance imaging slice. Am J Clin Nutr 65: 403–408, 1997.[Abstract/Free Full Text]
  3. Akahoshi M, Amasaki Y, Soda M, Tominaga T, Ichimaru S, Nakashima E, Seto S, and Yano K. Correlation between fatty liver and coronary risk factors: a population study of elderly men and women in Nagasaki, Japan. Hypertens Res 24: 337–343, 2001.[Medline]
  4. Alberti KG and Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 15: 539–553, 1998.[CrossRef][ISI][Medline]
  5. Anderwald C, Bernroider E, Krssak M, Stingl H, Brehm A, Bischof MG, Nowotny P, Roden M, and Waldhausl W. Effects of insulin treatment in type 2 diabetic patients on intracellular lipid content in liver and skeletal muscle. Diabetes 51: 3025–3032, 2002.[Abstract/Free Full Text]
  6. Angulo P. Nonalcoholic fatty liver disease. N Engl J Med 346: 1221–1231, 2002.[Free Full Text]
  7. Aronson D, Rayfield EJ, and Chesebro JH. Mechanisms determining course and outcome of diabetic patients who have had acute myocardial infarction. Ann Intern Med 126: 296–306, 1997.[Abstract/Free Full Text]
  8. Brea A, Mosquera D, Martin E, Arizti A, Cordero JL, and Ros E. Nonalcoholic fatty liver disease is associated with carotid atherosclerosis. A case-control study. Arterioscler Thromb Vasc Biol 25: 1045–1050, 2005.[Abstract/Free Full Text]
  9. Brunken R, Schwaiger M, Grover-McKay M, Phelps ME, Tillisch J, and Schelbert HR. Positron emission tomography detects tissue metabolic activity in myocardial segments with persistent thallium perfusion defects. J Am Coll Cardiol 10: 557–567, 1987.[Abstract]
  10. Brunken RC, Kottou S, Nienaber CA, Schwaiger M, Ratib OM, Phelps ME, and Schelbert HR. PET detection of viable tissue in myocardial segments with persistent defects at T1-201 SPECT. Radiology 172: 65–73, 1989.[Abstract/Free Full Text]
  11. Bugianesi E, McCullough AJ, and Marchesini G. Insulin resistance: a metabolic pathway to chronic liver disease. Hepatology 42: 987–1000, 2005.[CrossRef][ISI][Medline]
  12. Buja LM. Does atherosclerosis have an infectious etiology? Circulation 94: 872–873, 1996.[Free Full Text]
  13. Camici P, Ferrannini E, and Opie LH. Myocardial metabolism in ischemic heart disease: basic principles and application to imaging by positron emission tomography. Prog Cardiovasc Dis 32: 217–238, 1989.[CrossRef][ISI][Medline]
  14. DeFronzo RA, Tobin JD, and Andres R. Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol Endocrinol Metab Gastrointest Physiol 237: E214–E223, 1979.[Abstract/Free Full Text]
  15. Donhoffer H. Quantitative estimation of lipids in needle biopsy sized specimens of cadaver liver. Acta Med Acad Sci Hung 31: 47–49, 1974.[Medline]
  16. Donnelly KL, Smith CI, Schwarzenberg SJ, Jessurun J, Boldt MD, and Parks EJ. Sources of fatty acids stored in liver and secreted via lipoproteins in patients with nonalcoholic fatty liver disease. J Clin Invest 115: 1343–1351, 2005.[CrossRef][ISI][Medline]
  17. Egert S, Nguyen N, Brosius FC, III, and Schwaiger M. Effects of wortmannin on insulin- and ischemia-induced stimulation of GLUT4 translocation and FDG uptake in perfused rat hearts. Cardiovasc Res 35: 283–293, 1997.[Abstract/Free Full Text]
  18. Hallsten K, Virtanen KA, Lonnqvist F, Sipila H, Oksanen A, Viljanen T, Ronnemaa T, Viikari J, Knuuti J, and Nuutila P. Rosiglitazone but not metformin enhances insulin- and exercise-stimulated skeletal muscle glucose uptake in patients with newly diagnosed type 2 diabetes. Diabetes 51: 3479–3485, 2002.[Abstract/Free Full Text]
  19. Hamacher K, Coenen HH, and Stocklin G. Efficient stereospecific synthesis of no-carrier-added 2-[18F]-fluoro-2-deoxy-D-glucose using aminopolyether supported nucleophilic substitution. J Nucl Med 27: 235–238, 1986.[Abstract/Free Full Text]
  20. Hamaguchi M, Kojima T, Takeda N, Nakagawa T, Taniguchi H, Fujii K, Omatsu T, Nakajima T, Sarui H, Shimazaki M, Kato T, Okuda J, and Ida K. The metabolic syndrome as a predictor of nonalcoholic fatty liver disease. Ann Intern Med 143: 722–728, 2005.[Abstract/Free Full Text]
  21. Iida H, Rhodes CG, de Silva R, Araujo LI, Bloomfield PM, Lammertsma AA, and Jones T. Use of the left ventricular time-activity curve as a noninvasive input function in dynamic oxygen-15-water positron emission tomography. J Nucl Med 33: 1669–1677, 1992.[Abstract/Free Full Text]
  22. Iida H, Takahashi A, Tamura Y, Ono Y, and Lammertsma AA. Myocardial blood flow: comparison of oxygen-15-water bolus injection, slow infusion and oxygen-15-carbon dioxide slow inhalation. J Nucl Med 36: 78–85, 1995.[Abstract/Free Full Text]
  23. Iozzo P, Chareonthaitawee P, Dutka D, Betteridge DJ, Ferrannini E, and Camici PG. Independent association of type 2 diabetes and coronary artery disease with myocardial insulin resistance. Diabetes 51: 3020–3024, 2002.[Abstract/Free Full Text]
  24. Jarvisalo MJ, Harmoinen A, Hakanen M, Paakkunainen U, Viikari J, Hartiala J, Lehtimaki T, Simell O, and Raitakari OT. Elevated serum C-reactive protein levels and early arterial changes in healthy children. Arterioscler Thromb Vasc Biol 22: 1323–1328, 2002.[Abstract/Free Full Text]
  25. Knuuti MJ, Maki M, Yki-Jarvinen H, Voipio-Pulkki LM, Harkonen R, Haaparanta M, and Nuutila P. The effect of insulin and FFA on myocardial glucose uptake. J Mol Cell Cardiol 27: 1359–1367, 1995.[CrossRef][ISI][Medline]
  26. Knuuti MJ, Nuutila P, Ruotsalainen U, Saraste M, Harkonen R, Ahonen A, Teras M, Haaparanta M, Wegelius U, and Haapanen A. Euglycemic hyperinsulinemic clamp and oral glucose load in stimulating myocardial glucose utilization during positron emission tomography. J Nucl Med 33: 1255–1262, 1992.[Abstract/Free Full Text]
  27. Krebs M, Geiger M, Polak K, Vales A, Schmetterer L, Wagner OF, Waldhausl W, Binder BR, and Roden M. Increased plasma levels of plasminogen activator inhibitor-1 and soluble vascular cell adhesion molecule after triacylglycerol infusion in man. Thromb Haemost 90: 422–428, 2003.[Medline]
  28. Kurkijarvi R, Adams DH, Leino R, Mottonen T, Jalkanen S, and Salmi M. Circulating form of human vascular adhesion protein-1 (VAP-1): increased serum levels in inflammatory liver diseases. J Immunol 161: 1549–1557, 1998.[Abstract/Free Full Text]
  29. Kurkijarvi R, Yegutkin GG, Gunson BK, Jalkanen S, Salmi M, and Adams DH. Circulating soluble vascular adhesion protein 1 accounts for the increased serum monoamine oxidase activity in chronic liver disease. Gastroenterology 119: 1096–1103, 2000.[CrossRef][Medline]
  30. Lautamaki R, Airaksinen KE, Seppanen M, Toikka J, Luotolahti M, Ball E, Borra R, Harkonen R, Iozzo P, Stewart M, Knuuti J, and Nuutila P. Rosiglitazone improves myocardial glucose uptake in patients with type 2 diabetes and coronary artery disease: a 16-week randomized, double-blind, placebo-controlled study. Diabetes 54: 2787–2794, 2005.[Abstract/Free Full Text]
  31. Law WR and McLane MP. Adrenergic, insulin, and work interactions with adenosine's effects on in situ myocardial glucose uptake. Cardiovasc Res 31: 691–698, 1996.[Abstract/Free Full Text]
  32. Listenberger LL, Ory DS, and Schaffer JE. Palmitate-induced apoptosis can occur through a ceramide-independent pathway. J Biol Chem 276: 14890–14895, 2001.[Abstract/Free Full Text]
  33. Longo R, Pollesello P, Ricci C, Masutti F, Kvam BJ, Bercich L, Croce LS, Grigolato P, Paoletti S, de Bernard B, Tiribelli C, and Dalla Palma L. Proton MR spectroscopy in quantitative in vivo determination of fat content in human liver steatosis. J Magn Reson Imaging 5: 281–285, 1995.[ISI][Medline]
  34. Maki M, Luotolahti M, Nuutila P, Iida H, Voipio-Pulkki LM, Ruotsalainen U, Haaparanta M, Solin O, Hartiala J, Harkonen R, and Knuuti J. Glucose uptake in the chronically dysfunctional but viable myocardium. Circulation 93: 1658–1666, 1996.[Abstract/Free Full Text]
  35. Marchesini G, Brizi M, Morselli-Labate AM, Bianchi G, Bugianesi E, McCullough AJ, Forlani G, and Melchionda N. Association of nonalcoholic fatty liver disease with insulin resistance. Am J Med 107: 450–455, 1999.[CrossRef][ISI][Medline]
  36. McFalls EO, Baldwin D, Marx D, Fashingbauer P, and Ward HB. Effect of regional hyperemia on myocardial uptake of 2-deoxy-2-[18F]fluoro-D-glucose. Am J Physiol Endocrinol Metab 278: E96–E102, 2000.[Abstract/Free Full Text]
  37. Mullenix PS, Andersen CA, and Starnes BW. Atherosclerosis as inflammation. Ann Vasc Surg 19: 130–138, 2005.[CrossRef][ISI][Medline]
  38. Ng CK, Soufer R, and McNulty PH. Effect of hyperinsulinemia on myocardial fluorine-18-FDG uptake. J Nucl Med 39: 379–383, 1998.[Abstract/Free Full Text]
  39. Nuutila P, Knuuti MJ, Raitakari M, Ruotsalainen U, Teras M, Voipio-Pulkki LM, Haaparanta M, Solin O, Wegelius U, and Yki-Järvinen H. Effect of antilipolysis on heart and skeletal muscle glucose uptake in overnight fasted humans, Am J Physiol Endocrinol Metab 267: E941–E946, 1994.[Abstract/Free Full Text]
  40. Nuutila P, Koivisto VA, Knuuti J, Ruotsalainen U, Teras M, Haaparanta M, Bergman J, Solin O, Voipio-Pulkki LM, Wegelius U, and Yki-Jarvinen H. Glucose-free fatty acid cycle operates in human heart and skeletal muscle in vivo. J Clin Invest 89: 1767–1774, 1992.[ISI][Medline]
  41. Peltoniemi P, Lonnroth P, Laine H, Oikonen V, Tolvanen T, Gronroos T, Strindberg L, Knuuti J, and Nuutila P. Lumped constant for [18F]fluorodeoxyglucose in skeletal muscles of obese and nonobese humans. Am J Physiol Endocrinol Metab 279: E1122–E1130, 2000.[Abstract/Free Full Text]
  42. Salmi M, Stolen C, Jousilahti P, Yegutkin GG, Tapanainen P, Janatuinen T, Knip M, Jalkanen S, and Salomaa V. Insulin-regulated increase of soluble vascular adhesion protein-1 in diabetes. Am J Pathol 161: 2255–2262, 2002.[Abstract/Free Full Text]
  43. Sipilä H, Clark J, Peltola O, and Teräs M. An automatic [15O]H2O production system for heart and brain studies (Abstract). J Labelled Cpd Radiopharm 44, Suppl 1: 1066–1068, 2001.
  44. Sjoholm A and Nystrom T. Endothelial inflammation in insulin resistance. Lancet 365: 610–612, 2005.[ISI][Medline]
  45. Sokoloff L, Reivich M, Kennedy C, Des Rosiers MH, Patlak CS, Pettigrew KD, Sakurada O, and Shinohara M. The [14C]deoxyglucose method for the measurement of local cerebral glucose utilization: theory, procedure, and normal values in the conscious and anesthetized albino rat. J Neurochem 28: 897–916, 1977.[ISI][Medline]
  46. Stolen CM, Madanat R, Marti L, Kari S, Yegutkin GG, Sariola H, Zorzano A, and Jalkanen S. Semicarbazide sensitive amine oxidase overexpression has dual consequences: insulin mimicry and diabetes-like complications. FASEB J 18: 702–704, 2004.[Abstract/Free Full Text]
  47. Sundell J, Nuutila P, Laine H, Luotolahti M, Kalliokoski K, Raitakari O, and Knuuti J. Dose-dependent vasodilating effects of insulin on adenosine-stimulated myocardial blood flow. Diabetes 51: 1125–1130, 2002.[Abstract/Free Full Text]
  48. Sundell J, Ronnemaa T, Laine H, Raitakari OT, Luotolahti M, Nuutila P, and Knuuti J. High-sensitivity C-reactive protein and impaired coronary vasoreactivity in young men with uncomplicated type 1 diabetes. Diabetologia 47: 1888–1894, 2004.[CrossRef][Medline]
  49. Szczepaniak LS, Babcock EE, Schick F, Dobbins RL, Garg A, Burns DK, McGarry JD, and Stein DT. Measurement of intracellular triglyceride stores by H spectroscopy: validation in vivo. Am J Physiol Endocrinol Metab 276: E977–E989, 1999.[Abstract/Free Full Text]
  50. Taegtmeyer H, McNulty P, and Young ME. Adaptation and maladaptation of the heart in diabetes: Part I: general concepts. Circulation 105: 1727–1733, 2002.[Free Full Text]
  51. Targher G. Associations between liver histology and early carotid atherosclerosis in subjects with nonalcoholic fatty liver disease. Hepatology 42: 974–975, 2005.[Medline]
  52. Targher G, Bertolini L, Padovani R, Zenari L, Zoppini G, and Falezza G. Relation of nonalcoholic hepatic steatosis to early carotid atherosclerosis in healthy men: role of visceral fat accumulation. Diabetes Care 27: 2498–2500, 2004.[Free Full Text]
  53. Targher G, Bertolini L, Poli F, Rodella S, Scala L, Tessari R, Zenari L, and Falezza G. Nonalcoholic fatty liver disease and risk of future cardiovascular events among type 2 diabetic patients. Diabetes 54: 3541–3546, 2005.[Abstract/Free Full Text]
  54. Thomsen C, Becker U, Winkler K, Christoffersen P, Jensen M, and Henriksen O. Quantification of liver fat using magnetic resonance spectroscopy. Magn Reson Imaging 12: 487–495, 1994.[CrossRef][ISI][Medline]
  55. Unger RH and Orci L. Diseases of liporegulation: new perspective on obesity and related disorders. FASEB J 15: 312–321, 2001.[Abstract/Free Full Text]
  56. Vanhamme L, van den Booogaart A, and Van Huffel S. Improved method for accurate and efficient quantification of MRS data with use of prior knowledge. J Magn Reson 129: 35–43, 1997.[CrossRef][ISI][Medline]
  57. Villanova N, Moscatiello S, Ramilli S, Bugianesi E, Magalotti D, Vanni E, Zoli M, and Marchesini G. Endothelial dysfunction and cardiovascular risk profile in nonalcoholic fatty liver disease. Hepatology 42: 473–480, 2005.[CrossRef][ISI][Medline]
  58. Yeh ET and Willerson JT. Coming of age of C-reactive protein: using inflammation markers in cardiology. Circulation 107: 370–371, 2003.[Free Full Text]
  59. Young ME, McNulty P, and Taegtmeyer H. Adaptation and maladaptation of the heart in diabetes: Part II: potential mechanisms. Circulation 105: 1861–1870, 2002.[Free Full Text]
  60. Zhou YT, Grayburn P, Karim A, Shimabukuro M, Higa M, Baetens D, Orci L, and Unger RH. Lipotoxic heart disease in obese rats: implications for human obesity. Proc Natl Acad Sci USA 97: 1784–1789, 2000.[Abstract/Free Full Text]



This article has been cited by other articles:


Home page
 HypertensionHome page
R. Harmancey, C. R. Wilson, and H. Taegtmeyer
Adaptation and Maladaptation of the Heart in Obesity
Hypertension, August 1, 2008; 52(2): 181 - 187.
[Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
291/2/E282    most recent
00604.2005v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (8)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Lautamäki, R.
Right arrow Articles by Nuutila, P.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Lautamäki, R.
Right arrow Articles by Nuutila, P.

HOME HELP