1 Research Division, Joslin Diabetes Center, and Department of Medicine, Harvard Medical School, Boston, Massachusetts
2 Division of Endocrinology, Childrens Hospital, Boston, Massachusetts
3 Department of Biochemistry, University of Wisconsin, Madison, Wisconsin
4 Department of Nutritional Sciences, University of Wisconsin, Madison, Wisconsin
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ABSTRACT |
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The metabolic syndrome is a constellation of findings, including central obesity, insulin resistance, dyslipidemia, hypertension, and hepatic steatosis, which predispose to diabetes, cardiovascular disease, and cancer. As the prevalence of diabetes, obesity, and the metabolic syndrome reach staggering proportions, much attention has been focused on their etiologies and the relationship among them (1,2). Although both genetic and environmental factors clearly play a role, exactly how these factors interact to produce the metabolic syndrome and its various components remains unclear.
In most humans, insulin resistance appears to be polygenic and heterogeneous (3). Thus, there are multiple genes that potentially contribute to the phenotype, and the development of disease in any individual may involve only a specific subset of these genes that varies from population to population. High-risk populations predisposed to the development of obesity and insulin resistance, such as Pima Indians and Mexican Americans, are thought to be enriched for clusters of genes acting together to produce the metabolic syndrome in the context of an appropriate environmental trigger, such as the high-fat western diet.
Dysregulation of hepatic lipid metabolism may play a central role in the pathogenesis of the metabolic syndrome. McGarry (7) has proposed that increased synthesis of lipids by the liver produces insulin resistance in other tissues, such as muscle. Increased storage of lipids in the liver results in fatty changes that are now known to be a feature of the metabolic syndrome (8). These changes form a spectrum of pathology, labeled nonalcoholic fatty liver disease, ranging from simple benign steatosis to nonalcoholic steatohepatitis, which can progress to cirrhosis and liver failure (9). It is thought that nonalcoholic fatty liver disease may now be the most common cause of cryptogenic cirrhosis in this country (10). Patients with the metabolic syndrome also typically have increased triglycerides and decreased HDL (11). Dyslipidemia is closely tied to the cardiovascular morbidities associated with the metabolic syndrome and may be attributed, at least in part, to the aberrant handling of lipids by the liver (12).
To understand how genes interact with dietary fat to produce the changes in lipid metabolism that occur in the metabolic syndrome, we used two strains of mice, representing differences in susceptibility to the development of insulin resistance. C57Bl/6 (B6) mice have previously been shown to develop diabetes when subjected to genetically induced insulin resistance due to a double heterozygous deletion of one insulin receptor allele and one insulin receptor substrate-1 allele (13,14). 129Sv (129) mice on the other hand are protected from diabetes when carrying the same insulin receptor/insulin receptor substrate-1 double heterozygous defect. In the present study, B6 and 129 mice were placed on two extremes of diet: a low-fat diet (LFD; 14% calories from fat) and a high-fat diet (HFD; 55% calories from fat). We have compared the effects of genetic and dietary factors not only on glucose, but also on serum and hepatic lipid profiles and hepatic lipogenic gene expression, to better understand how these factors alter lipid metabolism and to identify the key elements controlling the progression of the metabolic syndrome.
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RESEARCH DESIGN AND METHODS |
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Serum lipid analysis.
Equal volumes of serum from three to four mice fasted for 6 h (beginning in the morning) were pooled. Cholesterol and triglycerides were measured using Sigma kits 352 and 339, adapted for microtiter plates. Additionally, the serum was subjected to fast-performance liquid chromatography (FPLC) as previously described (15), and cholesterol was measured in the eluted fractions. Serum lipid analysis was performed by the Lipid, Lipoprotein and Atherosclerosis Core of the Vanderbilt Mouse Metabolic Phenotyping Centers.
Immunohistochemistry.
Livers from the dead animals were frozen in liquid nitrogen, embedded in an optimal temperature cutting compound, and cut into 6-µm sections. Hematoxylin/eosin and Oil-Red-O staining was performed using standard techniques.
Hepatic lipid analysis.
Hepatic lipid analysis was performed by the Lipid, Lipoprotein and Atherosclerosis Core of the Vanderbilt Mouse Metabolic Phenotyping Centers. Lipids were extracted, filtered, and recovered in the chloroform phase. Individual lipid classes were separated by thin-layer chromatography using Silica Gel 60 A plates and visualized by rhodamine 6G. Phospholipids, triglycerides, and cholesterol esters were scraped, methylated, and analyzed by gas chromatography (16,17).
Oligonucleotide microarrays.
Total RNA (25 µg) was pooled from two to three animals to make cRNA as described previously (18). cRNA (15 µg) was hybridized on Affymetrix murine chips U74Av.2, with four chips representing each group. Data were analyzed using MAS v5, with each chip being normalized to an average intensity of 1,500.
Real-time PCR.
Total RNA was extracted and purified using the RNeasy kit (Qiagen) and used to direct cDNA synthesis using the RT for PCR kit (Clontech). RT-PCR was performed using SYBR green master mix (ABI), 5% of the cDNA synthesis reaction, and 300 nmol/l of the relevant primers. Sterol regulatory element-binding protein (SREBP)-1c and SREBP-1a primers were isoform specific and have been previously described (19). Other primers were as follows: suppressor of cytokine signaling (SOCS)-3, 5'-CCTCGGGGACCATAGGAG-3' and 5'-AACTTGCTGTGGGTGACCAT-3'; SREBP-2, 5'GCGTTCTGGAGACCATGGA-3' and 5'-ACAAAGTTGCTCTGAAAACAAATCA-3'; peroxisome proliferator-activated receptor- coactivator (PGC)-1
, 5'-GTCAACAGCAAAAGCCACAA-3' and 5'-TCTGGGGTCAGAGGAAGAGAg-3'; and PGC-1ß, 5'-CCCTGTCCGTGAGGAACG-3' and 5'-ATCCATGGCTTCGTACTTGC-3'. The primers were found to amplify linearly. Because common housekeeping genes such as TATA- binding protein and the ribosomal protein 36B4 varied between strains, expression was normalized to the input RNA and calculated as a function of 2Ct.
Immunoblotting of SREBP-1.
Nuclear protein extracts of mouse liver were prepared as described by Sheng et al. (20). For each condition, equal portions of two to three mouse livers were pooled to produce nuclear extracts; these experiments were done in duplicate or triplicate. Immunoblotting was performed per the Amersham ECL detection system kit protocol, except that the washing solutions were supplemented with 0.1% SDS (wt/vol), 1% (vol/vol) Nonidet P-40, and 0.5% (wt/vol) sodium deoxycholate. Antibodies against mouse SREBP-1 have been previously described (21).
Stearoyl-CoA desaturase enzymatic activity.
Conversion of [1-14C]stearoyl-CoA to [1-14C]oleate was used to measure stearoyl-CoA desaturase (SCD) enzyme activity from microsomes prepared from individual liver extracts as previously described (22).
Immunoblotting of SOCS-3.
Approximately 100 mg frozen liver from 16-week-old male mice, fed an HFD for 6 weeks, was homogenized in 25 mmol/l Tris 7.4, 2 mmol/l Na3VO4, 10 mmol/l NaF, 10 mmol/l Na4P2O7, 1 mmol/l EGTA, 1 mmol/l EDTA, 1% NP40, and one protease inhibitor tablet (Complete Protease Inhibitor tablets; Roche) in 50 ml and subjected to ultracentrifugation at 50,000 rpm for 45 min in a TLA100.2 rotor. Protein concentration was determined using a Bradford Assay (Bio-Rad). Protein (75 µg) was subjected to SDS-PAGE, and immunoblotting was performed using a Roche Chemiluminescence Kit with antibodies against SOCS-3 (Santa Cruz).
Statistical analysis.
Statistically significant effects of diet and strain were identified using a two-way ANOVA model with interaction. Normality of the data was assessed by the histogram and normal probability plot of residuals of the ANOVA model. Data exhibiting significant departure from normality were transformed in logarithmic scale and refit. In each ANOVA model, the significance of the interaction term was assessed first, and, if the interaction was not statistically significant (P < 0.05), the significance of main effects was assessed. The analyses were carried out using the GLM procedure in SAS version 8.2. Unless otherwise indicated, data are presented as the mean ± SE.
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RESULTS |
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High-fat feeding of both 129 and B6 mice led to significant increases in serum cholesterol (Fig. 1A). FPLC analysis revealed that the excess cholesterol was associated with the HDL fractions in both strains but that B6 mice also had an increase in LDL cholesterol. Even on the LFD, B6 mice had higher levels of LDL cholesterol than 129 mice, although their total serum cholesterol was slightly lower.
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Hepatic steatosis.
It is now recognized that hepatic steatosis is an important component of the metabolic syndrome. Hematoxylin and eosin staining showed normal liver architecture in both 129 and B6 mice fed an LFD (Fig. 2A). On an HFD, 129 mice showed microvesicular fat accumulation, consistent with a mild degree of hepatic steatosis. B6 mice on the other hand showed more profound steatosis with macrovesicular fat accumulation. These changes were confirmed with Oil-Red-O staining (Fig. 2B). Thus, the presence of steatosis appeared to depend on diet, whereas genetic factors were important in determining the degree of steatosis.
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Hepatic lipid profiling.
To further analyze the changes in hepatic lipid accumulation, the distribution of fatty acids in each of the major lipid fractions was performed using gas chromatography, yielding several insights (Table 1 of online appendix [available at http://diabetes.diabetesjournals.org]). First, in the phospholipid fraction, high-fat feeding led to a decrease in the relative contributions of several polyunsaturated fatty acids such as 18:2, 22:5, and 22:6, but not 20:4. Arachidonic acid (20:4) is a precursor of the prostaglandins and leukotrienes, which are potent mediators of inflammation (25). The relative abundance of arachidonic acid in the phospholipid fraction was increased 40% in both 129 and B6 mice by the HFD.
Another intriguing finding was the relative increase in MUFAs by both high-fat feeding and B6 background. This is depicted in Fig. 3 as the ratio of the monounsaturated (16:1 + 18:1) fatty acids to the saturated fatty acids (16:0 + 18:0). This ratio was increased by both high-fat feeding and B6 genetic background in the triglyceride and phospholipid fractions, although there was no significant change in the cholesterol ester fraction.
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Changes in SCD1 with genetic background and diet.
The increase in monounsaturated fatty acid content with diet and genetic background seen in Fig. 3 suggests that there might also be changes in SCD1. Stearoyl-CoA desaturases are the rate-determining enzymes in the synthesis of MUFAs, introducing a double bond at the -9 position converting palmitate (16:0) to palmitoleate (16:1) and stearate (18:0) to oleate (18:1) (11). There are four known isoforms of SCD in mice, with SCD1 being the dominant form in liver. Because SCD1 is a target of SREBP-1c, one might expect changes in SCD1 expression (27). As shown in Fig. 6A, SCD1 mRNA was increased 3-fold by high-fat feeding of 129 mice and 1.5-fold by high-fat feeding of B6 mice. There was also a dramatic difference between strains, with B6 LFD mice having three to four times more SCD1 transcript than 129 LFD mice.
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Other candidate genes.
PGC-1 and PGC-1ß are transcriptional coactivators that are important in directing energy metabolism. They coordinate the livers response to fasting by activating numerous processes including gluconeogenesis, mitochondrial biogenesis, and fatty acid oxidation (28,29). Using real-time PCR, we found that high-fat feeding increases PGC-1
by approximately twofold in the B6 strain (Fig. 7A). However, high-fat feeding had no effect on PGC-1
mRNA in the 129 strain. There were no significant effects of diet or strain on PGC-1ß (Fig. 7B).
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DISCUSSION |
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In certain respects, both 129 and B6 strains respond similarly to high-fat feeding. On the HFD, both gain more weight and develop hypercholesterolemia, a reduction in serum triglycerides, and an increase in hepatic lipid accumulation. They both accrue triglycerides and phospholipids enriched in monounsaturated fatty acids. We also find that both strains of mice have a relative increase in phospholipid-associated arachidonate (20:4) when exposed to an HFD. Because arachidonate is the precursor for prostaglandins and leukotrienes, which are potent mediators of inflammation, it is tempting to speculate that its increased abundance contributes to the proinflammatory state associated with the metabolic syndrome (33,34). Finally, both strains respond to high-fat feeding with an increase in glycerol-3-PO4 acyltransferase and long-chain fatty acyl elongase, a finding also noted in other strains of mice (35).
Despite similarities in their response to high-fat feeding, dramatic differences exist between the two strains. B6 mice are more obese, glucose intolerant, hyperinsulinemic, and hyperleptinemic than 129 mice on either diet. Whereas both strains develop hypercholesterolemia in response to high-fat feeding, the excess in serum cholesterol is associated with HDL particles in 129 HFD mice, but both LDL and HDL particles in B6 HFD mice. B6 mice also have a higher content of liver triglycerides and an increased abundance of MUFAs in the triglyceride fraction. The expression of fatty acid synthase, malic enzyme, and citrate lyase was also higher in B6 mice compared with 129 mice.
These changes in lipogenic gene expression and MUFA content found with transcriptional and lipid profiling suggested that there might be changes in SREBP-1c, a transcription factor capable of activating transcription of all the enzymes required for MUFA synthesis, and SCD1, which catalyzes the rate-determining step in the production of MUFAs. Indeed, both SREBP-1c mRNA and nuclear protein and SCD1 mRNA and activity are increased by high-fat feeding and the B6 genetic background. Our findings are somewhat in contrast to those of Kakuma et al. (38) that Sprague-Dawley rats fed an HFD for 6 weeks have an 80% suppression of SCD1 transcript. Whether this represents a difference in species or the duration of high-fat feeding is unknown, but clearly the effect of prolonged high-fat feeding in our study is to increase both mRNA and activity of this enzyme, and this is consistent with the increased MUFA content of the triglyceride and phospholipid fractions.
The importance of SREBP-1c in regulating lipid metabolism is illustrated by transgenic mice expressing a truncated constitutively active form of SREBP-1c. These mice have increased transcription of all the enzymes needed for the synthesis of unsaturated fatty acids (27), increased hepatic lipid synthesis, particularly MUFAs, and hepatic steatosis (39). Additionally, SREBP-1c transgenic mice, like B6 mice, have decreased serum triglycerides; this is thought to be due to the fourfold induction of lipoprotein lipase transcription by SREBP-1c resulting in increased triglyceride clearance (39). Conversely, ob/ob mice with a superimposed knockout of SREBP-1 do not develop the massive steatosis characteristic of ob/ob mice. Thus, SREBP-1 appears to be necessary and sufficient for the development of steatosis.
SCD1 activation also appears to be required for the development of hepatic steatosis, since ob/ob mice with a knockout of SCD1 do not develop steatosis (22,40). Interestingly, ob/ob mice with a knockout of SCD1 also have decreased obesity and increased energy expenditure compared with ob/ob mice (22). Similarly, SCD1 knockout mice without leptin deficiency exhibit increased insulin sensitivity, energy expenditure, and fatty acid oxidation and are resistant to diet-induced obesity compared with wild-type controls (41). These data are consistent with a global role for SCD1 in regulating energy metabolism.
The dramatic increases in SREBP-1c and SCD1 observed in leptin-deficient ob/ob mice and lipoatrophic mice (22,43,44) are thought to mediate, at least in part, the hepatic steatosis and insulin resistance found in these models. Our data suggest that even more modest changes in SREBP-1c and SCD1 resulting from differences in genetic background or diet may produce similar effects, and account for some of the phenotypic differences between the B6 and other strains. For example, B6 mice, with relatively high levels of SREBP-1c and SCD1 have been shown in this study and others to have a genetic predisposition toward steatosis and low serum triglycerides. Thus, the A-ZIP/F-1 mutation causes lipoatrophy and severe hyperinsulinemia on both B6 and FVB/N backgrounds (24). However, lipoatrophic B6 mice have more marked steatosis and lower serum triglycerides than lipoatrophic FVB/N mice. Similarly, the ob/ob mutation also leads to worsened steatosis but decreased serum triglycerides on the B6 background compared with the FVB/N background (23). Conversely, 129 mice, with relatively low levels of SCD1, are somewhat similar to the SCD1 knockout mouse. They have previously been shown to gain less weight than B6 mice while eating more and being less active (50). The metabolic rate of 129 mice, measured by O2 consumption, is 6 and 14% higher than that of B6 mice on the LFD and HFD, respectively (50).
The mechanism by which SREBP-1c and SCD1 are activated by the B6 genetic background is not clear. Neither SREBP-1c nor SCD1 is near the quantitative trait loci thus far associated with insulin resistance in these strains. Because insulin is a known positive regulator of both genes, it is possible that changes in SREBP-1c and SCD1 are secondary to high serum insulin levels. In fact, B6 mice have fivefold higher insulin levels than 129 mice. This may be due to differences in insulin secretion by the islets, since other studies have shown that B6 mice have increased insulin secretion in vivo in response to glucose and arginine compared with 129 mice (45). Furthermore, islets isolated from B6 mice have increased insulin content and sensitivity to glucose compared with those isolated from 129 mice (45).
In summary, we have characterized a model of the metabolic syndrome in which genetic heterogeneity and high-fat feeding interact to produce obesity, insulin resistance, hepatic steatosis, and hypercholesterolemia. Using a combination of transcriptional and lipid profiling, we have identified two key regulators that, at least in part, appear to mediate these changes: SREBP-1c and SCD1. SREBP-1c can be activated by either diet or strain, whereas there is a synergistic effect of diet and strain on SCD1. We propose that these genes are on a common final pathway in the progression of the metabolic syndrome and represent important targets for therapeutic intervention.
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ACKNOWLEDGMENTS |
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The authors wish to thank Laureen Mazzola for technical help, Dr. Paola Sebestiani and Wang Ling for statistical analysis, and Dr. Jay Horton for the antibody to SREBP-1.
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FOOTNOTES |
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Address correspondence and reprint requests to C. Ronald Kahn, Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA 02215. E-mail: c.ronald.kahn{at}joslin.harvard.edu
Received for publication September 29, 2004 and accepted in revised form February 15, 2005
FPLC, fast-performance liquid chromatography; HFD, high-fat diet; LFD, low-fat diet; MUFA, monounsaturated fatty acid; PGC, peroxisome proliferator-activated receptor- coactivator; SCD, stearoyl-CoA desaturase; SOCS, suppressor of cytokine signaling; SREBP, sterol regulatory element-binding protein
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REFERENCES |
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