While lower concentrations of palmitate decrease receptor-mediated insulin degradation in rat hepatocytes, higher concentrations of palmitate concentrations enhance this degradation This can also explain the lack of increased insulin concentrations in the face of increased GLP-1 and GIP.

In humans, most studies on insulin extraction used infusions of mainly polyunsaturated lipids, which revealed either unchanged or lower splanchnic insulin extraction 17 , The marked alterations in hepatic glucose fluxes in humans and the predominant hepatic insulin resistance in mice raise interest in the effects of saturated fatty acids on hepatic gene expression, which has been previously examined mostly upon exposure to polyunsaturated fatty acids The present study showed that a single dose of PO differentially regulated the canonical pathways TWEAK and AHR.

The AHR pathway promotes NAFLD via upregulation of fatty acid transport 42 , which is in line with the observed upregulation of Fabp5 and increase in HCL content in humans. The TNF-related TWEAK is known to promote cell turnover homeostasis through the NF-κB and p38 MAPK pathways and could serve as a biomarker of obesity and T2DM TWEAK was also found to be associated with reduced TG accumulation in palmitic acid—treated hepatocytes and may be involved in hepatic tissue repair The present study cannot prove the activation status of TWEAK, thus making it difficult to interpret the observed downregulation of the Tweak gene and its receptor Tnfrsf12a.

However, recent findings of decreased circulating TWEAK concentrations correlating with obesity and concomitant NAFLD 45 could suggest that inhibition of the TWEAK pathway might increase susceptibility to hepatic injury.

The expression analyses further predicted PO-induced activation of LPS with or without insulin stimulation. This study also found upregulation of Ifit3 , Clec4a3 , Slc22a3 , and C3ar1 , genes regulated by LPS-stimulated macrophages.

These data are in line with the reported increase in LPS concentrations upon high-fat ingestion 28 , 46 resulting from lipid-induced disruption of the intestinal barrier Interestingly, LPS is also known to decrease TWEAK signaling Downstream from LPS, NF-κB was found to be differentially regulated by PO.

Generally known for its proinflammatory properties, NF-κB is also an important antiapoptotic factor 48 , LPS activation and TNF collectively lead to increased TLR4 expression, proinflammatory cytokine production, and inflammation, on the one hand, and NF-κB activation and cytoprotection on the other NF-κB activation leads to modest and short-lived JNK activation, in turn inducing antiapoptotic genes, such as c-FLIP a caspase 8 inhibitor and X-linked inhibitor of apoptosis As a result, the active NF-κB pathway is critical for LPS-induced resistance to hepatotoxicity Additionally, a high-fat diet and obesity are associated with prolonged JNK activation and TNF-induced cell death 51 , Furthermore, the constitutive activation of NF-κB has been associated with severe hepatic and moderate peripheral insulin resistance The present data suggest that a single PO challenge promotes pathways of LPS- and TLR4-mediated inflammation and cytotoxicity, which are buffered by the activation of NF-κB, which in turn contributes to insulin resistance.

This study also found altered regulation of other putative cytoprotective mechanisms including the phospholipase C4 pathway, which is important for hepatic regeneration 54 , and PPARα, which serves as both a canonical pathway and an upstream regulator protecting against NAFLD progression Our analyses of the differential regulation of single genes by saturated fat revealed several genes of interest.

The observed upregulation of G0s2 may contribute to decreased TG clearance, thereby promoting NAFLD The observed greater expression of Arl6 in the present study may also serve to protect against NAFLD, because loss of function of this gene has been implicated in obesity, NAFLD, and diabetes in Bardet-Biedl syndrome Of note, the descriptive nature of the transcriptome analyses and expression profiling carried out in our study does not allow final conclusions to be drawn as to causality.

That is to say, given the results of this study, it is impossible to single out 1 gene, transcription factor, or pathway that is activated by acute exposure to PO and that can be causally linked to either insulin resistance or steatosis. This study offers the advantages of the translational approach in mice and humans, the use of near-physiologic administration of saturated fat, and the comprehensive phenotyping of in vivo hepatic glucose and energy metabolism.

Nevertheless, the results demonstrate marked metabolic and transcriptional changes associated with PO treatment, even in these small groups. Another caveat of this study is that the hepatic expression data obtained in mice are not necessarily transferable to humans, as we could not obtain liver specimens from our human participants for ethical reasons.

The lack of proteomic analysis of the targets identified by Ingenuity software constitutes another limitation of this study. Each pathway and regulator necessitates a thorough study of their role in the pathogenesis of insulin resistance and NAFLD, a task that must be tackled in subsequent studies.

The practical implication of this work is that the PO challenge used in this study most likely resembles the effects of ingestion of a meal rich in saturated fat, e. One such meal would probably be sufficient to induce transient insulin resistance and impair hepatic metabolism, which necessitates the activation of hepatic defense mechanisms.

Other simultaneously ingested biomacromolecules would exacerbate this metabolic challenge The amount and types of fatty acids and carbohydrates in one such meal are in contrast to the diet recommendations of the American Diabetes Association ADA.

Furthermore, intake of monounsaturated fatty acids and carbohydrates from vegetables, fruits, whole grains, and legumes is recommended We presume that lean, healthy individuals are able to compensate adequately for excessive intake of saturated fatty acids, however, sustained and repeated exposure to such nutrients will ultimately lead to chronic insulin resistance and NAFLD.

These results suggest that even lower doses of fatty acids are capable of inducing alterations similar to those observed with ingestion of pure PO. In conclusion, the initial effects of ingestion of saturated fat include a augmented hepatic energy metabolism and lipid storage; b impaired hepatic insulin sensitivity, along with increased GNG flux; and c altered hepatic expression of genes regulating inflammatory and protective pathways, which predispose to and protect against the development of NAFLD.

Fourteen lean, young male volunteers were enrolled in this randomized, controlled crossover trial Figure 1 and Figure 9. Participants were recruited from March through December The sample size calculation was based on a 2-sided, paired t test, assuming a mean difference of EGP of 0.

The random allocation sequence was generated using SAS software SAS Institute by our in-house statistician. The possible order of treatments was randomly permuted in 2 blocks, with 1 extra block being generated to account for dropouts.

Allocation was not concealed. Participants were enrolled and assigned to their treatment order by the study physician. Exclusion criteria included dysglycemia, a family history of T2DM, acute, or chronic diseases, and the use of pharmacological agents known to affect insulin sensitivity, lipid metabolism, or immunological function.

All participants underwent screening that included recording of clinical history, physical examination, bioimpedance assessment of lean body mass, routine laboratory tests, and a g oral glucose tolerance test. Upon inclusion, participants were instructed to maintain their usual physical activity during the study period and to ingest a carbohydrate-rich diet for 3 days before each study day.

They were then randomly assigned to 1 intervention and 8 weeks later to the other intervention. Basal hepatic ATP and HCL values from the study by Gancheva et al. were used as part of the control group data Human study design. Lean, healthy male adults randomly received either PO or VCL on 2 occasions.

Experimental design. Participants arrived at the Clinical Research Center at 5 pm and received a standardized dinner containing approximately kcal at pm. At pm, pm, and am, volunteers drank 1.

Starting at am defined as time point — minutes of the next day, participants drank ml of water containing 0. At —, , and minutes, participants received an oral dose of acetaminophen mg. For EGP calculation, participants received a 5-minute priming bolus 0. At zero time, participants drank either VCL or PO within 10 minutes.

Patients with more than 70 kg BW drank 92 g, and those with less than 70 kg BW drank 80 g of PO ~1. To facilitate ingestion, PO was heated to 60°C, mixed with 1. Oil test drinks were stirred constantly and served hot.

For VCL administration, PO was substituted with Urine was sampled from — to 0 minutes, from to minutes, and from to minutes for the quantification of GNG and GLY. Blood was sampled at —60 and minutes for assessment of GNG. Indirect calorimetry.

Indirect calorimetry IC was performed in the canopy mode using Vmax Encore 29n CareFusion , as described previously 19 , during baseline at — min , intervention at min , and steady-state clamp conditions at min for 20 minutes after a minute adaptation period. RQ, REE, and substrate oxidation rates were calculated as reported previously Nonoxidative glucose disposal was calculated from the difference between rates of glucose disappearance and carbohydrate oxidation.

Metabolites and hormones. Blood samples were immediately chilled, centrifuged, and the supernatants stored at either —20°C or —80°C until analysis. Venous blood glucose concentration was measured immediately using the glucose oxidase method EKF Biosen C-Line glucose analyzer; EKF Diagnostics TG concentration was analyzed enzymatically on a Roche Cobas c Analyzer Roche Diagnostics.

Serum chylomicron content was determined from the TG concentration in the first fraction of density-gradient ultracentrifugation FFA were assayed enzymatically Wako using orlistat to prevent in vitro lipolysis Serum C-peptide, insulin, and plasma glucagon levels were measured by radioimmunoassay EMD Millipore.

Cortisol levels in serum samples were measured by immunoassay using a Siemens Immulite XPi Analyzer GLP-1 and GIP were measured by ELISA TECOmedical; EMD Millipore Glucose and glucuronide 2H enrichment measurements by ex vivo 2H MRS.

The positional enrichment of urinary acetaminophen glucuronide and plasma glucose, resulting from ingestion of 2 H 2 O and acetaminophen at the level of glucose 6-phosphate G6P , was assessed as previously described 30 to estimate the contributions of GNG and GLY to EGP.

Plasma glucose was derivatized to monoacetone glucose MAG , while urinary acetaminophen glucuronide was converted into 5- O -acetyl monoacetone glucuronic lactone MAGLA When plasma glucose enrichment was inadequate, urinary glucuronide enrichment was analyzed instead, since both methods yield identical estimates of EGP contributions 68 , In total, 9 participants yielded sufficient data for NMR analysis, 5 of them for glucuronide.

For MAGLA samples, 5,—10, free-induction decays FIDs were collected. For MAG samples, 20,—40, FIDs were collected. Positional 2 H enrichments of MAG and MAGLA derived from plasma glucose and urinary anion gap AG were determined using the methyl signals as an intramolecular standard All spectra were analyzed using the curve-fitting routine supplied with the NUTS PC-based NMR Spectral Analysis Program Acorn NMR.

Gas chromatography—mass spectrometry. Determination of atom percentage enrichment APE of 2 H in blood glucose was done after deproteinization and derivatization to the aldonitrile-pentaacetate.

Selected ion monitoring was used to determine enrichments of fragments C3 to C6 Supplemental Figure 1, A and B. Average mass units were for endogenous glucose and for D-[6,6- 2 H 2 ]glucose as described previously All measurements were conducted with the volunteers lying in a supine position within a whole-body 3.

Twelve volunteers were studied, including all participants for whom flux measurements were obtained. The effects of PO or VCL on HCL and hepatic ATP concentrations were assessed at baseline and minutes after intervention. For hepatic 1 H MRS, a Q-body coil was used for shimming and HCL acquisition.

Clinical T2-weighted turbo spin-echo TSE images were obtained in the transverse and coronal planes for localization and repositioning of the voxels used for HCL and ATP measurements. Respiratory-triggered 1 H spectra were acquired with a single-voxel 30 × 30 × 20 mm 3 stimulated echo acquisition mode STEAM sequence.

The variables were as follow: repetition time TR 3, ms, echo time 10 ms, and signal averages To accurately assess hepatic lipid volume, sets of non—water-suppressed and water-suppressed 1 H spectra were acquired, using a STEAM sequence TR 3, ms, echo time 10 ms, signal averages 16 ms and variable power and optimization relaxation VAPOR STEAM sequences TR, echo time, and signal averages 3,, 10, and 16 ms, respectively.

Water and lipid peaks were fitted and quantified using the NUTS software package Acorn NMR , and lipid was expressed as the summation of the methyl and methylene fat peaks relative to water content using the equations described in ref. For hepatic 31 P MRS, a cm 31 P circular surface coil Philips Healthcare was placed over the liver for the acquisition of hepatic 31 P spectra.

Afterwards, 31 P-MRS proton-decoupled liver ATP measurements were conducted with a 3D image-selected in vivo spectroscopy 3D-ISIS localized sequence voxel: 60 × 60 × 60 mm 3 , TR: 6, ms, averages: , decoupling: WALTZ-4 [wideband alternating-phase low-power technique for zero-residual splitting —4], time: 13 min.

Liver volume measurements were made from the coronal plane T2-weighted TSE images. Liver glycogen spectra were acquired with a block pulse μs that produced an Ernst angle at a distance of 35 mm. Coil loading was corrected via integration of the right-most peak of a 13 C-enriched sample of formic acid placed within the coil housing.

Glycogen concentrations were determined from the integration of the C1-glycogen resonance zero filling: 4k, effective line broadening: 20 Hz after the addition of 2 scans and baseline correction within NUTS software Acorn NMR Inc. Total AUC were calculated using the trapezoidal method.

Glycogen cycling, i. In order to measure glycogen cycling, isotopic tracer measurements of EGP, GNG, and GP fluxes must be supplemented by a measurement of GLYnet in this case, 13 C MRS GLYnet was calculated from the linear regression of hepatic glycogen content at —2, 0, 2, and 4 hours of PO or VCL ingestion using the least mean squares method.

Whole-body glucose disposal M value was calculated from glucose infusion rates during the clamp steady state. To account for the incorporation of 2 H from 2 H 2 O by GNG during the overnight fast, background D-[6,6- 2 H 2 ]glucose was determined before administration of 2 H 2 O as well as at — minutes on the day of the study.

Consequently, for determination of basal EGP and EGP at the end of the intervention, the background D-[6,6- 2 H 2 ]glucose enrichment from the —minute time point was used for calculations, whereas, during clamp conditions, with GNG being close to zero, the D-[6,6- 2 H 2 ] value before administration of 2 H 2 O was used.

The fractional GP flux contribution to EGP, i. Glycogen cycling was then calculated as: GP — GLYnet. Animals had ad libitum access to water and a standard chow diet. BM and composition MiniSpec LF50; Bruker Optics were measured 1 day prior to the start of the experiment. Experiments under insulin-stimulated conditions.

Six hours later, unrestrained, conscious mice underwent hyperinsulinemic-euglycemic clamps. After minutes of primed-continuous [3- 3 H]glucose infusion 1. A [3- 3 H]glucose infusion 3. Blood glucose concentrations were measured every 10 minutes and target glycemia established by adjusting the GIR.

At minute , 2-[ 14 C]deoxyglucose kBq was injected intravenously to assess tissue-specific Rg rates. Livers were collected, immediately snap-frozen in liquid nitrogen, and stored at —80°C. Blood was collected at culling, and plasma 3 H and 14 C radioactivity was determined in deproteinized plasma before and after 3 H 2 O evaporation to estimate glycolysis rates.

In hepatic lysates, 2-[ 14 C]deoxyglucosephosphate was separated from 2-[ 14 C]deoxyglucose via ion-exchange columns Poly-Prep AG1-X8; Bio-Rad as previously described Radioisotopes were purchased from PerkinElmer and samples measured in an Ultima-Gold Scintillation Cocktail Tri-CarbTR; PerkinElmer Figure Whole-body glucose disposal M value was calculated from the tracer infusion rate, the specific activity of [3- 3 H]glucose, and BW.

Mouse study design. One cohort underwent hyperinsulinemic-euglycemic clamps after receiving either PO or vehicle via gavage A , whereas another identical cohort underwent analysis of tissue and blood samples B.

Biochemical analyses. Blood glucose concentrations were assessed using a Contour hand-held glucometer Bayer Vital. Plasma TG levels were determined by a colorimetric assay Cayman Chemical , and plasma FFA levels were assessed with the FFA-HR 2 -Test Wako. Hepatic TG levels were measured in whole-liver homogenates biochemically with the BioVision Assay.

Experiments under noninsulin-stimulated conditions. Lateral tail vein blood samples were obtained prior to treatment and 2 hours afterward. Six hours after treatment, mice were euthanized with isoflurane, and a vena cava blood sample was collected and centrifuged at 4°C, and plasma aliquots were immediately frozen in liquid nitrogen.

Liver was dissected and immediately snap-frozen in liquid nitrogen Figure Snap-frozen liver samples from both cohorts were processed after administration of PO.

Total RNA was isolated using the mRNeasy Mini Kit QIAGEN. Total RNA ~30 ng was amplified using the Ovation PicoSL WTA System V2 in combination with the Encore Biotin Module both from NuGEN. Amplified cDNA was hybridized on Affymetrix Mouse Gene 2.

Expression Console software version 1. Genewise testing for differential expression was done using the limma t test, and a P value of less than 0. Filters for a fold change greater than 1.

Pathway analyses were generated using the Ingenuity Pathway Analysis QIAGEN; www. The activation Z score helps infer activation states of predicted transcriptional regulators, with values of 2 or more indicating activation and values of —2 or less indicating inhibition. Calculations were performed using GraphPad Prism, version 6.

A P value of less than 0. All participants provided written informed consent before inclusion in the study, which was performed according to the Declaration of Helsinki of and approved by the ethics board of the Heinrich Heine University Düsseldorf.

All animal experiments were approved by the Upper Bavarian district government AZ MR initiated the investigation, led the clinical experiments and wrote, reviewed, and edited the manuscript. EÁH obtained and analyzed the data and wrote, edited, and reviewed the manuscript.

SK obtained and analyzed the data, aided in designing the clinical study, and edited and reviewed the manuscript. AS obtained data and edited and reviewed the manuscript. PB designed the MRS study, obtained MRS data, and reviewed and edited the manuscript. EÁH, SK, AS, and PB contributed equally to this project.

YK interpreted MRS data. BN researched the clinical data and reviewed and edited the manuscript. CB and FC performed derivatization experiments and enrichment analysis for 2 H-MRS. JGJ performed the 2 H-MRS analyses and reviewed and edited the manuscript.

PN conducted analyses and reviewed and edited the manuscript. CH conducted laboratory analyses and reviewed and edited the manuscript. SN and JR supervised the mouse studies and edited and reviewed the manuscript. MI analyzed transcriptomics data and edited and reviewed the manuscript.

JB and MHdA supervised transcriptome analyses and edited and reviewed the manuscript. All authors gave final approval of the version to be published. We thank Ulrike Partke and Anika Morcinietz at the German Diabetes Center Düsseldorf, Germany as well as Anke Bettenbrock, Jürgen Schultheiß, Moya Wu, and Anne Junker at the Helmholtz Center Munich, Germany for their excellent technical support.

We also thank Alessandra Bierwagen at the German Diabetes Center for her guidance with MRS data analysis.

This study was supported in part by the Ministry of Innovation, Science, and Research North Rhine—Westphalia MIWF NRW ; the German Federal Ministry of Health BMG ; as well as by a grant from the Federal Ministry of Education and Research BMBF to the German Center for Diabetes Research DZD e.

Reference information: J Clin Invest. See the related article at Out of the frying pan: dietary saturated fat influences nonalcoholic fatty liver disease. Go to JCI Insight.

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View PDF Download citation information Send a comment Terms of use Standard abbreviations Need help? Email the journal. Top Abstract Introduction Results Discussion Methods Author contributions Supplemental material Acknowledgments Footnotes References Version history. Published in Volume , Issue 2 on February 1, J Clin Invest.

Copyright © , American Society for Clinical Investigation. Published January 23, - Version history Received: July 27, ; Accepted: November 10, Out of the frying pan: dietary saturated fat influences nonalcoholic fatty liver disease.

Elizabeth Parks, … , Hannele Yki-Järvinen, Meredith Hawkins Elizabeth Parks, … , Hannele Yki-Järvinen, Meredith Hawkins. Text PDF. gov NCT Figure 1 CONSORT flow diagram.

Table 1 Anthropometric and blood parameters of study participants. This work will address the interaction of obesity and dietary fatty acids in regulating satiety and energy metabolism. The primary objective is to determine the effects of chronic intake of dietary fatty acids of varied saturation and chain length on satiety, thermogenesis and energy utilization in healthy individuals.

The investigators hypothesize that unsaturated fatty acids will 1 increase satiety and 2 increase energy metabolism and that 3 the fatty acid binding protein polymorphisms are associated with reduced energy expenditure in response to dietary fat intake.

Data sourced from clinicaltrials. Notes about this trial. Status Terminated. Other: LCn3. Other: SFA. Other: PUFA. Other: MUFA. Full description.

Read more. Study type. Funder types. Other U. Federal agency.

Other: PUFA. Other: MUFA. Full description. Read more. Study type. Funder types. Other U. Federal agency. NCT GFHNRC Take notes.

Trial design 1 participants in 4 patient groups. Other group. Patient eligibility Sex All. Ages 20 to 55 years old. Volunteers Accepts Healthy Volunteers. Inclusion criteria. We showed that the health effects of a low protein-high carbohydrate diet are dependent on the type of carbohydrate consumed Starch a polymer of glucose , sucrose a disaccharide of glucose and fructose , and high-fructose corn syrup HFCS; most commonly a ~ mixture of monosaccharide glucose and fructose are the key sources of carbohydrate energy in modern food systems 1 , In the present study, we aimed to use NG to investigate the metabolic consequences of fat-sugar interaction and evaluate if the metabolic outcomes align with the tenets of the CIM or the EBM model.

A total of mice were maintained on one of 18 isocaloric diets containing either lower, medium or higher fat content. Carbohydrates comprised glucose or fructose or their combinations and a fixed level of starch. We also investigated the metabolic consequences of the source of dietary fat plant vs animal.

Mice were fed ad libitum on one of 18 isocaloric ~ Diets were maintained isocaloric by adjusting the content of cellulose which is a commonly used strategy in rodent studies 16 , 19 , Thus, dietary fructose levels increased with decreasing glucose level, and vice versa.

Overall, total fat content increased with decreasing carbohydrate content, and the presence of starch prevented fructose malabsorption, as we reported previously This experimental design facilitated the investigation of the effect of fructose, glucose and fat and their interactions using the NG platform.

This allowed enough scope in the dietary carbohydrate compartment to use amounts of fructose and glucose that could induce detectable phenotypic changes Animals were maintained on experimental diets for 18—19 weeks, and in vivo metabolic parameters were analysed after 5—6 and 12—14 weeks of dietary intervention or as specified Fig.

The interpretation of NG response surfaces is described in detail in the supplementary information, and elsewhere 16 , See Supplementary Data 2 for statistics. Source data are provided as a Source Data file. a Overall study timeline.

Mice were fed on experimental diets for 18—19 weeks. After 5—6 and 12—14 weeks, metabolic parameters were measured.

GTT glucose tolerance test, ITT insulin tolerance test. Along the x-axis, as fructose levels increase, glucose content in the diet decreases. For diets with a fructose:glucose ratio, each monosaccharide was supplied at 3. The fitted lines were derived from generalised additive modelling GAM , fitting an interaction between a smooth term for fructose content in one dimension and fat content as a three-level categorical factor, and the dotted lines represent s.

for fitted values. See Supplementary Information for the details of how to interpret these NG surfaces. Average daily energy intakes were analysed at 5—6 weeks and 12—14 weeks. The major driver of food and energy intake was the ratio of fructose to glucose in the diet, with maximum intake observed on diets containing them in equal parts Intake was lower on diets containing glucose or fructose in isolation.

Reducing dietary fat content further increased total energy intake in the first few weeks of the dietary intervention, but the effect of fat was not statistically significant in the longer-term Fig. S1a , Supplementary Data 2 , 5. Note that fructose:glucose translated into 3.

Commensurate with the intake data, mice consuming fructose:glucose had the highest body weights, mainly due to greater fat mass Fig. S1b—h , Supplementary Data 2 and 5. Gonadal and inguinal white fat pad weights were highest in mice ingesting equal amounts of fructose and glucose Fig.

S2a , Supplementary Data 2 and 6. Increasing fat intake blunted the impact of a fructose-glucose ratio, and the body weights and adiposity of mice with the highest fat intake were minimally influenced by the ratio of fructose and glucose eaten. The body weight and fat mass of the mice with the highest fat intakes were similar to those ingesting lower quantities of fat and fructose:glucose, and higher than those consuming lower amounts of fat and only glucose or only fructose.

This was accompanied by higher gonadal and inguinal fat pad weights with increasing fat intake Fig. S1b—h and Fig. S2a , Supplementary Data 2 , 5 and 6. The purple line in Fig. On the other hand, the brown line also intersects the peak fat mass but shows the impact of increasing total energy intake across diets at a fixed fructose:glucose ratio.

Visual inspection of these purple and brown lines shows that in this study, even at a fixed calorie intake, the ratio of fructose and glucose eaten strongly influenced adiposity. Concurrent with differences in total fat mass, interscapular brown was highest in mice eating fructose:glucose, and energy expenditure measured by indirect calorimetry and normalised to lean mass declined with increasing fat intake Fig.

S2c , Supplementary Data 2 and 6. This decrease in energy expenditure could be partly responsible for a generalised increase in body weight and adiposity with increasing fat consumption Fig.

Of note, absolute energy expenditure and physical activity were not significantly affected by differences in fat, fructose and glucose intake Fig. S2b, d , Supplementary Data 6. Respiratory quotient showed an expected increase with increasing glucose and decreasing fat intake Fig.

S2e , Supplementary Data 6. The hepatokine, fibroblast growth factor FGF21 , is known to increase energy expenditure 22 , and its circulating concentrations increased with increasing total carbohydrate and decreasing fat intake Fig.

Glucose intake was relatively more potent in increasing FGF21 levels than fructose Fig. Insulin sensitivity was assessed by insulin tolerance tests and by measuring the product of fasting blood glucose and fasting blood insulin concentrations similar to HOMA-IR in humans.

Ingestion of a fructose:glucose combination reduced insulin sensitivity Fig. S3a—e , Supplementary Data 3 and 7 , and fat mass significantly correlated with reduced insulin sensitivity Fig. Whereas on low and medium fat intake, insulin sensitivity was relatively worse in mice consuming a mixture of fructose and glucose, high fat intake produced a generalised impairment of insulin sensitivity irrespective of the ratio of fructose to glucose consumed Fig.

S3a—e , Supplementary Data 3 and 7. At weeks 5—6, high carbohydrate intake more strongly increased the product of fasting glucose and fasting insulin than did high fat intake.

However, at weeks 12—14, this pattern was reversed, suggesting that high fat intake is more harmful to fasting glycaemia and insulinaemia in the longer term Fig. S3d, e , Supplementary Data 3 and 7. Moreover, animals consuming a mixture of fructose and glucose in combination with a high fat intake showed the worst glucose tolerance and peak blood insulin concentrations in response to oral administration of a glucose bolus Fig.

S3g, h , Supplementary Data 3 , 7. It is unlikely that in mice with higher fat intake, the greater GTT area under the curve AUC and peak blood insulin concentrations after administration of a glucose bolus merely reflects their chronic exposure to relatively lower carbohydrate diets.

This is because even the fasting blood insulin levels were higher in these mice consuming diets with higher fat-lower carbohydrate content Fig. S3c , Supplementary Data 7. See Supplementary Data 3 for statistics. Increasing values of the AUC for the insulin tolerance test ITT indicate decreasing insulin sensitivity.

Mice co-consuming glucose and fructose, particularly at a ratio of , showed increased hepatic fat content. This was evident both when hepatic fat content was measured by a biochemical assay and on histological assessment of liver tissue Fig. Interestingly, increasing fat intake had a minimal effect on hepatic fat deposition Fig.

See Supplementary Data 4 for statistics. b Relationship between the intake of fructose-, glucose- and fat-derived energy kJ per mouse per day and the risk of increased hepatic fat deposition fitted probabilities is shown.

Slides were scored for liver fat 0 red line , 1 green line , 2 blue line and 3 light blue line , with increasing scores reflecting greater liver fat deposition. c Response surfaces showing the relationship between the intake of fructose-, glucose- and fat-derived energy kJ per mouse per day and liver triglyceride content μmol triglyceride per g tissue in mice fed on experimental diets for 18—19 weeks.

Response surfaces showing the relationship between the intake of fructose-, glucose- and fat-derived energy kJ per mouse per day and the relative expression of fructose metabolism gene Khk d , de novo lipogenesis pathway genes Acly e and Fasn f and inflammation pathway gene Mcp1 g , in liver tissue harvested at weeks 18— Fructose metabolism in the liver by the enzyme ketohexokinase KHK induces the expression of de novo lipogenic DNL genes 4 , High fructose intake produced an expected increase in hepatic Khk expression, which was most pronounced in mice with the lowest fat and the highest total carbohydrate intake Fig.

Similarly, genes associated with fatty acid synthesis Acly and Fasn were expressed at relatively higher levels in mice with higher fructose intakes Fig. Interestingly, the expression of DNL gene Scd1 and glycerol synthesis pathway gene Gpat3 were highest in mice on fructose:glucose Fig.

S4a, b , Supplementary Data 8. This suggests that possibly due to the increase in Gpat3 and Scd1 expression, liver triglyceride content peaked in mice ingesting fructose:glucose and not in mice with the highest fructose intakes.

We observed a decrease in the expression of lipogenic genes with increasing dietary fat intake Fig. This indicates that de novo fat synthesis in the liver decreases as dietary fat intake increases and is consistent with previous findings Moreover, the gene expression of Apolipoprotein-B Apob , which is involved in exporting lipids out of the liver into circulation 25 , also decreased with high fat intake Fig.

S4c , Supplementary Data 8. In contrast, the hepatic expression of the pro-inflammatory gene Mcp1 was highest in mice with the highest fat intake Fig. The patterns of lipogenic gene expression in the liver did not translate into significant changes in circulating triglyceride concentrations Fig.

S4d , Supplementary Data 8. This is consistent with our previous observations that protein intake is the key determinant of triglyceridaemia 16 , In the experiments described above, dietary fat was sourced from plant-based soy oil. Plant oils have a relatively lower saturated fat content especially palmitic acid than animal fats Therefore, we investigated if replacing soy oil with lard altered the nature of fat-fructose-glucose interaction and the associated metabolic outcomes.

For both soy-based and lard-based diets, diets containing a ratio of fructose and glucose led to the highest body weights, absolute and per cent fat mass, and interscapular brown fat pad weight Fig.

S5a, b , while absolute lean mass was similar across the diets Fig. However, the source of fat soy oil vs lard did not make any statistically significant difference to body weight, body composition and energy intake Fig.

Similarly, data for insulin sensitivity, glucose tolerance, peak blood insulin and liver triglyceride content showed that mice fed diets containing fructose and glucose were metabolically the worst but replacing soy oil with lard had no effect Fig. Plasma triglyceride concentrations were also similar in mice-fed diets containing either soy oil or lard Fig.

b Per cent fat mass of mice fed on experimental diets at weeks 12— The numbers of animals for GS, GL, F50G50S, F50G50L, FS and FL were 16, 12, 16, 12, 28 and 16, respectively. Each symbol represents an individual mouse.

c Lean mass of mice fed on experimental diets at weeks 12— No significant difference was reported from two-way ANOVA Tukey—Kramer post hoc test. The numbers of cages for GS, GL, F50G50S, F50G50L, FS and FL were 4, 3, 4, 3, 7 and 4, respectively. Each symbol represents an individual cage.

The numbers of animals for GS, GL, F50G50S, F50G50L, FS and FL were 16, 12, 15, 11, 25 and 15, respectively. b GTT curves and AUC of mice fed on experimental diets at weeks 12— The numbers of animals for GS, GL, F50G50S, F50G50L, FS and FL were 16, 12, 15, 12, 28 and 16 respectively.

Peak blood insulin of mice fed on experimental diets at weeks 12— The numbers of animals for GS, GL, F50G50S, F50G50L, FS and FL were 16, 12, 15, 12, 27 and 16 respectively.

d Liver triglyceride content μmol triglyceride per g tissue in mice fed on experimental diets for 18—19 weeks. In this study, we used nutritional geometry to investigate how the dietary fat-sugar interaction influences metabolic status and if the consequences of this interaction are dependent on the type of sugar fructose vs glucose vs their mixtures and fat soy oil vs lard consumed.

Consistent with our previous work 16 , we found that a mixture of fructose and glucose was more obesogenic than the consumption of fructose or glucose alone. The fructose-glucose ratio increased body weight and adiposity by promoting greater calorie intake as well as ratio-specific effects independent of the caloric value.

Similar to these results, experiments in humans showed that the decrease in appetite scores after consuming a ratio of fructose and glucose was the lowest when compared with various other ratios of fructose and glucose Moreover, our finding that co-ingestion of fructose and glucose led to maximum hepatic fat content is supported by observations in humans and mice where co-ingestion of fructose and glucose was shown to strongly induce de novo lipogenesis in the liver compared with consumption of individual monosaccharides 16 , 30 , The level of fat intake influenced the metabolic effects of consuming a mixture of fructose and glucose.

At low-to-medium fat intakes, body weights and adiposity were highest in mice consuming the fructose-glucose mixture, but at higher fat intakes, the body weights of animals consuming fructose-glucose mixture became very similar to those consuming only fructose or only glucose.

Thus, a high fat intake caused a more generalised increase in adiposity and body weight that was largely independent of the type of sugar in the diet. In addition, compared with the consumption of a mixture of fructose and glucose, a higher fat intake more adversely affected fasting insulin levels, insulin sensitivity and glucose tolerance.

Our results show how certain aspects of both the EBM and the CIM models of obesity could be valid depending on the dietary context. For example, supporting the EBM model, mice with the highest energy intakes, which were achieved on diets containing fructose and glucose, had the highest body weights and adiposity.

Moreover, a higher fat intake caused a greater increase in fasting insulinemia and more adversely affected glucose tolerance than a higher carbohydrate intake. These results are contrary to the outcomes that would have been expected from the CIM model.

For example, the glycaemic index of glucose, fructose and HFCS is , 19 and 58, respectively But supporting the CIM, higher carbohydrate intake in the form of mixtures of fructose and glucose led to greater liver fat content, and this was minimally affected by an increase in fat intake.

In addition, partly consistent with CIM, energy intake itself was increased primarily by diets with fructose to glucose and was not significantly affected by dietary fat content. Our work sheds light on how both low fat-high carbohydrate and high fat-low carbohydrate diets could reduce obesity 33 , 34 , Low fat-high carbohydrate diets containing HFCS as the major carbohydrate would be predicted to cause obesity by facilitating greater calorie intake.

However, low fat-high carbohydrate diets could be more effective than low carbohydrate-high fat diets in reducing ad libitum energy intake and inducing loss of fat mass if carbohydrate is not consumed in the form of fructose-glucose mixtures.

This has been confirmed in a recent human study where a low-fat diet led to lower calorie intake and a greater decrease in adiposity than a ketogenic diet In contrast, the results of the present study suggest that minimal improvement in metabolic status is to be expected if dietary fat is replaced with HFCS or sucrose.

Therefore, unsurprisingly, the prevalence of obesity continued to increase as dietary fats were replaced by processed caloric sugars over the last few decades 3 , Two aspects of our data on dietary fat and its metabolic effects warrant further comment.

First, similar to other reports where the dietary fat-carbohydrate ratio was altered in isocaloric settings 19 , 20 , increasing dietary fat content and fat-to-carbohydrate ratio did not alter ad libitum energy intake in our study. This may, at first, seem contrary to a recent mouse study that showed an increase in ad libitum energy intake and adiposity with increasing dietary fat content However, in contrast with the present study, the diets used were not isocaloric, making it impossible to differentiate the effects of dietary caloric density from the effects of fat per se on energy intake.

It is important to make this distinction because EBM argues that excess calories from all sources including fats and sugars are obesogenic 9 , Second, our expectation was that, because of their greater saturated fat content, consuming lard-based diets would be metabolically more detrimental than soy oil-based diets, especially when coupled with HFCS.

However, we found that replacing soy oil with lard did not affect the metabolic phenotype of the mice. Others have also observed in rodents that the type of fat in the diet did not alter body weight and composition 39 , This indicates that total fat content is more important than the proportion of saturated fat for inducing detectable metabolic changes.

The main limitations of this study include: a only simple sugars were used, and they were not compared with complex carbohydrates with low glycaemic index, b post prandial glycaemic and insulinemic response to experimental diets and the effects of insulin on glucose clearance, fat metabolism and appetite were not studied, c impact of diets on hypothalamic appetite and hedonic signalling was not examined, d diets with very high-fat content or high energy densities were not used, e cellulose content was adjusted to keep the diets isocaloric, f fructose and glucose were given only as solid diets, and not as liquid solutions, g metabolic effects of fat and sugars were not tested in pair feeding experiments, h single strain and single-sex of the mice was used, i mouse experiments were not repeated in thermoneutral conditions.

The aim of this study was to interrogate the consequences of fat-sugar interaction. Thus, we used the monosaccharides found in major caloric sugars i. We have already compared the metabolic effects of simple sugars with glucose polymers starch and resistant starch in our previous work Although postprandial glucose and insulin levels were not specifically examined in response to experimental diets, data shown for glucose and insulin levels from fasting state and from oral glucose tolerance tests Fig.

S3b, c is a good indicator of glucose metabolism. Further, hypothalamic appetite signalling and hedonic stimuli in response to experimental diets are most likely to reflect energy intake data Fig.

Using large amounts of fat would have also meant using substantial amounts of cellulose to keep the diet isocaloric. This would have made dietary cellulose content a potentially important confounder when interpreting our data.

There is evidence that fructose-containing sugars are more obesogenic when consumed via beverages Therefore, not testing metabolic outcomes when fructose is ingested in liquid form makes our findings less relevant to the role of sugary beverages in human obesity 17 , However, a direct experimental comparison of the metabolic effects of consuming fats and sugars in liquid form requires making mice drink large amounts of oil solutions which is challenging, and we were able to identify the ratio of fructose and glucose , which is obesogenic in the solid form.

While pair feeding could provide additional information in separating the impact of nutrients from their caloric value, such studies often lead to extended periods of fasting in the pair-fed group as these mice tend to consume their food soon after it is made available Importantly, with the NG methodology, we can evaluate the impact of nutrients on metabolic phenotype at fixed levels of energy intakes e.

However, not repeating our experiments in females, other strains of mice and under thermoneutral conditions is an important limitation of this work. Future research should examine if the metabolic effects observed in this study are dependent on the strain and sex of the mice as well as their housing temperatures.

In conclusion, this study showed that in diets with a low-to-medium fat content, HFCS consumption led to greater food and energy intakes, body weights and adiposity when compared with consumption of glucose or fructose alone.

However, with increasing fat intake, sugar-specific differences in metabolic effects became less pronounced, and there was a more generalised increase in body weight and adiposity, and greater impairment of glucose tolerance and insulin sensitivity.

Using NG to disentangle the relative roles of fat and sugar intake in human data will further reconcile the differences between CIM and EBM as models of obesity.

This study was approved by the institutional ethics committee at the University of Sydney. A detailed explanation of how to interpret nutritional geometry surfaces shown in the figures is available in supplementary materials. Male mice were chosen as they are more prone to diet-induced metabolic abnormalities than females Mice were acclimatised in the animal facility for 4 weeks while being fed regular brown chow.

The ad libitum dietary intervention commenced when the mice became 8 weeks old. In vivo metabolic procedures, food intake, body weight measurements and animal tissue collections were performed as previously described Further details about the study design and animal numbers per diet are available in the Supplementary information.

All 18 experimental diets were isocaloric with a net metabolisable energy of ~ Protein was sourced from casein and carbohydrate comprised of a mixture of the sources shown in Supplementary Data 1. The diets were kept isocaloric by altering their cellulose content.

All 18 diets were manufactured by Specialty Feeds TM Glen Forrest, Western Australia with the following catalogue numbers: SF, SF, SF, SF, SF, SF, SF, SF, SF, SF, SF, SF, SF, SF, SF, SF, SF and SF MRI scanning of mice EchoMRI TM was used to determine the body composition fat and lean mass of mice.

Conscious mice were analysed after weeks 5—6 and 12—14 on diets. Physical activity was measured by cumulative y-axis beam break counts. Data were analysed by using the CalR online tool Total AUC was calculated from blood glucose readings Higher AUC indicates worse glucose tolerance. An insulin tolerance test was performed at weeks 15—16 of dietary treatment.

Mice were intraperitoneally injected with 0. Individual AUC was calculated from blood glucose readings. Higher AUC indicates lower insulin sensitivity. Blood samples were collected during GTTs, and insulin levels were quantified with the Ultrasensitive Insulin ELISA kit Crystal Chem.

Plasma FGF21 was quantified with the mouse FGF21 ELISA kit Bio Vendor for blood samples collected at the end of dietary interventions. After harvesting, livers were fixed in formalin and embedded in paraffin. Triglyceride levels in plasma samples were analysed by a clinical chemistry analyser at the Charles Perkins Centre, University of Sydney.

cDNA was then synthesised using the iScript Reverse Transcriptase enzyme and random hexamer primers Bio-Rad. cDNA was loaded in a well plate format with SYBR Green Bio-Rad fluorescent chemistry in a total 10 microlitres reaction volume with specific forward and reverse primers. Ribosomal protein gene Rpl13a was chosen as the housekeeping gene 47 after testing a fraction of samples for gene expression of actin, Rpl13a and cyclophilin.

Ct values of housekeeping and candidate genes were determined, and their expression was calculated by the DDCt method. Primer sequences for Rpl13a 47 , Apob 48 , Khk isoform C 49 , Gpat3 50 , Acly 16 , Fasn 16 , Scd1 16 and Mcp1 51 were from previous publications.

Liver triglyceride level was quantified as reported in previous studies 16 , A colourimetric assay was then used to quantify the triglyceride concentration with glycerol standards Precimat glycerol, Roche and the Triglyceride-GPO-PAP reagent Roche.

Details of data analysis by the NG platform and its interpretation with general additive models GAMs were described previously 16 , 19 , For the NG-based analysis, GAMs with thin-plate splines were used to model the responses of mice over the nutrient-intake space in R version 4.

Statistical outcomes retrieved from GAMs are provided in Supplementary Data. Scatter plots such as energy intake analysis were analysed by GAMs as well, fitting an interaction between a smooth term for dietary sugar content in one carbohydrate dimension and fat contents as three-level categorical factors and shown as scatterplots the dotted lines on scatterplots represent the standard error for the fitted values.

All GAMs underwent model validation with analysis of the residuals. Data were log-transformed if needed. For histological studies, sections were given scores ranging from 0 to 3, and the scores were modelled with an ordinal regression proportional odds in R.

For soy oil versus lard studies, data were analysed with ANOVA in GraphPad Prism software. Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

All data supporting the findings described in this article are available in the article and in the Supplementary Information and from the corresponding authors upon reasonable request. Source data are provided in this paper.

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