Accumulation of saturated intramyocellular lipid is associated with insulin resistance
2019; Elsevier BV; Volume: 60; Issue: 7 Linguagem: Inglês
10.1194/jlr.m091942
ISSN1539-7262
AutoresDavid B. Savage, Laura Watson, Katie Carr, Claire Adams, Søren Brage, Krishna Chatterjee, Leanne Hodson, Chris Boesch, Graham J. Kemp, Alison Sleigh,
Tópico(s)Metabolomics and Mass Spectrometry Studies
ResumoIntramyocellular lipid (IMCL) accumulation has been linked to both insulin-resistant and insulin-sensitive (athletes) states. Biochemical analysis of intramuscular triglyceride composition is confounded by extramyocellular triglycerides in biopsy samples, and hence the specific composition of IMCLs is unknown in these states. 1H magnetic resonance spectroscopy (MRS) can be used to overcome this problem. Thus, we used a recently validated 1H MRS method to compare the compositional saturation index (CH2:CH3) and concentration independent of the composition (CH3) of IMCLs in the soleus and tibialis anterior muscles of 16 female insulin-resistant lipodystrophic subjects with that of age- and gender-matched athletes (n = 14) and healthy controls (n = 41). The IMCL CH2:CH3 ratio was significantly higher in both muscles of the lipodystrophic subjects compared with controls but was similar in athletes and controls. IMCL CH2:CH3 was dependent on the IMCL concentration in the controls and, after adjusting the compositional index for quantity (CH2:CH3adj), could distinguish lipodystrophics from athletes. This CH2:CH3adj marker had a stronger relationship with insulin resistance than IMCL concentration alone and was inversely related to VO2max. The association of insulin resistance with the accumulation of saturated IMCLs is consistent with a potential pathogenic role for saturated fat and the reported benefits of exercise and diet in insulin-resistant states. Intramyocellular lipid (IMCL) accumulation has been linked to both insulin-resistant and insulin-sensitive (athletes) states. Biochemical analysis of intramuscular triglyceride composition is confounded by extramyocellular triglycerides in biopsy samples, and hence the specific composition of IMCLs is unknown in these states. 1H magnetic resonance spectroscopy (MRS) can be used to overcome this problem. Thus, we used a recently validated 1H MRS method to compare the compositional saturation index (CH2:CH3) and concentration independent of the composition (CH3) of IMCLs in the soleus and tibialis anterior muscles of 16 female insulin-resistant lipodystrophic subjects with that of age- and gender-matched athletes (n = 14) and healthy controls (n = 41). The IMCL CH2:CH3 ratio was significantly higher in both muscles of the lipodystrophic subjects compared with controls but was similar in athletes and controls. IMCL CH2:CH3 was dependent on the IMCL concentration in the controls and, after adjusting the compositional index for quantity (CH2:CH3adj), could distinguish lipodystrophics from athletes. This CH2:CH3adj marker had a stronger relationship with insulin resistance than IMCL concentration alone and was inversely related to VO2max. The association of insulin resistance with the accumulation of saturated IMCLs is consistent with a potential pathogenic role for saturated fat and the reported benefits of exercise and diet in insulin-resistant states. After it was demonstrated that 1H magnetic resonance spectroscopy (MRS) can noninvasively distinguish intramyocellular lipids (IMCLs) from extramyocellular lipids (EMCLs) (1Schick F. Eismann B. Jung W-I. Bongers H. Bunse M. Lutz O. Comparison of localized proton NMR signals of skeletal muscle and fat tissue in vivo: two lipid compartments in muscle tissue.Magn. Reson. Med. 1993; 29: 158-167Crossref PubMed Scopus (322) Google Scholar, 2Boesch C. Slotboom J. Hoppeler H. Kreis R. In vivo determination of intra-myocellular lipids in human muscle by means of localized 1H-MR-spectroscopy.Magn. Reson. 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This marker, which we call the IMCL saturation index (CH2:CH3), utilizes good-quality spectra acquired at 3T with a short echo time and compares the CH2 resonance located at 1.3 ppm (which is influenced by both concentration and composition) with that of the CH3 resonance at 0.9 ppm (which is independent of triglyceride composition); this is illustrated in Fig. 1. Figure 1 also shows that using a concentration of hydrogen that resonates at 1.3 ppm (CH2) to represent the concentration of lipids without knowing the underlying composition, as has been the practice in virtually all published 1H MRS studies of IMCLs so far, confounds the contributions of both the concentration of lipids and their composition. This can potentially lead to a significant error in estimating the concentration: the composition would contribute as much as 50% to the observed signal (equivalent to a 100% theoretical increase in the signal) if the pool were stearic acid instead of linoleic acid. Therefore, we used the IMCL CH3 peak at 0.9 ppm to estimate the total concentration of IMCLs, as this is independent of the degree of saturation of the FA chains within triglycerides (i.e., composition). We call this the composition-independent IMCL concentration estimate to distinguish it from the conventional estimate using CH2. Lipodystrophy is a rare cause of severe insulin resistance and is typically characterized by prominent ectopic fat accumulation due to both the reduction in adipocyte lipid storage capacity and the associated hyperphagia induced by leptin deficiency. To ascertain whether IMCL composition is altered in lipodystrophic (LD) subjects and if such changes in lipid composition might help to elucidate the athlete's paradox, we determined the compositional saturation index (CH2:CH3 ratio) and composition-independent concentration (from CH3) of IMCLs in the SOL and tibialis anterior (TA) muscles of female insulin-resistant LD subjects as well as age- and gender-matched athletes and nonathlete controls. Sixteen female subjects with lipodystrophy were identified as part of a long-standing study of human insulin-resistant syndromes, while age- and gender-matched controls (n = 41) and athletes (n = 14) were recruited by advertisement. SOL IMCL data from five of the subjects were included in a previously published study (18Sleigh A. Stears A. Thackray K. Watson L. Gambineri A. Nag S. Campi V.I. Schoenmakers N. Brage S. Carpenter T.A. et al.Mitochondrial oxidative phosphorylation is impaired in patients with congenital lipodystrophy.J. Clin. Endocrinol. Metab. 2012; 97: E438-E442Crossref PubMed Scopus (21) Google Scholar). Control and athlete exclusion criteria included current smoking; drug or alcohol addiction; any current or past medical disorder or medications that could affect measurements, including supplements such as creatine; and standard MRI contraindications. Controls were recruited who exercised less than three times per week for 1 h each time, while the athletes, some of whom competed in international events, were part of a running club and regularly ran distances between 10 and 40 km. Subjects with lipodystrophy were recruited if they could perform an overnight fast without insulin or a rapid-acting insulin analogue. The studies relating to lipodystrophy were approved by the NHS Research Ethics Committee, and the healthy volunteer studies were approved by the East of England Cambridge Central Ethics Committee. Studies were conducted in accordance with the Declaration of Helsinki, and all participants provided written informed consent. Volunteers were instructed to follow normal dietary habits for 3 days before arriving at the National Institute for Health Research (NIHR)/Wellcome Trust Clinical Research Facility. Participants provided fasting blood samples and were given a light breakfast of either toast or cereal immediately prior to 1H MRS. Athletes and controls were instructed to refrain from vigorous exercise for at least 24 and 19 h, respectively, prior to 1H MRS. HOMA-IR was calculated as fasting insulin (pmol/l) × fasting glucose (μU/ml)/22.5. Body composition was assessed by dual-energy X-ray absorptiometry (Lunar Prodigy enCORE version 12.5 for controls and Lunar iDXA enCORE version 16 for athletes; GE Healthcare, Madison, WI). 1H MRS studies were performed on a 3T scanner (Siemens; Erlangen, Germany) using the point-resolved spectroscopy sequence with a short echo time of 35 ms. A water-suppressed 1H spectrum was acquired from a voxel with a cube length of 1.3 cm positioned to avoid visible fat on T1-weighted images within TA and SOL using a 5 s repetition time and 64 averages (4 averages for the nonwater-suppressed spectrum). Data were analyzed in jMRUI (19Naressi A. Couturier C. Devos J.M. Janssen M. Mangeat C. de Beer R. Graveron-Demilly D. Java-based graphical user interface for the MRUI quantitation package.MAGMA. 2001; 12: 141-152Crossref PubMed Google Scholar, 20Stefan D. Di Cesare F. Andrasescu A. Popa E. Lazariev A. Vescovo E. Strbak O. Williams S. Starcuk Z. Cabanas M. et al.Quantitation of magnetic resonance spectroscopy signals: the jMRUI software package.Meas. Sci. Technol. 2009; 20: 104035Crossref Scopus (334) Google Scholar) and fitted with the AMARES (21Vanhamme L. Van Den Boogaart A. Van Huffel S. Improved method for accurate and efficient quantification of MRS data with use of prior knowledge.J. Magn. Reson. 1997; 129: 35-43Crossref PubMed Scopus (1316) Google Scholar) algorithm using identical prior-knowledge parameters: Gaussian line shapes (except water: Lorentzian), soft constraints on EMCL/IMCL CH2 frequencies and line widths, CH3 resonant frequencies and line widths determined from known and inferred prior knowledge relative to the CH2 resonance (22Boesch C. Machann J. Vermathen P. Schick F. Role of proton MR for the study of muscle lipid metabolism.NMR Biomed. 2006; 19: 968-988Crossref PubMed Scopus (161) Google Scholar), and with all amplitudes estimated. Because the CH3 resonance is small and may be subject to spectral overlap, the results were later checked for robustness by reanalyzing the data using different fitting parameters, as outlined in supplemental Table S1. IMCL CH2 and CH3 are quantified relative to the methyl group of creatine plus phosphocreatine at 3.0 ppm. Because this resonance exhibits different line-shape characteristics in the TA and SOL muscles (23Vermathen P. Boesch C. Kreis R. Mapping fiber orientation in human muscle by proton MR spectroscopic imaging.Magn. Reson. Med. 2003; 49: 424-432Crossref PubMed Scopus (49) Google Scholar), comparable quantification between muscles using a nominal concentration of muscle creatine is not valid; instead, a scaling factor of creatine to water for each muscle was established from a subset of participants who had nonwater-suppressed data sets, yielding a calculated water signal. Absolute composition-independent IMCL concentrations in mmol/kg muscle wet weight were calculated from the compositionally invariant CH3 IMCL resonance, with standard assumptions regarding muscle water content and correction for T2 relaxation effects, J coupling, and proton density as outlined below. Absolute IMCL concentrations in mmol/kg muscle wet weight were calculated using the CH3 IMCL resonance (which is compositionally invariant) using the following equation: [IMCL]=(So IMCL CH3/So water−calc).[water] where S o is the corrected signal intensity of the resonance, water-calc is the calculated water signal from the internal standard (creatine and phosphocreatine), and [water] is the concentration of water in skeletal muscle [calculated using a pure water concentration of 55,342 mmol/l and assuming a relative tissue water content in human skeletal muscle of 0.81 (kg/kg) and tissue density of 1.05 g/ml (24Szczepaniak L.S. Babcock E.E. Schick F. Dobbins R.L. Garg A. Burns D.K. Denis Mcgarry J. Stein D.T. Denis McGarry J. Measurement of intracellular triglyceride stores by 1H spectroscopy: validation in vivo.Am. J. Physiol. Endocrinol. Metab. 1999; 276: E977-E989Crossref PubMed Google Scholar)]. Because the IMCL CH3 resonance is subject to J-coupling effects and has an unknown T2 relaxation time, we utilized the theoretical-to-measured IMCL CH3:CH2 ratio that would take into effect both J-coupling and T2 effects at this echo time as well as any bias of constrained fitting prior knowledge of the CH3 resonance. (So IMCL CH3/So water-calc)=(So IMCL CH3/So IMCL CH2). (So IMCL CH2/So water-calc) Therefore, (So IMCL CH3/So water−calc)=(SIMCL CH3/Swater−calc).(GTMCH3:CH2).(T2corrCH2/water).(nwater:IMCL CH3) where S is the uncorrected signal intensity of the resonance. (G TM CH3:CH2) = 1.1966 and is the gradient of the line of best fit through the origin of the graph of theoretical-to-measured CH3:CH2 in vitro in IMCL- and EMCL-simulated phantoms using the point-resolved spectroscopy sequence at 3T with an echo time of 35 ms with the same fitting (17Thankamony A. Kemp G.J. Koulman A. Bokii V. Savage D.B. Boesch C. Hodson L. Dunger D.B. Sleigh A. Compositional marker in vivo reveals intramyocellular lipid turnover during fasting-induced lipolysis.Sci. Rep. 2018; 8: 2750Crossref PubMed Scopus (2) Google Scholar), assuming that J-coupling and T2 relaxation effects would be similar in vivo. (T 2corr CH2/water) is the correction factor for T2 effects of CH2 and water that was calculated using accepted T2 values at 3T for each muscle (25Krssák M. Roden M. Mlynárik V. Meyerspeer M. Moser E. 1H NMR relaxation times of skeletal muscle metabolites at 3 T.MAGMA. 2004; 16: 155-159Crossref PubMed Scopus (67) Google Scholar), and (n water:IMCL CH3) is the correction for proton density. The IMCL saturation index (CH2:CH3) was calculated as IMCL CH2:CH3, and the IMCL saturation index adjusted for quantity (CH2:CH3adj) = CH2 – (mCH3 + c), where m and c are the gradient and intercept, respectively, of the regression line through the control data points of CH2 versus CH3. Investigators were blind to the insulin-resistance status of the participants during 1H MRS analysis. Participants underwent continuous incremental exercise testing to an 85% age-predicted maximum heart rate (controls) or volitional exhaustion (athletes) on a Trackmaster TMX425 treadmill (Med-Electronics, Beltsville, MD). LD subjects did not perform an exercise test. Oxygen consumption was measured using a spiroergometer (Medical Graphics UK Ltd, Gloucester, UK) and BreezeSuite gas-exchange software. For the control participants, a standard incremental protocol was performed (26Brage S. Brage N. Ekelund U. Luan J. Franks P.W. Froberg K. Wareham N.J. Effect of combined movement and heart rate monitor placement on physical activity estimates during treadmill locomotion and free-living.Eur. J. Appl. Physiol. 2006; 96: 517-524Crossref PubMed Scopus (81) Google Scholar), whereas the athletes undertook a protocol that began with a 10 min warm-up period at each participant's preferred warm-up running speed, after which the test was initiated at 9 km/h and increased steadily (0.74 km/h/min), with a ramp at 5 min (increasing 0.5% every 15 s) until exhaustion or a plateau in VO2 was apparent. VO2max was calculated in the control participants by extrapolating the submaximal heart rate – VO2 relationship to the age-predicted maximum heart rate (27Tanaka H. Monahan K.D. Seals D.R. Age-predicted maximal heart rate revisited.J. Am. Coll. Cardiol. 2001; 37: 153-156Crossref PubMed Scopus (2230) Google Scholar). All statistics were performed in SPSS Statistics 24 (IBM, Armonk, NY) with significance set at P < 0.05. Normality was assessed by the Shapiro-Wilk test, and nonnormally distributed data were log-transformed prior to statistical testing. ANOVA with Games-Howell post hoc analysis was used to compare means between groups, and Pearson's correlation coefficient was used for analyzing associations. Due to the nonnormality of ln(HOMA-IR), IMCL associations with HOMA-IR were assessed by Spearman's rank correlation coefficient. Data are presented as means ± SEMs. Of the insulin-resistant subjects with lipodystrophy, 13 had partial forms [8 subjects with familial partial lipodystrophy (FPLD) type 2 due to LMNA mutations, 5 subjects with FPLD3 due to PPARG mutations), and 3 had generalized lipodystrophy [2 subjects with acquired generalized lipodystrophy (AGLD) and 1 due to mutations in the PCYT1A gene (28Payne F. Lim K. Girousse A. Brown R.J. Kory N. Robbins A. Xue Y. Sleigh A. Cochran E. Adams C. et al.Mutations disrupting the Kennedy phosphatidylcholine pathway in humans with congenital lipodystrophy and fatty liver disease.Proc. Natl. Acad. Sci. USA. 2014; 111: 8901-8906Crossref PubMed Scopus (92) Google Scholar)]. Of the LD subjects, two were taking no medication at all, eight were prescribed metformin, three were taking statins, five were taking fibrates, and five were taking long-acting insulin analogues. The age- and gender-matched controls had a wide BMI range (19.6–35.6 kg/m2) and HOMA-IR (0.3–4.9). As a group, insulin and HOMA-IR were significantly higher in the LD subjects and lower in the athletes (Table 1) compared with controls, as expected. Fat mass and percentage body fat were similar between LD subjects and athletes, which were both lower compared with controls (Table 1). Serum triglycerides were higher and HDL-cholesterol concentrations were lower in the LD subjects (Table 1) compared with either controls or athletes. EMCLs were absent in the two subjects with AGLD (Fig. 2), but those with partial forms of lipodystrophy had an EMCL concentration such that overall LD subjects' EMCL concentration was similar to both controls and athletes (Table 1).TABLE 1Participant characteristics and conventional muscle lipid estimatesLD Females (n = 16)Female Controls (n = 41)Female Athletes (n = 14)PANOVALD—ControlsLD—AthletesControls—AthletesParticipant characteristicsAge (years)38.9 ± 3.935.5 ± 2.036.5 ± 2.90.694BMI (kg/m2)24.2 ± 0.724.4 ± 0.620.3 ± 0.6<0.0010.9990.001<0.001Mass (kg)66.1 ± 2.865.2 ± 2.354.6 ± 1.30.0130.9160.0060.001Fat mass (kg)10.6 ± 1.423.1 ± 1.611.6 ± 1.1<0.0010.0010.631<0.001Fat-free mass (kg)55.4 ± 1.742.1 ± 0.943.0 ± 1.2<0.001<0.001<0.0010.705Body fat (%)16.1 ± 1.734.2 ± 1.221.1 ± 1.8<0.001<0.0010.129<0.001Triglycerides (mmol/l)3.54 ± 0.670.92 ± 0.07an = 38.0.84 ± 0.08<0.001<0.001<0.0010.920HDL-cholesterol (mmol/l)0.97 ± 0.711.64 ± 0.06an = 38.2.20 ± 0.12<0.001<0.001<0.0010.001Glucose (mmol/l)6.00 ± 0.584.56 ± 0.06an = 38.4.46 ± 0.13<0.0010.0630.0020.764Insulin (pmol/l)bTo convert to μU/ml divide by 6.945.145.6 ± 22.038.6 ± 4.2an = 38.22.6 ± 4.7<0.001<0.001<0.0010.025HOMA-IR5.53 ± 1.01.14 ± 0.13an = 38.0.66 ± 0.15<0.001<0.001<0.0010.025HbA1c (%)6.6 ± 0.4cn = 13.ND5.3 ± 0.1ND0.008VO2max (ml/kg/min)ND36.1 ± 1.5dn = 24.46.9 ± 1.4ND<0.001Conventional estimateseExpressed as methylene protons resonating at 1.3 ppm quantified as a percentage of the uncorrected calculated water resonance.SOL IMCLs1.90 ± 0.211.22 ± 0.070.79 ± 0.10<0.0010.027<0.0010.007TA IMCLs0.89 ± 0.16fn = 12.0.61 ± 0.040.45 ± 0.040.0350.5620.1150.078SOL EMCLs2.05 ± 0.342.22 ± 0.191.81 ± 0.200.493TA EMCLs1.43 ± 0.28fn = 12.2.30 ± 0.191.24 ± 0.150.0020.1630.7850.005Data are presented as mean ± SEM unless otherwise stated. Nonnormally distributed variables were log-transformed prior to performing ANOVA and Games-Howell post hoc analysis; bold P values are statistically significant.a n = 38.b To convert to μU/ml divide by 6.945.c n = 13.d n = 24.e Expressed as methylene protons resonating at 1.3 ppm quantified as a percentage of the uncorrected calculated water resonance.f n = 12. Open table in a new tab Data are presented as mean ± SEM unless otherwise stated. Nonnormally distributed variables were log-transformed prior to performing ANOVA and Games-Howell post hoc analysis; bold P values are statistically significant. In the SOL muscle, IMCL concentrations derived from the IMCL CH3 peak (0.9 ppm) (composition-independent IMCL concentrations) were not significantly increased (P = 0.477) in the LD subjects compared with controls but were higher compared with the lean athletes (P = 0.003) (Fig. 3A). In the more glycolytic TA muscle, composition-independent IMCL concentrations were similar in all three groups (Fig. 3B). We also observed linear inverse correlations of VO2max and the IMCL concentration in the subset of controls who underwent VO2max testing and athletes together (Fig. 3C, D). SOL IMCL concentration was significantly lower in the athletes compared with the controls (P = 0.004; Fig. 3A), and this remained significant (P = 0.025) compared with a subset of the controls matched for percentage body fat (controls: body fat = 21.5 ± 2.3%, n = 10; athletes: 21.1 ± 1.8%, n = 14; see supplemental Fig. S1). The conventional estimate of IMCL concentration using the CH2 resonance uncorrected for composition, CH2/water, showed similar trends to the composition-independent estimate using the CH3 peak with the exception that the LD subjects' SOL IMCL CH2 was significantly increased compared with controls (Table 1). This could be regarded as an artifact of the effects of compositional differences, which we consider next. IMCLs had a significantly higher saturation index (CH2:CH3) in both muscles of the LD subjects compared with controls (SOL P = 0.008; TA P = 0.024) but not athletes (Fig. 4A, B). In the control group, smaller IMCL pools were associated with a higher saturation index, as shown by the linear regression line (dotted line in Fig. 3E, F) having a gradient (ΔCH2/ΔCH3) that was less than the mean CH2:CH3 (e.g., gradient SOL = 6.7 vs. mean CH2:CH3 = 8.8; gradient TA = 4.2 vs. mean CH2:CH3 = 6.0). This phenomenon seemed to be independent of insulin sensitivity in the controls (Table 2; there was no relation of HOMA-IR with IMCL concentration). To generate a pathophysiologically meaningful measure of composition that is independent of IMCL quantity, the vertical (CH2) deviation from this regression line was measured and taken as a marker of the saturation of the pool that is adjusted for quantity, which we term the adjusted saturation index (CH2:CH3adj). This adjusted compositional marker was significantly higher in LD subjects compared with athletes (SOL P = 0.001; TA P = 0.046) and controls (SOL P = 0.003), with a tendency in the TA that falls just short of conventional statistical significance (P = 0.06) (Fig. 4C, D).TABLE 2Correlation coefficients of whole-body insulin resistance with IMCLsIMCL MeasureHOMA-IRControls (n = 38)Controls and Athletes (n = 52)Controls and LD Subjects (n = 54)an = 50 for TA.Controls, LD Subjects, and Athletes (n = 68)bn = 64 for TA.SOLConcentration (CH3)−0.0160.2480.1490.312*Concentration and composition (CH2)0.1530.315*0.394**0.477***Composition (CH2:CH3)0.217−0.0480.439***0.241*Composition adjusted for quantity (CH2:CH3adj)0.320*0.271*0.583***0.532***TAConcentration (CH3)0.2000.2510.2050.258*Concentration and composition (CH2)0.2240.2470.338*0.344**Composition (CH2:CH3)0.100−0.0460.337*0.202Composition adjusted for quantity (CH2:CH3adj)0.2180.1270.445***0.364***P < 0.05, **P < 0.01, and ***P ≤ 0.001.a n = 50 for TA.b n = 64 for TA. Open table in a new tab *P < 0.05, **P < 0.01, and ***P ≤ 0.001. Unlike the uncorrected measure of composition, this adjusted composition also had a significant relation to VO2max (Fig. 4E, F) within the control subset alone, athletes alone (SOL), and control and athletes combined, such that fitter individuals had less saturated IMCLs for the same absolute quantity of IMCLs. VO2max was significantly correlated with HOMA-IR in the control subset (r = −0.59, P = 0.003, n = 23) and in controls and athletes together (r = −0.53, P = 0.001, n = 37). Figure 4G and H show the relation of the adjusted composition to HOMA-IR. Table 2 shows relat
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