Dimethylguanidino valeric acid is independently associated with intrahepatic triglyceride content in patients with nonalcoholic fatty liver disease (NAFLD) and decreased after long-term exercise

Dimethylguanidino valeric acid is independently associated with intrahepatic triglyceride content in patients with nonalcoholic fatty liver disease (NAFLD) and decreased after long-term exercise | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article Dimethylguanidino valeric acid is independently associated with intrahepatic triglyceride content in patients with nonalcoholic fatty liver disease (NAFLD) and decreased after long-term exercise Jia Li, Yinxiang Huang, Caoxin Huang, Yan Zhao, Xiulin Shi, Zhen Chen, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-26934/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Backgrounds: Dimethylguanidino valeric acid (DMGV) is closely associated with nonalcoholic fatty liver disease (NAFLD), the most recommended therapy of NAFLD is Exercise. Our aim was to investigate the correlation between DMGV concentrations and clinical characters in patients with NAFLD, and assessed the effect on DMGV concentrations changes after 6 month exercise training. Methods: NAFLD individuals (n = 220) were selected and randomly divided into control group (n = 74), moderate exercise group (n = 73) and vigorous exercise group (n = 73) with 6 month followed-up. Clinical characteristics were obtained from our previous clinical trial, serum DMGV levels were determined by a validated ultrahigh performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method. Results: On baseline, DMGV levels were positive associated with age, visceral fat and intrahepatic triglyceride (IHTG) content, and inversely associated with fasting blood glucose and diastolic blood pressure. In addition, the association between DMGV levels and IHTG content remained significant after adjusting other main clinical characters (β coefficient = 0.174, P = 0.018). After 6 month exercise training, IHTG was decreased by both exercise intensities without a significant difference ( P = 0.45), however, moderate exercise was more efficient on DMGV decreasing than vigorous exercise (-9.96 to 2.27 ng/ml, P < 0.001 for moderate exercise; -4.53 to 4.56 ng/ml, P = 0.762 for vigorous exercise) with a significant difference ( P = 0.047). Conclusions: DMGV was a potential indicator during development and progression of NAFLD, and moderate exercise was more efficient on metabolic changes than vigorous exercise with equal IHTG improvement, suggesting a priority of exercise intensity during NAFLD treatment. ClinicalTrials.gov Identifier: NCT01418027, August 16, 2011 Endocrinology & Metabolism dimethylguanidino valeric acid nonalcoholic fatty liver disease intrahepatic triglyceride content exercise ultrahigh performance liquid chromatography-tandem mass spectrometry Figures Figure 1 Figure 2 Figure 3 Background Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease and has become an increasingly pandemic disease as the improvement of people's life, which is also the hepatic manifestation of the metabolic syndrome and a risk factor for many metabolic diseases 1 , 2 . Exercise was a major recommended treatment for NAFLD by decreasing visceral adipose tissue, liver fat, body fat and weight as well as improvement of cardiovascular risk factors 3 , 4 . Our previous clinical trial 5 found that intrahepatic triglyceride (IHTG) content was decreased significantly by long term moderate and vigorous exercise in NAFLD subjects without a significant difference, while the metabolic profile changes during exercise was unknown, which exercise intensity was more efficient on metabolic alteration was unclear. With the development of analytical technologies, metabolomic study has been widely used to discover a panel of biomarkers in development and progression of NAFLD 6 , 7 . Recently, Targeted and non-targeted metabolomics studies has identified that circulating dimethylguanidino valeric acid (DMGV) was acted as a marker of liver fat and predicted future diabetes up to 12 years in 3 distinct human cohorts 8 , in addition, plasma DMGV levels had a strong relationship with visceral adiposity and decreased insulin sensitivity, and was recognized as an early marker of cardiometabolic dysfunction in health white people 9 . However, DMGV’ character in NAFLD status and its response to exercise were limited. This current study aimed to figure out the relationship between DMGV levels and clinical parameters among NALFD patients, especially IHTG content, and compare the DMGV levels changes after 6 month moderate and vigorous exercise training. Methods Study protocol The study protocol, informed consent form and all steps from blood extraction to analysis were approved by a steering committee, institutional review boards of Xiamen University and the First Affiliated Hospital of Xiamen University in China, and written informed consent was obtained from all participants. All methods were carried out in accordance with the relevant guidelines and regulations. Study participant and protocol were described in our previous study (Trial registration number: NCT01418027) 5 , briefly, a total of 220 individuals with NAFLD were selected and randomly assigned to control group (n = 74), moderate exercise group (n = 73, brisk walking 150 minutes per week at 45%-55% of maximum heart rate) and vigorous-moderate exercise group (n = 73, jogging 150 minutes per week at 65%-80% of maximum heart rate for 6 months and brisk walking 150 minutes per week at 45%-55% of maximum heart rate for another 6 months) with a 12-month followed-up. At 8:00 am after an overnight fast, blood samples were collected, and then were centrifuged at 3000 × g for 10 min, serum were stored at -80 °C until analysis. In this present study, only 6 month exercise intervention was concerned. Determination Of Serum Dmgv Concentration 50 µL serum was added 200 µL acetonitrile and 5 µL inner standard (IS) solution (L-phenyl-d5-alanine, 10 µg/mL), after centrifuging at 19,000 \times g for 10 min at 4 °C, 50 µL of the supernatant was then mixed with 200 µL initial mobile phase, the aliquot of which (5 µL) was injected into the ultrahigh performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) system for analysis. DMGV (purity > 97%) was synthesized by Nanjing Fanyida Biotechnology co. LTD (Nanjing China). LC-MS/MS was run on an Agilent 6460 triple stage quadrupole mass spectrometer equipped with an ESI ion source and an Agilent 1290 HPLC system with auto-sampler (Agilent Technologies, Santa Clara, CA, USA). DMGV was separated on an HSS T3 column (2.1 \times 100 mm, 1.8 µm, Waters, Milford, USA) at 30 °C. The mobile phase consisting of water with 2.5 mM ammonium formate and 0.1% formic acid (Solvent A) and acetonitrile (Solvent B) was used with a gradient elution: 0-4.5 min, 3–5% B at a flow rate of 0.2 mL/min, then column was washed by 90% B and equilibrated by 3% B for another 1.5 min, respectively. MS/MS conditions were as follows: Gas temperature 325 °C, Gas flow 10 L/min, Nebulizer 30 psi, Sheath gas temperature 400 °C, Sheath gas flow 11 L/min, Capillary 3500 V, Nozzle voltage 2000 V. Quantification was obtained by using multiple reaction monitoring (MRM) mode in positive ion mode (DMGV: m/z 202.1–71.1, Fragmentor 123 V, Collision Energy 25 V, Cell Cell Accelerator Voltage 0 V; IS: m/z 171.1-125.1, Fragmentor 83 V, Collision Energy 10 V, Cell Cell Accelerator Voltage 0 V ). Mass Hunter workstation software (Version B. 05. 00, Agilent Technologies, Santa Clara, CA, USA) was employed for data acquisition and processing. Statistical Analysis Pearson’s correlation coefficient (for normally distributed variables) and Spearman’s rank correlation (for non-normally distributed variables) were performed to analyze the correlation between clinical characteristics and DMGV levels in NAFLD subjects at baseline. The subjects were classified into four quartiles according to DMGV levels, other parameters in different groups were compared using an ANOVA test. DMGV levels changes after exercise testing were assessed by a paired t test in each group. All statistical analyses were performed using SPSS 22.0 software. P value less than 0.05 was considered statistically significant. Results Subjects characteristics A total of 220 NAFLD participants were recruited and followed up for 12 months 5 , only 6 month intervention were concerned in the present study (flow diagram was showed in Fig. S1). There were no significant difference in basic anthropometric data among three groups (Table S1); after 6 month exercise training, main clinical characteristics changed (Table S2), particularly, IHTG content were significant decreased (by 5.0% in the vigorous exercise, P < 0.001; 4.2% in the moderate exercise, P < 0.001), but high-intensity exercise offered no additional benefit to moderate intensity exercise in decreasing IHTG ( P = 0.45) 5 , 10 . Uhplc-ms/ms Method Validation For determination of DMGV concentration in human serum, serum sample preparation, LC condition and MS parameters of m/z 202.1→71.1 was carefully optimized. The lower limit of detection (LLOD) of DMGV in human serum was 1 ng/ml, and the lower limit of quantification (LLOQ) was 5 ng/ml. Calibration curve, accuracy, precision of intra-day and inter-day, recovery and matrix effect were carefully validated and all within the acceptable limit (data were not shown). Correlation Between Dmgv Levels And Clinical Characteristics At Baseline There were no significant difference on DMGV concentration among three groups at baseline ( P = 0.842). Serum DMGV levels were positive associated with age, visceral fat and IHTG content, and inversely associated with fasting blood glucose, diastolic blood pressure (Table 1 ). After adjusting age, sex, BMI (body mass index) and visceral fat, correlation with IHTG remained highly significant (β coefficient = 0.169, P = 0.021), moreover, DMGV was still significant positive associated with IHTG after additional adjusting weight, subcutaneous fat, fasting blood glucose and DBP (β coefficient = 0.174, P = 0.018). Table 1 Bivariate analysis between DMGV concentration and clinical characteristics in NAFLD subjects at baseline (n = 220). Variables r P Age 0.177 0.013 Fasting blood glucose -0.193 0.007 Total cholesterol (TC) 0.052 0.479 Total Triglyceride (TG) -0.016 0.833 High-density lipoprotein-cholesterol (HDL-C) 0.087 0.231 Low-density lipoprotein-cholesterol (LDL-C) -0.064 0.384 Alanine transaminase (ALT) 0.11 0.139 Aspartate aminotransferase (AST) 0.122 0.095 γ-Glutamyltransferase (GGT) -0.097 0.186 Systolic blood pressure (SBP) -0.073 0.31 Diastolic blood pressure (DBP) -0.156 0.03 Weigh -0.135 0.061 Body Mass Index (BMI) -0.121 0.095 Waist circumference -0.082 0.257 Visceral fat 0.16 0.027 Subcutaneous fat 0.128 0.077 Total Fat 0.11 0.13 Intrahepatic triglyceride (IHTG) content 0.19 0.009 Subjects were divided into four quartiles according to DMGV levels, TG, LDL-C, ALT, AST, GGT, SBP, weigh, BMI, subcutaneous fat and total fat were did not different in these four groups (Table 2 ), visceral fat and IHTG content were elevated with higher DMGV levels ( P < 0.001). Moreover, DMGV levels were elevated with higher IHTG content when subjects were divided into four quartiles according to IHTG content (Fig. 1 ). Table 2 Clinical characteristics as DMGV levels were divided into four quartiles (data were presented as mean ± SD). Variables Quartile 1 (n = 55) Quartile 2 (n = 55) Quartile 3 (n = 55) Quartile 4 (n = 55) P DMGV, ng/ml 18.3 ± 4.3 29.6 ± 4.8 *** 60.0 ± 10.0 *** 84.9 ± 6.6 *** < 0.001 Age, years 51.7 ± 7.1 54.7 ± 6.9 * 53.1 ± 7.4 56.7 ± 5.2 ** 0.001 Fasting blood glucose, mg/dl 106.7 ± 9.6 104.4 ± 9.5 101.8 ± 9.8 * 101.1 ± 9.7 ** 0.022 TC, mg/dl 222.6 ± 36.0 232.8 ± 33.8 241.3 ± 40.1 ** 222.8 ± 37.0 0.023 TG, mg/dl 168. 1 ± 79.4 175.5 ± 68.7 168.2 ± 70.1 159.2 ± 47.3 0.689 HDL-C, mg/dl 45.0 ± 7.9 47.7 ± 6.6 52.4 ± 9.9 *** 47.4 ± 7.7 < 0.001 LDL-C, mg/dl 144.9 ± 29.3 143.7 ± 27.6 152.0 ± 43.4 133.5 ± 35.7 0.051 ALT, U/L 23.8 ± 6.9 24. 9 ± 8.4 26.1 ± 10.9 25.3 ± 8.3 0.602 AST, U/L 22.6 ± 3.4 23.7 ± 5.4 23.4 ± 5.98 24.3 ± 5.3 0.420 FFT, U/L 39.8 ± 17. 9 36.6 ± 20.1 33.9 ± 17.1 32.3 ± 12.7 * 0.117 SBP, mmHg 134.5 ± 15.4 134.4 ± 14.5 128.6 ± 13.1 * 133.1 ± 15.9 0.120 DBP, mmHg 82.0 ± 10.2 82.4 ± 8.3 77.6 ± 8.7 * 79.5 ± 9.1 0.020 Weigh, kg 72.8 ± 8.6 72.0 ± 9.8 69.5 ± 8.6 * 70.1 ± 8.1 0.177 BMI, kg/m 2 28.2 ± 2.9 27.8 ± 2.6 27.5 ± 2.1 27.6 ± 2.5 0.431 Waist circumference, cm 96.3 ± 7.1 95.6 ± 6.4 92.9 ± 5.2 ** 96.0 ± 6.6 0.026 Visceral fat, cm 2 116.1 ± 32.9 126.9 ± 33.0 141.6 ± 37.5 *** 146.1 ± 29.4 *** < 0.0001 Subcutaneous fat, cm 2 230.4 ± 78.7 213.6 ± 55.2 232.5 ± 58.3 244.8 ± 69.3 0.116 Total Fat, kg 23.5 ± 5.4 22.1 ± 3.8 23.1 ± 3.7 24.6 ± 4.9 0.051 IHTG content, % 12.8 ± 5. 6 13.8 ± 6.1 17.9 ± 6.5 *** 20.4 ± 8.5 *** < 0.0001 P value was calculated among four groups by ANOVA analysis * P < 0.05, ** P < 0.01, *** P < 0.001, vs Quartile 1 Dmgv Levels Changes After Exercise Intervention After 6 month exercise training, DMGV levels were decreased by moderate (-9.96 to 2.27 ng/ml, P < 0.001) and vigorous exercise training (-4.53 to 4.56 ng/ml, P = 0.762) (Fig. 2 ). Compared to control, moderate exercise was more efficient on decreasing DMGV concentration than vigorous exercise with a significant difference ( P = 0.047) (Fig. 3 ). Correlation between baseline DMGV levels and longitudinal changes of clinical characteristics Baseline DMGV levels were inversely correlated with the changes of waist circumference (r=-0.312, P = 0.010) and subcutaneous fat (r=-0.278, P = 0.022), and positive correlated with changes of LDL-C (r = 0.286, P = 0.018) after 6 month moderate exercise training, and it was not associated with changes of IHTG content (r = 0.189, P = 0.122). We then investigate the correlations between changes of DMGV levels and changes of clinical parameters, unfortunately, there were no strong correlation (data were not shown). Discussion This study has two principal findings. First, DMGV levels were positive associated with IHTG content, and elevated with higher IHTG content in NAFLD subjects. After 6 month exercise intervention, DMGV levels were decreased in both exercise groups, and moderate exercise was more efficient on decreasing DMGV levels than vigorous exercise. Taken together, these findings highlight the important role of DMGV in NAFLD progression, and moderate was a preferred exercise intensity in NAFLD treatment. DMGV was a product of asymmetric dimethylarginine (ADMA) metabolized by alanine-glyoxylate aminotransferase 2 (AGXT2) and participated in nitric oxide signaling as a part of the arginine metabolism in human 12 . DMGV was higher in individuals with nonalcoholic steatohepatitis and confirmed a strong positive correlation with liver fat 8 . Moreover, DMGV was a beneficial metabolic intervention, since its level was decreased in participants after weight loss surgery. Recent study proposed that DMGV levels were positively associated with body fat, abdominal visceral fat, TG and an inverse associated with insulin sensitivity, LDL-C and HDL-C in healthy people 9 ; however, DMGV remains an incompletely understood metabolite with few data in NAFLD. For DMGV concentration quantitation in human serum in our study, LC condition, MS/MS parameters and serum sample preparation was carefully optimized, method validation was strictly performed. Acetonitrile was chosen for proteins participate in serum sample preparation since it was widely used and relatively simple before LC-MS/MS analysis 11 , 15 . Isotope-labeled DMGV was the best inner standard for DMGV quantitation 16 , unfortunately, there was no commercial reference and it had to be synthesized, therefore, L-phenyl-d5-alanine was used as inner standard because of its widely used in other similar metabolomics studies 11 , 17 . In this work, the relationship between DMGV levels and clinical parameters in NAFLD subjects was investigated, and it was demonstrated a positive association with age, IHTG content and visceral fat, and an inverse association with fasting blood glucose and DBP for the first time. In particular, DMGV had a close positive relationship with IHTG content after adjusting other main clinical characteristics in NAFLD participants. In addition, DMGV concentration and IHTG content were elevated with each other according to the four quartiles analysis, which indicated that DMGV might be a potential indicator during NAFLD development and progression (IHTG content > 5% was diagnosed as NAFLD in clinic). These results further supported DMGV as independent biomarker in NAFLD. Exercise benefited NAFLD in different exercise intensities without a significant difference on decreasing IHTC content in our previous clinical trial, but the metabolic profile changes were poorly understood. A previous metabolomics study found a panel of altered serum metabolites after 6 month vigorous exercise training 11 , however, whether these metabolites altered by moderate exercise was unknown, which exercise intensity was more efficient on metabolites changes was unclear. Thus, in the present study, DMGV was used to evaluate the effect on metabolic changes under different exercise intensities. We found that DMGV concentration was decreased after 6 month exercise training, which was corresponding to another similar study 9 . Interestingly, compared to control, moderate exercise was much more efficient on decreasing DMGV than vigorous exercise with an equal effect on IHTG reduction, though vigorous exercise was more efficient on improvement of weight, waist circumference, body fat and visceral fat. It was confirmed that various exercise intensities impacted plasma metabolic profile differently 18 – 20 , and low-intensity exercise favors a fat oxidation rate than in the high intensity exercise group with a greater decrease in body mass and fat mass 21 , thus, we considered that moderate exercise benefits DMGV metabolism better than vigorous exercise might due to the better improvement on enzyme related to DMGV metabolism and oxidation ability, which needed further investigation. This work has several limitations. All participants in this study were diagnosed as NAFLD by protonmagnetic resonance spectroscopy (IHTG content ≥ 5%) without healthy subjects. Another limitation was a lack of specific pathologies of NAFLD (steatosis, nonalcoholic steatohepatitis, liver fibrosis and cirrhosis) without liver biopsy. Moreover, DMGV levels altered differently response to different exercise intensities, the inner mechanism were needed to figure out in further study. Conclusions To the best of our knowledge, this is the first study to demonstrate that DMGV levels was closely associated with main clinical characteristics and decreased after 6 month exercise training in NAFLD subjects. Compared to vigorous exercise, moderate exercise was more efficient on decreasing DMGV concentration with an equal IHTG improvement. Overall, this finding provided a meaningful metabolic indicator in the development and progression in NAFLD, and optimized the clinical guideline in NAFLD treatment by long term exercise. Abbreviations NAFLD: nonalcoholic fatty liver diseas DMGV: Dimethylguanidino valeric acid UHPLC-MS/MS: ultrahigh performance liquid chromatography-tandem mass spectrometry IHTG: intrahepatic triglyceride IS: inner standard BMI: mody mass index TG: Total Triglyceride TC: Total cholesterol HDL-C: High-density lipoprotein-cholesterol LDL-C: Low-density lipoprotein-cholesterol ALT: Alanine transaminase AST: Aspartate aminotransferase GGT: γ-Glutamyltransferase SBP: Systolic blood pressure DBP: Diastolic blood pressure ADMA: asymmetric dimethylarginine AGXT2: alanine-glyoxylate aminotransferase 2 Declarations Ethics approval and consent to participate: The study protocol, informed consent form and all steps from blood extraction to analysis were approved by a steering committee, institutional review boards of Xiamen University and the First Affiliated Hospital of Xiamen University in China. Written informed consent was obtained from all participants and which was clearly stated in section “Study protocol”. All methods were carried out in accordance with the relevant guidelines and regulations. Consent for publication: not applicable. Availability of data and materials: Data sharing is not applicable to this article as no datasets were generated. Competing interests: All authors declare no conflicts relative to this manuscript. Funding: This work was financially supported by National Natural Science Foundation of China (No. 81870606, No. 81570770 and No. 81400419). The funders supported the collection of clinical characteristics of NAFLD participants in clinical trial, measurement the DMGV concentration and analysis work, and also were responsible for charges if this manuscript was accepted for publication. Authors’ contributions: JL, XL and Zhong C contributed the study conception and design. JL and was responsible for data analysis and wrote the manuscript. XL, YH, YZ, Zheng C, XS, LW and LH were participated in clinical trial study, clinical characteristics detection, data analysis and blood sample collection. All authors have read and approved the manuscript Acknowledgements: Not Applicable. References Musso G, Gambino R, Bo S, Uberti B, Biroli G, Pagano G, et al. Should nonalcoholic fatty liver disease be included in the definition of metabolic syndrome? A cross-sectional comparison with Adult Treatment Panel III criteria in nonobese nondiabetic subjects. Diabetes Care. 2008; 31: 562-568. Samuel VT, Shulman GI. Nonalcoholic fatty liver disease as a nexus of metabolic and hepatic diseases. Cell Metab. 2018; 27: 22-41. Keating SE, Hackett DA, Parker HM, O'Connor HT, Gerofi JA, Sainsbury A, et al. Effect of aerobic exercise training dose on liver fat and visceral adiposity. J 2015; 63: 174-182. Shojaee-Moradie F, Cuthbertson DJ, Barrett M, , Barrett M, Jackson NC, Herring R, et al. 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Low and moderate, rather than high intensity strength exercise induces benefit regarding plasma lipid profile. Diabetol Metab Syndr. 2010; 2: 31. Additional Figure Legend Fig. S1 Flow diagram of clinical trial in this work. Supplementary Files Fig.S1.tif CONSORTChecklist.doc TableS1.docx TableS2.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-26934","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":596192,"identity":"caf081bd-38b5-43d4-903c-12d2b9d51911","order_by":1,"name":"Jia Li","email":"","orcid":"https://orcid.org/0000-0003-4233-9021","institution":"The First Affiliated Hospital of Xiamen University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jia","middleName":"","lastName":"Li","suffix":""},{"id":596193,"identity":"4e59a394-d8a7-4356-85b8-36fa75b7fc17","order_by":2,"name":"Yinxiang 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Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYBACPmYQycPAwA/hMxPWwgbTItlAtBYYw+AA0VrYecwkPsgczjO+kZ0mwVBhndjAfvYAAYexpUnO4DlcbHbm7DYJhjPpiQ08eQkEtDAfk+bhOZy47XjvNgnGtsOJDRI8BgS0MLZJ/wFq2dzMC9TyjygtQFsYgFo2sINsaSBKC1uyZQ9PeuKMM2c3WyQcSzdu48nBr4Wf/4zhjZ891on9M3I33vhQYy3bz34GvxYwYOyBMhIYkGIKP/hBnLJRMApGwSgYoQAAocE8G82uVbIAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-0578-2633","institution":"","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xuejun","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2020-05-03 14:05:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-26934/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-26934/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":1181802,"identity":"a33e140a-0c5a-441d-8edc-46b94796efb7","added_by":"auto","created_at":"2020-05-26 21:25:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27427,"visible":true,"origin":"","legend":"DMGV concentration in each quartile (Q) when subjects were divided into four quartiles according to IHTG content.","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-26934/v1/1.png"},{"id":1181805,"identity":"822e89e6-31f7-4c7b-9a11-de00cf103044","added_by":"auto","created_at":"2020-05-26 21:25:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":79876,"visible":true,"origin":"","legend":"DMGV concentration in control (C), moderate exercise (ME) and vigorous exercise (VE) groups on baseline (0 M) and 6 month (6 M). (Data were compared by a paired t test in each group, and presented as mean with 95% confidence interval)","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-26934/v1/2.png"},{"id":1181806,"identity":"f9fa32f1-277b-4150-ba2c-b8f813d3dddc","added_by":"auto","created_at":"2020-05-26 21:25:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":39255,"visible":true,"origin":"","legend":"DMGV concentration changes after 6 month exercise intervention in control, moderate exercise and vigorous exercise groups (mean ± SEM).","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-26934/v1/3.png"},{"id":13532395,"identity":"81621080-3531-491e-af87-662552b6901f","added_by":"auto","created_at":"2021-09-17 01:16:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":579981,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-26934/v1/20ede279-6848-4a4d-95cd-6ca9d2d5156b.pdf"},{"id":1181807,"identity":"024abcf1-20f9-4f01-a2e6-36519b7bbf5a","added_by":"auto","created_at":"2020-05-26 21:25:35","extension":"tif","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":304004,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.S1.tif","url":"https://assets-eu.researchsquare.com/files/rs-26934/v1/Fig.S1.tif"},{"id":1181808,"identity":"2cbad6bc-c7e2-43de-a555-4d6390114d7d","added_by":"auto","created_at":"2020-05-26 21:25:35","extension":"doc","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":224768,"visible":true,"origin":"","legend":"","description":"","filename":"CONSORTChecklist.doc","url":"https://assets-eu.researchsquare.com/files/rs-26934/v1/CONSORTChecklist.doc"},{"id":1181803,"identity":"6655678f-6da3-4254-aea5-be73ed6eed43","added_by":"auto","created_at":"2020-05-26 21:25:34","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":16114,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-26934/v1/TableS1.docx"},{"id":1181804,"identity":"fc20ccec-1e8d-4ae3-bdc9-f4f80d6c8db0","added_by":"auto","created_at":"2020-05-26 21:25:34","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":17022,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-26934/v1/TableS2.docx"}],"financialInterests":"","formattedTitle":"Dimethylguanidino valeric acid is independently associated with intrahepatic triglyceride content in patients with nonalcoholic fatty liver disease (NAFLD) and decreased after long-term exercise","fulltext":[{"header":"Background","content":" \u003cp\u003eNonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease and has become an increasingly pandemic disease as the improvement of people's life, which is also the hepatic manifestation of the metabolic syndrome and a risk factor for many metabolic diseases \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Exercise was a major recommended treatment for NAFLD by decreasing visceral adipose tissue, liver fat, body fat and weight as well as improvement of cardiovascular risk factors \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Our previous clinical trial \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e found that intrahepatic triglyceride (IHTG) content was decreased significantly by long term moderate and vigorous exercise in NAFLD subjects without a significant difference, while the metabolic profile changes during exercise was unknown, which exercise intensity was more efficient on metabolic alteration was unclear.\u003c/p\u003e \u003cp\u003eWith the development of analytical technologies, metabolomic study has been widely used to discover a panel of biomarkers in development and progression of NAFLD \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Recently, Targeted and non-targeted metabolomics studies has identified that circulating dimethylguanidino valeric acid (DMGV) was acted as a marker of liver fat and predicted future diabetes up to 12\u0026nbsp;years in 3 distinct human cohorts \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, in addition, plasma DMGV levels had a strong relationship with visceral adiposity and decreased insulin sensitivity, and was recognized as an early marker of cardiometabolic dysfunction in health white people \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. However, DMGV\u0026rsquo; character in NAFLD status and its response to exercise were limited.\u003c/p\u003e \u003cp\u003eThis current study aimed to figure out the relationship between DMGV levels and clinical parameters among NALFD patients, especially IHTG content, and compare the DMGV levels changes after 6 month moderate and vigorous exercise training.\u003c/p\u003e "},{"header":"Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy protocol\u003c/h2\u003e \u003cp\u003eThe study protocol, informed consent form and all steps from blood extraction to analysis were approved by a steering committee, institutional review boards of Xiamen University and the First Affiliated Hospital of Xiamen University in China, and written informed consent was obtained from all participants. All methods were carried out in accordance with the relevant guidelines and regulations.\u003c/p\u003e \u003cp\u003eStudy participant and protocol were described in our previous study (Trial registration number: NCT01418027) \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, briefly, a total of 220 individuals with NAFLD were selected and randomly assigned to control group (n\u0026thinsp;=\u0026thinsp;74), moderate exercise group (n\u0026thinsp;=\u0026thinsp;73, brisk walking 150 minutes per week at 45%-55% of maximum heart rate) and vigorous-moderate exercise group (n\u0026thinsp;=\u0026thinsp;73, jogging 150 minutes per week at 65%-80% of maximum heart rate for 6 months and brisk walking 150 minutes per week at 45%-55% of maximum heart rate for another 6 months) with a 12-month followed-up. At 8:00 am after an overnight fast, blood samples were collected, and then were centrifuged at 3000\u0026thinsp;\u0026times;\u0026thinsp;g for 10\u0026nbsp;min, serum were stored at -80\u0026nbsp;\u0026deg;C until analysis. In this present study, only 6 month exercise intervention was concerned.\u003c/p\u003e \u003c/div\u003e \n\u003ch2\u003eDetermination Of Serum Dmgv Concentration\u003c/h2\u003e\n \u003cp\u003e50\u0026nbsp;\u0026micro;L serum was added 200\u0026nbsp;\u0026micro;L acetonitrile and 5\u0026nbsp;\u0026micro;L inner standard (IS) solution (L-phenyl-d5-alanine, 10\u0026nbsp;\u0026micro;g/mL), after centrifuging at 19,000\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\u003cscript type=\"math/tex; mode=inline\"\u003e \\times \u003c/script\u003e\u003c/span\u003e\u003c/span\u003eg for 10\u0026nbsp;min at 4\u0026nbsp;\u0026deg;C, 50\u0026nbsp;\u0026micro;L of the supernatant was then mixed with 200\u0026nbsp;\u0026micro;L initial mobile phase, the aliquot of which (5\u0026nbsp;\u0026micro;L) was injected into the ultrahigh performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) system for analysis.\u003c/p\u003e \u003cp\u003eDMGV (purity\u0026thinsp;\u0026gt;\u0026thinsp;97%) was synthesized by Nanjing Fanyida Biotechnology co. LTD (Nanjing China). LC-MS/MS was run on an Agilent 6460 triple stage quadrupole mass spectrometer equipped with an ESI ion source and an Agilent 1290 HPLC system with auto-sampler (Agilent Technologies, Santa Clara, CA, USA). DMGV was separated on an HSS T3 column (2.1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\u003cscript type=\"math/tex; mode=inline\"\u003e \\times \u003c/script\u003e\u003c/span\u003e\u003c/span\u003e100 mm, 1.8\u0026nbsp;\u0026micro;m, Waters, Milford, USA) at 30\u0026nbsp;\u0026deg;C. The mobile phase consisting of water with 2.5\u0026nbsp;mM ammonium formate and 0.1% formic acid (Solvent A) and acetonitrile (Solvent B) was used with a gradient elution: 0-4.5\u0026nbsp;min, 3\u0026ndash;5% B at a flow rate of 0.2\u0026nbsp;mL/min, then column was washed by 90% B and equilibrated by 3% B for another 1.5\u0026nbsp;min, respectively. MS/MS conditions were as follows: Gas temperature 325\u0026nbsp;\u0026deg;C, Gas flow 10\u0026nbsp;L/min, Nebulizer 30 psi, Sheath gas temperature 400\u0026nbsp;\u0026deg;C, Sheath gas flow 11\u0026nbsp;L/min, Capillary 3500\u0026nbsp;V, Nozzle voltage 2000\u0026nbsp;V. Quantification was obtained by using multiple reaction monitoring (MRM) mode in positive ion mode (DMGV: \u003cem\u003em/z\u003c/em\u003e 202.1\u0026ndash;71.1, Fragmentor 123\u0026nbsp;V, Collision Energy 25\u0026nbsp;V, Cell Cell Accelerator Voltage 0\u0026nbsp;V; IS: \u003cem\u003em/z\u003c/em\u003e 171.1-125.1, Fragmentor 83\u0026nbsp;V, Collision Energy 10\u0026nbsp;V, Cell Cell Accelerator Voltage 0\u0026nbsp;V ). Mass Hunter workstation software (Version B. 05. 00, Agilent Technologies, Santa Clara, CA, USA) was employed for data acquisition and processing.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003ePearson\u0026rsquo;s correlation coefficient (for normally distributed variables) and Spearman\u0026rsquo;s rank correlation (for non-normally distributed variables) were performed to analyze the correlation between clinical characteristics and DMGV levels in NAFLD subjects at baseline. The subjects were classified into four quartiles according to DMGV levels, other parameters in different groups were compared using an ANOVA test. DMGV levels changes after exercise testing were assessed by a paired \u003cem\u003et\u003c/em\u003e test in each group. All statistical analyses were performed using SPSS 22.0 software. \u003cem\u003eP\u003c/em\u003e value less than 0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSubjects characteristics\u003c/h2\u003e \u003cp\u003eA total of 220 NAFLD participants were recruited and followed up for 12 months \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, only 6 month intervention were concerned in the present study (flow diagram was showed in Fig. S1). There were no significant difference in basic anthropometric data among three groups (Table S1); after 6 month exercise training, main clinical characteristics changed (Table S2), particularly, IHTG content were significant decreased (by 5.0% in the vigorous exercise, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 4.2% in the moderate exercise, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but high-intensity exercise offered no additional benefit to moderate intensity exercise in decreasing IHTG (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.45) \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch2\u003e Uhplc-ms/ms Method Validation\u003c/h2\u003e\n \u003cp\u003eFor determination of DMGV concentration in human serum, serum sample preparation, LC condition and MS parameters of \u003cem\u003em/z\u003c/em\u003e 202.1\u0026rarr;71.1 was carefully optimized. The lower limit of detection (LLOD) of DMGV in human serum was 1\u0026nbsp;ng/ml, and the lower limit of quantification (LLOQ) was 5\u0026nbsp;ng/ml. Calibration curve, accuracy, precision of intra-day and inter-day, recovery and matrix effect were carefully validated and all within the acceptable limit (data were not shown).\u003c/p\u003e \n\u003ch2\u003eCorrelation Between Dmgv Levels And Clinical Characteristics At Baseline\u003c/h2\u003e\n \u003cp\u003eThere were no significant difference on DMGV concentration among three groups at baseline (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.842). Serum DMGV levels were positive associated with age, visceral fat and IHTG content, and inversely associated with fasting blood glucose, diastolic blood pressure (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). After adjusting age, sex, BMI (body mass index) and visceral fat, correlation with IHTG remained highly significant (β coefficient\u0026thinsp;=\u0026thinsp;0.169, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021), moreover, DMGV was still significant positive associated with IHTG after additional adjusting weight, subcutaneous fat, fasting blood glucose and DBP (β coefficient\u0026thinsp;=\u0026thinsp;0.174, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate analysis between DMGV concentration and clinical characteristics in NAFLD subjects at baseline (n\u0026thinsp;=\u0026thinsp;220).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting blood glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol (TC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Triglyceride (TG)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-density lipoprotein-cholesterol (HDL-C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-density lipoprotein-cholesterol (LDL-C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlanine transaminase (ALT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspartate aminotransferase (AST)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eγ-Glutamyltransferase (GGT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic blood pressure (SBP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic blood pressure (DBP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody Mass Index (BMI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisceral fat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubcutaneous fat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Fat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntrahepatic triglyceride (IHTG) content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSubjects were divided into four quartiles according to DMGV levels, TG, LDL-C, ALT, AST, GGT, SBP, weigh, BMI, subcutaneous fat and total fat were did not different in these four groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), visceral fat and IHTG content were elevated with higher DMGV levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Moreover, DMGV levels were elevated with higher IHTG content when subjects were divided into four quartiles according to IHTG content (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical characteristics as DMGV levels were divided into four quartiles (data were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuartile 1 (n\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQuartile 2 (n\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuartile 3 (n\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQuartile 4 (n\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMGV, ng/ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e18.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e60.0\u0026thinsp;\u0026plusmn;\u0026thinsp;10.0\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e84.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e51.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e54.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e53.1\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e56.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting blood glucose, mg/dl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e106.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e104.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e101.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e101.1\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC, mg/dl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e222.6\u0026thinsp;\u0026plusmn;\u0026thinsp;36.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e232.8\u0026thinsp;\u0026plusmn;\u0026thinsp;33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e241.3\u0026thinsp;\u0026plusmn;\u0026thinsp;40.1\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e222.8\u0026thinsp;\u0026plusmn;\u0026thinsp;37.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG, mg/dl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e168. 1\u0026thinsp;\u0026plusmn;\u0026thinsp;79.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e175.5\u0026thinsp;\u0026plusmn;\u0026thinsp;68.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e168.2\u0026thinsp;\u0026plusmn;\u0026thinsp;70.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e159.2\u0026thinsp;\u0026plusmn;\u0026thinsp;47.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.689\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C, mg/dl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e45.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e47.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e52.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e47.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C, mg/dl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e144.9\u0026thinsp;\u0026plusmn;\u0026thinsp;29.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e143.7\u0026thinsp;\u0026plusmn;\u0026thinsp;27.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e152.0\u0026thinsp;\u0026plusmn;\u0026thinsp;43.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e133.5\u0026thinsp;\u0026plusmn;\u0026thinsp;35.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e23.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e24. 9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e26.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e25.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e23.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e23.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e24.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFFT, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e39.8\u0026thinsp;\u0026plusmn;\u0026thinsp;17. 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e36.6\u0026thinsp;\u0026plusmn;\u0026thinsp;20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e33.9\u0026thinsp;\u0026plusmn;\u0026thinsp;17.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e32.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.7\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e134.5\u0026thinsp;\u0026plusmn;\u0026thinsp;15.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e134.4\u0026thinsp;\u0026plusmn;\u0026thinsp;14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e128.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e133.1\u0026thinsp;\u0026plusmn;\u0026thinsp;15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e82.0\u0026thinsp;\u0026plusmn;\u0026thinsp;10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e82.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e77.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e79.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeigh, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e72.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e72.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e69.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e70.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e28.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e27.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e27.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e27.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e96.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e95.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e92.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e96.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisceral fat, cm\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e116.1\u0026thinsp;\u0026plusmn;\u0026thinsp;32.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e126.9\u0026thinsp;\u0026plusmn;\u0026thinsp;33.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e141.6\u0026thinsp;\u0026plusmn;\u0026thinsp;37.5\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e146.1\u0026thinsp;\u0026plusmn;\u0026thinsp;29.4\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubcutaneous fat, cm\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e230.4\u0026thinsp;\u0026plusmn;\u0026thinsp;78.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e213.6\u0026thinsp;\u0026plusmn;\u0026thinsp;55.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e232.5\u0026thinsp;\u0026plusmn;\u0026thinsp;58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e244.8\u0026thinsp;\u0026plusmn;\u0026thinsp;69.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Fat, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e23.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e22.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e23.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e24.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIHTG content, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e12.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5. 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e17.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e20.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.5\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eP\u003c/em\u003e value was calculated among four groups by ANOVA analysis\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e* \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003evs\u003c/em\u003e Quartile 1\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \n\u003ch2\u003eDmgv Levels Changes After Exercise Intervention\u003c/h2\u003e\n \u003cp\u003eAfter 6 month exercise training, DMGV levels were decreased by moderate (-9.96 to 2.27\u0026nbsp;ng/ml, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and vigorous exercise training (-4.53 to 4.56\u0026nbsp;ng/ml, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.762) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Compared to control, moderate exercise was more efficient on decreasing DMGV concentration than vigorous exercise with a significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003ch2\u003eCorrelation between baseline DMGV levels and longitudinal changes of clinical characteristics\u003c/h2\u003e \u003cp\u003eBaseline DMGV levels were inversely correlated with the changes of waist circumference (r=-0.312, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010) and subcutaneous fat (r=-0.278, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022), and positive correlated with changes of LDL-C (r\u0026thinsp;=\u0026thinsp;0.286, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018) after 6 month moderate exercise training, and it was not associated with changes of IHTG content (r\u0026thinsp;=\u0026thinsp;0.189, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.122). We then investigate the correlations between changes of DMGV levels and changes of clinical parameters, unfortunately, there were no strong correlation (data were not shown).\u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eThis study has two principal findings. First, DMGV levels were positive associated with IHTG content, and elevated with higher IHTG content in NAFLD subjects. After 6 month exercise intervention, DMGV levels were decreased in both exercise groups, and moderate exercise was more efficient on decreasing DMGV levels than vigorous exercise. Taken together, these findings highlight the important role of DMGV in NAFLD progression, and moderate was a preferred exercise intensity in NAFLD treatment.\u003c/p\u003e \u003cp\u003eDMGV was a product of asymmetric dimethylarginine (ADMA) metabolized by alanine-glyoxylate aminotransferase 2 (AGXT2) and participated in nitric oxide signaling as a part of the arginine metabolism in human \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. DMGV was higher in individuals with nonalcoholic steatohepatitis and confirmed a strong positive correlation with liver fat \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Moreover, DMGV was a beneficial metabolic intervention, since its level was decreased in participants after weight loss surgery. Recent study proposed that DMGV levels were positively associated with body fat, abdominal visceral fat, TG and an inverse associated with insulin sensitivity, LDL-C and HDL-C in healthy people \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e; however, DMGV remains an incompletely understood metabolite with few data in NAFLD. For DMGV concentration quantitation in human serum in our study, LC condition, MS/MS parameters and serum sample preparation was carefully optimized, method validation was strictly performed. Acetonitrile was chosen for proteins participate in serum sample preparation since it was widely used and relatively simple before LC-MS/MS analysis \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Isotope-labeled DMGV was the best inner standard for DMGV quantitation \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, unfortunately, there was no commercial reference and it had to be synthesized, therefore, L-phenyl-d5-alanine was used as inner standard because of its widely used in other similar metabolomics studies \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. In this work, the relationship between DMGV levels and clinical parameters in NAFLD subjects was investigated, and it was demonstrated a positive association with age, IHTG content and visceral fat, and an inverse association with fasting blood glucose and DBP for the first time. In particular, DMGV had a close positive relationship with IHTG content after adjusting other main clinical characteristics in NAFLD participants. In addition, DMGV concentration and IHTG content were elevated with each other according to the four quartiles analysis, which indicated that DMGV might be a potential indicator during NAFLD development and progression (IHTG content\u0026thinsp;\u0026gt;\u0026thinsp;5% was diagnosed as NAFLD in clinic). These results further supported DMGV as independent biomarker in NAFLD.\u003c/p\u003e \u003cp\u003eExercise benefited NAFLD in different exercise intensities without a significant difference on decreasing IHTC content in our previous clinical trial, but the metabolic profile changes were poorly understood. A previous metabolomics study found a panel of altered serum metabolites after 6 month vigorous exercise training \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, however, whether these metabolites altered by moderate exercise was unknown, which exercise intensity was more efficient on metabolites changes was unclear. Thus, in the present study, DMGV was used to evaluate the effect on metabolic changes under different exercise intensities. We found that DMGV concentration was decreased after 6 month exercise training, which was corresponding to another similar study \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Interestingly, compared to control, moderate exercise was much more efficient on decreasing DMGV than vigorous exercise with an equal effect on IHTG reduction, though vigorous exercise was more efficient on improvement of weight, waist circumference, body fat and visceral fat. It was confirmed that various exercise intensities impacted plasma metabolic profile differently \u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, and low-intensity exercise favors a fat oxidation rate than in the high intensity exercise group with a greater decrease in body mass and fat mass \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, thus, we considered that moderate exercise benefits DMGV metabolism better than vigorous exercise might due to the better improvement on enzyme related to DMGV metabolism and oxidation ability, which needed further investigation.\u003c/p\u003e \u003cp\u003eThis work has several limitations. All participants in this study were diagnosed as NAFLD by protonmagnetic resonance spectroscopy (IHTG content\u0026thinsp;\u0026ge;\u0026thinsp;5%) without healthy subjects. Another limitation was a lack of specific pathologies of NAFLD (steatosis, nonalcoholic steatohepatitis, liver fibrosis and cirrhosis) without liver biopsy. Moreover, DMGV levels altered differently response to different exercise intensities, the inner mechanism were needed to figure out in further study.\u003c/p\u003e "},{"header":"Conclusions","content":" \u003cp\u003eTo the best of our knowledge, this is the first study to demonstrate that DMGV levels was closely associated with main clinical characteristics and decreased after 6 month exercise training in NAFLD subjects. Compared to vigorous exercise, moderate exercise was more efficient on decreasing DMGV concentration with an equal IHTG improvement. Overall, this finding provided a meaningful metabolic indicator in the development and progression in NAFLD, and optimized the clinical guideline in NAFLD treatment by long term exercise.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eNAFLD: nonalcoholic fatty liver diseas\u003c/p\u003e\n\u003cp\u003eDMGV: Dimethylguanidino valeric acid\u003c/p\u003e\n\u003cp\u003eUHPLC-MS/MS: ultrahigh performance liquid chromatography-tandem mass spectrometry\u003c/p\u003e\n\u003cp\u003eIHTG: intrahepatic triglyceride\u003c/p\u003e\n\u003cp\u003eIS: inner standard\u003c/p\u003e\n\u003cp\u003eBMI: mody mass index\u003c/p\u003e\n\u003cp\u003eTG: Total Triglyceride\u003c/p\u003e\n\u003cp\u003eTC: Total cholesterol\u003c/p\u003e\n\u003cp\u003eHDL-C: High-density lipoprotein-cholesterol\u003c/p\u003e\n\u003cp\u003eLDL-C: Low-density lipoprotein-cholesterol\u003c/p\u003e\n\u003cp\u003eALT: Alanine transaminase\u003c/p\u003e\n\u003cp\u003eAST: Aspartate aminotransferase\u003c/p\u003e\n\u003cp\u003eGGT: \u0026gamma;-Glutamyltransferase\u003c/p\u003e\n\u003cp\u003eSBP: Systolic blood pressure\u003c/p\u003e\n\u003cp\u003eDBP: Diastolic blood pressure\u003c/p\u003e\n\u003cp\u003eADMA: asymmetric dimethylarginine\u003c/p\u003e\n\u003cp\u003eAGXT2: alanine-glyoxylate aminotransferase 2\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate: \u003c/strong\u003eThe study protocol, informed consent form and all steps from blood extraction to analysis were approved by a steering committee, institutional review boards of Xiamen University and the First Affiliated Hospital of Xiamen University in China. Written informed consent was obtained from all participants and which was clearly stated in section \u0026ldquo;Study protocol\u0026rdquo;. All methods were carried out in accordance with the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication: \u003c/strong\u003enot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials: \u003c/strong\u003eData sharing is not applicable to this article as no datasets were generated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests: \u003c/strong\u003eAll authors declare no conflicts relative to this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding: \u003c/strong\u003eThis work was financially supported by National Natural Science Foundation of China (No. 81870606, No. 81570770 and No. 81400419). The funders supported the collection of clinical characteristics of NAFLD participants in clinical trial, measurement the DMGV concentration and analysis work, and also were responsible for charges if this manuscript was accepted for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions: \u003c/strong\u003eJL, XL and Zhong C contributed the study conception and design. JL and was responsible for data analysis and wrote the manuscript. XL, YH, YZ, Zheng C, XS, LW and LH were participated in clinical trial study, clinical characteristics detection, data analysis and blood sample collection. All authors have read and approved the manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements: \u003c/strong\u003eNot Applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMusso G, Gambino R, Bo S, Uberti B, Biroli G, Pagano G, et al. Should nonalcoholic fatty liver disease be included in the definition of metabolic syndrome? A cross-sectional comparison with Adult Treatment Panel III criteria in nonobese nondiabetic subjects. Diabetes Care. 2008; 31: 562-568.\u003c/li\u003e\n\u003cli\u003eSamuel VT, Shulman GI. Nonalcoholic fatty liver disease as a nexus of metabolic and hepatic diseases. Cell Metab. 2018; 27: 22-41.\u003c/li\u003e\n\u003cli\u003eKeating SE, Hackett DA, Parker HM, O'Connor HT, Gerofi JA, Sainsbury A, et al. Effect of aerobic exercise training dose on liver fat and visceral adiposity. \u003cem\u003eJ \u003c/em\u003e 2015; 63: 174-182.\u003c/li\u003e\n\u003cli\u003eShojaee-Moradie F, Cuthbertson DJ, Barrett M, , Barrett M, Jackson NC, Herring R, et al. Exercise training reduces liver fat and increases rates of VLDL clearance but not VLDL production in NAFLD. J Clin Endocrinol Metab. 2016; 101: 4219-4228.\u003c/li\u003e\n\u003cli\u003eZhang HJ, He J, Pan LL, Ma ZM, Han CK, Chen CS, et al. Effects of moderate and vigorous exercise on nonalcoholic fatty liver disease: a randomized clinical trial. JAMA Intern Med. 2016; 176: 1074-1082.\u003c/li\u003e\n\u003cli\u003eKalhan SC, Guo L, Edmison J, Dasarathy S, McCullough AJ, Hanson RW, et al. Plasma metabolomic profile in nonalcoholic fatty liver disease. Metabolism. 2011; 60: 404-413.\u003c/li\u003e\n\u003cli\u003eGorden DL, Myers DS, Ivanova PT, Fahy E, Maurya MR, Gupta S, et al. Biomarkers of NAFLD progression: a lipidomics approach to an epidemic. J Lipid Res. 2015; 56: 722\u0026ndash;736.\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;sullivan JF, Morningstar JE, Yang Q, Zheng B, Gao Y, Jeanfavre S, et al. Dimethylguanidino valeric acid is a marker of liver fat and predicts diabetes. J Clin Invest. 2017; 127: 4394-4402.\u003c/li\u003e\n\u003cli\u003eRobbins JM, Herzig M, Morningstar J, Sarzynski MA, Cruz DE, Wang TJ, et al. Association of Dimethylguanidino Valeric Acid With Partial Resistance to Metabolic Health Benefits of Regular Exercise. JAMA cardiol. 2019; 4: 636-643.\u003c/li\u003e\n\u003cli\u003eCuthbertson DJ, Sprung VS. High-intensity exercise offers no additional benefit to moderate-intensity exercise in reducing liver fat in patients with non-alcoholic fatty liver disease. Evid Based Med. 2017; 22: 103.\u003c/li\u003e\n\u003cli\u003eLi J, Zhao Y, Huang C, , Chen Z, Shi X, Li L, et al. Serum metabolomics analysis of the effect of exercise on nonalcoholic fatty liver disease. Endocr Connect. 2019; 8: 299-308.\u003c/li\u003e\n\u003cli\u003eKittel A, Maas R, K\u0026ouml;nig J, Mieth M, Weiss N, Jarzebska N, et al. In vivo evidence that Agxt2 can regulate plasma levels of dimethylarginines in mice. Biochem Biophys Res Commun. 2013; 430: 84-89.\u003c/li\u003e\n\u003cli\u003eRodionov, R.N.; Martens-Lobenhoffer, J.; Brilloff, S.; Hohenstein, B.; Jarzebska, N.; Jabs, N.; Kittel, N.; Maas, R.; Weiss, N.; Bode-B\u0026ouml;ger SM. Role of alanine: glyoxylate aminotransferase 2 in metabolism of asymmetric dimethylarginine in the settings of asymmetric dimethylarginine overload and bilateral nephrectomy. Nephrol Dial Transplant. 2014; 29: 2035-2042.\u003c/li\u003e\n\u003cli\u003eRochette L, Lorin J, Zeller M, Guilland JC, Lorgis L, Cottin Y, et al. Nitric oxide synthase inhibition and oxidative stress in cardiovascular diseases: possible therapeutic targets? Pharmacol Ther. 2013; 140: 239-257.\u003c/li\u003e\n\u003cli\u003eLi R, Liu P, Liu P, Tian Y, Hua Y, Gao Y, et al. A novel liquid chromatography tandem mass spectrometry method for simultaneous determination of branched-chain amino acids and branched-chain \u0026alpha;-keto acids in human plasma. Amino Acids. 2016; 48: 1523-1532.\u003c/li\u003e\n\u003cli\u003eMartens-Lobenhoffer J, Rodionov RN, Drust A, Bode-B\u0026ouml;ger SM. Detection and quantification of \u0026alpha;-keto-\u0026delta;-(NG, NG-dimethylguanidino) valeric acid: a metabolite of asymmetric dimethylarginine. Anal Biochemi. 2011, 419: 234-240.\u003c/li\u003e\n\u003cli\u003eXu Y, Yang L, Yang F, Xiong YH, Wang ZT, Hu ZB. Metabolic profiling of fifteen amino acids in serum of chemical-induced liver injured rats by hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry. Metabolomics. 2012; 8: 475-483.\u003c/li\u003e\n\u003cli\u003ePeake JM, Tan S, Markworth JF, Broadben, JA. Skinne TL, Cameron-Smith D. Metabolic and hormonal responses to isoenergetic high-intensity interval exercise and continuous moderate-intensity exercise. Am J Physiol Endocrinol Metab. 2014; 307: E539-E552.\u003c/li\u003e\n\u003cli\u003eRiberio DF, Cella PS, da Silva LECM, Jordao AA. Deminice R. Acute exercise alters homocysteine plasma concentration in an intensity-dependent manner due increased methyl flux in liver of rats. Life Sci. 2018; 196: 63-68.\u003c/li\u003e\n\u003cli\u003eKartaram S, Mensink M, Teunis M, Schoen E, Witte G, Duijghuijsen LJ, et al. Plasma citrulline concentration, a marker for intestinal functionality, reflects exercise intensity in healthy young men. Clin Nutr. 2019; 38: 2251-2258.\u003c/li\u003e\n\u003cli\u003eLira FS, Yamashita AS, Uchida MC, Zanchi NE, Gualano B, Martins J E, et al. Low and moderate, rather than high intensity strength exercise induces benefit regarding plasma lipid profile. Diabetol Metab Syndr. 2010; 2: 31.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Additional Figure Legend","content":"\u003cp\u003e\u003cstrong\u003eFig. S1\u003c/strong\u003e Flow diagram of clinical trial in this work.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"dimethylguanidino valeric acid; nonalcoholic fatty liver disease; intrahepatic triglyceride content, exercise; ultrahigh performance liquid chromatography-tandem mass spectrometry","lastPublishedDoi":"10.21203/rs.3.rs-26934/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-26934/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackgrounds: \u003c/strong\u003eDimethylguanidino valeric acid (DMGV) is closely associated with nonalcoholic fatty liver disease (NAFLD), the most recommended therapy of NAFLD is Exercise. Our aim was to investigate the correlation between DMGV concentrations and clinical characters in patients with NAFLD, and assessed the effect on DMGV concentrations changes after 6 month exercise training.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eNAFLD individuals (n = 220) were selected and randomly divided into control group (n = 74), moderate exercise group (n = 73) and vigorous exercise group (n = 73) with 6 month followed-up. Clinical characteristics were obtained from our previous clinical trial, serum DMGV levels were determined by a validated ultrahigh performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOn baseline, DMGV levels were positive associated with age, visceral fat and intrahepatic triglyceride (IHTG) content, and inversely associated with fasting blood glucose and diastolic blood pressure. In addition, the association between DMGV levels and IHTG content remained significant after adjusting other main clinical characters (β coefficient = 0.174, \u003cem\u003eP\u003c/em\u003e = 0.018). After 6 month exercise training, IHTG was decreased by both exercise intensities without a significant difference (\u003cem\u003eP\u003c/em\u003e = 0.45), however, moderate exercise was more efficient on DMGV decreasing than vigorous exercise (-9.96 to 2.27\u0026nbsp;ng/ml, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001 for moderate exercise; -4.53 to 4.56\u0026nbsp;ng/ml, \u003cem\u003eP\u003c/em\u003e = 0.762 for vigorous exercise) with a significant difference (\u003cem\u003eP\u003c/em\u003e = 0.047).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eDMGV was a potential indicator during development and progression of NAFLD, and moderate exercise was more efficient on metabolic changes than vigorous exercise with equal IHTG improvement, suggesting a priority of exercise intensity during NAFLD treatment.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eClinicalTrials.gov Identifier: \u003c/strong\u003eNCT01418027, August 16, 2011\u003c/p\u003e","manuscriptTitle":"Dimethylguanidino valeric acid is independently associated with intrahepatic triglyceride content in patients with nonalcoholic fatty liver disease (NAFLD) and decreased after long-term exercise","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-05-26 21:25:33","doi":"10.21203/rs.3.rs-26934/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65c1ebd4-f7af-4756-a6c9-b9c88fcd7557","owner":[],"postedDate":"May 26th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":106939,"name":"Endocrinology \u0026 Metabolism"}],"tags":[],"updatedAt":"2020-08-18T16:48:33+00:00","versionOfRecord":[],"versionCreatedAt":"2020-05-26 21:25:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-26934","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-26934","identity":"rs-26934","version":["v1"]},"buildId":"ehx78VzkSd0WSzXnipQa-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}