Omega-3 polyunsaturated fatty acids are associated with sarcopenia in patients with liver cirrhosis and hepatocellular carcinoma

Omega-3 polyunsaturated fatty acids are associated with sarcopenia in patients with liver cirrhosis and hepatocellular carcinoma | 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 Article Omega-3 polyunsaturated fatty acids are associated with sarcopenia in patients with liver cirrhosis and hepatocellular carcinoma Akitoshi Sano, Jun Inoue, Eiji Kakazu, Masashi Ninomiya, Tomoaki Iwata, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2344312/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 Sarcopenia is associated with the prognosis of patients with hepatic cirrhosis and hepatocellular carcinoma. This study aimed to clarify the composition of blood fatty acids and the association between fatty acids and sarcopenia in patients with cirrhosis and hepatocellular carcinoma. In this single center-retrospective study, 414 patients were enrolled. The skeletal muscle index was measured by a transverse computed tomography scan image at the third lumbar vertebra. The cutoff value for sarcopenia followed the criteria for sarcopenia of the Japan Society of Hepatology. The concentrations of fatty acids were measured by gas-chromatography. Of each fatty acid fraction, only omega-3 (n-3) polyunsaturated fatty acids showed a significant correlation with skeletal muscle index (R = 0.15, p = 0.0026). In the multivariate analysis, the level of n-3 polyunsaturated fatty acids was an independent variable associated with sarcopenia (odds ratio (95% CI): 0.9946 (0.9915–0.9977), p = 0.0004). N-3 polyunsaturated fatty acids were lower in patients with sarcopenia when the patient backgrounds were aligned using propensity score matching. These results showed an association between sarcopenia and n-3 polyunsaturated fatty acids. We believe this study will contribute to the research of nutritional therapy or fatty acid-supplementation therapy for sarcopenia in patients with cirrhosis and hepatocellular carcinoma. Health sciences/Gastroenterology/Hepatology/Liver diseases/Liver cirrhosis Health sciences/Rheumatology/Musculoskeletal system/Muscle/Skeletal muscle Health sciences/Gastroenterology/Hepatology/Liver diseases/Liver cancer/Hepatocellular carcinoma Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Morbidity and mortality due to liver cirrhosis is increasing worldwide and liver cirrhosis is the most potent risk factor for the development of hepatocellular carcinoma (HCC), which is the 6th most commonly occurring cancer in the world 1 , 2 . Cirrhosis is a major predisposing condition for the development of malnutrition, frailty and sarcopenia 3 . Sarcopenia has been defined by the European Working Group on Sarcopenia as “a progressive and generalized skeletal muscle disorder associated with an increased likelihood of adverse outcomes including falls, fractures, disability, and mortality 4 .” Pathophysiological factors that contribute to sarcopenia include hepatocellular necrosis with cytokine release, host biomolecules including danger-associated and pathogen-associated molecular patterns, portosystemic shunting resulting in hyperammonemia and endotoxemia, and the underlying etiology of liver disease (ethanol, cholestasis, insulin resistance, etc) 3 . Sarcopenia is associated with shorter survival and recurrence of HCC in cirrhosis and HCC patients 5 , 6 . Fatty acids (FAs) are important components of lipids and play important roles in cell and tissue metabolism and function. Omega-3 (n-3) polyunsaturated fatty acids (PUFAs) are a class of long-chain fatty acids with many beneficial biological effects. It has been shown that n-3 PUFAs suppress muscle protein degradation, enhance the rate of muscle protein synthesis in response to anabolic stimuli, oxidative stress and inflammation, and improve insulin sensitivity and lipid profile 7 , 8 . Although the impact of FAs on skeletal muscle systems has come to attention recently, few studies have been reported on the composition of plasma FAs in cirrhosis with sarcopenia. The aim of this study is to elucidate the association of plasma FAs associated with sarcopenia in patients with cirrhosis and HCC. Results Clinical characteristics of enrolled patients Baseline characteristics of the patients in our study (n = 414) are shown in Table 1 . The average age of the analyzed patients was 71.5 years, with males predominant (80.9%). In terms of liver disease etiology, patients with HCC due to hepatitis virus were in the majority (45.9%), followed by alcoholic liver disease (25.8%). Most cases were in TNM stage 1 (41.5%) or 2 (42.8%). In the analyzed patients, the fibrosis-4 score (Fib-4) index and albumin-bilirubin score (ALBI score) were high, suggesting the progression of hepatic fibrosis and decreased liver reserve capacity. Sarcopenia was observed in 247 patients (59.7%) based on the skeletal muscle index (SMI). Plasma fatty acids were correlated with liver dysfunction in subjects with liver cirrhosis We analyzed the relationship between the composition of plasma FAs and liver function. When the plasma levels of FAs were compared among Child-Pugh (CP) grades, it was found that saturated fatty acids (SFAs), n-3 PUFAs and n-6 PUFAs were lowered in patients with severe cirrhosis (CP grade B and C) than in those with CP grade A (Fig. 1 ). There was no significant difference in the monounsaturated fatty acids (MUFAs) level. In addition, ALBI scores were evaluated as another index of liver function. Pearson correlation analysis revealed negative correlations between each FA fraction and ALBI score (Fig. 2 ). These results suggested that the progression of liver disease was associated with lower blood FA levels. Plasma fatty acids were not associated with the progression of hepatocellular carcinoma To evaluate whether HCC progression affects the plasma levels of FAs, we examined the association between the FA levels and HCC status with the UICC TNM classification, number of tumors in the liver and maximum tumor diameter. Each of the FA fractions showed no differences with the TNM classification or number of tumors (Supplementary Fig. 1A,B). Similarly, no correlations between FAs and the tumor diameter were shown (Supplementary Fig. 1C). Comparison of patients according to the presence of sarcopenia The clinical characteristics of the patients were compared among those with and without sarcopenia, which was evaluated with SMI (Table 2 ). The proportion of females, AST and Fib-4 index were significantly higher and total bilirubin was significantly lower in patients with sarcopenia than in those without. In the nutritional aspect, total branched-chain amino acids (BCAAs) were significantly lower in subjects with sarcopenia, as described previously 9 . Notably, total FAs were significantly lower in patients with sarcopenia than in those without. As for its composition, SFAs, MUFAs and n-3 PUFAs fractions were significantly lower in patients with sarcopenia. N-3 polyunsaturated fatty acids were associated with skeletal muscle index We analyzed the correlation between SMI values and each of the FA fractions in all subjects. Although SFAs, MUFAs and n-6 PUFAs did not show significant correlations, only n-3 PUFAs were positively associated with SMI (Fig. 3 A). Since we found a significant association between liver function and FA levels, as shown in Figs. 1 and 2 , we performed a similar analysis only in the CP grade A cohort (Fig. 3 B). Then, even in the CP grade A population, only n-3 PUFAs were positively correlated with SMI. Logistic regression analysis revealed that n-3 PUFAs were the independent variable related to sarcopenia Since a correlation between n-3 PUFAs and skeletal muscle mass was suggested, we analyzed the association between the levels of n-3 PUFAs and the risk of sarcopenia with logistic regression analysis. Table 3 shows the odds ratio (OR) of the presence of sarcopenia in patients with liver cirrhosis for each variable. When a univariate analysis was performed, sex, subjects with non-alcoholic fatty liver disease (NAFLD), TNM stage, Fib-4 index, BCAA level and n-3 PUFA level were associated with the presence of sarcopenia, with OR of 0.4335 in sex (men) (95% CI: 0.2498–0.7523, p = 0.0019), 0.4731 in NAFLD (95% CI: 0.2697-0.8300, p = 0.0091), 2.3355 in TNM stage: 3–4 (95% CI: 1.2782–4.2674, p = 0.0058), 1.0821 in Fib-4 index (95% CI: 1.0018–1.1687, p = 0.0365), 0.9961 in BCAA level (95% CI: 0.9934–0.9982, p = 0.0002), 0.9944 in n-3 PUFA level (95% CI: 0.9917–0.9971, p = < 0.0001). Multivariate analysis showed that the n-3 PUFAs fraction was associated with the presence of sarcopenia, with adjusted OR of 0.9946 (95% CI: 0.9915–0.9977, p = 0.0004). In the univariate analysis, every n-3 PUFAs except C20:3 (eicosatrienoic acid) were significant variables: C18:3 (alpha-linolenic acid, OR: 0.9618, 95% CI: 0.9399–0.9842, p = 0.0004), C20:5 (eicosapentaenoic acid (EPA), OR: 0.9899, 95% CI: 0.9833–0.9965, p = 0.0023), C22:5 (docosapentaenoic acid, OR: 0.9281, 95% CI: 0.8969–0.9603, p < 0.0001) and C22:6 (docosahexaenoic acid (DHA), OR: 0.9904, 95% CI: 0.9856–0.9953, p < 0.0001) (Supplementary Table 1). These results revealed that a lower n-3 PUFA level was associated with a risk of sarcopenia. The comparison of n-3 polyunsaturated fatty acids with and without sarcopenia in matched patients with cirrhosis Finally, the n-3 PUFAs level was compared between patients with sarcopenia and those without whose background was matched using the propensity score. The covariates included age, sex, etiology, The union for International Cancer Control (UICC) tumor node metastasis (TNM) stage, CP grade, ALBI score, Fib-4 index and BCAA, and it was confirmed that there were no significant differences in each factor among the two groups (Supplementary Table 2). Then, the total levels of n-3 PUFAs were shown to be significantly lower in the group of patients with sarcopenia even among patient with matched backgrounds (Fig. 4 A). Additionally, among the n-3 PUFAs fraction, the levels of C18:3, C20:5, C22:5 and C22:6 were significantly lower in patients with sarcopenia than in those without (Fig. 4 B). Discussion Sarcopenia is a prevalent muscle abnormality in patients with cirrhosis. The presence of sarcopenia is a major predictor of mortality pre- and post-liver transplantation 10 – 13 , longer hospital stay 14 – 16 , hepatic encephalopathy 17 . Sarcopenia is also associated with poor survival in patients with HCC 18 . The pathogenesis of sarcopenia is multifactorial: hyperammonemia 19 , 20 , increased autophagy 19 , proteasomal activity 21 , myostatin 22 and impaired mitochondrial function 21 play important roles in sarcopenia with cirrhosis. Nutritional factors are also main factors in the pathogenesis of sarcopenia. Nutritional deficits, especially BCAAs, are frequent in patients with cirrhosis. Skeletal muscle consumption of BCAAs is accelerated in liver cirrhosis, leading to muscle protein breakdown and resulting in sarcopenia 23 . Thus, BCAAs are widely known to be important in the progression of sarcopenia, but the association between sarcopenia and FAs in liver diseases is unclear. In the present study, we analyzed the relationship between sarcopenia and blood FAs levels in patients with liver cirrhosis and HCC and found that sarcopenia in patients with cirrhosis and HCC was associated with lower levels of n-3 PUFAs. We revealed that the FA levels were lower in patients with low liver reserve function (CP score B or C) and, especially, n-3 PUFAs were most negatively correlated with the albumin-bilirubin score (R=-0.33, p < 0.0001). This result is consistent with previous reports showing that patients with liver cirrhosis have a lack of crucial FAs including n-3 PUFAs, which could be explained by a reduced alimentary intake as well as an impaired synthesis in the liver and an increased degradation of PUFAs due to lipid peroxidation 24 – 26 . It was expected that the FA levels would decrease with worsening cancer disease due to the worsening nutritional status. However, there was no association between the HCC status and FA levels in the patient background of this study. This might be because the patients in this study were mainly those with good hepatic reserve who could be treated for cancer. Further case studies are needed on the FA composition in patients with HCC with impaired hepatic reserve. Next, we analyzed the association between the composition of FAs and skeletal muscle mass. The correlation analysis revealed that SMI was significantly correlated only with the n-3 PUFAs level. Because we elucidated the association between hepatic reserve (CP score and ALBI score) and blood FA levels, we also analyzed the correlation only in patients with CP grade A (Fig. 3 B). The only FA that showed a significant correlation with muscle mass, even for patients with CP grade A, was n-3 FAs. In the multivariate analysis, the lower level of n-3 PUFAs was associated with an increased risk of sarcopenia among patients with cirrhosis when adjusted for patient backgrounds (etiology, TNM classification, Fib-4 index and plasma BCAA level). Furthermore, we found lower n-3 PUFAs levels in patients with sarcopenia when patient backgrounds were aligned using propensity score matching. These results showed an association between loss of skeletal muscle and lower level of n-3 FAs fraction in patients with cirrhosis and HCC. It has been known that n-3 PUFAs, especially EPA and DHA, play important roles in decreasing inflammatory processes 27 and the impact that n-3 PUFAs may have on skeletal muscle systems has recently come to attention. A cross-sectional study of 363 people aged 60 years and above assessed the relationship between dietary fish oil intake and frailty and found that fish oil intake had a positive effect on the frailty status of younger subjects 28 . Studies have also demonstrated a relationship between n-3 PUFAs and sarcopenia in patients with cancer: the change in muscle mass during chemotherapy was calculated in 41 patients with non-small cell lung cancer receiving chemotherapy, and patients with muscle loss had lower plasma EPA and DHA compared with those who were gaining muscle 29 . Itoh, et al. showed that low EPA and DHA levels were associated with preoperative sarcopenia in patients with HCC 30 . The effect of n-3 PUFAs supplementation on sarcopenia is controversial but randomized controlled trials have been conducted to elucidate the impacts of n-3 PUFAs on sarcopenia in older individuals 31 – 33 . Although further clinical studies are needed to examine the effects of adding n-3 PUFA, we believe that our large retrospective cohort study identifying the association between n-3 PUFAs and sarcopenia represents a new target for nutritional therapy in patients with HCC and cirrhosis. There are some limitations in this study. Firstly, this study was a single-center retrospective design. Prospective multicenter studies are needed. As the second limitation, we could not assess such factors as the effects of daily eating and exercise habits and medications of dyslipidemia and diabetes mellitus. The lack of grip strength data is also a limitation. The sarcopenia guidelines of the Japan Society of Hepatology, Asian Working Group for Sarcopenia, and European Working Group on Sarcopenia in Older People includes grip strength criteria 34 – 36 . The assessment of grip strength is becoming increasingly important༎ For example, a large multicenter study in Japan showed that reduced grip strength predicts poorer survival in chronic liver diseases 37 . These factors should be evaluated in future studies. Despite these limitations, the strength of this study is that it consisted of a large number of recent patients with FAs profiles and detailed analyses were performed such as multivariate analysis and propensity score matching. In conclusion, this retrospective study elucidated that FA levels, especially n-3 PUFAs were decreased with impaired hepatic reserve, and a low n-3 PUFAs level was associated with sarcopenia in patients with hepatic cirrhosis and HCC. These results showed that n-3 PUFAs may be a target for nutritional therapy or FA supplementation therapy for sarcopenia in patients with HCC and cirrhosis. Further prospective and multi-center studies are needed to elucidate whether intervention with n-3 PUFAs can prevent sarcopenia and improve the prognosis and quality of life in patients with HCC and hepatic cirrhosis. Methods Patients We retrospectively enrolled 414 patients with cirrhosis and HCC who were admitted to Tohoku University Hospital for the treatment of HCC from December 2017 to June 2021. The diagnosis of HCC was performed by the combination of computed tomography (CT) and tumor markers (alpha-fetoprotein: AFP, and protein induced by vitamin K absence-II: PIVKA-II). UICC-TNM stage was used for the evaluation of tumor progression 38 . Liver cirrhosis diagnosis was based on histological findings (F4) or imaging findings (presence of varices, deformity of liver, splenomegaly, etc.). Blood Examination and Fatty Acids Measurement Blood samples were obtained in the early morning after overnight fasting. The concentration of fatty acids was measured by gas-chromatography at a central laboratory (SRL, inc., Tokyo, Japan). CP grade and ALBI score were calculated for an assessment of the severity of liver dysfunction 39 , 40 . Fib-4 index was derived from aspartate aminotransferase (AST), alanine aminotransferase (ALT), platelet count (PLT) and age to predict advanced fibrosis 41 . Measurement of Skeletal Muscle Volume for Evaluating Sarcopenia CT scans used for analysis were carried out as a part of the preoperative HCC assessment. A transverse CT image at the level of third lumbar spine (L3) was assessed from each scan. Skeletal muscle was identified and the cross-sectional areas (cm 2 ) was quantified by Hounsfield unit (HU) thresholds of -29 to + 150 using image analysis software (WeVIEW Z-edition, HITACHI, Japan) after calibration with air, water and bone (air, water and bone are defined as -1000 HU, 0 HU and 1000 HU, respectively) 42 . Multiple muscles were quantified by manual tracing on the CT images including the psoas, erector spinae, quadratus lumborum, abdominal obliques and rectus abdominis muscle. The cross-sectional areas were then normalized for height (cm 2 /m 2 ) for SMI 43 . We defined sarcopenia as an L3 SMI value < 42cm 2 /m 2 for males and < 38 cm 2 /m 2 for females according to the Japan Society of hepatology guidelines for secondary sarcopenia in liver disease 34 . Statistical Analysis Comparison of the variables in the two groups was made using the unpaired t-test. Pearson’s chi-square test was used for the comparison of sex, etiology and UICC stage. Data are expressed as mean ± standard deviation (SD). The linear association between FAs and other variables was quantified via Pearson’s correlation coefficient. We analyzed the association between sarcopenia and FAs by univariate and multivariate analysis using logistic regression analysis. The selection of priori variables was based on previous literature and included age, etiology, cirrhosis status (CP grade, ALBI score), BCAA levels, liver fibrosis, and tumor progression 44 – 46 . Fib-4 index and TNM classification were used as variables of the hepatic fibrosis and tumor condition, respectively. The final multivariable model was developed by including the variable in the subsequent stage of analysis if the statistical significance was p value of < 0.10. Propensity score-matching analysis was performed in this study with the add-in package in JMP® Pro 16 software (SAS, Institute, NC) and conducted with the 1:1 nearest available matching method. The covariates included age, sex, etiology, UICC stage, CP grade, ALBI score, Fib-4 index and BCAAs. In all analyses, a P value of < 0.05 was considered statistically significant. All statistical analyses were performed with JMP® Pro 16. Declarations Data Availability All data generated or analyzed during this study are included in this article. Further enquiries can be directed to the corresponding author. Acknowledgments The authors thank the Division of Gastroenterology, Tohoku University Hospital for providing their facilities to conduct this study. This research was supported by AMED under Grant Number JP22fk0210114 and JSPS KAKENHI Grant Number JP21K20915. Author Contributions Akitoshi Sano: study concept and design, acquisition of data, interpretation of data, statistical analysis and manuscript preparation. Jun Inoue: statistical analysis, manuscript preparation, final drafting of the manuscript. Eiji Kakazu: acquisition of data, interpretation of data Masashi Ninomiya: acquisition of data, critical discussion, and support. Tomoaki Iwata: acquisition of data, critical discussion, and support. Mio Tsuruoka: acquisition of data, critical discussion, and support. Kosuke Sato: acquisition of data, critical discussion, and support. Masazumi Onuki: acquisition of data, critical discussion, and support. Satoko Sawahashi: acquisition of data, critical discussion, and support. Atsushi Masamune: critical discussion and support, revision of the manuscript, study supervision. All authors have approved the final version of the article including the authorship list. Competing interests The authors have declared that no conflict of interest exists. Statement of Ethics This study followed the principles of the Declaration of Helsinki (Fortaleza revision, 2013). Study approval statement: This study was reviewed and approved by the institutional review board of Tohoku University Hospital (approval number: 2019-1-378). Consent to participate statement Due to the retrospective observational study, the institutional review board of Tohoku University Hospital waived the need for written informed consent. The identifying data of the enrolled patients has been delinked and the authors could not access the individual data. References Ginès, P. et al. Liver cirrhosis. Lancet 398 , 1359–1376, doi: 10.1016/s0140-6736(21)01374-x (2021). Villanueva, A. Hepatocellular Carcinoma. N Engl J Med 380 , 1450–1462, doi: 10.1056/NEJMra1713263 (2019). Tandon, P., Montano-Loza, A. J., Lai, J. C., Dasarathy, S. & Merli, M. Sarcopenia and frailty in decompensated cirrhosis. J Hepatol 75 Suppl 1 , S147-s162, doi: 10.1016/j.jhep.2021.01.025 (2021). Lai, J. C. et al. 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Appl Physiol Nutr Metab 33 , 997–1006, doi: 10.1139/h08-075 (2008). Ebadi, M., Bhanji, R. A., Mazurak, V. C. & Montano-Loza, A. J. Sarcopenia in cirrhosis: from pathogenesis to interventions. J Gastroenterol 54 , 845–859, doi: 10.1007/s00535-019-01605-6 (2019). Perisetti, A. et al. Sarcopenia in hepatocellular carcinoma: Current knowledge and future directions. World J Gastroenterol 28 , 432–448, doi: 10.3748/wjg.v28.i4.432 (2022). Tantai, X. et al. Effect of sarcopenia on survival in patients with cirrhosis: A meta-analysis. J Hepatol 76 , 588–599, doi: 10.1016/j.jhep.2021.11.006 (2022). Tables Table 1. Characteristics of the analyzed patients with hepatic cirrhosis and hepatocellular carcinoma. y.o.: years old; NAFLD: non-alcoholic fatty liver disease; TNM: tumor-node-metastasis; T-Bil: total bilirubin; AST: aspartate aminotransferase; ALT: alanine aminotransferase; PT: prothrombin time; PLT: platelet; ALBI: albumin-bilirubin; Fib-4: fibrosis-4 score; BCAA: branched chain amino acid; FA: fatty acid; SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; SMI: skeletal muscle index Table 2. Comparison of clinical characteristics of patients with and without sarcopenia. y.o.: years old; n.s.: not significant; NAFLD: non-alcoholic fatty liver disease; TNM: tumor-node-metastasis; T-Bil: total bilirubin; AST: aspartate aminotransferase; ALT: alanine aminotransferase; PT: prothrombin time; PLT: platelet; ALBI: albumin-bilirubin; Fib-4: fibrosis-4 score; BCAA: branched chain amino acid; FA: fatty acid; SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; SMI: skeletal muscle index Table 3. Logistic regression analysis for variates associated with sarcopenia in patients with hepatic cirrhosis CI: confidence interval; n.s.: not significant; NAFLD: non-alcoholic fatty liver disease; TNM: tumor-node-metastasis; ALBI: albumin-bilirubin; Fib-4: fibrosis-4 score; BCAA: branched chain amino acid; PUFA: polyunsaturated fatty acid Additional Declarations No competing interests reported. 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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-2344312","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":159780392,"identity":"36dd5877-def9-4fb7-864b-cd26bc22fa17","order_by":0,"name":"Akitoshi Sano","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Akitoshi","middleName":"","lastName":"Sano","suffix":""},{"id":159780395,"identity":"5983b55b-772a-4fed-bff3-84334a778ef8","order_by":1,"name":"Jun Inoue","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYBACxmYwZQPECUBeA4MBRJyHoJY0kBbGBqK0QMFhdC14AHM778HHPBXno/nZE9gffNxhY2xwgPnhBwaZO3gcxpdszHPmdu7MngeMjTPPpJkZHGAzlmDgeYZHC4+ZNG/b7dwNNxIYm3nbDtsYHGAwA/rlMAEt/87l7kdoYf9GhJaGA7kbJCBagA7jIWiLseGcY8m5M848bJw5sy3NWPIwT7FEAh6/GPafMXzwpsYut789+cCHj202hn3H2zd++NiDO8QMGxAWQpnMQJzYcwCnFnkc4j9waxkFo2AUjIIRBwBXFlWZvX1AQQAAAABJRU5ErkJggg==","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Inoue","suffix":""},{"id":159780397,"identity":"1970dd8f-513f-4436-b735-e6c918f2fb06","order_by":2,"name":"Eiji Kakazu","email":"","orcid":"","institution":"National Center for Global Health and Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Eiji","middleName":"","lastName":"Kakazu","suffix":""},{"id":159780400,"identity":"2aa063e6-2f3f-442f-aaab-b4b43d292596","order_by":3,"name":"Masashi Ninomiya","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Masashi","middleName":"","lastName":"Ninomiya","suffix":""},{"id":159780402,"identity":"5dd99326-d58d-4d34-9b7b-17d2ceb32761","order_by":4,"name":"Tomoaki Iwata","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tomoaki","middleName":"","lastName":"Iwata","suffix":""},{"id":159780404,"identity":"ac4fb87f-5c64-420f-ba43-8adfe36bda41","order_by":5,"name":"Mio Tsuruoka","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mio","middleName":"","lastName":"Tsuruoka","suffix":""},{"id":159780406,"identity":"5bef5d18-dbb5-40da-8d72-ec9acb8f1b11","order_by":6,"name":"Kosuke Sato","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kosuke","middleName":"","lastName":"Sato","suffix":""},{"id":159780408,"identity":"22db910e-2a7f-4abd-829b-48f62995bb13","order_by":7,"name":"Masazumi Onuki","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Masazumi","middleName":"","lastName":"Onuki","suffix":""},{"id":159780409,"identity":"bbf7e4ea-dc30-4a5b-8b94-8a1c4687c0fe","order_by":8,"name":"Satoko Sawahashi","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Satoko","middleName":"","lastName":"Sawahashi","suffix":""},{"id":159780410,"identity":"ec1c10f4-05eb-4f62-b2b3-c99db5c0570c","order_by":9,"name":"Atsushi Masamune","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Atsushi","middleName":"","lastName":"Masamune","suffix":""}],"badges":[],"createdAt":"2022-12-05 04:29:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2344312/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2344312/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":30397482,"identity":"ab9a346c-0942-46df-a67f-03dd59db5a71","added_by":"auto","created_at":"2022-12-15 22:52:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":73181,"visible":true,"origin":"","legend":"\u003cp\u003ePlasma fatty acids level of patients with hepatic cirrhosis and hepatocellular carcinoma for Child-Pugh grade.\u003c/p\u003e\n\u003cp\u003en.s.: not significant\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2344312/v1/ff7d99856beb2f45381c0ddf.png"},{"id":30397480,"identity":"06fa97bb-3e52-48b9-b42f-7ff4f5fd31bd","added_by":"auto","created_at":"2022-12-15 22:52:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":111974,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between the albumin-bilirubin score and plasma fatty acids level in patients with hepatic cirrhosis.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2344312/v1/539f71fb3f6462877ee7dec6.png"},{"id":30397479,"identity":"9bffd7ef-74ad-4010-bfbc-1ee8f4fc8918","added_by":"auto","created_at":"2022-12-15 22:52:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":138820,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between the skeletal muscle index and plasma fatty acids level in patients with hepatic cirrhosis. (A) Analysis in the whole subjects. (B) Analysis in subject with Child-pugh grade A.\u003c/p\u003e\n\u003cp\u003en.s.: not significant\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-2344312/v1/436dc9431bece70960d13f81.png"},{"id":30398234,"identity":"340407ae-8406-44a9-a640-bde634ab5506","added_by":"auto","created_at":"2022-12-15 23:00:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":89009,"visible":true,"origin":"","legend":"\u003cp\u003eThe comparison of n-3 polyunsaturated fatty acids with and without sarcopenia in matched patients with cirrhosis. (A) The levels of n-3 polyunsaturated fatty acids is shown. (B) The levels of each fatty acid in n-3 polyunsaturated fatty acids are shown.\u003c/p\u003e\n\u003cp\u003en.s.: not significant\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-2344312/v1/738cf0830b12961aa8fd8ca4.png"},{"id":35745869,"identity":"16c3562a-e595-43e8-a8a3-9753c6e08c8f","added_by":"auto","created_at":"2023-04-14 03:44:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1355802,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2344312/v1/f6dd1656-5b28-48ca-a251-504862f45208.pdf"},{"id":30397483,"identity":"59b587fb-1330-4e06-ad06-8189af3ce582","added_by":"auto","created_at":"2022-12-15 22:52:59","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":806599,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryinformationver2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2344312/v1/e483150b4f8194029334a622.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Omega-3 polyunsaturated fatty acids are associated with sarcopenia in patients with liver cirrhosis and hepatocellular carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMorbidity and mortality due to liver cirrhosis is increasing worldwide and liver cirrhosis is the most potent risk factor for the development of hepatocellular carcinoma (HCC), which is the 6th most commonly occurring cancer in the world\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Cirrhosis is a major predisposing condition for the development of malnutrition, frailty and sarcopenia\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Sarcopenia has been defined by the European Working Group on Sarcopenia as \u0026ldquo;a progressive and generalized skeletal muscle disorder associated with an increased likelihood of adverse outcomes including falls, fractures, disability, and mortality\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u0026rdquo; Pathophysiological factors that contribute to sarcopenia include hepatocellular necrosis with cytokine release, host biomolecules including danger-associated and pathogen-associated molecular patterns, portosystemic shunting resulting in hyperammonemia and endotoxemia, and the underlying etiology of liver disease (ethanol, cholestasis, insulin resistance, etc)\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Sarcopenia is associated with shorter survival and recurrence of HCC in cirrhosis and HCC patients\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFatty acids (FAs) are important components of lipids and play important roles in cell and tissue metabolism and function. Omega-3 (n-3) polyunsaturated fatty acids (PUFAs) are a class of long-chain fatty acids with many beneficial biological effects. It has been shown that n-3 PUFAs suppress muscle protein degradation, enhance the rate of muscle protein synthesis in response to anabolic stimuli, oxidative stress and inflammation, and improve insulin sensitivity and lipid profile\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Although the impact of FAs on skeletal muscle systems has come to attention recently, few studies have been reported on the composition of plasma FAs in cirrhosis with sarcopenia. The aim of this study is to elucidate the association of plasma FAs associated with sarcopenia in patients with cirrhosis and HCC.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eClinical characteristics of enrolled patients\u003c/h2\u003e\n\u003cp\u003eBaseline characteristics of the patients in our study (n\u0026thinsp;=\u0026thinsp;414) are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The average age of the analyzed patients was 71.5 years, with males predominant (80.9%). In terms of liver disease etiology, patients with HCC due to hepatitis virus were in the majority (45.9%), followed by alcoholic liver disease (25.8%). Most cases were in TNM stage 1 (41.5%) or 2 (42.8%). In the analyzed patients, the fibrosis-4 score (Fib-4) index and albumin-bilirubin score (ALBI score) were high, suggesting the progression of hepatic fibrosis and decreased liver reserve capacity. Sarcopenia was observed in 247 patients (59.7%) based on the skeletal muscle index (SMI).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003ePlasma fatty acids were correlated with liver dysfunction in subjects with liver cirrhosis\u003c/h2\u003e\n\u003cp\u003eWe analyzed the relationship between the composition of plasma FAs and liver function. When the plasma levels of FAs were compared among Child-Pugh (CP) grades, it was found that saturated fatty acids (SFAs), n-3 PUFAs and n-6 PUFAs were lowered in patients with severe cirrhosis (CP grade B and C) than in those with CP grade A (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). There was no significant difference in the monounsaturated fatty acids (MUFAs) level. In addition, ALBI scores were evaluated as another index of liver function. Pearson correlation analysis revealed negative correlations between each FA fraction and ALBI score (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). These results suggested that the progression of liver disease was associated with lower blood FA levels.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003ePlasma fatty acids were not associated with the progression of hepatocellular carcinoma\u003c/h2\u003e\n\u003cp\u003eTo evaluate whether HCC progression affects the plasma levels of FAs, we examined the association between the FA levels and HCC status with the UICC TNM classification, number of tumors in the liver and maximum tumor diameter. Each of the FA fractions showed no differences with the TNM classification or number of tumors (Supplementary Fig.\u0026nbsp;1A,B). Similarly, no correlations between FAs and the tumor diameter were shown (Supplementary Fig.\u0026nbsp;1C).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003eComparison of patients according to the presence of sarcopenia\u003c/h2\u003e\n\u003cp\u003eThe clinical characteristics of the patients were compared among those with and without sarcopenia, which was evaluated with SMI (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The proportion of females, AST and Fib-4 index were significantly higher and total bilirubin was significantly lower in patients with sarcopenia than in those without. In the nutritional aspect, total branched-chain amino acids (BCAAs) were significantly lower in subjects with sarcopenia, as described previously\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Notably, total FAs were significantly lower in patients with sarcopenia than in those without. As for its composition, SFAs, MUFAs and n-3 PUFAs fractions were significantly lower in patients with sarcopenia.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003eN-3 polyunsaturated fatty acids were associated with skeletal muscle index\u003c/h2\u003e\n\u003cp\u003eWe analyzed the correlation between SMI values and each of the FA fractions in all subjects. Although SFAs, MUFAs and n-6 PUFAs did not show significant correlations, only n-3 PUFAs were positively associated with SMI (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA). Since we found a significant association between liver function and FA levels, as shown in Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, we performed a similar analysis only in the CP grade A cohort (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB). Then, even in the CP grade A population, only n-3 PUFAs were positively correlated with SMI.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eLogistic regression analysis revealed that n-3 PUFAs were the independent variable related to sarcopenia\u003c/h2\u003e\n\u003cp\u003eSince a correlation between n-3 PUFAs and skeletal muscle mass was suggested, we analyzed the association between the levels of n-3 PUFAs and the risk of sarcopenia with logistic regression analysis. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows the odds ratio (OR) of the presence of sarcopenia in patients with liver cirrhosis for each variable. When a univariate analysis was performed, sex, subjects with non-alcoholic fatty liver disease (NAFLD), TNM stage, Fib-4 index, BCAA level and n-3 PUFA level were associated with the presence of sarcopenia, with OR of 0.4335 in sex (men) (95% CI: 0.2498\u0026ndash;0.7523, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0019), 0.4731 in NAFLD (95% CI: 0.2697-0.8300, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0091), 2.3355 in TNM stage: 3\u0026ndash;4 (95% CI: 1.2782\u0026ndash;4.2674, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0058), 1.0821 in Fib-4 index (95% CI: 1.0018\u0026ndash;1.1687, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0365), 0.9961 in BCAA level (95% CI: 0.9934\u0026ndash;0.9982, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0002), 0.9944 in n-3 PUFA level (95% CI: 0.9917\u0026ndash;0.9971, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Multivariate analysis showed that the n-3 PUFAs fraction was associated with the presence of sarcopenia, with adjusted OR of 0.9946 (95% CI: 0.9915\u0026ndash;0.9977, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0004). In the univariate analysis, every n-3 PUFAs except C20:3 (eicosatrienoic acid) were significant variables: C18:3 (alpha-linolenic acid, OR: 0.9618, 95% CI: 0.9399\u0026ndash;0.9842, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0004), C20:5 (eicosapentaenoic acid (EPA), OR: 0.9899, 95% CI: 0.9833\u0026ndash;0.9965, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0023), C22:5 (docosapentaenoic acid, OR: 0.9281, 95% CI: 0.8969\u0026ndash;0.9603, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and C22:6 (docosahexaenoic acid (DHA), OR: 0.9904, 95% CI: 0.9856\u0026ndash;0.9953, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Supplementary Table\u0026nbsp;1). These results revealed that a lower n-3 PUFA level was associated with a risk of sarcopenia.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eThe comparison of n-3 polyunsaturated fatty acids with and without sarcopenia in matched patients with cirrhosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinally, the n-3 PUFAs level was compared between patients with sarcopenia and those without whose background was matched using the propensity score. The covariates included age, sex, etiology, The union for International Cancer Control (UICC) tumor node metastasis (TNM) stage, CP grade, ALBI score, Fib-4 index and BCAA, and it was confirmed that there were no significant differences in each factor among the two groups (Supplementary Table\u0026nbsp;2). Then, the total levels of n-3 PUFAs were shown to be significantly lower in the group of patients with sarcopenia even among patient with matched backgrounds (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA). Additionally, among the n-3 PUFAs fraction, the levels of C18:3, C20:5, C22:5 and C22:6 were significantly lower in patients with sarcopenia than in those without (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eSarcopenia is a prevalent muscle abnormality in patients with cirrhosis. The presence of sarcopenia is a major predictor of mortality pre- and post-liver transplantation\u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, longer hospital stay\u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, hepatic encephalopathy\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Sarcopenia is also associated with poor survival in patients with HCC\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. The pathogenesis of sarcopenia is multifactorial: hyperammonemia\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, increased autophagy\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, proteasomal activity\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, myostatin\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and impaired mitochondrial function\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e play important roles in sarcopenia with cirrhosis.\u003c/p\u003e \u003cp\u003eNutritional factors are also main factors in the pathogenesis of sarcopenia. Nutritional deficits, especially BCAAs, are frequent in patients with cirrhosis. Skeletal muscle consumption of BCAAs is accelerated in liver cirrhosis, leading to muscle protein breakdown and resulting in sarcopenia\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Thus, BCAAs are widely known to be important in the progression of sarcopenia, but the association between sarcopenia and FAs in liver diseases is unclear. In the present study, we analyzed the relationship between sarcopenia and blood FAs levels in patients with liver cirrhosis and HCC and found that sarcopenia in patients with cirrhosis and HCC was associated with lower levels of n-3 PUFAs.\u003c/p\u003e \u003cp\u003eWe revealed that the FA levels were lower in patients with low liver reserve function (CP score B or C) and, especially, n-3 PUFAs were most negatively correlated with the albumin-bilirubin score (R=-0.33, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). This result is consistent with previous reports showing that patients with liver cirrhosis have a lack of crucial FAs including n-3 PUFAs, which could be explained by a reduced alimentary intake as well as an impaired synthesis in the liver and an increased degradation of PUFAs due to lipid peroxidation\u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. It was expected that the FA levels would decrease with worsening cancer disease due to the worsening nutritional status. However, there was no association between the HCC status and FA levels in the patient background of this study. This might be because the patients in this study were mainly those with good hepatic reserve who could be treated for cancer. Further case studies are needed on the FA composition in patients with HCC with impaired hepatic reserve.\u003c/p\u003e \u003cp\u003eNext, we analyzed the association between the composition of FAs and skeletal muscle mass. The correlation analysis revealed that SMI was significantly correlated only with the n-3 PUFAs level. Because we elucidated the association between hepatic reserve (CP score and ALBI score) and blood FA levels, we also analyzed the correlation only in patients with CP grade A (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The only FA that showed a significant correlation with muscle mass, even for patients with CP grade A, was n-3 FAs. In the multivariate analysis, the lower level of n-3 PUFAs was associated with an increased risk of sarcopenia among patients with cirrhosis when adjusted for patient backgrounds (etiology, TNM classification, Fib-4 index and plasma BCAA level). Furthermore, we found lower n-3 PUFAs levels in patients with sarcopenia when patient backgrounds were aligned using propensity score matching. These results showed an association between loss of skeletal muscle and lower level of n-3 FAs fraction in patients with cirrhosis and HCC. It has been known that n-3 PUFAs, especially EPA and DHA, play important roles in decreasing inflammatory processes\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e and the impact that n-3 PUFAs may have on skeletal muscle systems has recently come to attention. A cross-sectional study of 363 people aged 60 years and above assessed the relationship between dietary fish oil intake and frailty and found that fish oil intake had a positive effect on the frailty status of younger subjects\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Studies have also demonstrated a relationship between n-3 PUFAs and sarcopenia in patients with cancer: the change in muscle mass during chemotherapy was calculated in 41 patients with non-small cell lung cancer receiving chemotherapy, and patients with muscle loss had lower plasma EPA and DHA compared with those who were gaining muscle\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Itoh, et al. showed that low EPA and DHA levels were associated with preoperative sarcopenia in patients with HCC\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. The effect of n-3 PUFAs supplementation on sarcopenia is controversial but randomized controlled trials have been conducted to elucidate the impacts of n-3 PUFAs on sarcopenia in older individuals\u003csup\u003e\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Although further clinical studies are needed to examine the effects of adding n-3 PUFA, we believe that our large retrospective cohort study identifying the association between n-3 PUFAs and sarcopenia represents a new target for nutritional therapy in patients with HCC and cirrhosis.\u003c/p\u003e \u003cp\u003eThere are some limitations in this study. Firstly, this study was a single-center retrospective design. Prospective multicenter studies are needed. As the second limitation, we could not assess such factors as the effects of daily eating and exercise habits and medications of dyslipidemia and diabetes mellitus. The lack of grip strength data is also a limitation. The sarcopenia guidelines of the Japan Society of Hepatology, Asian Working Group for Sarcopenia, and European Working Group on Sarcopenia in Older People includes grip strength criteria\u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. The assessment of grip strength is becoming increasingly important༎ For example, a large multicenter study in Japan showed that reduced grip strength predicts poorer survival in chronic liver diseases\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. These factors should be evaluated in future studies.\u003c/p\u003e \u003cp\u003eDespite these limitations, the strength of this study is that it consisted of a large number of recent patients with FAs profiles and detailed analyses were performed such as multivariate analysis and propensity score matching.\u003c/p\u003e \u003cp\u003eIn conclusion, this retrospective study elucidated that FA levels, especially n-3 PUFAs were decreased with impaired hepatic reserve, and a low n-3 PUFAs level was associated with sarcopenia in patients with hepatic cirrhosis and HCC. These results showed that n-3 PUFAs may be a target for nutritional therapy or FA supplementation therapy for sarcopenia in patients with HCC and cirrhosis. Further prospective and multi-center studies are needed to elucidate whether intervention with n-3 PUFAs can prevent sarcopenia and improve the prognosis and quality of life in patients with HCC and hepatic cirrhosis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eWe retrospectively enrolled 414 patients with cirrhosis and HCC who were admitted to Tohoku University Hospital for the treatment of HCC from December 2017 to June 2021. The diagnosis of HCC was performed by the combination of computed tomography (CT) and tumor markers (alpha-fetoprotein: AFP, and protein induced by vitamin K absence-II: PIVKA-II). UICC-TNM stage was used for the evaluation of tumor progression\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Liver cirrhosis diagnosis was based on histological findings (F4) or imaging findings (presence of varices, deformity of liver, splenomegaly, etc.).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBlood Examination and Fatty Acids Measurement\u003c/h2\u003e \u003cp\u003eBlood samples were obtained in the early morning after overnight fasting. The concentration of fatty acids was measured by gas-chromatography at a central laboratory (SRL, inc., Tokyo, Japan). CP grade and ALBI score were calculated for an assessment of the severity of liver dysfunction\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Fib-4 index was derived from aspartate aminotransferase (AST), alanine aminotransferase (ALT), platelet count (PLT) and age to predict advanced fibrosis\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of Skeletal Muscle Volume for Evaluating Sarcopenia\u003c/h2\u003e \u003cp\u003eCT scans used for analysis were carried out as a part of the preoperative HCC assessment. A transverse CT image at the level of third lumbar spine (L3) was assessed from each scan. Skeletal muscle was identified and the cross-sectional areas (cm\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e) was quantified by Hounsfield unit (HU) thresholds of -29 to +\u0026thinsp;150 using image analysis software (WeVIEW Z-edition, HITACHI, Japan) after calibration with air, water and bone (air, water and bone are defined as -1000 HU, 0 HU and 1000 HU, respectively)\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Multiple muscles were quantified by manual tracing on the CT images including the psoas, erector spinae, quadratus lumborum, abdominal obliques and rectus abdominis muscle. The cross-sectional areas were then normalized for height (cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e) for SMI\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. We defined sarcopenia as an L3 SMI value\u0026thinsp;\u0026lt;\u0026thinsp;42cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e for males and \u0026lt;\u0026thinsp;38 cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e for females according to the Japan Society of hepatology guidelines for secondary sarcopenia in liver disease\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eComparison of the variables in the two groups was made using the unpaired t-test. Pearson\u0026rsquo;s chi-square test was used for the comparison of sex, etiology and UICC stage. Data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). The linear association between FAs and other variables was quantified via Pearson\u0026rsquo;s correlation coefficient. We analyzed the association between sarcopenia and FAs by univariate and multivariate analysis using logistic regression analysis. The selection of priori variables was based on previous literature and included age, etiology, cirrhosis status (CP grade, ALBI score), BCAA levels, liver fibrosis, and tumor progression\u003csup\u003e\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Fib-4 index and TNM classification were used as variables of the hepatic fibrosis and tumor condition, respectively. The final multivariable model was developed by including the variable in the subsequent stage of analysis if the statistical significance was p value of \u0026lt;\u0026thinsp;0.10. Propensity score-matching analysis was performed in this study with the add-in package in JMP\u0026reg; Pro 16 software (SAS, Institute, NC) and conducted with the 1:1 nearest available matching method. The covariates included age, sex, etiology, UICC stage, CP grade, ALBI score, Fib-4 index and BCAAs. In all analyses, a \u003cem\u003eP\u003c/em\u003e value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant. All statistical analyses were performed with JMP\u0026reg; Pro 16.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this article. Further enquiries can be directed to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the Division of Gastroenterology, Tohoku University Hospital for providing their facilities to conduct this study.\u003c/p\u003e\n\u003cp\u003eThis research was supported by AMED under Grant Number JP22fk0210114 and JSPS KAKENHI Grant Number JP21K20915.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eAkitoshi Sano: study concept and design, acquisition of data, interpretation of data, statistical analysis and manuscript preparation.\u003c/li\u003e\n \u003cli\u003eJun Inoue: statistical analysis, manuscript preparation, final drafting of the manuscript.\u003c/li\u003e\n \u003cli\u003eEiji Kakazu: acquisition of data, interpretation of data\u003c/li\u003e\n \u003cli\u003eMasashi Ninomiya:\u0026nbsp;acquisition of data, critical discussion, and support.\u003c/li\u003e\n \u003cli\u003eTomoaki Iwata:\u0026nbsp;acquisition of data, critical discussion, and support.\u003c/li\u003e\n \u003cli\u003eMio Tsuruoka:\u0026nbsp;acquisition of data, critical discussion, and support.\u003c/li\u003e\n \u003cli\u003eKosuke Sato:\u0026nbsp;acquisition of data, critical discussion, and support.\u003c/li\u003e\n \u003cli\u003eMasazumi Onuki:\u0026nbsp;acquisition of data, critical discussion, and support.\u003c/li\u003e\n \u003cli\u003eSatoko Sawahashi:\u0026nbsp;acquisition of data, critical discussion, and support.\u003c/li\u003e\n \u003cli\u003eAtsushi Masamune:\u0026nbsp;critical discussion and support, revision of the manuscript, study supervision.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eAll authors have approved the final version of the article including the authorship list.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared that no conflict of interest exists.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of Ethics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study followed the principles of the Declaration of Helsinki (Fortaleza revision, 2013). Study approval statement: This study was reviewed and approved by the institutional review board of Tohoku University Hospital (approval number: 2019-1-378).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDue to the retrospective observational study, the institutional review board of Tohoku University Hospital waived the need for written informed consent. The identifying data of the enrolled patients has been delinked and the authors could not access the individual data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGin\u0026egrave;s, P. \u003cem\u003eet al.\u003c/em\u003e Liver cirrhosis. 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World J Gastroenterol \u003cb\u003e28\u003c/b\u003e, 432\u0026ndash;448, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3748/wjg.v28.i4.432\u003c/span\u003e\u003cspan address=\"10.3748/wjg.v28.i4.432\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTantai, X. \u003cem\u003eet al.\u003c/em\u003e Effect of sarcopenia on survival in patients with cirrhosis: A meta-analysis. J Hepatol \u003cb\u003e76\u003c/b\u003e, 588\u0026ndash;599, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2021.11.006\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2021.11.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Characteristics of the analyzed patients with hepatic cirrhosis and hepatocellular carcinoma.\u003c/p\u003e\n\u003cp\u003e\u003cimg 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IuI2XDHQe298PFbewvPiEJ3rHv2wATDTyjo5nhSvkqGyLdBPZ73kqaEys9CdDeq15XCbo+JJKjj79LKO9b4o59f+abiBdk4F8/tlPTXO/rmGJNl6NIb+vq03O9xG6zmZzN8HUGph/URDlCyo64bZZQK9lf1d5X0HttzWn9pzM63jPIEeERERt2HXQJ8O6LNAPwv8LfN7j3550+p8sM4Pt5FtgT5Yb2rsexmYfb350FoG/6Mn2Xk0PRxuc907b+WenxXHti9nT5DRa2/S+/RR3fjQTb4PHoyKI1vneR3u5+et1HpSw21ePDopbyAu91lroNeQoMQNtR7oGUe/Nqs0b6QmIiIiIq7XtkB/PZQl2aseBvRyWsdAv9Djr8CeG27j09cQ6G29+Z70arjN0ZPcsJx4uE01/6y3/aWeAKTl9LSbe7ad9evJxkHQU6/w3/h0G82bGG7jQ228YZQN9Ar+Gs5j60oNq/EhN/TQr80qzRupiYiIiIjrtT3Qh2H58PHz4lV90+fV9LI48x7pWdhfMtA3DreRWwj05fCZHsNttM6y57uu09wy12E/OW6/HEJzVpyeHhV3y/2h8L84rv563ni4TSLkNwR61dV76Q/febdsfGn6+1e2Dd4oYQz92qzSvJGaiIiIiLheuwR6U8+dP7PwWf9Y053D0+Lx+aticlaFwevw3hzoZ2PooyE3zcNt5GqBfjY0pmHITd/hNteBXmPTF5fJrrNsXFyPl/dn0Kvu5Y21UahODbdJvdYc6M36B6+qBpXewwfFO89f2ntY9d4/ePd/Nex/7GMZ5kVqIiIiIuJ67RjoUy6Mn9frKi8O+demb4pVGE89ez60LdCvelNs1aOeH26j8B4/e7450Fc9/to/wXS9pqfcxE/E8dctaM+Pc1fPevTs+WSPvdkW6FNaWYyfX791nCfQIyIi4jZcPtDnHk+Zez2eNgutGoajseDJIO22Bfqo7Kis1sdWluG7YbiNetWtjvONAR9WU9cpXq4s00J60EOvhoV+zTU5Zr7subdAHvbSK6RrvUGvvZdhcbFFNSSaQ/qLR19V9s7zDPr1avu/IjURERERcb0uF+gbHz+pgJ6c5r33VQD2dSmI60ktySA9sz3QX6837oVvCd5m2YPfMNxGDYKz83zPv3rVs4E+6I1vDPRlb7zVMwj0uplV6+00FKZnD73/oBRj59dvHecJ9IiIiLgN+wf6uXHwC6G0suotX7zxdfEXZLsMt5EdAr2p9d6z9c4NgfFgvdbhNuE0q1dibH4V9kfzjQjvhbf5F0K36nn/bjlkqArwieE2TfYI9LMwr3mT24WrWMd5Aj0iIiJuQQvZD+9WY7dPH79s6CWfFleXT4uzI5vXQnXzvFJBvQrvZejXTbVqOIyikK9e9dbhNqbqqfLKer5XvH2TmKe0CtgK7+WTXHQjqL4VsPWmHx9pLjXcZn6698TPnh6j7bLXUj331S/C3ikOg/l1w2r5bHo1OhqG2zTaGuivrF62H+tvSR68k2vA4KrWcZ5Aj4iIiJvUe+bjcdfqAZ8Pgz42/c7hYXF4el68etUxBJYh/tiWPSjLPbRw/yoKkO3DbbxnPlXPTE99GeIX15sM8+ayw23mtEbBw3B/Br8Cm5q/fLKNze8/QqV9++C57iu43j+9htvIhkA/ew59+R5aI+ul7Y+u5WJv7T2tSE1ERERERMT9to7zBHpERERExCFax3kCPSIiIiLiEK3jPIEeEREREXGI1nGeQI+IiIiIOETrOD/UQD8tLifjYjyZJqat4rSYjHQX+KgYX6Sm79qLYnxnXFwmpy3h9KKYjEfFyLZ3Mk1MX6vT4upiUoxHI9u/a9yG0M7bs+b9iJG2fw9s/67lqQbzn5uL4KkM++DV5Kw4m1wUU57ggIiIO7CO80MM9BYWLHSPxhfFlf19Oa4fwxQ7mpTT55f1wJ6bzxoKZXl7GugvxsUd2+7ktFIF1Tvd6j6dWPD1/bD5QK/9er2+DYTpPtvzOYVDn7dylG0cJj4zsvF9cLu+H5l15LR1V48Ia16u9zbFWogejcfF5MJCdbKcjPY5PZjVcTUvzw7mPjf7FujLc8bZUXFg55Hp3tUNERFvunZ9rEhN3F/rMB8HlWn1um1O6dgCyNz0OdW7XwW60aRqFKTn2z8VipvC4VW9XenGTEoPdtvooTdnoXtTvePdtme2H+se/evPzeK819Zld963q7wfuTBeT18Iy94QlRbAO7+XwfqszPk6qmd8XIzq6eU+7fg86Mvxge3L5cPt1WQy//mwz81R+YznfQz0lVdPFer3t36IiHgztWt0RWrivlqGllzP6CwsdginCiq5cvZW9fY2BeGqN9je0m77oLRbAF6bexHo4/3Yfb8poOd7vWOXeT+uGwHZ9Wgfpj676hXXuhbCfrPX63uVWU6NBYXpalvag7pt90rDbS6Ks3L5YD0DCPRS3yYcjM/5ARVERNyadm2uSE3cSzXcpDEYtfVuXqsQ02lYyh7ZGia1f8aTzvug8vYF+sX9qOBtr9X7rak3vfU9CF3q/QgDdm5+28bJNgO9tHUeeahvDutXk6Oy7n3qEKrlDyzQzwX3gQR6/Vy86jk+z/9KJCIi4jq1a3NFauL+WQe1tl71MvQ3h7IywPUYNrEfavvbGjPVdA9o3YZ51Pv11gT61H5UoLf6zOpmZj5n3QP9su/H9fydGw7uRgO9WYbqav809eZPjrTdy4XuKsxrHQMN9Lb9T63hczB6wnh6RETcinZdrkhN3DvroN4ecjzQNYyHtrKy5SSfkhI/nUVDEDyk/VTxU/X6KoOg6o2L2rg+VxOrRzltVIw1lt9CyyRXZ4XNpkAYTtf/M+tctCUAl/cm1Nsq7f/J+xPi+XybFuabD/RzY7RHDWO/u5bfuj2p/VgHev0/eM9Sn5HOgX7p9yMM2PF6bNtSPfOu1X2jgV7r915627bkU11sW4+03fG01vdPZVuYn02/dvTE6qVyg0B/dXFm66nnsc/Nk8zY/uq49W8W4nnjp+e8qm5uLedTIK/LmNi6ykaG1fnJeTG1umSPU7McS2/z00uPiIjb0K5vFamJ+6bf8NcnEKV7RBX4GsKeX/iDQKh1X7+uR2Wq3Do42jo8mPr0uZ5nK9PHUYd1L+uoZet1lME2mie0LUjObvIM/i7r0/aNhm9HKgCX2xQGeJ83Cpv1fHoSis/nNx0vvAezfaz9eB3gffsX9p/sU37T9pjp/RgE+nqesuxEGW3vg7v8+3G9/ng95WesKazb9M0Gem2Hh2PbX4lAnxxuo3od2L48n3//quAcNww0fj7REx8E+vETfW6qaWWwT/Xoa5oP3fEAb42Kqmz7TFvY1rbMHddPrC76/NQ97BdWr7IMq+PFq7rMen2NYd3mKb9lYCw9IiJuQbuOVaQm7pfNIW1RBbTM/AqUjaEqs65ZEM3UIQiq84H0OgRfB7zqtYXAZiEnHeg1f9O2zwfS0jIEp+oT27y9qTqW5XqQzsw3N2+4v1v3U7d6yGT5uXJm01Kvx/vPy1isp9aZqsu8q7wfwXal3HGgLwNuWRfbjwu94rbf4uE29v4pAKfKnpWl4Dt7vT3Qzwd3rdMCuNVnrpe+nD9RRw/b3gM/KzdavrQqO6676n120RDo63H01TriMhEREderXcMrUhP3Sw/o7WHIzfWIKrzkesErPcxFwa8Oltk6ZKdfh8M40JfzRutIfpWvshd6oq9Nh0zfZ/M9xYumt7faf9E+COev65OfT3odgum99tMS5We2pzS7HxMBPNh/4bcAXQL9au9Htbzmi8vYhx76xkBv+zcebqNecIXt9OMubZ/UYfp6+rKB3vZr0GtePm0mGDYzc1ZOHeCz5Uov26aF9bdlmobcZLcBERFxA9o1vCI1cb/0MJQJ0yntolsFxzDYWTmjtjIygXBWXmb57PR0UPUQJUeqUzKwVjaHSJUf1bV21qhpaAykt9df67qvcvMltr3Xflqi/Nlri/skvx/1+UqsY1ZXs24YNr8XUutf5f24/mwsrsfK3ukY+iqgl9ug/RWFZYV91fm6DKuvBWLNq+Er4bzz08Mwvo5Af/1aVde05fzZcivLBkw5pKc6TueCfVYCPSIibk+7RlWkJu6XSwR6XdTrsDcLRnUP5+K8ob7cZgO9vB43Xjkad+09DtQ2BWWkTQfMytT2dt3f7fN5iF0u0C9Rfu79a9yP+Wkedn0drYF+5ffjep3NDYeEGw/0tm/rAK5GSTz2ffHZ83rNg234+rVVD77t27UG+rqMVA99bEugl9fj9CtH47ZyCfSIiLg97dpUkZq4X7YHu6SzcFUtpyfTNAWpykwg3ECg9+lzwT7uvdU2ZBshVdnpcuX1uvPhMLW9bXV2/X3J79eFITNLBfoe5Se3x2zcj1pP/rM161m3Msd6AlLLvlzt/dhOoL8sb+yu/t850Jfh1+sfzat1L6zXA729F5me7cUhOevsoW8I1Bf1sJlsubE6ToNg39hYINAjIuL2tOtSRWrifpkJaa16ILQAMtbjEZuHOlRm1pUNom3Tr0PcddCz1xZ649PrVZjMBkSts+Pwjfwwj/x6G5ezAKdA5PPlwmc1PdgnvfbTEuUvsx9bAn1Yt6a6rOf92EKgt3qOg7K7BXrbB9neee3fA9u/i+HVe+BzZVfTFXz9tXUEeitXY+i1Xj3ycjbvtZdnZ/b5sHKy5Uor+8zep7lt9fWlbqKt5aZYRETconZtrkhN3Dc92OVDWdpZgCpDRZeA5OGtZ6CfNR66BFW9FpVvVnUNX2/vOW7fH9eNmvS8me1Vj3a9nALc/Bh/K9PvRWjcL9W65/Z7dv7UfjL7lp/cnub92D7dnNUj/zlaz/ux+UAfh+/2QK/fXajDvPbrQpC1bVoYblNr+63q1Q5Du6vl4qfIeKBPPbWme6CfPc1G26UhMsHnt3qGfd0oyZYrVfbRwvZW4+obAr2vm8dWIiLiFrRrXUVq4t5ZB8zeIWcWxBYDdFKbfxa4gnWVTxhp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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003ey.o.: years old; NAFLD: non-alcoholic fatty liver disease; TNM: tumor-node-metastasis; T-Bil: total bilirubin; AST: aspartate aminotransferase; ALT: alanine aminotransferase; PT: prothrombin time; PLT: platelet; ALBI: albumin-bilirubin; Fib-4: fibrosis-4 score; BCAA: branched chain amino acid; FA: fatty acid; SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; SMI: skeletal muscle index\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Comparison of clinical characteristics of patients with and without sarcopenia.\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003ey.o.: years old; n.s.: not significant; NAFLD: non-alcoholic fatty liver disease; TNM: tumor-node-metastasis; T-Bil: total bilirubin; AST: aspartate aminotransferase; ALT: alanine aminotransferase; PT: prothrombin time; PLT: platelet; ALBI: albumin-bilirubin; Fib-4: fibrosis-4 score; BCAA: branched chain amino acid; FA: fatty acid; SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; SMI: skeletal muscle index\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Logistic regression analysis for variates associated with sarcopenia in patients with hepatic cirrhosis\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eCI:\u0026nbsp;confidence interval; n.s.: not significant; NAFLD: non-alcoholic fatty liver disease; TNM: tumor-node-metastasis; ALBI: albumin-bilirubin; Fib-4: fibrosis-4 score; BCAA: branched chain amino acid; PUFA: polyunsaturated fatty acid\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\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":"","lastPublishedDoi":"10.21203/rs.3.rs-2344312/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2344312/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSarcopenia is associated with the prognosis of patients with hepatic cirrhosis and hepatocellular carcinoma. This study aimed to clarify the composition of blood fatty acids and the association between fatty acids and sarcopenia in patients with cirrhosis and hepatocellular carcinoma. In this single center-retrospective study, 414 patients were enrolled. The skeletal muscle index was measured by a transverse computed tomography scan image at the third lumbar vertebra. The cutoff value for sarcopenia followed the criteria for sarcopenia of the Japan Society of Hepatology. The concentrations of fatty acids were measured by gas-chromatography. Of each fatty acid fraction, only omega-3 (n-3) polyunsaturated fatty acids showed a significant correlation with skeletal muscle index (R\u0026thinsp;=\u0026thinsp;0.15, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0026). In the multivariate analysis, the level of n-3 polyunsaturated fatty acids was an independent variable associated with sarcopenia (odds ratio (95% CI): 0.9946 (0.9915\u0026ndash;0.9977), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0004). N-3 polyunsaturated fatty acids were lower in patients with sarcopenia when the patient backgrounds were aligned using propensity score matching. These results showed an association between sarcopenia and n-3 polyunsaturated fatty acids. We believe this study will contribute to the research of nutritional therapy or fatty acid-supplementation therapy for sarcopenia in patients with cirrhosis and hepatocellular carcinoma.\u003c/p\u003e","manuscriptTitle":"Omega-3 polyunsaturated fatty acids are associated with sarcopenia in patients with liver cirrhosis and hepatocellular carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-12-15 22:52:54","doi":"10.21203/rs.3.rs-2344312/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":"758c86d0-0c44-4817-9912-4d5a2dccb1a6","owner":[],"postedDate":"December 15th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":17676571,"name":"Health sciences/Gastroenterology/Hepatology/Liver diseases/Liver cirrhosis"},{"id":17676572,"name":"Health sciences/Rheumatology/Musculoskeletal system/Muscle/Skeletal muscle"},{"id":17676573,"name":"Health sciences/Gastroenterology/Hepatology/Liver diseases/Liver cancer/Hepatocellular carcinoma"}],"tags":[],"updatedAt":"2023-04-14T03:44:20+00:00","versionOfRecord":[],"versionCreatedAt":"2022-12-15 22:52:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2344312","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2344312","identity":"rs-2344312","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}