Authors: Anthony Loria, BS Katherine Doyle, MS Ali A. Weinstein, PhD Patrice Winter, MS Carey Escheik, BS Jillian Price, MS Lei Wang, MS Aybike Birerdinc, PhD Ancha Baranova, PhD Lynn Gerber, MD Zobair M. Younossi, MD, MPH
Affiliations: From the Betty and Guy Beatty Center for Integrated Research, Inova Health System, Falls Church, Virginia (AL, KD, PW, CE, JP, A. Birerdinc, A. Baranova, LG, ZMY); Center for the Study of Chronic Illness and Disability (AAW, PW, JP, LG) and Center for the Study of Genomics in Liver Diseases, School of Systems Biology (KD, LW, A. Birerdinc, A. Baranova, ZMY), George Mason University, Fairfax, Virginia; and Department of Medicine, Inova Fairfax Hospital, Falls Church, Virginia (CE, LG, ZMY).
Correspondence: All correspondence and requests for reprints should be addressed to: Zobair M. Younossi, MD, MPH, Betty and Guy Beatty Center for Integrated Research, Claude Moore Health Education and Research Building, 3300 Gallows Rd, Falls Church, VA 22042.
Disclosures: Supported in part by the Beatty Liver and Obesity Research Fund and Liver Disease Outcomes Fund, Inova Health System, Falls Church, VA. Financial disclosure statements have been obtained, and no conflicts of interest have been reported by the authors or by any individuals in control of the content of this article.
0894-9115/14/9306-0470 American Journal of Physical Medicine & Rehabilitation Copyright * 2014 by Lippincott Williams & Wilkins DOI: 10.1097/PHM.0000000000000050
Fatigue
ORIGINAL RESEARCH ARTICLE
Multiple Factors Predict Physical Performance in People with Chronic Liver Disease ABSTRACT Loria A, Doyle K, Weinstein AA, Winter P, Escheik C, Price J, Wang L, Birerdinc A, Baranova A, Gerber L, Younossi ZM: Multiple factors predict physical performance in people with chronic liver disease. Am J Phys Med Rehabil 2014;93:470Y476.
Objective: The aim of this study was to assess whether physical performance correlates with metabolic and inflammatory measures in research subjects with chronic liver disease.
Design: This is a prospective, descriptive cohort study correlating performance on a 6-min walk test with cardiorespiratory variables, metabolic measures (glucose [GLU], C-peptide insulin, and lipids), liver enzymes (aspartate aminotransferase and alanine aminotransferase), and the proinflammatory cytokine interleukin-8 (IL-8).
Results: This study enrolled 51 subjects (18 women) with chronic liver disease: 41% (n = 21) with nonalcoholic fatty liver disease and 59% (n = 30) with hepatitis C virus. Age, resting heart rate, and fasting GLU correlated significantly with distance walked (P’s G 0.05). First quartile Bpoor performers[ (n = 14) and fourth quartile Bhigh performers[ (n = 14) showed differences in age, sex, fasting GLU, and IL-8 level (P’s G 0.05). Combining the number of abnormal serum values (IL-8, C-peptide insulin, GLU, aspartate aminotransferase, alanine aminotransferase, high-density lipoprotein, triglyceride, and total cholesterol) did not correlate with distance walked (P 9 0.90). However, in multiple regression analysis, a model that included sex, age, resting heart rate, IL-8 level, and fasting GLU level explained approximately 39% of the variance in the distance walked during the test.
Conclusions: Older age, female sex, abnormal levels of the proinflammatory cytokine IL-8, abnormalities of GLU metabolism, and high resting heart rate are associated with poor physical performance in subjects with chronic liver disease. Poor physical performance is associated with physiologic, metabolic, and inflammatory abnormalities in subjects with nonalcoholic fatty liver disease and hepatitis C virus. Key Words:
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6MWT, NAFLD, Hepatitis C, Chronic Liver Disease, QOL
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onalcoholic fatty liver disease (NAFLD) and hepatitis C virus (HCV) are two of the most common forms of chronic liver disease (CLD) in the United States. Currently, NAFLD affects approximately 25% of the United States population and HCV affects up to 4.1 million persons.1,2 NAFLD is associated with obesity or type 2 diabetes and is considered to be the hepatic manifestation of metabolic syndrome. HCV is believed to promote the development of metabolic syndrome and is associated with dyslipidemia, insulin resistance, and intrahepatic steatosis.3,4 Patients with these two diagnoses are very likely to be fatigued, to be less active than their peers without CLD, and to have less aerobic capacity.5Y10 Fatigue in CLD is experienced as a distressing and debilitating symptom and may be a contributor to the observed lower activity level in this population.5Y10 It remains unclear whether metabolic and/or inflammatory factors contribute to the low level of activity and, if so, whether this is related to cardiorespiratory performance. Associations among fatigue, performance, and biomarkers have not been well studied. Fatigue impacts patients’ physical performance and is well known to have negative effects on functional capacity, health, and quality-of-life.11,12 Notably, reduced quality-of-life has been shown to correlate with poorer long-term survival across a spectrum of diseases.13,14 In some patient groups, this has been linked to a profound deregulation in the nuclear factor (NF) kB inflammatory pathway as a major contributor to fatigue.15Y20 Abnormal levels of serum proinflammatory cytokines including tumor necrosis factor alpha, interleukin-6 (IL-6), and IL-8 have been linked to fatigue.18Y21 Liver injury, whether induced by viral disease and fatty infiltration or secondary to alcohol and other toxic substances, may result in chronic inflammation and fibrosis. Inflammatory cytokines have been shown to contribute to liver injury in CLD.2,22Y24 Although the etiologies of hepatic inflammatory activity differ among these groups, fatigue remains a distressing symptom across a range of liver diseases.24Y26 Exploring the connections between physical performance (walking speed or distance) and biomarkers may provide insight into the observed poor physical performance in patients with CLD.5Y7 In addition, these cytokine and metabolic abnormalities may be targets for future therapeutic approaches aiming to ameliorate fatigue. The study reported uses a standard measure of performance, the 6-min walk test (6MWT; details provided in the BMETHODS[ section),27 in two www.ajpmr.com
populations of patients with CLD and correlate it with biologic measures in an effort to identify biologic correlates of physical performance as a marker of fatigue. The authors use the distance achieved during the walk test as a measure of physical fatigue.
METHODS Study Population The purpose of this institutional review boardYapproved, prospective, descriptive study was to assess relationships among serum cytokine levels, cardiorespiratory measures, and performance based on distance walked during the 6MWT. Patients with ultrasound-proven or histologically proven NAFLD, nonalcoholic steatohepatitis, or HCV (positive HCV antibody, HCV genotype, and/or HCV RNA viral load) with a body mass index (BMI) greater than or equal to 25 were eligible. NAFLD remains a diagnosis of exclusion, and the fatty infiltration was determined to be of nonalcoholic etiology via self-report. All patients attended the Center for Liver Diseases at Inova Fairfax Hospital and provided informed consent. Patients currently receiving antiviral therapies or those with recent myocardial infarction or cardiovascular or musculoskeletal comorbidities affecting exertion were excluded. Metabolic syndrome was defined as expressing three or more of the following: obesity, hypertension, hyperlipidemia, or a diagnosis of diabetes mellitus.
Biological and Clinical Variables The patients underwent fasting morning venipucture to assess levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), glucose (GLU), C-peptide insulin (CPI), total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), and low-density lipoprotein. Serum levels of IL-8 were determined. Cytokines were measured using R&D Systems enzyme-linked immunosorbent assay kits (R&D Systems, Minneapolis, MN) as per the manufacturer’s instructions. All subjects completed a 6MWT according to the American Thoracic Society protocol.27 The 6MWT is a self-paced (with breaks allowed), timed test in which patients are encouraged to walk as far as they can over a hard flat surface to determine the total distance walked in 6 mins. Resting cardiorespiratory data were determined using a multichannel bioimpedance measure, Physioflow (Manatec Biomedical, Neumedx, Bristol, PA) to assess the following resting measures: heart rate (HR; resting HR), blood pressure (resting blood pressure), and cardiac output (resting cardiac output). Physical Performance in Chronic Liver Disease
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Statistical Analysis Spearman rank sum correlations of serum parameters, anthropomorphic parameters, and cardiovascular parameters to distance walked were performed. The patients stratified as Bhigh performers[ (fourth quartile) and Blow performers[ (first quartile) on the basis of distance walked were compared using the Mann-Whitney U test. In addition, serum profiles of the patients were assessed by categorizing laboratory results as Bnormal[ or Babnormal[ using clinically accepted thresholds (CPI G2.72 ng/ml; IL-8 G7.8 pg/ml; ALT G50 U/liter for men, G38 U/liter for women; AST G40 U/liter for men, G34 U/liter for women; TC G200 mg/dl; TG G150 mg/dl; HDL 940 mg/dl for men, 950 mg/dl for women; GLU G110 mg/dl). Scores were summed and correlated to distance walked. The clinical variables above were categorized as within normal range and designated as 0 or outside normal range and designated as 1 according to established Bclinical normal[ values. Thus, cumulative sums of abnormal serum variables for each patient could range from 0 (no values outside normal range) to 8 (with all values outside normal parameters). Summed scores ranging from 0 to 8 were correlated to distance walked using the Spearman rank sum test to measure cumulative effects of a variety of abnormalities common to population with CLD. Statistically significant variables related to walk distance (or those that demonstrated a trend toward
statistical significance) in the univariate analyses were included in a linear regression to determine the amount of variance explained in performance. All statistical analyses were performed on the Statistical Package for the Social Sciences 19.0 for Mac.
RESULTS Clinical and Demographic Data This study included 51 eligible subjects, 33 men and 18 women. Thirty subjects (59%) had HCV, with 3 meeting the criteria for metabolic syndrome, and 21 (41%) had NAFLD, with metabolic syndrome present in 7 participants (Table 1). The mean T SD age for the population was 51 T 9 yrs, with a mean T SD BMI of 31.5 T 5.9 (Table 1). Most of the patients, 73% (n = 37), were white, and 6% (n = 3) were African American; 6% (n = 3), Hispanic; and 14% (n = 7), other. The mean T SD distance walked for the cohort was 560.0 T 86.5 m. In the univariate analyses, there was no observed statistical difference in distance walked between diagnosis of NAFLD vs. HCV, race, or overweight (BMI, 25Y30) vs. obese (BMI, 930) (data not presented).
Correlates to Distance Walked Baseline HR (Rs = j0.315, P = 0.03), age (Rs = j0.397, P G 0.006), and fasting GLU (Rs = j0.434, P G 0.003) were significantly correlated to distance walked. From serum samples, IL-8 showed a modest correlation to distance walked (Rs = j0.262,
TABLE 1 Characteristics of entire cohort, low performers (first quartile as determined by 6-min walk distance), and high performers (fourth quartile)
n Distance walked, m HCV, n (%) NAFLD, n (%) Age, yrs BMI Female, n (%) Metabolic syndrome, n (%) AST, IU/liter ALT, IU/liter GLU, mg/dl CPI, ng/ml IL-8, pg/ml TC, mg/dl TG, mg/dl HDL, mg/dl LDL, mg/dl Resting HR (beats per minute) Resting cardiac output
Entire Cohort
Low Performers (G502.9 m)
High Performers (9624.8 m)
51 560.0 T 86.5 30 (59%) 21 (41%) 51.1 T 8.8 31.5 T 5.9 18 (35%) 10 (20%) 51.4 T 36.3 59.4 T 38.7 107.7 T 35.4 2.25 T 1.11 19.0 T 10.0 184.8 T 41.2 126.7 T 96.6 45.6 T 16.8 106.0 T 57.9 71.7 T 9.9 6.2 T 1.8
14 461.0 T 35.7 7 (50%) 7 (50%) 57.5 T 6.0 30.9 T 5.4 10 (71%) 5 (36%) 55.3 T 56.1 57.0 T 54.1 121.8 T 54.2 2.05 T 0.72 24.1 T 15.0 181.5 T 39.0 110.0 T 47.2 47.3 T 11.1 113.2 T 45.8 75.4 T 6.3 6.2 T 1.7
14 664.2 T 38.9 8 (57%) 6 (43%) 46.4 T 9.4 30.0 T 6.6 4 (29%) 2 (14%) 43.2 T 17.4 59.4 T 30.1 90.5 T 13.2 1.74 T 0.84 15.0 T 4.0 173.1 T 36.6 141. 9 T 93.0 45.0 T 18.4 99.7 T 32.5 70.1 T 10.0 5.5 T 1.7
P V 0.50 0.001 0.71 0.03 0.19 0.47 0.89 0.05 0.33 0.05 0.59 0.29 0.72 0.44 0.10 0.33
LDL, low-density lipoprotein.
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TABLE 2 Binary accumulation of abnormalities in serum correlated to 6-min walk distance (Rs = j0.005)
Normal Range
% of Entire Cohort Outside Normal Range
G2.72 ng/ml e110 mg/dl e7.8 pg/ml Male: G40 U/liter Female: G34 U/liter Male: G50 U/liter Female: G38 U/liter G150 G200 Male: 940 mg/dl Female: 950 mg/dl
26% 26% 100% Male: 60% Female: 53% Male: 53% Female: 47% 30% 36% Male: 57% Female: 44%
Serum Measure CPI GLU IL-8 AST ALT TG TC HDL
P 0.975
P = 0.090). Comparison of the first quartile/low performers (G502.9 m, n = 14) with the fourth quartile/high performers (9624.8 m, n = 14) showed significant differences in age, sex, fasting GLU, and IL-8 (Table 1). The low performers tended to be older, female patients with higher fasting GLU and IL-8 levels.
Binary Correlation and Accumulation of Abnormalities In the binary analyses of whether the patients have values within the acceptable normal ranges, 26% of the cohort had abnormal CPI and GLU, 100% had abnormal IL-8, 30% had abnormal TG, and 36% had abnormal TC (Table 2). For the men, 60% had abnormal AST, 53% had abnormal ALT, and 57% had abnormal HDL. For the women, 53% had abnormal AST, 47% had abnormal ALT, and 44% had abnormal HDL. The sum of binary scores for the accumulation of serum abnormalities did not correlate with distance walked (Rs = j0.005; P = 0.975) (Table 2).
Prediction of Poor Performance The distance walked was predicted by a combination of age, sex, resting HR, fasting GLU, and IL-8 in a multiple regression analysis (P = 0.002) while explaining 39% of the variance in distance walked (Table 3).
DISCUSSION Ambulation and physical capacity are important factors in maintaining a high level of function, independence, and quality-of-life for many individuals with chronic disease.28Y31 The 6MWT is used in many populations as a measure of performance and physical fatigue.27,32Y35 Distance walked in 6 mins has been shown to correlate with fatigue levels in patients with a wide variety of disorders including multiple sclerosis, traumatic brain injury, and respiratory diseases.36Y38 Previous studies have shown that the distance walked in 6 mins is an important indicator of vitality and mortality in many chronic diseases.35,39Y42 As compared with healthy individuals, patients with CLD show a significant reduction in distance walked during the 6MWT.34 The deficiencies observed in functional capacity in patients with CLD, as with other chronic diseases, correspond to significant reductions in quality-of-life.43Y46 Although comparative distances walked for patients with varying diagnoses of CLD have been examined, the underlying biologic contributors to performance have remained unknown.22 The data obtained from this study demonstrate that the distance walked by patients with HCV and NAFLD do not exclusively rely on diagnoses of NAFLD or HCV, cardiorespiratory parameters, or BMI ( Table 1). In correlative analyses, resting HR, age, and fasting GLU significantly correlated with distance walked, whereas serum IL-8 trended toward significance. When stratified by distance walked, the highest and lowest performers were significantly different in age, sex, fasting GLU, and IL-8 (Table 1). Baseline
TABLE 3 Best-fitting multiple linear regression model predicting the distance walked in patients with CLD Model Variable Age Sex Resting HR IL-8, pg/ml GLU, mg/dl
Regression Coefficient A j0.346 j0.166 j0.209 j0.191 j0.170
Regression Coefficient B (95% Confidence Intervals) j11.10 j96.23 j6.17 j5.43 j1.33
(j19.65 to j2.54) (j248.95 to 56.50) (j14.33 to 2.00) (j15.2 to 4.35) (j4.12 to 1.46)
P Value of Coefficient
P Value of Complete Model
0.012 0.210 0.134 0.268 0.340
0.002
Regression coefficient A represents slope estimate.
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cardiorespiratory difference between those who walked the farthest and the least was not significantly different (Table 1). Interestingly, the presence of metabolic syndrome tended to be more frequently observed in the lowest-performing group (36% vs. 14%; not statistically significantly different). With a larger cohort, examining the deleterious role metabolic syndrome plays as a comorbid condition superimposed on CLD as it pertains to function and fatigue would be an interesting avenue of inquiry. Furthermore, there were no significant differences between diagnoses or transaminases for the high vs. low performers (Table 1). In the analysis of binary accumulation of abnormalities, physical performance did not significantly relate to the cumulative number of abnormal cytokines and metabolic measures present (Table 2). Despite this, it is interesting to note the high level of systemic inflammatory activity observed in these patients. Whether the high level of IL-8 (100% of the cohort having values outside the normal range) observed in this cohort is due to the etiology of CLD is unclear. On the basis of these data, metabolic and inflammatory dysfunction are pervasive in these cohorts. Using distance walked as a surrogate of physical fatigue, it was shown that the highest fatigue (lowest walk distance) is predicted by a combination of anthropomorphic variables (age, sex, and resting HR), inflammatory status (serum IL-8), and metabolic abnormalities (fasting GLU) (Table 3). These findings corroborate findings in cancer patients that show the relationship of serum cytokines of the NF-kB pathway to fatigue.47,48 Chronic deregulation of the NF-kB pathway, specifically IL-8, suggests a role for these proinflammatory cytokines in physical fatigue. The data of this study are consistent with previous observations demonstrating a positive correlation between levels of fatigue and levels of circulating IL-8 in acute myelogenous leukemia/myelodysplastic syndrome patients.20 These findings collectively support the hypothesis of Beyer et al.18 that mechanisms inhibiting the NF-kB inflammatory pathway may offer some protection against fatigue. Further evidence suggests that IL-6 has a significant negative correlation with physical ability subscores in chronic fatigue syndrome patients.49 Although physical performance levels in populations with CLD have not been investigated as frequently as those in other chronically ill populations, such as those with cardiorespiratory and oncologic conditions, the importance of preserving function in these populations has been demonstrated in numerous other studies.37,50,51 These have shown
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that maintaining functional capacity is paramount to the quality-of-life and vitality of patients with chronic illness.52 In healthy and diseased people, including initial studies in patients with CLD, the results of 6MWT were found to be predictive for cardiorespiratory measurements and an indicator of overall survival.25 In this study, distances walked correlated to age, resting HR, and fasting GLU. When stratified by performance level, cardiorespiratory variables lost significance, whereas GLU and IL-8 were significantly different (Table 1). Ultimately, a model including anthropometric measures, abnormal IL-8, and fasting GLU was a more significant factor contributing to the limitation of the distance walked (Table 3). Deregulation of the NF-kB pathway seems to contribute to low physical performance in this population of CLD patients. In addition, it may be useful to screen older, female patients with CLD for fatigue via validated self-reports of physical fatigue levels to determine the impact fatigue has on qualityof-life in this population.
Study Limitations The main limitations of this study are the small cohort size and that only some of the patients were observed to reach significant levels of exertion. Most of the patients walked at a comfortable pace and seemed to have only a modest level of exertion. Despite this, the 6MWT may have been an aboveaverage activity level for some participants (Table 1). An additional, interesting analysis that the authors were not able to fully explore because of the small sample size of the patients with HCV would be stratifying for sustained virologic response and comparing performance, cardiorespiratory response, and systemic inflammatory activity. Sustained virologic response is the standard for therapeutic efficacy for treatment and eradication of virus. Because patients who have achieved sustained virologic response often have persistent fatigue, it would be important to compare their performance and physiologic and biologic measures with those who had not achieved sustained virologic response. In addition, the small sample size enabled the authors to account for only 39% of the variance. Determination of other possible covariates (e.g., fitness level, arthritis, comorbid conditions) would require a larger sample size.
CONCLUSIONS In summary, this study provides important information about the relationship between the NF-kB
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inflammatory pathway and GLU metabolism to performance in patients with CLD. The complex relationships between performance (physical fatigue level), GLU metabolism, and inflammatory activity are beginning to become understood among patients with CLD who experience significant levels of fatigue. This level of fatigue can negatively impact quality-of-life and may provide targets for therapeutic intervention to help preserve performance and activity level and, ultimately, alleviate fatigue.53 Here, the authors describe the relationships between cytokine and metabolic profiles of patients and physical performance. Fatigue can manifest itself as poor physical performance and reflects patients’ abilities to participate in daily activities. In the future, this avenue of research may provide clinicians with quantifiable biologic biomarkers to score physical fatigue objectively. In turn, these measures may provide targets for effective pharmacologic, lifestyle, and behavioral treatments (i.e., weight loss and physical activity interventions) aimed to mitigate physical fatigue.53,54 REFERENCES 1. Lonardo A, Ballestri S, Adinolfi LE, et al: Hepatitis C virus-infected patients are Fspared_ from the metabolic syndrome but not from insulin resistance. A comparative study of nonalcoholic fatty liver disease and hepatitis C virusYrelated steatosis. Can J Gastroenterol 2009;23:273Y8 2. Armstrong GL, Wasley A, Simard EP, et al: The prevalence of hepatitis C virus infection in the United States, 1999 through 2002. Ann Intern Med 2006; 144:705Y14 3. Bugianesi E, Salamone F, Negro F: The interaction of metabolic factors with HCV infection: Does it matter? J Hepatol 2012;56(suppl 1):S56Y65 4. Younossi ZM, McCullough AJ: Metabolic syndrome, non-alcoholic fatty liver disease and hepatitis C virus: Impact on disease progression and treatment response. Liver Int 2009;29:617 5. Ware JE, Bayliss MS, Mannocchia M, et al: for the International Hepatitis Interventional Therapy Group: Health-related quality of life in chronic hepatitis C: Impact of disease and treatment response. Hepatology 1999;30:550Y5 6. Gerber L, Otgonsuren M, Mishra A, et al: Nonalcoholic fatty liver disease (NAFLD) is associated with low level of physical activity. Aliment Pharmacol Ther 2012;36:772Y81 7. Price JK, Srivastava R, Bai CH, et al: Comparison of activity level among patients with chronic liver disease. Disabil Rehabil 2013;35:907Y12 8. Elliott C, Frith J, Day CP, et al: Functional impairment in alcoholic liver disease and non-alcoholic fatty liver disease is significant and persists over 3 years of follow-up. Dig Dis Sci 2013;58:2383Y91 www.ajpmr.com
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Affiliations: From the Betty and Guy Beatty Center for Integrated Research, Inova Health System, Falls Church, Virginia (AL, KD, PW, CE, JP, A. Birerdinc, A. Baranova, LG, ZMY); Center for the Study of Chronic Illness and Disability (AAW, PW, JP, LG) and Center for the Study of Genomics in Liver Diseases, School of Systems Biology (KD, LW, A. Birerdinc, A. Baranova, ZMY), George Mason University, Fairfax, Virginia; and Department of Medicine, Inova Fairfax Hospital, Falls Church, Virginia (CE, LG, ZMY).
Correspondence: All correspondence and requests for reprints should be addressed to: Zobair M. Younossi, MD, MPH, Betty and Guy Beatty Center for Integrated Research, Claude Moore Health Education and Research Building, 3300 Gallows Rd, Falls Church, VA 22042.
Disclosures: Supported in part by the Beatty Liver and Obesity Research Fund and Liver Disease Outcomes Fund, Inova Health System, Falls Church, VA. Financial disclosure statements have been obtained, and no conflicts of interest have been reported by the authors or by any individuals in control of the content of this article.
0894-9115/14/9306-0470 American Journal of Physical Medicine & Rehabilitation Copyright * 2014 by Lippincott Williams & Wilkins DOI: 10.1097/PHM.0000000000000050
Fatigue
ORIGINAL RESEARCH ARTICLE
Multiple Factors Predict Physical Performance in People with Chronic Liver Disease ABSTRACT Loria A, Doyle K, Weinstein AA, Winter P, Escheik C, Price J, Wang L, Birerdinc A, Baranova A, Gerber L, Younossi ZM: Multiple factors predict physical performance in people with chronic liver disease. Am J Phys Med Rehabil 2014;93:470Y476.
Objective: The aim of this study was to assess whether physical performance correlates with metabolic and inflammatory measures in research subjects with chronic liver disease.
Design: This is a prospective, descriptive cohort study correlating performance on a 6-min walk test with cardiorespiratory variables, metabolic measures (glucose [GLU], C-peptide insulin, and lipids), liver enzymes (aspartate aminotransferase and alanine aminotransferase), and the proinflammatory cytokine interleukin-8 (IL-8).
Results: This study enrolled 51 subjects (18 women) with chronic liver disease: 41% (n = 21) with nonalcoholic fatty liver disease and 59% (n = 30) with hepatitis C virus. Age, resting heart rate, and fasting GLU correlated significantly with distance walked (P’s G 0.05). First quartile Bpoor performers[ (n = 14) and fourth quartile Bhigh performers[ (n = 14) showed differences in age, sex, fasting GLU, and IL-8 level (P’s G 0.05). Combining the number of abnormal serum values (IL-8, C-peptide insulin, GLU, aspartate aminotransferase, alanine aminotransferase, high-density lipoprotein, triglyceride, and total cholesterol) did not correlate with distance walked (P 9 0.90). However, in multiple regression analysis, a model that included sex, age, resting heart rate, IL-8 level, and fasting GLU level explained approximately 39% of the variance in the distance walked during the test.
Conclusions: Older age, female sex, abnormal levels of the proinflammatory cytokine IL-8, abnormalities of GLU metabolism, and high resting heart rate are associated with poor physical performance in subjects with chronic liver disease. Poor physical performance is associated with physiologic, metabolic, and inflammatory abnormalities in subjects with nonalcoholic fatty liver disease and hepatitis C virus. Key Words:
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6MWT, NAFLD, Hepatitis C, Chronic Liver Disease, QOL
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onalcoholic fatty liver disease (NAFLD) and hepatitis C virus (HCV) are two of the most common forms of chronic liver disease (CLD) in the United States. Currently, NAFLD affects approximately 25% of the United States population and HCV affects up to 4.1 million persons.1,2 NAFLD is associated with obesity or type 2 diabetes and is considered to be the hepatic manifestation of metabolic syndrome. HCV is believed to promote the development of metabolic syndrome and is associated with dyslipidemia, insulin resistance, and intrahepatic steatosis.3,4 Patients with these two diagnoses are very likely to be fatigued, to be less active than their peers without CLD, and to have less aerobic capacity.5Y10 Fatigue in CLD is experienced as a distressing and debilitating symptom and may be a contributor to the observed lower activity level in this population.5Y10 It remains unclear whether metabolic and/or inflammatory factors contribute to the low level of activity and, if so, whether this is related to cardiorespiratory performance. Associations among fatigue, performance, and biomarkers have not been well studied. Fatigue impacts patients’ physical performance and is well known to have negative effects on functional capacity, health, and quality-of-life.11,12 Notably, reduced quality-of-life has been shown to correlate with poorer long-term survival across a spectrum of diseases.13,14 In some patient groups, this has been linked to a profound deregulation in the nuclear factor (NF) kB inflammatory pathway as a major contributor to fatigue.15Y20 Abnormal levels of serum proinflammatory cytokines including tumor necrosis factor alpha, interleukin-6 (IL-6), and IL-8 have been linked to fatigue.18Y21 Liver injury, whether induced by viral disease and fatty infiltration or secondary to alcohol and other toxic substances, may result in chronic inflammation and fibrosis. Inflammatory cytokines have been shown to contribute to liver injury in CLD.2,22Y24 Although the etiologies of hepatic inflammatory activity differ among these groups, fatigue remains a distressing symptom across a range of liver diseases.24Y26 Exploring the connections between physical performance (walking speed or distance) and biomarkers may provide insight into the observed poor physical performance in patients with CLD.5Y7 In addition, these cytokine and metabolic abnormalities may be targets for future therapeutic approaches aiming to ameliorate fatigue. The study reported uses a standard measure of performance, the 6-min walk test (6MWT; details provided in the BMETHODS[ section),27 in two www.ajpmr.com
populations of patients with CLD and correlate it with biologic measures in an effort to identify biologic correlates of physical performance as a marker of fatigue. The authors use the distance achieved during the walk test as a measure of physical fatigue.
METHODS Study Population The purpose of this institutional review boardYapproved, prospective, descriptive study was to assess relationships among serum cytokine levels, cardiorespiratory measures, and performance based on distance walked during the 6MWT. Patients with ultrasound-proven or histologically proven NAFLD, nonalcoholic steatohepatitis, or HCV (positive HCV antibody, HCV genotype, and/or HCV RNA viral load) with a body mass index (BMI) greater than or equal to 25 were eligible. NAFLD remains a diagnosis of exclusion, and the fatty infiltration was determined to be of nonalcoholic etiology via self-report. All patients attended the Center for Liver Diseases at Inova Fairfax Hospital and provided informed consent. Patients currently receiving antiviral therapies or those with recent myocardial infarction or cardiovascular or musculoskeletal comorbidities affecting exertion were excluded. Metabolic syndrome was defined as expressing three or more of the following: obesity, hypertension, hyperlipidemia, or a diagnosis of diabetes mellitus.
Biological and Clinical Variables The patients underwent fasting morning venipucture to assess levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), glucose (GLU), C-peptide insulin (CPI), total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), and low-density lipoprotein. Serum levels of IL-8 were determined. Cytokines were measured using R&D Systems enzyme-linked immunosorbent assay kits (R&D Systems, Minneapolis, MN) as per the manufacturer’s instructions. All subjects completed a 6MWT according to the American Thoracic Society protocol.27 The 6MWT is a self-paced (with breaks allowed), timed test in which patients are encouraged to walk as far as they can over a hard flat surface to determine the total distance walked in 6 mins. Resting cardiorespiratory data were determined using a multichannel bioimpedance measure, Physioflow (Manatec Biomedical, Neumedx, Bristol, PA) to assess the following resting measures: heart rate (HR; resting HR), blood pressure (resting blood pressure), and cardiac output (resting cardiac output). Physical Performance in Chronic Liver Disease
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Statistical Analysis Spearman rank sum correlations of serum parameters, anthropomorphic parameters, and cardiovascular parameters to distance walked were performed. The patients stratified as Bhigh performers[ (fourth quartile) and Blow performers[ (first quartile) on the basis of distance walked were compared using the Mann-Whitney U test. In addition, serum profiles of the patients were assessed by categorizing laboratory results as Bnormal[ or Babnormal[ using clinically accepted thresholds (CPI G2.72 ng/ml; IL-8 G7.8 pg/ml; ALT G50 U/liter for men, G38 U/liter for women; AST G40 U/liter for men, G34 U/liter for women; TC G200 mg/dl; TG G150 mg/dl; HDL 940 mg/dl for men, 950 mg/dl for women; GLU G110 mg/dl). Scores were summed and correlated to distance walked. The clinical variables above were categorized as within normal range and designated as 0 or outside normal range and designated as 1 according to established Bclinical normal[ values. Thus, cumulative sums of abnormal serum variables for each patient could range from 0 (no values outside normal range) to 8 (with all values outside normal parameters). Summed scores ranging from 0 to 8 were correlated to distance walked using the Spearman rank sum test to measure cumulative effects of a variety of abnormalities common to population with CLD. Statistically significant variables related to walk distance (or those that demonstrated a trend toward
statistical significance) in the univariate analyses were included in a linear regression to determine the amount of variance explained in performance. All statistical analyses were performed on the Statistical Package for the Social Sciences 19.0 for Mac.
RESULTS Clinical and Demographic Data This study included 51 eligible subjects, 33 men and 18 women. Thirty subjects (59%) had HCV, with 3 meeting the criteria for metabolic syndrome, and 21 (41%) had NAFLD, with metabolic syndrome present in 7 participants (Table 1). The mean T SD age for the population was 51 T 9 yrs, with a mean T SD BMI of 31.5 T 5.9 (Table 1). Most of the patients, 73% (n = 37), were white, and 6% (n = 3) were African American; 6% (n = 3), Hispanic; and 14% (n = 7), other. The mean T SD distance walked for the cohort was 560.0 T 86.5 m. In the univariate analyses, there was no observed statistical difference in distance walked between diagnosis of NAFLD vs. HCV, race, or overweight (BMI, 25Y30) vs. obese (BMI, 930) (data not presented).
Correlates to Distance Walked Baseline HR (Rs = j0.315, P = 0.03), age (Rs = j0.397, P G 0.006), and fasting GLU (Rs = j0.434, P G 0.003) were significantly correlated to distance walked. From serum samples, IL-8 showed a modest correlation to distance walked (Rs = j0.262,
TABLE 1 Characteristics of entire cohort, low performers (first quartile as determined by 6-min walk distance), and high performers (fourth quartile)
n Distance walked, m HCV, n (%) NAFLD, n (%) Age, yrs BMI Female, n (%) Metabolic syndrome, n (%) AST, IU/liter ALT, IU/liter GLU, mg/dl CPI, ng/ml IL-8, pg/ml TC, mg/dl TG, mg/dl HDL, mg/dl LDL, mg/dl Resting HR (beats per minute) Resting cardiac output
Entire Cohort
Low Performers (G502.9 m)
High Performers (9624.8 m)
51 560.0 T 86.5 30 (59%) 21 (41%) 51.1 T 8.8 31.5 T 5.9 18 (35%) 10 (20%) 51.4 T 36.3 59.4 T 38.7 107.7 T 35.4 2.25 T 1.11 19.0 T 10.0 184.8 T 41.2 126.7 T 96.6 45.6 T 16.8 106.0 T 57.9 71.7 T 9.9 6.2 T 1.8
14 461.0 T 35.7 7 (50%) 7 (50%) 57.5 T 6.0 30.9 T 5.4 10 (71%) 5 (36%) 55.3 T 56.1 57.0 T 54.1 121.8 T 54.2 2.05 T 0.72 24.1 T 15.0 181.5 T 39.0 110.0 T 47.2 47.3 T 11.1 113.2 T 45.8 75.4 T 6.3 6.2 T 1.7
14 664.2 T 38.9 8 (57%) 6 (43%) 46.4 T 9.4 30.0 T 6.6 4 (29%) 2 (14%) 43.2 T 17.4 59.4 T 30.1 90.5 T 13.2 1.74 T 0.84 15.0 T 4.0 173.1 T 36.6 141. 9 T 93.0 45.0 T 18.4 99.7 T 32.5 70.1 T 10.0 5.5 T 1.7
P V 0.50 0.001 0.71 0.03 0.19 0.47 0.89 0.05 0.33 0.05 0.59 0.29 0.72 0.44 0.10 0.33
LDL, low-density lipoprotein.
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TABLE 2 Binary accumulation of abnormalities in serum correlated to 6-min walk distance (Rs = j0.005)
Normal Range
% of Entire Cohort Outside Normal Range
G2.72 ng/ml e110 mg/dl e7.8 pg/ml Male: G40 U/liter Female: G34 U/liter Male: G50 U/liter Female: G38 U/liter G150 G200 Male: 940 mg/dl Female: 950 mg/dl
26% 26% 100% Male: 60% Female: 53% Male: 53% Female: 47% 30% 36% Male: 57% Female: 44%
Serum Measure CPI GLU IL-8 AST ALT TG TC HDL
P 0.975
P = 0.090). Comparison of the first quartile/low performers (G502.9 m, n = 14) with the fourth quartile/high performers (9624.8 m, n = 14) showed significant differences in age, sex, fasting GLU, and IL-8 (Table 1). The low performers tended to be older, female patients with higher fasting GLU and IL-8 levels.
Binary Correlation and Accumulation of Abnormalities In the binary analyses of whether the patients have values within the acceptable normal ranges, 26% of the cohort had abnormal CPI and GLU, 100% had abnormal IL-8, 30% had abnormal TG, and 36% had abnormal TC (Table 2). For the men, 60% had abnormal AST, 53% had abnormal ALT, and 57% had abnormal HDL. For the women, 53% had abnormal AST, 47% had abnormal ALT, and 44% had abnormal HDL. The sum of binary scores for the accumulation of serum abnormalities did not correlate with distance walked (Rs = j0.005; P = 0.975) (Table 2).
Prediction of Poor Performance The distance walked was predicted by a combination of age, sex, resting HR, fasting GLU, and IL-8 in a multiple regression analysis (P = 0.002) while explaining 39% of the variance in distance walked (Table 3).
DISCUSSION Ambulation and physical capacity are important factors in maintaining a high level of function, independence, and quality-of-life for many individuals with chronic disease.28Y31 The 6MWT is used in many populations as a measure of performance and physical fatigue.27,32Y35 Distance walked in 6 mins has been shown to correlate with fatigue levels in patients with a wide variety of disorders including multiple sclerosis, traumatic brain injury, and respiratory diseases.36Y38 Previous studies have shown that the distance walked in 6 mins is an important indicator of vitality and mortality in many chronic diseases.35,39Y42 As compared with healthy individuals, patients with CLD show a significant reduction in distance walked during the 6MWT.34 The deficiencies observed in functional capacity in patients with CLD, as with other chronic diseases, correspond to significant reductions in quality-of-life.43Y46 Although comparative distances walked for patients with varying diagnoses of CLD have been examined, the underlying biologic contributors to performance have remained unknown.22 The data obtained from this study demonstrate that the distance walked by patients with HCV and NAFLD do not exclusively rely on diagnoses of NAFLD or HCV, cardiorespiratory parameters, or BMI ( Table 1). In correlative analyses, resting HR, age, and fasting GLU significantly correlated with distance walked, whereas serum IL-8 trended toward significance. When stratified by distance walked, the highest and lowest performers were significantly different in age, sex, fasting GLU, and IL-8 (Table 1). Baseline
TABLE 3 Best-fitting multiple linear regression model predicting the distance walked in patients with CLD Model Variable Age Sex Resting HR IL-8, pg/ml GLU, mg/dl
Regression Coefficient A j0.346 j0.166 j0.209 j0.191 j0.170
Regression Coefficient B (95% Confidence Intervals) j11.10 j96.23 j6.17 j5.43 j1.33
(j19.65 to j2.54) (j248.95 to 56.50) (j14.33 to 2.00) (j15.2 to 4.35) (j4.12 to 1.46)
P Value of Coefficient
P Value of Complete Model
0.012 0.210 0.134 0.268 0.340
0.002
Regression coefficient A represents slope estimate.
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cardiorespiratory difference between those who walked the farthest and the least was not significantly different (Table 1). Interestingly, the presence of metabolic syndrome tended to be more frequently observed in the lowest-performing group (36% vs. 14%; not statistically significantly different). With a larger cohort, examining the deleterious role metabolic syndrome plays as a comorbid condition superimposed on CLD as it pertains to function and fatigue would be an interesting avenue of inquiry. Furthermore, there were no significant differences between diagnoses or transaminases for the high vs. low performers (Table 1). In the analysis of binary accumulation of abnormalities, physical performance did not significantly relate to the cumulative number of abnormal cytokines and metabolic measures present (Table 2). Despite this, it is interesting to note the high level of systemic inflammatory activity observed in these patients. Whether the high level of IL-8 (100% of the cohort having values outside the normal range) observed in this cohort is due to the etiology of CLD is unclear. On the basis of these data, metabolic and inflammatory dysfunction are pervasive in these cohorts. Using distance walked as a surrogate of physical fatigue, it was shown that the highest fatigue (lowest walk distance) is predicted by a combination of anthropomorphic variables (age, sex, and resting HR), inflammatory status (serum IL-8), and metabolic abnormalities (fasting GLU) (Table 3). These findings corroborate findings in cancer patients that show the relationship of serum cytokines of the NF-kB pathway to fatigue.47,48 Chronic deregulation of the NF-kB pathway, specifically IL-8, suggests a role for these proinflammatory cytokines in physical fatigue. The data of this study are consistent with previous observations demonstrating a positive correlation between levels of fatigue and levels of circulating IL-8 in acute myelogenous leukemia/myelodysplastic syndrome patients.20 These findings collectively support the hypothesis of Beyer et al.18 that mechanisms inhibiting the NF-kB inflammatory pathway may offer some protection against fatigue. Further evidence suggests that IL-6 has a significant negative correlation with physical ability subscores in chronic fatigue syndrome patients.49 Although physical performance levels in populations with CLD have not been investigated as frequently as those in other chronically ill populations, such as those with cardiorespiratory and oncologic conditions, the importance of preserving function in these populations has been demonstrated in numerous other studies.37,50,51 These have shown
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that maintaining functional capacity is paramount to the quality-of-life and vitality of patients with chronic illness.52 In healthy and diseased people, including initial studies in patients with CLD, the results of 6MWT were found to be predictive for cardiorespiratory measurements and an indicator of overall survival.25 In this study, distances walked correlated to age, resting HR, and fasting GLU. When stratified by performance level, cardiorespiratory variables lost significance, whereas GLU and IL-8 were significantly different (Table 1). Ultimately, a model including anthropometric measures, abnormal IL-8, and fasting GLU was a more significant factor contributing to the limitation of the distance walked (Table 3). Deregulation of the NF-kB pathway seems to contribute to low physical performance in this population of CLD patients. In addition, it may be useful to screen older, female patients with CLD for fatigue via validated self-reports of physical fatigue levels to determine the impact fatigue has on qualityof-life in this population.
Study Limitations The main limitations of this study are the small cohort size and that only some of the patients were observed to reach significant levels of exertion. Most of the patients walked at a comfortable pace and seemed to have only a modest level of exertion. Despite this, the 6MWT may have been an aboveaverage activity level for some participants (Table 1). An additional, interesting analysis that the authors were not able to fully explore because of the small sample size of the patients with HCV would be stratifying for sustained virologic response and comparing performance, cardiorespiratory response, and systemic inflammatory activity. Sustained virologic response is the standard for therapeutic efficacy for treatment and eradication of virus. Because patients who have achieved sustained virologic response often have persistent fatigue, it would be important to compare their performance and physiologic and biologic measures with those who had not achieved sustained virologic response. In addition, the small sample size enabled the authors to account for only 39% of the variance. Determination of other possible covariates (e.g., fitness level, arthritis, comorbid conditions) would require a larger sample size.
CONCLUSIONS In summary, this study provides important information about the relationship between the NF-kB
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inflammatory pathway and GLU metabolism to performance in patients with CLD. The complex relationships between performance (physical fatigue level), GLU metabolism, and inflammatory activity are beginning to become understood among patients with CLD who experience significant levels of fatigue. This level of fatigue can negatively impact quality-of-life and may provide targets for therapeutic intervention to help preserve performance and activity level and, ultimately, alleviate fatigue.53 Here, the authors describe the relationships between cytokine and metabolic profiles of patients and physical performance. Fatigue can manifest itself as poor physical performance and reflects patients’ abilities to participate in daily activities. In the future, this avenue of research may provide clinicians with quantifiable biologic biomarkers to score physical fatigue objectively. In turn, these measures may provide targets for effective pharmacologic, lifestyle, and behavioral treatments (i.e., weight loss and physical activity interventions) aimed to mitigate physical fatigue.53,54 REFERENCES 1. Lonardo A, Ballestri S, Adinolfi LE, et al: Hepatitis C virus-infected patients are Fspared_ from the metabolic syndrome but not from insulin resistance. A comparative study of nonalcoholic fatty liver disease and hepatitis C virusYrelated steatosis. Can J Gastroenterol 2009;23:273Y8 2. Armstrong GL, Wasley A, Simard EP, et al: The prevalence of hepatitis C virus infection in the United States, 1999 through 2002. Ann Intern Med 2006; 144:705Y14 3. Bugianesi E, Salamone F, Negro F: The interaction of metabolic factors with HCV infection: Does it matter? J Hepatol 2012;56(suppl 1):S56Y65 4. Younossi ZM, McCullough AJ: Metabolic syndrome, non-alcoholic fatty liver disease and hepatitis C virus: Impact on disease progression and treatment response. Liver Int 2009;29:617 5. Ware JE, Bayliss MS, Mannocchia M, et al: for the International Hepatitis Interventional Therapy Group: Health-related quality of life in chronic hepatitis C: Impact of disease and treatment response. Hepatology 1999;30:550Y5 6. Gerber L, Otgonsuren M, Mishra A, et al: Nonalcoholic fatty liver disease (NAFLD) is associated with low level of physical activity. Aliment Pharmacol Ther 2012;36:772Y81 7. Price JK, Srivastava R, Bai CH, et al: Comparison of activity level among patients with chronic liver disease. Disabil Rehabil 2013;35:907Y12 8. Elliott C, Frith J, Day CP, et al: Functional impairment in alcoholic liver disease and non-alcoholic fatty liver disease is significant and persists over 3 years of follow-up. Dig Dis Sci 2013;58:2383Y91 www.ajpmr.com
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