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Effect of a high-protein diet with β-cryptoxanthin supplementation on metabolic risk factors, oxidative and inflammatory biomarkers in non-alcoholic fatty liver disease (NAFLD): study protocol for a randomized controlled clinical trial

  • 1,
  • 1Email author,
  • 1,
  • 2 and
  • 3
Trials201819:634

https://doi.org/10.1186/s13063-018-3014-8

  • Received: 6 July 2018
  • Accepted: 21 October 2018
  • Published:
Open Peer Review reports

Abstracts

Background

Excessive hepatic fat is associated with increased metabolic risk factors, production of inflammatory factors, and oxidative stress. High protein intake might trigger an increased hepatic lipid oxidation through an increase in hepatic energy expenditure. Furthermore, the majority of randomized controlled trials (RCT) in humans have failed to show whether carotenoids can be used to prevent and treat non-alcoholic fatty liver disease (NAFLD). However, it is notable and contradictory that NAFLD is rapidly escalating in Iran and other countries with lower intakes of fruit and vegetables (as sources of β-cryptoxanthin [β-CX] and carbohydrates) and higher intake of carbohydrates (as an agent of NAFLD); and the effects of β-CX and a high protein diet (HPD) on NAFLD need to be investigated further.

Methods/design

This study will be conducted as a randomized, double-blind, placebo-controlled clinical trial for 12 weeks to receive daily β-CX 6 mg supplementation combined with a HPD on levels of metabolic factors, β-CX, glycemic and lipid profiles, inflammatory factors, adipocytokines, and body composition. Ninety-two eligible patients, aged 18–60 years, of both genders, who are obese and overweight (body mass index [BMI] 25–40 kg/m2) will be randomly assigned to four groups as follow: HPD + placebo; normal protein diet + β-CX (NPD + β-CX); HPD + β-CX; and NPD + placebo (control group). Two populations will be analyzed in this work. The intention-to-treat (ITT) population includes all patients who will be randomized, while the per-protocol (PP) population includes all individuals who complete the 12- week intervention (i.e. study completers).

Discussion

Our findings from this trial will contribute to the knowledge of the relationship between β-CX supplementation and a HPD on NAFLD patients and determination of optimal macronutrient ratios without energy restriction.

Trial registration

Iran clinical trials registry, IRCT2017060210181N10. Registered on 20 June 2017.

Keywords

  • High dose of β-CX supplementation
  • High protein diet
  • Biochemical metabolic risk factors
  • NAFLD

Background

Non-alcoholic fatty liver disease (NAFLD) includes a disease spectrum ranging from simple steatosis to non-alcoholic steatohepatitis (NASH), liver fibrosis, cirrhosis, and hepatocellular carcinoma [1]. It is now present in 15–30% of Asians, has a worldwide distribution, and associates with central adiposity, obesity, insulin resistance (IR), metabolic syndrome, cardiovascular diseases (CVD), and type 2 diabetes [24]. It occurs in individuals whose alcohol consumption is insignificant (< 10 g per day for women, < 20 g per day for men) and is characterized histologically by at least 5% steatosis and other parenchymal changes, ranging from inflammation to hepatocyte apoptosis/necrosis and to fibrosis [5]. Excessive hepatic fat and visceral adipose tissue mass are also positively associated with systemic inflammation, lipid metabolism disorders [6], serum insulin, free fatty acids, blood glucose, and IR in that each of these causes increased production of inflammatory factors such as TNF-α and oxidative stress [79]. C-reactive protein (CRP), TNF-α, and other acute-phase proteins are increased in NAFLD and there is a strong, graded relationship between the histological severity of NAFLD and these markers [10]. The severity of fatty liver is positively correlated with visceral fat accumulation and insulin resistance and may contribute to higher serum liver tests (aspartate transaminase [AST], alanine transaminase [ALT], alkaline phosphatase [ALP], and gamma-glutamyl transferase [GGT]) [11]. There is no precise consent on the effects and features of an optimal nutritional strategy in NAFLD [12]. Common medical interventions include diet therapy to reduce weight, improved nutritional patterns, physical activity, and supplements such as vitamin E and polyunsaturated fatty acids. The goal of each of these interventions is to reduce fat accumulation in the liver or to increase the antioxidant defense [13]. Weight loss may improve NAFLD: although a ≥ 5% weight loss ameliorates steatosis and cardio-metabolic variables, a ≥ 7% weight loss also improves histological disease activity in NASH [14]. Carbohydrate-rich diets increase abdominal fat deposition, free fatty acids, metabolic syndrome, IR, and diabetes [1519], and associate with obesity [20, 21]. Several mechanisms have been suggested for the potential effects of a high protein diet (HPD; 25–35% of total energy expenditure) versus a normal protein diet (12–18% of total energy expenditure) [22] on NAFLD. Amino acid catabolism is a high energetic process and it is also a well-known fact that taurine increases bile acid conjugation and energy metabolism to prevent diabetes, obesity, and NAFLD [23]. However, well-controlled dietary intervention studies are restricted [24]. β-cryptoxanthin (β-CX) is another component that we want to investigate in this study. β-CX, one of the six major carotenoids routinely measured in human serum (beta-carotene, lycopene, lutein, β-CX, zeaxanthin, and a-carotene), is obtained primarily from citrus fruits [25]. β-CX is also prevalent in corn, peas, and some yellow-colored animal products such as egg yolk and butter. There are many health benefits of a high β-CX diet. Having a high dietary β-CX allows any byproducts to be safely dealt with by more efficient antioxidants in neutralizing free radicals [26]. The recent studies have reported the inverse association of serum GGT, ALT, AST, with serum carotenoids in NAFLD [2729]. The β-CX is inversely associated with oxidative DNA damage, lipid peroxidation and inflammation, GGT, and insulin resistance [3035].

There are several reasons for doing this study: heretofore, it is unknown why β-CX as a source of carotenoids can prevent and treat NAFLD. Iranians exhibit lower intake of fruit and vegetables (as source of beta-CX) [36] and higher intake of carbohydrates (as an agent of NAFLD) [37], Observational, in vitro, animal models and human studies suggest that β-CX has greater bioavailability and absorption than alpha- and beta-carotene-rich foods [38]. As the effect of a prolonged intake of high dose of β-CX (6 mg) and a HPD (25% protein of total calorie intake) on NAFLD has received little research attention, a lack of optimal macronutrient ratios without energy restriction, few long-term studies up to now, and few clinical trial studies, we decided to design a clinical RCT to evaluate the effect of a HPD with β-CX supplementation on some metabolic risk factors, oxidative and inflammatory biomarkers, and adipocytokines among NAFLD.

Methods/design

Study design

This is a 2 × 2 factorial design that accomplished as a randomized double-blind, placebo-controlled clinical trial. The Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 2013 Statement will be followed in this trial (Additional file 1) [36].

Setting

The proposed clinical trial will be held at the clinic located in the hospital, Ahvaz Jundishapur University of Medical Science, for 12 weeks to assess the efficacy of daily β-CX 6 mg supplementation adjunctive with a HPD in NAFLD individuals. Figure 1 illustrates the overview of the study.
Fig. 1
Fig. 1

Overview of the study

Participants (inclusion and exclusion criteria)

Patients will be recruited in the study after fulfilling certain criteria, including: overweight and obese (BMI 25–40 kg/m2) individuals aged 18–60 years of both genders, existence of NAFLD by ultrasound, NAFLD activity score < 3, and willingness to participate by signing an informed consent document, Patients with viral hepatitis, cirrhosis, Wilson’s disease, pregnancy acute fatty liver, hepatocellular carcinoma, hypothyroidism and a history of chronic liver disease, lipodystrophy, menopause, parenteral nutrition, bladder and bile duct disease, significant weight loss (≥ 10% of body weight in preceding six months) or weight loss due to surgery, congenital metabolic diseases, individuals on antioxidant supplementations, milk thistle, and omega-3 fatty acids in the previous six months, a history of liver-damaging drugs (amiodarone, anti-virus, aspirin, non-steroidal anti-inflammatories, corticosteroids, methotrexate, tamoxifen, tetracycline, valproic acid), alcohol consumption > 20 g/day, calorie intake < 800 kcal or > 4200 kcal a day, pregnancy and lactation, serum ALT levels more than five times the upper limit (maximum limit of 30 for women and 40 for men), or history of cardiovascular and kidney disease (urine analysis albumin ≥ 30 mg/24 h and GFR ≤ 90 mL/min/1.73 m2) will be not included.

Randomization and blinding

Each eligible patient will receive a randomization number which will be determined by a computer-generated schedule. A randomization table will then be generated by the method of random permuted blocks. Persons who will be operationally independent from the study investigator will perform the study randomization. The investigator, clinician prescriber, and patients will be blinded to the treatment condition. To maintain and guarantee blinding, β-CX and placebo will be identical in appearance. Also, all patients will be outpatients and none of the patients will be in contact with each other. Therefore, they cannot compare their diet. Patients’ data collected during this trial will be kept confidential and will be locked in a secure area. Randomization codes of the study will be opened only after all participants complete the study protocol. After the screening phase, participants will be assigned to four equal groups—HPD + placebo; NPD + β-CX; HPD + β-CX; and NPD + placebo (control group)—to receive an outpatient dietary regimen for 12 weeks. The supplements will be bought by Shanghai Tianfu Chemical Ltd. The study will be conducted in accordance with the ethical standards of the responsible Committee on Human Experimentation (institutional and regional) and the guidelines for the design, conduct, and reporting of human intervention studies [37].

Interventions

According to (SPIRIT) Fig. 2, the study will be conducted for 12 weeks. The visits and the evaluations will be as follows: baseline (visit 0); 0 week; 6 weeks; and 12 weeks. The nutrient goals for the normal protein diet groups are 30% fat, 15% protein, and 55% carbohydrates and for the HPDF are 30% fat, 25% protein, and 45% carbohydrates. The amount of calorie intake will be similar in the four groups and all participants will be instructed to reduce their calorie intake by 500 kcal/day. Throughout this intervention, each patient will be advised not to make any changes in her/his physical activity level (PAL). As the study protocol will require the participants to maintain their pre-study level of physical activity throughout the study period, individuals’ PAL will be assessed at baseline and each follow-up visit using the IPAQ-short form. The supplemented β-CX dose [38, 39] and the recommended protein [1720, 40] will be set based on previous studies. The placebo will be manufactured to have a similar appearance, shape, weight, taste, and color as the β-CX capsule. The participants will receive either one capsule of β-CX or an identical placebo daily, taken after dinner for a period of 12 weeks.
Fig. 2
Fig. 2

**Schedule for enrollment, intervention, and assessment. 1 HPD + β-CX, 2 HPD + placebo, 3 normal protein diet + β-CX, 4 normal protein diet + placebo

Primary outcome measures

Fasting venous blood samples will be taken from patients on the morning of admission and on day 85. Primary outcomes including serum high-sensitive C-reactive protein (CRP) (μg/mL) and adiponectin (μg/mL) will be measured by high-sensitivity enzyme-linked immunosorbent assay (ELISA) with the following characteristics: hs-CRP (BioVendor, Heidelberg, Germany; #RH961CRP01HR); adiponectin (ALPCO Immunoassays, Salem, NH; #47-ADPHU-E01). Plasma insulin (IU/mL) (Pars Azmoon Co., Tehran, Iran), β-CX (HPLC- Column18), and free fatty acids (NEFA C Assay Kit; Wako Chemicals, Neuss, Germany, respectively) as other primary outcomes will be measured by the colorimetric methods. The enzymatic method (Pars Azmoon2 Co., Tehran, Iran) will be used for measuring serum hepatic enzymes (including ALT, AST, and ALP). IR will be assessed by homoeostasis model-insulin resistance index (HOMA-IR) [41], according to the following formulas: HOMA-IR [42] will be calculated using the formula “fasting insulin value fasting blood sugar level/405,” equivalent to the HOMA-formula: HOMA = fasting serum insulin (μU/mL) × fasting plasma glucose (mM/L)/22.5 [42]. HbA1c will be measured by spectrophotometry using the Biorad1 IN2IT devices. Glycemic status (fasting blood glucose) will be determined by the glucose oxidase/peroxidase (GOD-Perid) method using commercially available kits (Pars Azmoon Co., Tehran, Iran).

Secondary outcome measures

Weight will be measured to the nearest 0.1 kg without shoes while patients are in light clothing. Height will be measured without shoes, with shoulders in a normal position, and will be recorded to the nearest 0.1 cm. BMI will then be calculated as weight in kilograms divided by height in meters squared. Waist circumference will be measured with a non-elastic tape (SECA 203 by SECA GmbH & Co. KG, Hamburg, Germany) at a point midway between the lower border of the rib cage and the iliac crest at the end of normal expiration. Similarly, the hip circumference also will be measured at the widest part of the buttocks at the intertrochanteric level to the nearest 0.1 cm. All anthropometric measures will be taken by trained research assistants using standard equipment according to the standard guidelines [43]. Systolic (SBP) and diastolic blood pressure (DBP) will be measured after at least a 10-min rest with Omron RS6 (also known as HEM-6221-E; Omron Healthcare Co., Ltd., Kyoto, Japan), which is an electronic oscillometric device for BP measurement at the wrist with a cuff size appropriate for wrist circumferences in the range of 13–21 cm. Bioelectrical impendence analysis (BIA) will be performed to assess body composition (BIM4; Impedimed, Brisbane, QLD, Australia). The other anthropometric indices will be calculated using the following equations: waist-to-hip ratio (WHR) = waist (m)/hip (m); waist-to-height ratio (WHtR) = waist (m)/height (m); waist-to-hip-to-height ratio (WHHR) = WHR/height (m); body adiposity index (BAI) = hip (cm)/height (m)1.5–18; body shape index (ABSI) = WC (m)/(BMI2/3 × height [m]1/2) [44]. In addition, lipid parameters (total cholesterol, triglyceride levels, HDL cholesterol, and LDL cholesterol) will be measured. Cholesterol, triglyceride levels, and HDL cholesterol (HDL-C) will be measured with enzymatic colorimetric assays using commercially available kits (Pars Azmoon Co., Tehran, Iran). LDL cholesterol (LDL C) will be estimated based on the Friedewald equation [45]. The malondialdehyde (MDA) will be measured according to a procedure described by the Satoh method [46].

Dietary assessments

Individuals provided three days of 24-h recall questioner at the beginning and at the end of the study; data were collected by a professional nutritionist and analyzed by Nutritionist IV software (First Databank, San Bruno, CA, USA) modified for Iranian foods.

Statistical analysis

Two populations will be used in the analyses. The intention-to-treat (ITT) population includes all patients who will be randomized, while the per-protocol (PP) population includes all individuals who complete the 12-week intervention (i.e. study completers). The data will be checked for plausibility by randomly checking the accuracy and completeness and verifying against source data. The variables will be tested for normality using the Kolmogorov–Smirnov test, the Shapiro–Wilk test, and normality plots. All quantitative data will be reported as mean ± standard deviation. Baseline characteristics of participants will be compared among groups using analysis of variance (ANOVA) for parametric data and the Kruskal–Wallis test for non-parametric data. The primary analysis, comparing the effects of treatment on primary outcomes of fatty liver over 12 weeks, will be conducted using a generalized linear mixed-models procedure. Treatments and time will be included as fixed effects and the interactions between interventions and time will be tested. If significant main effects or interaction effects are observed, post-hoc analysis with Bonferroni adjustments will be performed. Potential confounding factors and effect modifiers (e.g. baseline age and gender, etc.) will be investigated within the model. Logistic regression will be used to test the multiplicative interaction. Rothman’s synergy index, which would be equal to unity under additively, and less than unity when suggesting antagonism, will be utilized to examine the postulated interaction effect of a HPD and β-CX on fatty liver. The secondary analysis, comparing the effects of treatment on secondary outcomes of fatty liver over 12 weeks, will be conducted using the same procedure. Potential confounding factors and effect modifiers will be investigated within the model. Differences between participants who complete and withdraw from the trial will be analyzed using an independent t test or the Mann–Whitney test for continuous variables (e.g. age) and chi-square for categorical variables (e.g. gender). Associations between severity of fatty liver and nutritional status at baseline will be assessed using regression analysis. McNemar’s test will be used to analyze the binary variables before and after the intervention. Our statistical analyses will be performed by using SPSS 21 (IBM, Armonk, NY, USA) and the results will be considered significant at P < 0.05.

Sample size and sampling

The sample size was calculated based on the primary outcome measures (12-week change in serum adiponectin, CRP, FFA, insulin, serum β-CX, FBS). Using the standard deviations reported in previous studies [17, 20, 47, 48], a maximum sample size of 18 individuals per group will be selected with mean changes of adiponectin as much as 1.3 and standard division of 1.4 g/day and 30% attrition rate. It calculated by pass 11.

To achieve the target sample size, all patients who will come to the gastrology clinic of Ahvaz hospitals will be included in the study if they will be willing to participate in the study considering the inclusion criteria of the study.

Safety, adverse effects, and monitoring data

There are no side effects of 6 mg/d of β-CX supplementation [38, 39] and the recommended protein [1720, 40]. This study will also monitor by a Data Monitoring Committee (DMC). All possible adverse events will also be reported to the Ethics Committee of the Ahvaz Jundishapur University of Medical Sciences. In addition, we will be monitoring compliance, gastrointestinal symptoms, and other adverse effects by phone calls and weekly meetings.

Discussion

In addition to calorie restriction as the main role of reducing fat in the liver, manipulating of macronutrients and supplementation of micronutrients, especially antioxidants, as a part of lifestyle interventions may prevent the progression of fat accumulation in the liver and prevent NAFLD [49]. There is strong evidence from both experimental and animal studies suggesting that a low protein diet can lead to IR, high blood pressure, and lipid abnormalities, all of which are underlying mechanisms involved in NAFLD [5052]; while dietary fat consumption may play a causative role in NAFLD [7, 5356]. A HPD may lead to improvement in fatty liver but it has been poorly assessed and most of these studies are mainly limited to animal models [57]. However, well-controlled dietary intervention is limited [24, 58]. In addition to the HPD, β-CX is another component that we want to study in this work. β-CX is an antioxidant and may protect convert free-radical damage to biomolecules including lipids, proteins, and nucleic acids [26]. The β-CX is inversely associated with oxidative DNA damage, lipid peroxidation, and inflammation, GGT, and IR [3035]. Of six carotenoids, only β-CX is inversely associated with type 2 diabetes [33].

According to the contradictory effects of β-CX and HPD on NAFLD, more long-term studies and clinical RCTs are needed to clarify the effects of carbohydrate restriction and β-CX supplementation on clinical outcome in patients with NAFLD. The findings will help physicians as a hugely important task to prevent the occurrence of NAFLD in people at risk and healthy individuals and will inform about the health impact of taking β-CX supplements and optimal dietary pattern to lose weight and thus avoid some chronic liver diseases. Finally, this study, as far as we are aware, will be the only study of its type to be conducted in Iran and one of the few studies conducted elsewhere in the world.

Strengths and weaknesses

The main strength of this study is the double-blind placebo-controlled trial as a highest level of research evidence. Other strengths of the study may be listed as follows:
  1. a)

    There are no side effects of 6 mg/d of β-CX supplementation and we expect a high level of patient compliance in this study;

     
  2. b)

    Measurement of plasma metabolic parameters will suggest to clinicians the best treatment approach of β-CX supplementation and optimal dietary macronutrients distribution on weight loss, liver biochemistry, and IR in patients with NAFLD;

     
  3. c)

    We will measure the serum β-CX values by HPLC and its association with NAFLD;

     
  4. d)

    There are few studies of a HPD on NAFLD.

     

However, the high cost of a HPD and β-CX supplementation within 12 weeks and the likelihood of increased uric acid and other complications of a HPD may be the main weaknesses of this study.

Trial status

This trial is in the ongoing phase.

Abbreviations

ABSI: 

Body shape index

ALP: 

Alkaline phosphatase

ALT: 

Alanine transaminase

ANCOVA: 

Analysis of covariance

AST: 

Aspartate transaminase

BAI: 

Body adiposity index

BIA: 

Bioelectrical impendence analysis

BMI: 

Body mass index

CBC: 

Cell blood count

CR-HPD: 

Calorie-restricted high protein diet

DBP: 

Diastolic blood pressure

FBS: 

Fasting blood sugar

FFA: 

Free fatty acids

GGT: 

Gamma-glutamyl transferase

GPPAQ: 

General practice physical activity questionnaire

HDL: 

High-density lipoprotein cholesterol

HOMA-IR: 

Homoeostasis model-insulin resistance index

HPLC: 

High-performance liquid chromatography

ITT: 

Intention-to-treat

LDL: 

Low-density lipoprotein cholesterol

NAFLD: 

Non-alcoholic fatty liver disease

NASH: 

Non-alcoholic steatohepatitis

SBP: 

Systolic blood pressure

TG: 

Triglyceride

TNF-α: 

Tumor necrosis factor alpha

WHHR: 

Waist-to-hip-to-height ratio

WHR: 

Waist-to-hip ratio

WHtR: 

Waist-to-height ratio

β-CX: 

Beta-cryptoxanthin

Declarations

Acknowledgements

Not applicable.

Funding

This research is funded by Ahvaz Jundishapur University of Medical Sciences.

Availability of data and materials

The data will not be shared because it is a protocol and results are secure before publishing.

Authors’ contributions

FH, AH, SSS, BH, KAA: First draft of manuscript and data collection. FH, AH: Concept and study design. FH, AH, SSS, BH, KAA: Data collection and critical review. All authors read and approved the final manuscript.

Ethics approval and consent to participate

This protocol, approved by Medical Ethics Committee of Ahvaz University of Medical Sciences, is in accordance with the Declaration of Helsinki (approval number: IR.AJUMS.REC.1396.138). Each participant will sign an informed consent form. This investigation was registered on the Iranian Registry of Clinical Trials (IRCT; registration number IRCT2017060210181N10). Anyone who has a complaint about the complications of the intervention can refer to the center of the Ethics Committee and get compensation.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
Department of Nutrition, Nutrition and Metabolic Diseases Research Center, Ahvaz Jundishapur University of Medical sciences, Ahvaz, Iran
(2)
Gastroenterology Department, Ahvaz Jundishapur University of Medical sciences, Ahvaz, Iran
(3)
Faculty of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

References

  1. Tiniakos DG, Vos MB, Brunt EM. Nonalcoholic fatty liver disease: pathology and pathogenesis. Annu Rev Pathol: Mech Dis. 2010;5:145–71.View ArticleGoogle Scholar
  2. Tilg H, Moschen AR. Evolution of inflammation in nonalcoholic fatty liver disease: the multiple parallel hits hypothesis. Hepatology. 2010;52:1836–46.View ArticlePubMed CentralGoogle Scholar
  3. Farrell GC, Larter CZ. Nonalcoholic fatty liver disease: from steatosis to cirrhosis. Hepatology. 2006;43:S99–112.View ArticlePubMed CentralGoogle Scholar
  4. Wong VWS. Nonalcoholic fatty liver disease in Asia: a story of growth. J Gastroenterol Hepatol. 2013;28:18–23.View ArticlePubMed CentralGoogle Scholar
  5. McCullough AJ. The clinical features, diagnosis and natural history of nonalcoholic fatty liver disease. Clin Liver Dis. 2004;8:521–33.View ArticlePubMed CentralGoogle Scholar
  6. Wang S, Miller B, Matthan NR, Goktas Z, Wu D, Reed DB, et al. Aortic cholesterol accumulation correlates with systemic inflammation but not hepatic and gonadal adipose tissue inflammation in low-density lipoprotein receptor null mice. Nutr Res. 2013;33:1072–82.View ArticlePubMed CentralGoogle Scholar
  7. Sanyal AJ, Campbell-Sargent C, Mirshahi F, Rizzo WB, Contos MJ, Sterling RK, et al. Nonalcoholic steatohepatitis: association of insulin resistance and mitochondrial abnormalities. Gastroenterology. 2001;120:1183–92.View ArticlePubMed CentralGoogle Scholar
  8. Timlin MT, Parks EJ. Temporal pattern of de novo lipogenesis in the postprandial state in healthy men. Am J Clin Nutr. 2005;81:35–42.View ArticlePubMed CentralGoogle Scholar
  9. Salmenniemi U, Ruotsalainen E, Pihlajamäki J, Vauhkonen I, Kainulainen S, Punnonen K, et al. Multiple abnormalities in glucose and energy metabolism and coordinated changes in levels of adiponectin, cytokines, and adhesion molecules in subjects with metabolic syndrome. Circulation. 2004;110:3842–8.View ArticlePubMed CentralGoogle Scholar
  10. Ajmal MR, Yaccha M, Malik MA, Rabbani M, Ahmad I, Isalm N, et al. Prevalence of nonalcoholic fatty liver disease (NAFLD) in patients of cardiovascular diseases and its association with hs-CRP and TNF-α. Indian Heart J. 2014;66:574–9.View ArticlePubMed CentralGoogle Scholar
  11. Verrijken A, Francque S, Mertens I, Talloen M, Peiffer F, Van Gaal L. Visceral adipose tissue and inflammation correlate with elevated liver tests in a cohort of overweight and obese patients. Int J Obes. 2010;34:899–907.View ArticleGoogle Scholar
  12. Catalano D, Trovato GM, Martines GF, Randazzo M, Tonzuso A. Bright liver, body composition and insulin resistance changes with nutritional intervention: a follow-up study. Liver Int. 2008;28:1280–7.View ArticlePubMed CentralGoogle Scholar
  13. Than NN, Newsome PN. A concise review of non-alcoholic fatty liver disease. Atherosclerosis. 2015;239:192–202.View ArticlePubMed CentralGoogle Scholar
  14. Musso G, Cassader M, Rosina F, Gambino R. Impact of current treatments on liver disease, glucose metabolism and cardiovascular risk in non-alcoholic fatty liver disease (NAFLD): a systematic review and meta-analysis of randomised trials. Diabetologia. 2012;55:885–904.View ArticlePubMed CentralGoogle Scholar
  15. Paniagua JA, De La Sacristana AG, Romero I, Vidal-Puig A, Latre J, Sanchez E, et al. Monounsaturated fat–rich diet prevents central body fat distribution and decreases postprandial adiponectin expression induced by a carbohydrate-rich diet in insulin-resistant subjects. Diabetes Care. 2007;30:1717–23.View ArticlePubMed CentralGoogle Scholar
  16. Valtueña S, Pellegrini N, Ardigò D, Del Rio D, Numeroso F, Scazzina F, et al. Dietary glycemic index and liver steatosis. Am J Clin Nutr. 2006;84:136–42.View ArticlePubMed CentralGoogle Scholar
  17. McAuley K, Hopkins C, Smith K, McLay R, Williams S, Taylor R, et al. Comparison of high-fat and high-protein diets with a high-carbohydrate diet in insulin-resistant obese women. Diabetologia. 2005;48:8–16.View ArticlePubMed CentralGoogle Scholar
  18. McLaughlin T, Abbasi F, Cheal K, Chu J, Lamendola C, Reaven G. Use of metabolic markers to identify overweight individuals who are insulin resistant. Ann Intern Med. 2003;139:802–9.View ArticlePubMed CentralGoogle Scholar
  19. Kang H, Greenson JK, Omo JT, Chao C, Peterman D, Anderson L, et al. Metabolic syndrome is associated with greater histologic severity, higher carbohydrate, and lower fat diet in patients with NAFLD. Am J Gastroenterol. 2006;101:2247–53.View ArticlePubMed CentralGoogle Scholar
  20. Noakes M, Keogh JB, Foster PR, Clifton PM. Effect of an energy-restricted, high-protein, low-fat diet relative to a conventional high-carbohydrate, low-fat diet on weight loss, body composition, nutritional status, and markers of cardiovascular health in obese women. Am J Clin Nutr. 2005;81:1298–306.View ArticlePubMed CentralGoogle Scholar
  21. Piatti P, Monti L, Magni F, Fermo I, Baruffaldi L, Nasser R, et al. Hypocaloric high-protein diet improves glucose oxidation and spares lean body mass: comparison to hypocaloric high-carbohydrate diet. Metabolism. 1994;43:1481–7.View ArticlePubMed CentralGoogle Scholar
  22. Clifton PM, Keogh J. Metabolic effects of high-protein diets. Curr Atheroscler Rep. 2007;9:472–8.View ArticlePubMed CentralGoogle Scholar
  23. de Wit NJ, Afman LA, Mensink M, Müller M. Phenotyping the effect of diet on non-alcoholic fatty liver disease. J Hepatol. 2012;57:1370–3.View ArticlePubMed CentralGoogle Scholar
  24. McCarthy EM, Rinella ME. The role of diet and nutrient composition in nonalcoholic fatty liver disease. J Acad Nutr Diet. 2012;112:401–9.View ArticlePubMed CentralGoogle Scholar
  25. Granado F, Olmedilla B, Blanco I, Rojas-Hidalgo E. Major fruit and vegetable contributors to the main serum carotenoids in the Spanish diet. Eur J Clin Nutr. 1996;50:246–50.PubMedPubMed CentralGoogle Scholar
  26. Lorenzo Y, Azqueta A, Luna L, Bonilla F, Domínguez G, Collins AR. The carotenoid β-cryptoxanthin stimulates the repair of DNA oxidation damage in addition to acting as an antioxidant in human cells. Carcinogenesis. 2009;30:308–14.View ArticlePubMed CentralGoogle Scholar
  27. Sugiura M, Nakamura M, Ogawa K, Ikoma Y, Yano M. High serum carotenoids are associated with lower risk for developing elevated serum alanine aminotransferase among Japanese subjects: the Mikkabi cohort study. Br J Nutr. 2016;115:1462–9.View ArticlePubMed CentralGoogle Scholar
  28. Sugiura M, Nakamura M, Ikoma Y, Yano M, Ogawa K, Matsumoto H, et al. High serum carotenoids are inversely associated with serum gamma-glutamyltransferase in alcohol drinkers within normal liver function. J Epidemiol. 2005;15:180–6.View ArticlePubMed CentralGoogle Scholar
  29. Sugiura M, Nakamura M, Ikoma Y, Yano M, Ogawa K, Matsumoto H, et al. Serum carotenoid concentrations are inversely associated with serum aminotransferases in hyperglycemic subjects. Diabetes Res Clin Pract. 2006;71:82–91.View ArticlePubMed CentralGoogle Scholar
  30. Haegele AD, Gillette C, O’Neill C, Wolfe P, Heimendinger J, Sedlacek S, et al. Plasma xanthophyll carotenoids correlate inversely with indices of oxidative DNA damage and lipid peroxidation. Cancer Epidemiol Prev Biomarkers. 2000;9:421–5.Google Scholar
  31. Sugiura M, Nakamura M, Ikoma Y, Yano M, Ogawa K, Matsumoto H, et al. The homeostasis model assessment-insulin resistance index is inversely associated with serum carotenoids in non-diabetic subjects. J Epidemiol. 2006;16:71–8.View ArticlePubMed CentralGoogle Scholar
  32. Katsuura S, Imamura T, Bando N, Yamanishi R. β-Carotene and β-cryptoxanthin but not lutein evoke redox and immune changes in RAW264 murine macrophages. Mol Nutr Food Res. 2009;53:1396–405.View ArticlePubMed CentralGoogle Scholar
  33. Montonen J, Knekt P, Järvinen R, Reunanen A. Dietary antioxidant intake and risk of type 2 diabetes. Diabetes Care. 2004;27:1845–6.View ArticleGoogle Scholar
  34. Sugiura M, Nakamura M, Ogawa K, Ikoma Y, Matsumoto H, Ando F, et al. Associations of serum carotenoid concentrations with the metabolic syndrome: interaction with smoking. Br J Nutr. 2008;100:1297–306.View ArticlePubMed CentralGoogle Scholar
  35. Ni Y, Nagashimada M, Zhan L, Nagata N, Kobori M, Sugiura M, et al. Prevention and reversal of lipotoxicity-induced hepatic insulin resistance and steatohepatitis in mice by an antioxidant carotenoid, β-cryptoxanthin. Endocrinology. 2015;156:987–999.View ArticlePubMed CentralGoogle Scholar
  36. Chan A-W, Tetzlaff JM, Gøtzsche PC, Altman DG, Mann H, Berlin JA, et al. SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ. 2013;346:e7586.View ArticlePubMed CentralGoogle Scholar
  37. Welch RW, Antoine J-M, Berta J-L, Bub A, de Vries J, Guarner F, et al. Guidelines for the design, conduct and reporting of human intervention studies to evaluate the health benefits of foods. Br J Nutr. 2011;106:S3–S15.View ArticlePubMed CentralGoogle Scholar
  38. Yamaguchi M. Role of carotenoid β-cryptoxanthin in bone homeostasis. J Biomed Sci. 2012;19:36.View ArticlePubMed CentralGoogle Scholar
  39. Yamaguchi M, Igarashi A, Uchiyama S, Sugawara K, Sumida T, Morita S, et al. Effect of β-crytoxanthin on circulating bone metabolic markers: intake of juice (Citrus unshiu) supplemented with β-cryptoxanthin has an effect in menopausal women. J Health Sci. 2006;52:758–68.View ArticleGoogle Scholar
  40. Bezerra Duarte SM, Faintuch J, Stefano JT, Sobral de Oliveira MB, de Campos Mazo DF, Rabelo F, et al. Hypocaloric high-protein diet improves clinical and biochemical markers in patients with nonalcoholic fatty liver disease (NAFLD). Nutr Hosp. 2014;29:94–101.PubMedPubMed CentralGoogle Scholar
  41. Matthews D, Hosker J, Rudenski A, Naylor B, Treacher D, Turner R. Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–9.View ArticleGoogle Scholar
  42. Ohnishi H, Saitoh S, Ura N, Takagi S, Obara F, Akasaka H, et al. Relationship between insulin resistance and accumulation of coronary risk factors. Diabetes Obes Metab. 2002;4:388–93.View ArticlePubMed CentralGoogle Scholar
  43. World Health Organization. Measuring obesity—classification and description of anthropometric data. Report on a WHO consultation of the epidemiology of obesity. Warsaw 21–23 October 1987. Copenhagen: WHO; 1989. Nutrition Unit document, EUR/ICP/NUT 1987, 123Google Scholar
  44. Fu S, Luo L, Ye P, Liu Y, Zhu B, Bai Y, et al. The abilities of new anthropometric indices in identifying cardiometabolic abnormalities, and influence of residence area and lifestyle on these anthropometric indices in a Chinese community-dwelling population. Clin Interv Aging. 2014;9:179.View ArticlePubMed CentralGoogle Scholar
  45. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18:499–502.PubMedPubMed CentralGoogle Scholar
  46. Kei S. Serum lipid peroxide in cerebrovascular disorders determined by a new colorimetric method. Clin Chim Acta. 1978;90:37–43.View ArticleGoogle Scholar
  47. Haufe S, Engeli S, Kast P, Böhnke J, Utz W, Haas V, et al. Randomized comparison of reduced fat and reduced carbohydrate hypocaloric diets on intrahepatic fat in overweight and obese human subjects. Hepatology. 2011;53:1504–14.View ArticlePubMed CentralGoogle Scholar
  48. Sacks FM, Bray GA, Carey VJ, Smith SR, Ryan DH, Anton SD, et al. Comparison of weight-loss diets with different compositions of fat, protein, and carbohydrates. N Engl J Med. 2009;2009:859–73.View ArticleGoogle Scholar
  49. Mouzaki M, Allard JP. The role of nutrients in the development, progression, and treatment of nonalcoholic fatty liver disease. J Clin Gastroenterol. 2012;46:457–67.View ArticlePubMed CentralGoogle Scholar
  50. Agius L. High-carbohydrate diets induce hepatic insulin resistance to protect the liver from substrate overload. Biochem Pharmacol. 2013;85:306–12.View ArticlePubMed CentralGoogle Scholar
  51. Nazarenko L, Petrova I, Raĭkhel'son K, Baranovskiĭ A. Nutrition mistakes in patients with nonalcoholic fatty liver disease and the ways of correction. Eksp Klin Gastroenterol. 2011;2:19–24.Google Scholar
  52. Schugar RC, Crawford PA. Low-carbohydrate ketogenic diets, glucose homeostasis, and nonalcoholic fatty liver disease. Curr Opin Clin Nutr Metab Care. 2012;15:374.View ArticlePubMed CentralGoogle Scholar
  53. Liu T, Yang L-L, Zhang L, Song H-Y, Li D-F, Ji G. Comparative study on the effects of different therapeutic methods in preventing and treating nonalcoholic fatty liver in rats. Zhong Xi Yi Jie He Xue Bao. 2012;10:1120–6.View ArticlePubMed CentralGoogle Scholar
  54. Morita M, Ishida N, Uchiyama K, Yamaguchi K, Itoh Y, Shichiri M, et al. Fatty liver induced by free radicals and lipid peroxidation. Free Radic Res. 2012;46:758–65.View ArticlePubMed CentralGoogle Scholar
  55. Van Der Meer RW, Hammer S, Lamb HJ, Frolich M, Diamant M, et al. Effects of short-term high-fat, high-energy diet on hepatic and myocardial triglyceride content in healthy men. J Clin Endocrinol Metab. 2008;93:2702–8.View ArticlePubMed CentralGoogle Scholar
  56. Westerbacka J, Lammi K, Häkkinen A-M, Rissanen A, Salminen I, Aro A, et al. Dietary fat content modifies liver fat in overweight nondiabetic subjects. J Clin Endocrinol Metab. 2005;90:2804–9.View ArticlePubMed CentralGoogle Scholar
  57. Uebanso T, Taketani Y, Fukaya M, Sato K, Takei Y, Sato T, et al. Hypocaloric high-protein diet improves fatty liver and hypertriglyceridemia in sucrose-fed obese rats via two pathways. Am J Physiol Endocrinol Metab. 2009;297:E76–84.View ArticlePubMed CentralGoogle Scholar
  58. Rafiq N, Bai C, Fang Y, Srishord M, McCullough A, Gramlich T, et al. Long-term follow-up of patients with nonalcoholic fatty liver. Clin Gastroenterol Hepatol. 2009;7:234–8.View ArticlePubMed CentralGoogle Scholar

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