Nonalcoholic fatty liver disease (NAFLD) is a disease of alarmingly increasing prevalence, linked to metabolic, cardiovascular and malignant morbidity and without any officially approved treatment. It is increasingly recognized that the gut microbiome is implicated in the pathogenesis and progression of numerous chronic diseases, including NAFLD. Through the so-called gut-liver axis, the liver is exposed to gut-bacterial-derived products, including toxins (lipopolysaccharides), enzymes (methylamines), alcohol, and short-chain fatty acids (mainly acetate, propionate, and butyrate), that may lead to accumulation of triglycerides, inflammatory responses, oxidative stress and accompanying damage to the hepatocytes. The primary objective is to study the effect of consecutive FMT on liver fat accumulation measured by Magnetic Resonance Images (MRI) LiverMultiscan at 12 weeks. Secondary objectives are weight, waist, blood pressure, metabolic parameters (including glucose, cholesterol, pancreatic beta-cell function, HOMA-IR), objective and subjective stress indicators, gut-microbiota and bile composition and liver enzymes. Stool samples will be collected for microbiota analysis at time point 0, 3, 6 and 12 weeks.
Nonalcoholic fatty liver disease (NAFLD) is a disease of alarmingly increasing prevalence, linked to metabolic, cardiovascular and malignant morbidity and without any officially approved treatment. It is increasingly recognized that the gut microbiome is implicated in the pathogenesis and progression of numerous chronic diseases, including NAFLD. Through the so-called gut-liver axis, the liver is exposed to gut-bacterial-derived products, including toxins (lipopolysaccharides), enzymes (methylamines), alcohol, and short-chain fatty acids (mainly acetate, propionate, and butyrate), that may lead to accumulation of triglycerides, inflammatory responses, oxidative stress and accompanying damage to the hepatocytes. The investigators hypothesize that altered gut microbiota underlie (hepatic) insulin resistance and liver fat accumulation in NAFLD patients. Fecal microbiota transplantation, through amelioration of gut-microbiota released products like lipopolysaccharides, short-chain fatty acids, alcohol and enzymes, and changes in bile acids, may positively affect NAFLD. During the study 20 patients will be randomized for infusion of allogenic (lean donor) or autologous (own) feces by gastroscopy at time points 0, 3 and 6 weeks on a 1:1 basis. Prior to randomization, and at 12 weeks, all patients will undergo LiverMultiscan to non-invasively quantify liver fat accumulation and other features of NAFLD. In addition, various metabolic parameters (lipids, HOMA-IR), objective and subjective stress indicators, gut-microbiota and bile composition, and liver enzymes will be measured. The primary objective is to study the effect on consecutive FMT on liver fat accumulation measured by Magnetic Resonance Images (MRI) LiverMultiscan at 12 weeks. Secondary objectives are alterations in anthropometrical data (weight, waist, blood pressure), changes in fecal microbiota, liver enzymes, bile composition and metabolic parameters including glucose, lipids, pancreatic beta-cell function and insulin resistance measured as HOMA-IR and objective and subjective stress indicators.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
QUADRUPLE
Enrollment
20
Fecal transplantation will be performed at baseline and at week 3 and 6. At the Department of Clinical Bacteriology either the autologous or allogenic feces is prepared for donation by an experienced lab co-worker. The fecal transplantation will be performed via gastroduodenal endoscopy at the Department of Gastroenterology by an experienced endoscopist. To alleviate the procedure, midazolam is offered to the participants. Following placement of the endoscope in the horizontal duodenum, 150 mL feces solution is inserted via the endoscope.
Leiden University Medical Center
Leiden, Netherlands
RECRUITINGthe effect on consecutive FMT on liver fat accumulation
measured by MRI Livermultiscan
Time frame: 12 weeks
alterations in anthropometric data
differences in weight in kilograms
Time frame: 3, 6 and 12 weeks
alterations in anthropometric data
differences in systolic and diastolic blood pressure in mmHg
Time frame: 3, 6 and 12 weeks
alterations in anthropometric data
differences in waist in centimeters
Time frame: 3, 6 and 12 weeks
alterations in pancreatic beta-cell function and insulin resistance
measured by plasma C-peptide in nmol/L derived during OGTT + arginin
Time frame: 3, 6 and 12 weeks
alterations in pancreatic beta-cell function and insulin resistance
measured by glucose in mmol/L derived during OGTT + arginin
Time frame: 3, 6 and 12 weeks
alterations in pancreatic beta-cell function and insulin resistance
measured by insulin in mU/L derived during OGTT + arginin
Time frame: 3, 6 and 12 weeks
alterations in liver enzymes
Aspartaat aminotransferase (ASAT), alanine aminotransferase (ALAT), gamma glutamyl transpeptidase (GGT), alkalic phosphatase (AF), bilirubin
Time frame: 3, 6 and 12 weeks
change in bile composition
measured using endoscopic bile samples (qualitative measurements)
Time frame: 3 and 6 weeks
change in bacterial species in small intestine and feces
measured by endoscopic duodenal biopsies and fecal samples
Time frame: 3 and 6 weeks
changes in lipid homeostasis
cholesterol, HDL, LDL, triglycerides
Time frame: 3, 6 and 12 weeks
alterations in psychological stress
by measuring cortisol levels in hair samples
Time frame: 0 and 12 weeks
alterations in psychological stress
by reporting psychological stress daily using stress diaries on a scale from 1-10 (non-validated scale)
Time frame: week 1, week 4, week 7, week 9 during 7 days
alterations in psychological stress
by Perceived Stres Scale (PSS) questionnaires, scores on a scale from 0-40
Time frame: 0 and 12 weeks
changes in physical activity
measuring physical activity by steps with FitBit activity tracker
Time frame: during 14 weeks
changes in physical activity
measuring physical activity by active minutes with FitBit activity tracker
Time frame: during 14 weeks
changes in physical activity
measuring physical activity by heart rate with FitBit activity tracker
Time frame: during 14 weeks
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