Treatment of nonalcoholic steatohepatitis with probiotics. A proof-of-concept study

Background. Probiotics have profound effect on nonalcoholic steatohepatitis (NASH) in animal models. We aimed to test the hypothesis that probiotics treatment was superior to usual care in reducing liver fat in NASH patients.Material and methods. Patients with histology-proven NASH were randomized to receive probiotics (n = 10) or usual care (n = 10) for 6 months. The Lepicol probiotic formula contained Lactobacillus plantarum, Lactobacillus deslbrueckii, Lactobacillus acidophilus, Lactobacillus rhamnosus and Bifidobacterium bifidum. The primary endpoint was change in intrahepatic triglyceride content (IHTG), as measured by proton-magnetic resonance spectroscopy, from baseline to month 6. Secondary endpoints included changes in liver biochemistry and metabolic profile.Results. IHTG decreased from 22.6 ± 8.2% to 14.9 ± 7.0% in the probiotic group (P = 0.034) but remained static in the usual care group (16.9 ± 6.1% to 16.0 ± 6.6%; P = 0.55). Six subjects in the probiotic group had IHTG reduced by more than 30% from baseline, compared to 2 subjects in the usual care group (p = 0.17). The probiotic group also had greater reduction in serum aspartate aminotransferase level (P = 0.008). On the other hand, the use of probiotics was not associated with changes in body mass index, waist circumference, glucose and lipid levels.Conclusions. Probiotics treatment may reduce liver fat and AST level in NASH patients. The therapeutic potential of probiotics in NASH should be tested in larger studies

Higher Estimated Net Endogenous Acid Production May Be Associated with Increased Prevalence of Nonalcoholic Fatty Liver Disease in Chinese Adults in Hong Kong

<div><p>Nonalcoholic fatty liver disease (NAFLD) has been associated with reduced growth hormone levels and signaling. Such hormonal changes also occur in metabolic acidosis. Since mild metabolic acidosis can be diet induced, diet-induced acid load may constitute a nutritional factor with possible influence on NAFLD development. This study explored whether a higher diet-induced acid load is associated with an increased likelihood of NAFLD. Apparently healthy Chinese adults (330 male, 463 female) aged 19-72 years were recruited through population screening between 2008 and 2010 in a cross-sectional population-based study in Hong Kong. Estimated net endogenous acid production (NEAP) was calculated using Frassetto’s method and potential renal acid load (PRAL) was calculated using Remer’s method based on dietary data from a food frequency questionnaire. NAFLD was defined as intrahepatic triglyceride content at >5% by proton-magnetic resonance spectroscopy. Possible advanced fibrosis was defined as liver stiffness at >7.9 kPa by transient elastography. Multivariate logistic regression models were used to examine the association between each measure of dietary acid load and prevalent NAFLD or possible advanced fibrosis with adjustment for potential anthropometric and lifestyle factors. 220 subjects (27.7%) were diagnosed with NAFLD. Estimated NEAP was positively associated with the likelihood of having NAFLD after adjustment for age, sex, body mass index, current drinker status and the presence of metabolic syndrome [OR (95% CI) = 1.25 (1.02-1.52), <i>p</i> = 0.022]. The association was slightly attenuated but remained significant when the model was further adjusted for other dietary variables. No association between PRAL and NAFLD prevalence was observed. Both estimated NEAP and PRAL were not associated with the presence of possible advance fibrosis. Our findings suggest that there may be a modest association between diet-induced acid load and NAFLD. More studies are needed to ascertain the link between diet-induced acid load and NAFLD and to investigate the underlying mechanisms.</p></div

Diet-Quality Scores and Prevalence of Nonalcoholic Fatty Liver Disease: A Population Study Using Proton-Magnetic Resonance Spectroscopy

<div><p>Dietary pattern analysis is an alternative approach to examine the association between diet and nonalcoholic fatty liver disease (NAFLD). This study examined the association of two diet-quality scores, namely Diet Quality Index-International (DQI-I) and Mediterranean Diet Score (MDS) with NAFLD prevalence. Apparently healthy Chinese adults (332 male, 465 female) aged 18 years or above were recruited through a population screening between 2008 and 2010 in a cross-sectional population-based study in Hong Kong. DQI-I and MDS, as well as major food group and nutrient intakes were calculated based on dietary data from a food frequency questionnaire. NAFLD was defined as intrahepatic triglyceride content at ≥5% by proton-magnetic resonance spectroscopy. Multivariate logistic regression models were used to examine the association between each diet-quality score or dietary component and prevalent NAFLD with adjustment for potential lifestyle, metabolic and genetic factors. A total of 220 subjects (27.6%) were diagnosed with NAFLD. DQI-I but not MDS was associated with the prevalence of NAFLD. A 10-unit decrease in DQI-I was associated with 24% increase in the likelihood of having NAFLD in the age and sex adjusted model (95% CI: 1.06–1.45, <i>p</i> = 0.009), and the association remained significant when the model was further adjusted for other lifestyle factors, metabolic and genetic factors [OR: 1.26 (95% CI: 1.03–1.54), <i>p</i> = 0.027]. Multivariate regression analyses showed an inverse association of the intake of vegetables and legumes, fruits and dried fruits, as well as vitamin C with the NAFLD prevalence (<i>p</i><0.05). In conclusion, a better diet quality as characterized by a higher DQI-I and a higher consumption of vegetables, legumes and fruits was associated with a reduced likelihood of having NAFLD in Hong Kong Chinese.</p></div

Molecular characterization of the fecal microbiota in patients with nonalcoholic steatohepatitis--a longitudinal study.

The human gut microbiota has profound influence on host metabolism and immunity. This study characterized the fecal microbiota in patients with nonalcoholic steatohepatitis (NASH). The relationship between microbiota changes and changes in hepatic steatosis was also studied.Fecal microbiota of histology-proven NASH patients and healthy controls was analyzed by 16S ribosomal RNA pyrosequencing. NASH patients were from a previously reported randomized trial on probiotic treatment. Proton-magnetic resonance spectroscopy was performed to monitor changes in intrahepatic triglyceride content (IHTG).A total of 420,344 16S sequences with acceptable quality were obtained from 16 NASH patients and 22 controls. NASH patients had lower fecal abundance of Faecalibacterium and Anaerosporobacter but higher abundance of Parabacteroides and Allisonella. Partial least-square discriminant analysis yielded a model of 10 genera that discriminated NASH patients from controls. At month 6, 6 of 7 patients in the probiotic group and 4 of 9 patients in the usual care group had improvement in IHTG (P=0.15). Improvement in IHTG was associated with a reduction in the abundance of Firmicutes (R(2)=0.4820, P=0.0028) and increase in Bacteroidetes (R(2)=0.4366, P=0.0053). This was accompanied by corresponding changes at the class, order and genus levels. In contrast, bacterial biodiversity did not differ between NASH patients and controls, and did not change with probiotic treatment.NASH patients have fecal dysbiosis, and changes in microbiota correlate with improvement in hepatic steatosis. Further studies are required to investigate the mechanism underlying the interaction between gut microbes and the liver

Logistic regression analysis linking individual food groups or nutrients and the presence of NAFLD (n = 797).

<p>¹ Tertiles based on the distribution of all subjects, except two categories for the fast food intake (intake = 0 vs. intake > 0 g per day)</p><p>² Further adjusted for BMI, current smoker status (yes/no), current drinker status (yes/no), central obesity (yes/no), triglyceride >1.7 mmol/l (yes/no), reduced HDL-cholesterol (yes/no), hypertension (yes/no), impaired fasting glucose or diabetes (yes/no), and the <i>PNPLA3</i> genotypes (CC vs. CG vs. GG genotypes). Energy intake was further adjusted in the multivariate model of food group intake analysis.</p><p>³<i>P</i>_<i>trend</i> was examined by entering tertiles of food group intake as a fixed factor for the models of food group intake analysis, whereas <i>P</i> value was used for the models of nutrient intake analysis.</p><p>⁴ Included mainly sweetened beverages or juice, carbonated drinks and sports drinks</p><p>NAFLD, non-alcoholic fatty liver disease</p><p>Logistic regression analysis linking individual food groups or nutrients and the presence of NAFLD (n = 797).</p

Correlation between each diet-quality score and selected food group and nutrient intakes (n = 797).

<p>¹ Spearman’s rank correlation was used for food group intake analysis and vitamin C intake analysis whereas Pearson’s correlation was used for other nutrient intakes analysis</p><p>² Included mainly sweetened beverages or juice, carbonated drinks and sports drinks</p><p>DQI-I, Diet Quality Index-International; MDS, Mediterranean Diet Score</p><p>Correlation between each diet-quality score and selected food group and nutrient intakes (n = 797).</p

Overall and stratified logistic regression analysis linking each diet-quality score and the presence of NAFLD (n = 797).

<p>¹ Adjusted for age and sex, expect for the stratified variable whenever appropriate.</p><p>² Further adjusted for BMI, energy intake, current smoker status (yes/no), current drinker status (yes/no), central obesity (yes/no), triglyceride >1.7 mmol/l (yes/no), reduced HDL-cholesterol (yes/no), hypertension (yes/no), impaired fasting glucose or diabetes (yes/no), and the <i>PNPLA3</i> genotypes (CC vs. CG vs. GG genotypes), except for the stratified variable whenever appropriate.</p><p>DQI-I, Diet Quality Index-International; MDS, Mediterranean Diet Score; NAFLD, non-alcoholic fatty liver disease</p><p>Overall and stratified logistic regression analysis linking each diet-quality score and the presence of NAFLD (n = 797).</p

Correlation between estimated NEAP or PRAL and selected nutrients and food groups (n = 793).

<p>¹ By Spearman’s rank correlation.</p><p>Correlation between estimated NEAP or PRAL and selected nutrients and food groups (n = 793).</p