Study Subject Characteristics
There were more women than men in this study, similar to a population-based study in Thailand by Summart (2017) . Metabolic syndrome was dominant in the study subjects, which aligned with many other studies stating an apparent relationship among NAFLD, obesity, diabetes mellitus, and metabolic syndrome. In this study, 25 out of 37 subjects were obese, and 30 from 37 subjects had type 2 diabetes mellitus. Such characteristics were similar to other previous studies, which stated that there is a higher prevalence of NAFLD in adults with obesity (65.7%) and type 2 diabetes mellitus (74%) [16,17]. Individuals with NAFLD have a five times higher risk of developing diabetes [18,19]. The association between NAFLD and type 2 diabetes mellitus can be explained through insulin resistance, dyslipidemia, and accumulation of liver triglyceride in NAFLD and β-cell defect in type 2 diabetes mellitus .
Although there were many previous studies on the microbiota, the results were inconsistent. A study by Raman et al. (2013) reported an increase in Firmicutes in obese patients with NAFLD compared with that of the patients without obesity and NALD . Another study by Jiang et al. (2015) found no significant microbiota differences in NAFLD and normal control group . Our study found that on average, Firmicutes was higher than Bacteroidetes. While at the genus level, Bacteroides (14.43%) were more numerous than Prevotella (9.14%), confirming that Bacteroides dominated other genera from the Firmicutes phylum.
Rahayu (2019) studied young Indonesian adult microbiota profile  and reported that in numerous orders, the microbiota was Clostridium, Prevotella, Atopobium, Bifidobacterium, and Bacteroides. The results were quite similar to other local studies showing dominant Prevotella but different from our study. This may be due to the different study population as the subjects in this study lived in Jakarta and represented the urban population with high protein and animal fat in their diet .
We attempted to identify the prevalence of dysbiosis by looking at the diversity of microbiota and/or an increase in the ratio of Firmicutes/Bacteroidetes. Using dysbiosis criteria of Firmicutes/Bacteroidetes ratio, there were 26 out of 37 subjects with dysbiosis. There were 25 subjects fulfilling the criteria if only based on the decrease of microbiota diversity. By combining the two criteria, we found dysbiosis in 18 subjects.
Microbiota Diversity Index in NAFLD
The microbiota diversity in our study was assessed using the alpha diversity index through OTUs, the Shannon index or the inverse Simpson index. The results showed significant differences in microbial diversity between the central obesity and non-central obesity group and between the high triglyceride and normal triglyceride group. Central obesity and high triglyceride groups showed a reduction in diversity compared with that of the other groups. This is similar with studies by Turnbaugh et al. (2009)  and Le Chatelier (2013) , which showed a total reduction in bacteria diversity in obesity. This is also in concordance with the dysbiosis theory commonly used in many studies as a marker for dysbiosis condition related to diseases.
Correlation of Firmicutes/Bacteroidetes with Fibrosis and Steatosis Based on Body Mass Index
We analyzed the correlation between the Firmicutes/Bacteroidetes ratio and microbiota in each taxonomy level with fibrosis and steatosis based on BMI. NAFLD analysis in each BMI group showed that the Firmicutes/Bacteroidetes ratio only had a positive correlation with steatosis in the obesity group. There was no significant correlation with fibrosis and also with steatosis in groups other than the obesity group. We also found that Firmicutes had a strong positive correlation with steatosis in the obesity group. This is similar to many previous studies that highlighted the role of Firmicutes in obesity [8, 21].
Further analysis in lower taxonomy level in each microbiota revealed that only the group from phylum Proteobacteria was correlated with fibrosis in the obesity and normal BMI group. This is similar to a study by Loomba et al. (2017) . The higher the fibrosis degree, the more numerous Proteobacteria and Bacteroidetes. Through this correlation study, we can see that Proteobacteria has a role in the process of liver fibrosis, although the exact mechanism is still unknown.
Most microbiotas had a positive correlation with steatosis, especially in obese patients. Some of which were from the order Clostridiales and Selemonodales in the Firmicutes phylum. While those correlated with steatosis in the normal BMI group were from the Actinobacteria phylum, the mechanism underlying steatosis by the microbiota were from several pathways especially related to fat metabolism . Lactobacillus was very consistent in protecting steatosis, while the Enterobacteriaceae family in our study showed a very strong positive correlation with steatosis in the normal BMI group. These findings differed from those of previous studies . However, in a study by Rahayu in healthy Indonesian population showed that the family of Enterobacteriaceae, especially Escherichia coli is part of the normal flora that increases in old age .
At present, there are very few studies that can show the direct cause and effect relationship between microbiota and NAFLD pathogenesis. However, some interventional studies in animals showed the important role of intestinal microbiota, especially in triggering a metabolic response. The intestinal microbiota from obese subjects can induce liver steatosis through modulation of fat metabolism. This is probably why most intestinal microbiota in our study correlated with steatosis but not with fibrosis. The process of turning steatosis into fibrosis needs more complex pathways and involving more factors aside from intestinal microbiota .
We acknowledge that the limitations of this study include the small sample size because of which we could not demonstrate that small variations in the bacterial counts were statistically significant. However, this cross-sectional single-center study was unable to view in detail the change in microbiota in relation to disease progression. We did not use normal healthy control because it was difficult to find a population in urban settings that was absolutely healthy and free of metabolic disorders and was not affected by extreme diet.
In conclusion, we assumed that the bigger the difference between the subgroups studied, the stronger the potential effect of the bacteria on the phenotype. This is the first study in Indonesia to thoroughly profile the microbiota in patients with NAFLD using next-generation sequencing and tried to find the correlation of each microbiota with fibrosis and steatosis. There was a strong positive correlation between the Firmicutes/Bacteroidetes ratio with steatosis in the obesity group. There were positive and negative correlations between some microbiota with fibrosis and steatosis. We suggest that future studies examine microbiota profiles in the general Indonesian population, the microbiota population in patients with NAFLD based on groups with other metabolic syndrome co-morbidities and the relationship between microbiota metabolism products and NAFLD.