Pathophysiological background in different phenotypes of nonalcoholic fatty liver disease (NAFLD) remains to be elucidated. The aim was to investigate the association between fecal and blood ...microbiota profiles and the presence of NAFLD in obese versus lean subjects. Demographic and clinical data were reviewed in 268 health checkup examinees, whose fecal and blood samples were available for microbiota analysis. NAFLD was diagnosed with ultrasonography, and subjects with NAFLD were further categorized as obese (body mass index (BMI) ≥25) or lean (BMI <25). Fecal and blood microbiota communities were analyzed by sequencing of the V3-V4 domains of the 16S rRNA genes. Correlation between microbiota taxa and NAFLD was assessed using zero-inflated Gaussian mixture models, with adjustment of age, sex, and BMI, and Bonferroni correction. The NAFLD group (n = 76) showed a distinct bacterial community with a lower biodiversity and a far distant phylotype compared with the control group (n = 192). In the gut microbiota, the decrease in Desulfovibrionaceae was associated with NAFLD in the lean NAFLD group (log2 coefficient (coeff.) = -2.107, P = 1.60E-18), but not in the obese NAFLD group (log2 coeff. = 1.440, P = 1.36E-04). In the blood microbiota, Succinivibrionaceae showed opposite correlations in the lean (log2 coeff. = -1.349, P = 5.34E-06) and obese NAFLD groups (log2 coeff. = 2.215, P = 0.003). Notably, Leuconostocaceae was associated with the obese NAFLD in the gut (log2 coeff. = -1.168, P = 0.041) and blood (log2 coeff. = -2.250, P = 1.28E-10). In conclusion, fecal and blood microbiota profiles showed different patterns between subjects with obese and lean NAFLD, which might be potential biomarkers to discriminate diverse phenotypes of NAFLD.
Gut microbiota plays an important role in the harvesting, storage, and expenditure of energy obtained from one's diet. Our cross-sectional study aimed to identify differences in gut microbiota ...according to body mass index (BMI) in a Korean population. 16S rRNA gene sequence data from 1463 subjects were categorized by BMI into normal, overweight, and obese groups. Fecal microbiotas were compared to determine differences in diversity and functional inference analysis related with BMI. The correlation between genus-level microbiota and BMI was tested using zero-inflated Gaussian mixture models, with or without covariate adjustment of nutrient intake.
We confirmed differences between 16Sr RNA gene sequencing data of each BMI group, with decreasing diversity in the obese compared with the normal group. According to analysis of inferred metagenomic functional content using PICRUSt algorithm, a highly significant discrepancy in metabolism and immune functions (P < 0.0001) was predicted in the obese group. Differential taxonomic components in each BMI group were greatly affected by nutrient adjustment, whereas signature bacteria were not influenced by nutrients in the obese compared with the overweight group.
We found highly significant statistical differences between normal, overweight and obese groups using a large sample size with or without diet confounding factors. Our informative dataset sheds light on the epidemiological study on population microbiome.
The need for physical activity for health promotion is recognized, yet young adults still perform insufficient physical activity. Smartphone health programs can be applied easily without time and ...space constraints, and various mobile health programs based on smartphone applications have recently been developed and applied. This study aimed to measure the effects of mobile smartphone-based health programs on physical activity and obesity outcomes in young adults through a systematic review and meta-analysis. We searched publications in English through electronic databases up to May 2019. Studies were included that provided interventions to improve physical activity using smartphone applications for young adults. After assessing study quality, data were extracted and synthesized concerning whether smartphone interventions affect health outcomes including physical activity and weight using Meta-Analysis software. Four randomized controlled studies and a quasi-experimental study were analyzed. They provided information related to health management, diet, physical activity, and personalized feedback using smartphone applications. The meta-analysis showed that smartphone-based health interventions significantly affect weight loss and increase physical activity. This study provides modest evidence for using smartphone health programs to improve young adults' physical activity, weight control, and body mass index (BMI). Future research is needed to understand long-term effects and the reliability of increasing physical activity through smartphone health programs.
Although obesity is associated with numerous diseases, the risks of disease may depend on metabolic health. Associations between the gut microbiota, obesity, and metabolic syndrome have been ...reported, but differences in microbiomes according to metabolic health in the obese population have not been explored in previous studies. Here, we investigated the composition of gut microbiota according to metabolic health status in obese and overweight subjects. A total of 747 overweight or obese adults were categorized by metabolic health status, and their fecal microbiota were profiled using 16S ribosomal RNA gene sequencing. We classified these adults into a metabolically healthy group (MH, N = 317) without any components of metabolic syndrome or a metabolically unhealthy group (MU, N = 430) defined as having at least one metabolic abnormality. The phylogenetic and non-phylogenetic alpha diversity for gut microbiota were lower in the MU group than the MH group, and there were significant differences in gut microbiota bacterial composition between the two groups. We found that the genus Oscillospira and the family Coriobacteriaceae were associated with good metabolic health in the overweight and obese populations. This is the first report to describe gut microbial diversity and composition in metabolically healthy and unhealthy overweight and obese individuals. Modulation of the gut microbiome may help prevent metabolic abnormalities in the obese population.
Background and Aims
The effects of low‐level alcohol consumption on fatty liver disease and the potential for effect modification by obesity is uncertain. We investigated associations among low‐level ...alcohol consumption, obesity status, and the development of incident hepatic steatosis (HS), either with or without an increase in noninvasive liver fibrosis score category (from low to intermediate or high category).
Approach and Results
A total of 190,048 adults without HS and a low probability of fibrosis with alcohol consumption less than 30 g/day (men) and less than 20 g/day (women) were followed for up to 15.7 years. Alcohol categories of no, light, and moderate consumption were defined as 0, 1‐9.9, and 10‐29.9 g/day (10‐19.9 g/day for women), respectively. HS was diagnosed by ultrasonography, and the probability of fibrosis was estimated using the fibrosis‐4 index (FIB‐4). Parametric proportional hazards models were used to estimate multivariable‐adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). A total of 43,466 participants developed HS, 2,983 of whom developed HS with an increase in FIB‐4 index (to intermediate or high scores). Comparing light drinkers and moderate drinkers with nondrinkers, multivariable‐adjusted HRs (95% CI) for incident HS were 0.93 (0.90‐0.95) and 0.90 (0.87‐0.92), respectively. In contrast, comparing light drinkers and moderate drinkers with nondrinkers, multivariable‐adjusted HRs (95% CI) for developing HS plus intermediate/high FIB‐4 were 1.15 (1.04‐1.27) and 1.49 (1.33‐1.66), respectively. The association between alcohol consumption categories and incident HS plus intermediate/high FIB‐4 was observed in both nonobese and obese individuals, although the association was stronger in nonobese individuals (P for interaction by obesity = 0.017).
Conclusions
Light/moderate alcohol consumption has differential effects on the development of different stages of fatty liver disease, which is modified by the presence of obesity.
Several recent studies showed that next-generation sequencing (NGS)-based human leukocyte antigen (HLA) typing is a feasible and promising technique for variant calling of highly polymorphic regions. ...To date, however, no method with sufficient read depth has completely solved the allele phasing issue. In this study, we developed a new method (HLAscan) for HLA genotyping using NGS data.
HLAscan performs alignment of reads to HLA sequences from the international ImMunoGeneTics project/human leukocyte antigen (IMGT/HLA) database. The distribution of aligned reads was used to calculate a score function to determine correctly phased alleles by progressively removing false-positive alleles. Comparative HLA typing tests using public datasets from the 1000 Genomes Project and the International HapMap Project demonstrated that HLAscan could perform HLA typing more accurately than previously reported NGS-based methods such as HLAreporter and PHLAT. In addition, the results of HLA-A, -B, and -DRB1 typing by HLAscan using data generated by NextGen were identical to those obtained using a Sanger sequencing-based method. We also applied HLAscan to a family dataset with various coverage depths generated on the Illumina HiSeq X-TEN platform. HLAscan identified allele types of HLA-A, -B, -C, -DQB1, and -DRB1 with 100% accuracy for sequences at ≥ 90× depth, and the overall accuracy was 96.9%.
HLAscan, an alignment-based program that takes read distribution into account to determine true allele types, outperformed previously developed HLA typing tools. Therefore, HLAscan can be reliably applied for determination of HLA type across the whole-genome, exome, and target sequences.
Studies using salivary inflammatory biomarkers for diagnosing and monitoring the progression of periodontal disease have garnered increased attention in recent years. The present study aimed to ...identify changes in clinical parameters and concentrations of salivary matrix metalloproteinases (MMPs) following 6 weeks of non-surgical periodontal therapy (NSPT).
A 6-week NSPT program was applied to 51 adults aged ≥ 20 years. The program involved scaling, root planing, and professional toothbrushing for healthy participants and those with periodontal disease. Patients with periodontal disease underwent professional toothbrushing during all three visits. Periodontal pocket depth (PD) and gingival bleeding were assessed at week 0, week 3, and week 6, and saliva samples were collected to measure the concentrations of MMP-3, -8, and -9.
All clinical parameters were improved in the periodontal disease groups following the NSPT course. Compared with healthy participants, the patients with periodontal disease showed increased concentrations of salivary MMP-3, -8, and -9. During the 6-week program, patients with periodontal disease also showed significant reductions in PD and gingival bleeding during the third week; no significant reduction was found during the sixth week. Significant reductions in the concentrations of salivary MMP-3, -8, and -9 were also noted in the periodontal disease group at week 3. The sensitivity and specificity of MMP-3 for predicting periodontitis were 81.8% and 55.5%, respectively.
The present study found that NSPT resulted in reductions of salivary MMP-3, -8, and -9, and identified the potential of MMP-3 as a biomarker in the diagnosis of periodontal disease. These findings may serve as foundational data for future studies into the development of diagnostic kits for periodontal disease.
This study aimed to confirm the presence of gingival inflammation through image analysis of the papillary gingiva using intra-oral photographs (IOPs) before and after orthodontic treatment and to ...confirm the possibility of using gingival image analysis for gingivitis screening. Five hundred and eighty-eight (n = 588) gingival sites from the IOPs of 98 patients were included. Twenty-five participants who had completed their orthodontic treatments and were aged between 20 and 37 were included. Six points on the papillary gingiva were selected in the maxillary and mandibular anterior incisors. The red/green (R/G) ratio values were obtained for the selected gingival images and the modified gingival index (GI) was compared. The change in the R/G values during the orthodontic treatment period appeared in the order of before orthodontic treatment (BO), mid-point of orthodontic treatment (MO), three-quarters of the way through orthodontic treatment (TO), and immediately after debonding (IDO), confirming that it was similar to the change in the GI. The R/G value of the gingiva in the image correlated with the GI. Therefore, it could be used as a major index for gingivitis diagnosis using images.
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