Resynchronized rhythmic oscillations of gut microbiota drive time-restricted feeding induced nonalcoholic steatohepatitis alleviation.

With the drive of the endogenous circadian clock and external cues such as feeding behavior, the microbial community generates rhythmic oscillations in composition and function. Microbial oscillations are crucial in orchestrating host metabolic homeostasis during the predictable 24-hour diurnal cycle. A time-restricted feeding (TRF) regimen is a promising dietary strategy to optimize energy utilization, alleviate metabolic syndrome and reinforce microbial cyclical fluctuations. However, the causative relationship between reinforced microbial rhythmicity and TRF-induced metabolic improvement remains elusive. In this study, we corroborated that the TRF regimen notably alleviated obesity and nonalcoholic steatohepatitis (NASH) with reinstated rhythmicity of genera such as Lactobacillus, Mucispirillum, Acetatifactor, and Lachnoclostridium. The reshaped microbial oscillations correlate with cyclical fluctuations in intestinal amino acids. Furthermore, fecal microbiota transplantation (FMT) indicated that only the TRF feeding phase-derived microbiota, but not the TRF fasting phase-derived microbiota, could protect mice from NASH and reinstate microbial rhythmicity, confirming that the microbiota improved NASH in a time-of-day-specific manner. The unique role of the TRF-feeding phase-derived microbiota was accompanied by regulation of the serotonergic synapse pathway and rejuvenation of the microbial production of indole derivatives. Our results revealed the discrepant characteristics between the feeding and fasting phases and the time-of-day-specific configuration of microbiota functionality in the TRF regimen.

Randomized control study of the use of faropenem for treating patients with pulmonary tuberculosis.

OBJECTIVES: Faropenem has antituberculosis activity in vitro but its utility in treating patients with tuberculosis (TB) is unclear. METHODS: We conducted an open-label, randomized trial in China, involving newly diagnosed, drug-susceptible pulmonary TB. The control group was treated with the standard 6-month regimen. The experimental group replaced ethambutol with faropenem for 2 months. The primary outcome was the treatment success rate after 6 months of treatment. Noninferiority was confirmed if the lower limit of a 95% one-sided confidence interval (CI) of the difference was greater than -10%. RESULTS: A total of 227 patients eligible for the study were enrolled in the trial group and the control group in a ratio of 1:1. Baseline characteristics of participants were similar in both groups. In the modified intention-to-treat population, 88.18% of patients in the faropenem group achieved treatment success, and 85.98% of those in the control group were successfully treated, with a difference of 2.2% (95% CI, -6.73-11.13). In the per-protocol population, treatment success was 96.04% in the faropenem group and 95.83% in the control group, with a difference of 2.1% (95% CI, -5.31-5.72). The faropenem group showed noninferiority to the control group in the 6-month treatment success rates. The faropenem group had significantly fewer adverse events (P <0.01). CONCLUSIONS: Our study proved that oral faropenem regimen can be used for the treatment of TB, with fewer adverse events. (Chinese Clinical Trial Registry, ChiCTR1800015959).

CoNet: Efficient Network Regression for Survival Analysis in Transcriptome-Wide Association Studies-With Applications to Studies of Breast Cancer.

Transcriptome-wide association studies (TWASs) aim to detect associations between genetically predicted gene expression and complex diseases or traits through integrating genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) mapping studies. Most current TWAS methods analyze one gene at a time, ignoring the correlations between multiple genes. Few of the existing TWAS methods focus on survival outcomes. Here, we propose a novel method, namely a COx proportional hazards model for NEtwork regression in TWAS (CoNet), that is applicable for identifying the association between one given network and the survival time. CoNet considers the general relationship among the predicted gene expression as edges of the network and quantifies it through pointwise mutual information (PMI), which is under a two-stage TWAS. Extensive simulation studies illustrate that CoNet can not only achieve type I error calibration control in testing both the node effect and edge effect, but it can also gain more power compared with currently available methods. In addition, it demonstrates superior performance in real data application, namely utilizing the breast cancer survival data of UK Biobank. CoNet effectively accounts for network structure and can simultaneously identify the potential effecting nodes and edges that are related to survival outcomes in TWAS.

Network regression analysis for binary and ordinal categorical phenotypes in transcriptome-wide association studies.

Transcriptome-wide association studies aim to integrate genome-wide association studies and expression quantitative trait loci mapping studies for exploring the gene regulatory mechanisms underlying diseases. Existing transcriptome-wide association study methods primarily focus on 1 gene at a time. However, complex diseases are seldom resulted from the abnormality of a single gene, but from the biological network involving multiple genes. In addition, binary or ordinal categorical phenotypes are commonly encountered in biomedicine. We develop a proportional odds logistic model for network regression in transcriptome-wide association study, Proportional Odds LOgistic model for NEtwork regression in Transcriptome-wide association study, to detect the association between a network and binary or ordinal categorical phenotype. Proportional Odds LOgistic model for NEtwork regression in Transcriptome-wide association study relies on 2-stage transcriptome-wide association study framework. It first adopts the distribution-robust nonparametric Dirichlet process regression model in expression quantitative trait loci study to obtain the SNP effect estimate on each gene within the network. Then, Proportional Odds LOgistic model for NEtwork regression in Transcriptome-wide association study uses pointwise mutual information to represent the general relationship among the network nodes of predicted gene expression in genome-wide association study, followed by the association analysis with all nodes and edges involved in proportional odds logistic model. A key feature of Proportional Odds LOgistic model for NEtwork regression in Transcriptome-wide association study is its ability to simultaneously identify the disease-related network nodes or edges. With extensive realistic simulations including those under various between-node correlation patterns, we show Proportional Odds LOgistic model for NEtwork regression in Transcriptome-wide association study can provide calibrated type I error control and yield higher power than other existing methods. We finally apply Proportional Odds LOgistic model for NEtwork regression in Transcriptome-wide association study to analyze bipolar and major depression status and blood pressure from UK Biobank to illustrate its benefits in real data analysis.

Network regression analysis in transcriptome-wide association studies.

BACKGROUND: Transcriptome-wide association studies (TWASs) have shown great promise in interpreting the findings from genome-wide association studies (GWASs) and exploring the disease mechanisms, by integrating GWAS and eQTL mapping studies. Almost all TWAS methods only focus on one gene at a time, with exception of only two published multiple-gene methods nevertheless failing to account for the inter-dependence as well as the network structure among multiple genes, which may lead to power loss in TWAS analysis as complex disease often owe to multiple genes that interact with each other as a biological network. We therefore developed a Network Regression method in a two-stage TWAS framework (NeRiT) to detect whether a given network is associated with the traits of interest. NeRiT adopts the flexible Bayesian Dirichlet process regression to obtain the gene expression prediction weights in the first stage, uses pointwise mutual information to represent the general between-node correlation in the second stage and can effectively take the network structure among different gene nodes into account. RESULTS: Comprehensive and realistic simulations indicated NeRiT had calibrated type I error control for testing both the node effect and edge effect, and yields higher power than the existed methods, especially in testing the edge effect. The results were consistent regardless of the GWAS sample size, the gene expression prediction model in the first step of TWAS, the network structure as well as the correlation pattern among different gene nodes. Real data applications through analyzing systolic blood pressure and diastolic blood pressure from UK Biobank showed that NeRiT can simultaneously identify the trait-related nodes as well as the trait-related edges. CONCLUSIONS: NeRiT is a powerful and efficient network regression method in TWAS.

Population-based active screening strategy contributes to the prevention and control of tuberculosis.

Despite the achievements obtained worldwide in the control of tuberculosis in recent years, many countries and regions including China still face challenges such as low diagnosis rate, high missed diagnosis rate, and delayed diagnosis of the disease. The discovery strategy of tuberculosis in China has changed from "active discovery by X-ray examination" to "passive discovery by self-referral due to symptoms", and currently the approach is integrated involving self-referral due to symptoms, active screening, and physical examination. Active screening could help to identify early asymptomatic and untreated cases. With the development of molecular biology and artificial intelligence-assisted diagnosis technology, there are more options for active screening among the large-scale populations. Although the implementation cost of a population-based active screening strategy is high, it has great value in social benefits, and active screening in special populations can obtain better benefits. Active screening of tuberculosis is an important component of the disease control. It is suggested that active screening strategies should be optimized according to the specific conditions of the regions to ultimately ensure the benefit of the tuberculosis control.

Restricted TcR ß chain CDR3 clonotype is associated with resolved acute hepatitis B subjects.

BACKGROUND: T cells play an important role in the prognosis of hepatitis B virus (HBV) infection, and are involved in the seroconversion of a patient from HBsAb negative to positive. To compare the T-cell receptor ß-chain variable region (TcRBV) complementarity-determining region 3 (CDR3) in subjects with or without hepatitis B surface antigen (HBsAg) convert to hepatitis B surface antibody (HBsAb), the TcRBV was determined using high throughput sequencing (HTS). METHODS: The clonotype and diversity of CDR3 in peripheral blood mononuclear cells of subjects with resolved acute hepatitis B (AHB, HBsAb+, HBsAg-) (n = 5), chronic hepatitis B (CHB, HBsAb-, HBsAg+) (n = 5), and healthy controls (HC, HBsAb-, HBsAg-) (n = 3) were determined and analyzed using HTS (MiSeq). RESULTS: The overlapping rate of CDR3 clones of any two samples in AHB group was 2.00% (1.74% ~ 2.30%), CHB group was 1.77% (1.43% ~ 2.61%), and HC group was 1.82% (1.62% ~ 2.12%), and there was no significant difference among the three groups by Kruskal-Wallis H test. However, among the top 10 cumulative frequencies of clonotypes, only the frequency of clonotype (TcRBV20-1/BD1/BJ1-2) in AHB group was lower than that of HC group (P < 0.001). Moreover, exclude the 10 top clonotypes, there are 57 markedly different frequency of clones between AHB and CHB groups (18 clones up, 39 clones down), 179 (180-1) different clones between AHB and HC groups, and 134 different clones between CHB and HC groups. With regard to BV and BJ genotypes, there was no significant different frequency among the groups. Furthermore, there was no significant difference in the diversity of TcRBV CDR3 among the three groups (P > 0.05). CONCLUSIONS: Thus, there are 57 TcRBV clonotypes that may be related to HBsAg seroconversion of AHB subjects, but the diversity of TcRBV CDR3 is not significantly related to the HBsAb positive status.

Altered faecal microbiota on the expression of Th cells responses in the exacerbation of patients with hepatitis E infection.

Fulminant hepatitis E may lead to acute liver failure (ALF). Perturbations of intestinal microbiota are related to severe liver disease. To study the correlations between faecal microbiota and the occurrence and exacerbation of hepatitis E virus (HEV) infection, we characterized 24 faecal samples from 12 patients with acute hepatitis E (AHE) and 12 patients with HEV-ALF using high-throughput sequencing. We found both the alpha and beta diversity indices showed no significant differences between the AHE and HEV-ALF groups. Several predominant taxa were significantly different between the AHE and HEV-ALF groups. Most notably, the HEV-ALF group had increased levels of Gammaproteobacteria, Proteobacteria, Xanthomonadceae and Stenotrophomonas, but reduced levels of Firmicutes, Streptococcus, Subdoligranulum and Lactobacillus, compared with the AHE group. The levels of Lactobacillaceae and Gammaproteobacteria could be used to distinguish patients with HEV-ALF from those with AHE. In addition, the level of Th lymphocytes was significantly lower in the HEV-ALF group than in the AHE group. The relative abundances of Lactobacillaceae and Gammaproteobacteria were positively correlated with Th lymphocytes, serum international normalized ratio (INR) and hepatic encephalopathy severity. Moreover, surviving patients had higher levels of Lactobacillus mucosae than deceased patients. Our study demonstrated that the presence of altered faecal microbiota is associated with exacerbation of HEV infection; this finding may be useful for exploring the interactions among faecal microbiota, immune responses, mechanisms of infection and progression in patients with HEV, as well as for the development of novel diagnostic and therapeutic strategies.

Seroprevalence of AIH-related autoantibodies in patients with acute hepatitis E viral infection: a prospective case-control study in China.

The seroprevalenc of autoimmune hepatitis (AIH)-related antibodies in patients, particularly Asians, with acute hepatitis E (AHE) is unclear. In this study, we investigated whether acute hepatitis E virus (HEV) infection is associated with the seroprevalence of AIH-related autoantibodies and assessed their impact on the disease characteristics. AIH-related autoantibodies were detected by indirect immunofluorescence in 198 AHE patients and 50 type 1 AIH patients. The positivity rates of against nuclear antigen (ANA) and smooth muscles antibody (SMA) in AHE patients were 37.4% and 22.7%, and the total positivity rate was 50%. Compared to those in AIH patients, the positivity rates of ANA-H and SMA-AA were significantly lower (35.1% vs. 82.1% and 4.4% vs. 88.4%). Female gender and the ALT level, but not immunosuppressive or antiviral drugs, were independently predictive of the presence of AIH-related autoantibodies in AHE patients. Fifty-two patients positive for AIH-related autoantibodies were followed up for 12 months. During this period, 33 of them became negative and 19 remained positive, albeit with significantly decreased titres. In conclusions, the seroprevalence of AIH-related autoantibodies in AHE patients was elevated, particularly in females, but their subspecificities and titres differed from those of type 1 AIH. Acute HEV infection may be related to AIH.Abbreviations: AIH: autoimmune hepatitis; AHE: acute hepatitis E; ANA: against nuclear antigen; SMA: smooth muscles antibody; ANA-H: ANA with homogeneous pattern; SMA-AA: SMA with anti-actin pattern; Anti-LKM1: anti- liver-kidney microsomes-1 antibody; ANCA: anti-neutrophil cytoplasmic antibody; AMA: anti-mitochondrial antibody; Anti-SLA: anti-soluble liver antigen; Anti-LC1: anti-liver cytoplasmic type 1 antibody; pANCA: perinuclear antineutrophil cytoplasmic antibody.

Multicenter evaluation of the biochip assay for rapid detection of mycobacterial isolates in smear-positive specimens.

OBJECTIVES: The objective of this study was to conduct a multicentre evaluation of the performance of the biochip assay in the rapid identification of mycobacteria in smear-positive sputum specimens. METHODS: A total of 1751 sputum specimens were obtained from 7 cities in Zhejiang, China. All of the specimens were used for the discrimination of Mycobacterium species using the biochip assay, and the results were compared to the golden standard method of culture, hsp65, 16S rRNA and rpoB sequence analysis. RESULTS: In the 1751 sputum specimens, 1685 samples were cultured successfully; among these samples, 1361 were Mycobacterium tuberculosis, 323 were NTM and 1 was Nocadia farcinica. Of the 323 NTM, most of them were Mycobacterium intracellulare(52.5%) followed by Mycobacterium abscessus (20.7%), Mycobacterium avium (11.7%), Mycobacterium kansasii (9.6%) and Mycobacterium fortuitum (1.9%). The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the biochip assay to differentiate TB and NTM from AFB positive specimens were 99.8%, 99.7%, 99.9%, 99.1%, 98.8%, 1, 1, and 99.7%, respectively. The concordance between the biochip assay and mycobacterial culture for the identification of NTM species was 95.4%. CONCLUSIONS: The biochip assay is a reliable tool for the rapid identification of most mycobacteria in clinical sputum specimens. This assay can be helpful for physicians in the early diagnosis and treatment of mycobacterium infections.

Performance of Biochip system in detecting drug resistant and multidrug-resistant tuberculosis using sputum collected from multiple clinical settings in Zhejiang, China.

The objective of the present study was to conduct a multicentre, prospective evaluation of the diagnostic performance of the Biochip system for the detection of drug-resistant tuberculosis using smear-positive sputum specimens. This prospective study evaluated the diagnostic performance of this new platform for drug resistant and multidrug-resistant tuberculosis (MDR-TB) using 1491 smear-positive sputum specimens collected from multiple clinical settings. Using conventional culture-based culturing and drug-susceptibility testing as reference standards, the biochip system had a sensitivity of 86.08% and a specificity of 97.7% for rifampicin (RIF) detection, in detecting isoniazid (INH) resistance, it had a sensitivity of 79.36% and a specificity of 98.71%. With respect to MDR-TB detection, the sensitivity was 78.01% and the specificity was 98.86%. The performance only varies among different sites for RIF resistance, and there are no other statistically difference in diagnostic performance for other variables considered. The Biochip system shows favourable sensitivity and specificity for RIF and INH resistance, along with MDR-TB detection, directly using clinical smear-positive sputum samples. It is an alternative to conventional drug-susceptibility testing (DST) for detecting drug resistance or MDR-TB and is a method worth expanding to clinical settings in China.