Population Pharmacokinetic Modeling of Bedaquiline among Multidrug-Resistant Pulmonary Tuberculosis Patients from China.

Bedaquiline has been widely used as a part of combination dosage regimens for the treatment of multidrug-resistant tuberculosis (MDR-TB) patients with limited options. Although the effectiveness and safety of bedaquiline have been demonstrated in clinical trials, limited studies have investigated the significant pharmacokinetics and the impact of genotype on bedaquiline disposition. Here, we developed a population pharmacokinetic model of bedaquiline to describe the concentration-time data from Chinese adult patients diagnosed with MDR-TB. A total of 246 observations were collected from 99 subjects receiving the standard recommended dosage. Bedaquiline disposition was well described by a one-compartment model with first-order absorption. Covariate modeling identified that gamma-glutamyl transferase (GGT) and the single-nucleotide polymorphism (SNP) rs319952 in the AGBL4 gene were significantly associated with the apparent clearance of bedaquiline. The clearance (CL/F) was found to be 1.4 L/h lower for subjects with allele GG in SNP rs319952 than for subjects with alleles AG and AA and to decrease by 30% with a doubling in GGT. The model-based simulations were designed to assess the impact of GGT/SNP rs319952 on bedaquiline exposure and showed that patients with genotype GG in SNP rs319952 and GGT ranging from 10 to 50 U/L achieved the targeted maximum serum concentration at steady state (Cmax,ss). However, when GGT was increased to 100 U/L, Cmax,ss was 1.68-fold higher than the highest concentration pursued. The model developed provides the consideration of genetic polymorphism and hepatic function for bedaquiline dosage in MDR-TB adult patients.

Discovering novel biomarkers for diagnosis and treatment monitoring of active pulmonary tuberculosis by ion metabolism analysis.

Tuberculosis (TB) is a highly lethal infectious disease that poses a global threat. Timely and accurate biomarker for TB diagnosis and treatment monitoring remains a pressing need. Ions, the crucial trace element for humans, may be potential targets for TB diagnosis and the forecasting of TB development. To explore the potential of ions as biomarkers, we measured and compared the levels of various ions in whole blood and plasma samples from healthy control (HC), pulmonary TB patients (TB), cured pulmonary TB patients (RxTB), and other non-TB pneumonia patients (PN) by using ultra-high performance liquid chromatography-tandem mass spectrometry. Our study demonstrated that Cu (AUC = 0.670), Pb (AUC = 0.660), and Zn (AUC = 0.701) in whole blood exhibited promising diagnostic performance for TB. Then we used a neural network (NNET) for TB prediction, the AUC values used to differentiate definite TB from HC or PN in plasma were 0.867 and 0.864, respectively. The AUC values used to differentiate definite TB from HC or PN in whole blood were 0.818 and 0.660, respectively. Our correlation analysis showed that Zn (r= 0.356, p=0.001) and Cu (r= 0.361, p=0.0004) in plasma are most closely related to disease severity. Additionally, six ions (Cu, Sb, V, Mn, Fe, Sr) in plasma and whole blood were altered following anti-TB therapy. These results showed that ions could be diagnostic biomarkers for TB. Furthermore, the level of particular ions can forecast the degree of lung damage and the success of the TB treatment. In conclusion, this study highlights the possibility of using ions from blood samples to enable rapid tuberculosis diagnosis.

Amino acid profiling as a screening and prognostic biomarker in active tuberculosis patients.

BACKGROUND: Tuberculosis (TB) is one of the world's most deadly chronic infectious diseases; early diagnosis contributes to reducing disease transmission among populations. However, discovering novel diagnostic and prognostic biomarkers is still an important topic in the field of TB. Amino acid is the basic unit of protein composition, and its structure and physicochemical characteristics are more stable. Therefore, it is a potential target for TB diagnosis and the prediction of TB development. METHODS: In this study, the blood of healthy people (HC), TB patients (TB), cured TB (RxTB), and other non-TB pneumonia patients (PN) were collected to detect the levels of amino acids in whole blood and plasma using ultra-high performance liquid chromatography coupled with mass spectrometry. RESULTS: We detected that the amino acid levels correlated with participants status (TB, HC, RxTB, or PN) and the degree of lung damage. The results showed that phenylalanine had a good effect on the screening of TB (AUC = 0.924). We then built a TB prediction model. The model, which was based on the ratio of plasma amino acid content to whole blood amino acid content, showed good performance for the screening of TB, with 84% (95% CI = 60-97) sensitivity and 97% (95% CI = 83-100) specificity. The result of correlation between the HRCT score and amino acid level indicated that the glutamine content of plasma was significantly inversely associated with disease severity. Additionally, ornithine levels in the plasma of RxTB group reduced and four amino acids of which the ratio in plasma to whole blood showed significantly changed. CONCLUSIONS: Taken together, amino acid profiling can be used for TB screening, and a multiparameter profiling model is better. The profiling can also reflect the severity of lung damage. Moreover, the amino acid profile is useful for reflecting the efficacy of TB treatment.

Sex differences in the oral microbiome, host traits, and their causal relationships.

The oral microbiome has been implicated in a growing number of diseases; however, determinants of the oral microbiome and their roles remain elusive. Here, we investigated the oral (saliva and tongue dorsum) metagenome, the whole genome, and other omics data in a total of 4,478 individuals and demonstrated that the oral microbiome composition and its major contributing host factors significantly differed between sexes. We thus conducted a sex-stratified metagenome-genome-wide-association study (M-GWAS) and identified 11 differential genetic associations with the oral microbiome (p sex-difference  < 5 × 10-8). Furthermore, we performed sex-stratified Mendelian randomization (MR) analyses and identified abundant causalities between the oral microbiome and serum metabolites. Notably, sex-specific microbes-hormonal interactions explained the mostly observed sex hormones differences such as the significant causalities enrichments for aldosterone in females and androstenedione in males. These findings illustrate the necessity of sex stratification and deepen our understanding of the interplay between the oral microbiome and serum metabolites.

Life History Recorded in the Vagino-cervical Microbiome Along with Multi-omes.

The vagina contains at least a billion microbial cells, dominated by lactobacilli. Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age, as well as cervical, fecal, and salivary samples from a second cohort of 632 women. Factors such as pregnancyhistory, delivery history, cesarean section, and breastfeeding were all more important than menstrual cycle in shaping the microbiome, and such information would be necessary before trying to interpret differences between vagino-cervical microbiome data. Greater proportion of Bifidobacterium breve was seen with older age at sexual debut. The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history. Potential markers for lack of menstrual regularity, heavy flow, dysmenorrhea, and contraceptives were also identified. Lactobacilli were rare during breastfeeding or post-menopause. Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome. Gut and salivary microbiomes, plasma vitamins, metals, amino acids, and hormones showed associations with the vagino-cervical microbiome. Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth.