Metformin promotes smear conversion in tuberculosis-diabetes comorbidity and construction of prediction models.

BACKGROUND: The comorbidity of tuberculosis (TB) and diabetes mellitus (DM) is a global health concern. Metformin is commonly used in DM but the potential effectiveness in comorbid patients is uncertain. This retrospective study aims to investigate the effect of metformin on TB-DM comorbidity and construct prediction models. METHODS: Patients diagnosed with TB-DM in West China Hospital were retrospectively enrolled from Nov 2013 to Sep 2019. Electronic health records of patients were extracted. Two-month smear conversion (2SC) was considered an outcome indicator of TB. Univariate and multivariate logistic regression (LR) were used to assess the role of metformin and other independent predictors. Meanwhile, prediction models were built by LR, elastic net regression, support vector machine, k-nearest neighbors, and random forest. RESULTS: A total of 927 individuals were recruited, among which 408 (44.01%) were metformin-exposed patients. A higher 2SC rate was observed in the metformin users. Other impact factors such as smoking, glucose, and creatinine levels were also identified. Multivariable models were then constructed using filtered variables. The support vector machine model yields the highest AUC (0.808, 95% CI: 0.767-0.849) and specificity (83.24%). LR model outperformed others in terms of sensitivity (69.71%). CONCLUSION: This retrospective study of a large population from southwestern China provides strong clinical evidence for the positive effects of metformin in TB-DM. Metformin is associated with a better therapeutic outcome and promising for the adjuvant therapy of TB-DM. Furthermore, a combination of support vector machine and LR models is recommended to discriminate the patients with poor treatment outcomes.

Collagen type XVIII alpha 1 chain (COL18A1) variants affect the risk of anti-tuberculosis drug-induced hepatotoxicity: A prospective study.

BACKGROUND: The role of collagen type XVIII alpha 1 chain (COL18A1) in anti-tuberculosis drug-induced hepatotoxicity (ATDH) has not been reported. This study aimed to explore the association between of COL18A1 variants and ATDH susceptibility. METHODS: A total of 746 patients were enrolled in our study from December 2016 to April 2018, and all subjects in the study signed an informed consent form. The custom-by-design 2x48-Plex SNPscanTM kit was used to genotype all selected 11 SNPs. Categorical variables were compared by chi-square (χ2 ) or Fisher's exact test, while continuous variables were compared by Mann-Whitney's U test. Plink was utilized to analyze allelic and genotypic frequencies, and genetic models. Multivariate logistic regression analyses were used to adjust potential factors. The odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were also calculated. RESULTS: Among patients with successfully genotyping, there were 114 cases and 612 controls. The mutant A allele of rs12483377 conferred the decreased risk of ATDH (OR = 0.13, 95%CI: 0.02-0.98, P = 0.020), and this significance still existed after adjusting age and gender (P = 0.024). The mutant homozygote AA genotype of rs12483377 was associated with decreased total protein levels (P = 0.018). CONCLUSION: Our study first revealed that the A allele of COL18A1 rs12483377 was associated with the decreased risk of ATDH in the Western Chinese Han population, providing new perspective for the molecular prediction, precise diagnosis, and individual treatment of ATDH.

Large-scale analysis reveals splicing biomarkers for tuberculosis progression and prognosis.

BACKGROUND: Emerging evidence suggests that aberrant alternative splicing (AS) may play an important role in tuberculosis (TB). However, current knowledge regarding the value of AS in TB progression and prognosis remains unclear. METHOD: Public RNA-seq datasets related to TB progression and prognosis were searched and AS analyses were conducted based on SUPPA2. Percent spliced in (PSI) was used for quantifying AS events and multiple machine learning (ML) methods were employed to construct predictive models. Area under curve (AUC), sensitivity and specificity were calculated to evaluate the model performance. RESULTS: A total of 1587 samples from 7 datasets were included. Among 923 TB-progression related differential AS events (DASEs), 3 events (GET1-skipping exon (SE), TPD52-alternative first exons (AF) and TIMM10-alternative 5' splice site (A5)) were selected as candidate biomarkers; however, their predictive performance was limited. For TB prognosis, 5 events (PHF23-AF, KIF1B-SE, MACROD2-alternative 3' splice site (A3), CD55-retained intron (RI) and GALNT11-AF) were selected as candidates from the 1282 DASEs. Six ML methods were used to integrate these 5 events and XGBoost outperformed than others. AUC, sensitivity and specificity of XGBoost model were 0.875, 81.1% and 83.5% in training set, while they were 0.805, 68.4% and 73.2% in test set. CONCLUSION: GET1-SE, TPD52-AF and TIMM10-A5 showed limited role in predicting TB progression, while PHF23-AF, KIF1B-SE, MACROD2-A3, CD55-RI and GALNT11-AF could well predict TB prognosis and work as candidate biomarkers. This work preliminarily explored the value of AS in predicting TB progression and prognosis and offered potential targets for further research.

Single-Cell Sequencing Reveals Functional Alterations in Tuberculosis.

Despite its importance, the functional heterogeneity surrounding the dynamics of interactions between mycobacterium tuberculosis and human immune cells in determining host immune strength and tuberculosis (TB) outcomes, remains far from understood. This work now describes the development of a new technological platform to elucidate the immune function differences in individuals with TB, integrating single-cell RNA sequencing and cell surface antibody sequencing to provide both genomic and phenotypic information from the same samples. Single-cell analysis of 23 990 peripheral blood mononuclear cells from a new cohort of primary TB patients and healthy controls enables to not only show four distinct immune phenotypes (TB, myeloid, and natural killer (NK) cells), but also determine the dynamic changes in cell population abundance, gene expression, developmental trajectory, transcriptomic regulation, and cell-cell signaling. In doing so, TB-related changes in immune cell functions demonstrate that the immune response is mediated through host T cells, myeloid cells, and NK cells, with TB patients showing decreased naive, cytotoxicity, and memory functions of T cells, rather than their immunoregulatory function. The platform also has the potential to identify new targets for immunotherapeutic treatment strategies to restore T cells from dysfunctional or exhausted states.

Association of Minimal Residual Disease by a Single-Tube 8-Color Flow Cytometric Analysis With Clinical Outcome in Adult B-Cell Acute Lymphoblastic Leukemia: A Real-World Study Based on 486 Patients.

CONTEXT.­: Minimal/measurable residual disease (MRD) measured by molecular and multiparametric flow cytometry (MFC) has been proven to be predictive of relapse and survival in patients with B-cell acute lymphoblastic leukemia (B-ALL). A universally applicable antibody panel at a low cost but without compromising sensitivity and power of prognosis prediction in adult B-ALL remains unestablished. OBJECTIVE.­: To report our experience of using a single-tube 8-color MFC panel to measure the MRD status as a prognostic indicator in adult B-ALL patients. DESIGN.­: We retrospectively analyzed the characteristics, MRD status, and prognosis of adult B-ALL based on a large real-world cohort of 486 patients during a 10-year period. RESULTS.­: MRD assessed by MFC and polymerase chain reaction (PCR) assays for BCR-ABL+ patients showed concordant results in 74.2% of cases. MRD- status by our MFC panel could clearly predict a favorable relapse-free survival (RFS) and overall survival (OS) both at the end of induction and at the end of 1 consolidation course. Patients with continuous MRD- and with at least 1 MRD- result showed a favorable RFS and OS compared with those with at least 1 MRD+ result and continuous MRD+, respectively. CONCLUSIONS.­: The single-tube 8-color MFC panel demonstrated a low cost, decent sensitivity, and comparability with polymerase chain reaction-MRD but an excellent performance in predicting RFS and OS, and thus could potentially be taken as a routine indicator in the evaluation of the treatment response for adult patients with B-ALL.

Prognostic value of cross-lineage expression of the myeloid-associated antigens CD13 and CD33 in adult B-lymphoblastic leukemia: A large real-world study of 1005 patients.

BACKGROUND: Cross-lineage expression of the myeloid-associated antigens CD13/CD33 is common in adult B-lymphoblastic leukemia (B-ALL) patients, yet its prognostic value is still controversial. METHODS: We conducted a retrospective study of 1005 de novo adult B-ALL patients from January 2009 to December 2019 in our hospital. Logistic and Cox regression were used to analyze the prognostic value of CD13/CD33 expression in B-ALL. A Cox regression model was established to predict overall survival (OS) for B-ALL patients. RESULTS: Of the 1005 B-ALL patients, 53.7% (n = 540) aberrantly expressed CD13/CD33 (CD13/CD33+ ). Patients in the CD13/CD33+ group showed a higher incidence of BCR::ABL1 rearrangement and minimal/measurable residual disease (MRD) positivity but similar complete remission rate, relapse-free survival, mortality, and OS with CD13/CD33- . CD13/CD33+ patients had a higher risk of MRD positivity than CD13/CD33- patients. Notably, CD13/CD33+ patients who underwent tyrosine kinase inhibitor (TKI) therapy had a better long-term prognosis than those without TKI experience. Sex, group based on CD13/CD33 expression and TKI experience and white blood cell count were variables independently associated with OS. The Cox regression model integrating these three variables showed a moderate performance for OS prediction (C-index: 0.724). CONCLUSIONS: In real-world practice, CD13/CD33 expression can predict the risk of MRD in patients without TKI experience, but has no adverse effect on the prognosis of adult B-ALL patients. Incorporating CD13/CD33 into the standard antibody panels of B-ALL diagnosis and MRD measurements can help predict relapse risk and decisions on therapy options.

Roles of alternative splicing in infectious diseases: from hosts, pathogens to their interactions.

ABSTRACT: Alternative splicing (AS) is an evolutionarily conserved mechanism that removes introns and ligates exons to generate mature messenger RNAs (mRNAs), extremely improving the richness of transcriptome and proteome. Both mammal hosts and pathogens require AS to maintain their life activities, and inherent physiological heterogeneity between mammals and pathogens makes them adopt different ways to perform AS. Mammals and fungi conduct a two-step transesterification reaction by spliceosomes to splice each individual mRNA (named cis -splicing). Parasites also use spliceosomes to splice, but this splicing can occur among different mRNAs (named trans -splicing). Bacteria and viruses directly hijack the host's splicing machinery to accomplish this process. Infection-related changes are reflected in the spliceosome behaviors and the characteristics of various splicing regulators (abundance, modification, distribution, movement speed, and conformation), which further radiate to alterations in the global splicing profiles. Genes with splicing changes are enriched in immune-, growth-, or metabolism-related pathways, highlighting approaches through which hosts crosstalk with pathogens. Based on these infection-specific regulators or AS events, several targeted agents have been developed to fight against pathogens. Here, we summarized recent findings in the field of infection-related splicing, including splicing mechanisms of pathogens and hosts, splicing regulation and aberrant AS events, as well as emerging targeted drugs. We aimed to systemically decode host-pathogen interactions from a perspective of splicing. We further discussed the current strategies of drug development, detection methods, analysis algorithms, and database construction, facilitating the annotation of infection-related splicing and the integration of AS with disease phenotype.

From tuberculosis bedside to bench: UBE2B splicing as a potential biomarker and its regulatory mechanism.

Alternative splicing (AS) is an important approach for pathogens and hosts to remodel transcriptome. However, tuberculosis (TB)-related AS has not been sufficiently explored. Here we presented the first landscape of TB-related AS by long-read sequencing, and screened four AS events (S100A8-intron1-retention intron, RPS20-exon1-alternaitve promoter, KIF13B-exon4-skipping exon (SE) and UBE2B-exon7-SE) as potential biomarkers in an in-house cohort-1. The validations in an in-house cohort-2 (2274 samples) and public datasets (1557 samples) indicated that the latter three AS events are potential promising biomarkers for TB diagnosis, but not for TB progression and prognosis. The excellent performance of classifiers further underscored the diagnostic value of these three biomarkers. Subgroup analyses indicated that UBE2B-exon7-SE splicing was not affected by confounding factors and thus had relatively stable performance. The splicing of UBE2B-exon7-SE can be changed by heat-killed mycobacterium tuberculosis through inhibiting SRSF1 expression. After heat-killed mycobacterium tuberculosis stimulation, 231 ubiquitination proteins in macrophages were differentially expressed, and most of them are apoptosis-related proteins. Taken together, we depicted a global TB-associated splicing profile, developed TB-related AS biomarkers, demonstrated an optimal application scope of target biomarkers and preliminarily elucidated mycobacterium tuberculosis-host interaction from the perspective of splicing, offering a novel insight into the pathophysiology of TB.

Deciphering a TB-related DNA methylation biomarker and constructing a TB diagnostic classifier.

We systemically identified tuberculosis (TB)-related DNA methylation biomarkers and further constructed classifiers for TB diagnosis. TB-related DNA methylation datasets were searched through October 3, 2020. Limma and DMRcate were employed to identify differentially methylated probes (DMPs) and regions (DMRs). Machine learning methods were used to construct classifiers. The performance of the classifiers was evaluated in discovery datasets and a prospective independent cohort. Eighty-nine DMPs and 24 DMRs were identified based on 67 TB patients and 45 healthy controls from 4 datasets. Nine and three DMRs were selected by elastic net regression and logistic regression, respectively. Among the selected DMRs, two regions (chr3: 195635643-195636243 and chr6: 29691631-29692475) were differentially methylated in the independent cohort (p = 4.19 × 10-5 and 0.024, respectively). Among the ten classifiers, the 3-DMR logistic regression classifier exhibited the strongest performance. The sensitivity, specificity, and area under the curve were, respectively, 79.1%, 84.4%, and 0.888 in the discovery datasets and 64.5%, 90.3%, and 0.838 in the independent cohort. The differential diagnostic ability of this classifier was also assessed. Collectively, these data showed that DNA methylation might be a promising TB diagnostic biomarker. The 3-DMR logistic regression classifier is a potential clinical tool for TB diagnosis, and further validation is needed.

Exploring the eligibility of all reported lipoarabinomannan-testing assays in different clinical situations: a systematic review and meta-analysis of 97 articles.

OBJECTIVES: How to choose proper lipoarabinomannan-testing assays for diagnosing tuberculosis (TB) in different populations baffles clinicians. This work assessed all reported lipoarabinomannan assays' performance and aimed to identify the eligibility of each assay and offer guidance for clinicians. METHODS: We searched PubMed, Embase, and Web of Science until August 23, 2020. The risk of bias was evaluated by QADAS-2. Heterogeneity was evaluated by the Cochran Q test and I2. Sensitivity and specificity were pooled by a bivariate mixed model (register number: CRD42021270506). RESULTS: A total of 97 articles, covering 144 trials, 16 assays, 45,679 participants, and eight sample types, were divided into five groups. Electrochemiluminescence (ECL) had a sensitivity of 65%, specificity of 92%, and an area under curve (AUC) of 0.85 in diagnosing pulmonary TB in adults. ECL showed a promising diagnostic ability (sensitivity: 78%; specificity: 88%; AUC: 0.88) in patients with HIV, especially for urine detection (sensitivity: 90%; specificity: 89%; AUC: 0.95). The enzyme-linked immune assay showed a preference for diagnosing TB in Asians and Africans, especially in Africans who were smear-positive (sensitivity: 80%; specificity: 88%; AUC: 0.91). CONCLUSION: ECL was recommended for diagnosing pulmonary TB in adults, especially for TB/HIV co-infection. Taking urine as a sample further enhanced ECL's diagnostic performance. Enzyme-linked immune assay was recommended as an additional TB-related detection for smear-positive Africans.