Advancing personalized medicine for tuberculosis through the application of immune profiling

Quantitative and Longitudinal Assessment of Systemic Innate Immunity in Health and Disease Using a 2D Gene Model

Dysregulation of innate immunity is deeply involved in infectious and autoimmune diseases. For a better understanding of pathogenesis and improved management of these diseases, it is of vital importance to implement convenient monitoring of systemic innate immunity. Built upon our previous works on the host transcriptional response to infection in peripheral blood, we proposed a 2D gene model for the simultaneous assessment of two major components of systemic innate immunity, including VirSig as the signature of the host response to viral infection and BacSig as the signature of the host response to bacterial infection. The revelation of dysregulation in innate immunity by this 2D gene model was demonstrated with a wide variety of transcriptome datasets. In acute infection, distinctive patterns of VirSig and BacSig activation were observed in viral and bacterial infection. In comparison, both signatures were restricted to a defined range in the vast majority of healthy adults, regardless of age. In addition, BacSig showed significant elevation during pregnancy and an upward trend during development. In tuberculosis (TB), elevation of BacSig and VirSig was observed in a significant portion of active TB patients, and abnormal BacSig was also associated with a longer treatment course. In cystic fibrosis (CF), abnormal BacSig was observed in a subset of patients, and no overall change in BacSig abnormality was observed after the drug treatment. In systemic sclerosis-associated interstitial lung disease (SSc-ILD), significant elevation of VirSig and BacSig was observed in some patients, and treatment with a drug led to the further deviation of BacSig from the control level. In systemic lupus erythematosus (SLE), positivity for the anti-Ro autoantibody was associated with significant elevation of VirSig in SLE patients, and the additive effect of VirSig/BacSig activation was also observed in SLE patients during pregnancy. Overall, these data demonstrated that the 2D gene model can be used to assess systemic innate immunity in health and disease, with the potential clinical applications including patient stratification, prescription of antibiotics, understanding of pathogenesis, and longitudinal monitoring of treatment response.

Evaluation of Systemic Inflammation Before and After Standard Anti-tuberculosis Treatment in Patients With Active Pulmonary Tuberculosis and Diabetes Mellitus

Background Diabetes mellitus (DM) is a common comorbidity of active pulmonary tuberculosis (APTB) that increases the risk of treatment failure during anti-tuberculosis chemotherapy. Evaluating systemic inflammatory response could help determine differences in response to treatment between APTB patients and those with APTB and DM. Methodology To explore changes in systemic inflammation, measured by a set of inflammatory mediators in subjects with APTB and TBDM before and after six months of anti-tuberculosis chemotherapy, 30 APTB and nine TBDM subjects underwent cytokine testing, including interleukin (IL)-6, IL-8, IL-10, interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), and transforming growth factor-beta 1 (TGF-β1) by enzyme-linked immunosorbent assay, C-reactive protein by nephelometry, and sialic acid by colorimetric assay at baseline and following six months of standard anti-tuberculosis treatment. Sputum smear microscopy or molecular biology (Xpert MTB/RIF) was used for diagnosis, and sputum smear microscopy was performed monthly during the treatment of the patient with pulmonary tuberculosis to evaluate his evolution. Principal component analysis examined changes in the inflammatory status. Results Both groups showed negative sputum smear microscopy in the sixth month after starting anti-tuberculosis chemotherapy. TGF-β1 was found to be significantly higher in subjects with TBDM before treatment compared to APTB patients (p<0.001), and systemic inflammation continued only in TBDM subjects after treatment (accumulation and persistence of inflammatory mediators like IL-6, IL-8, IL-10, IFN-γ, TNF-α, TGF-β1, C-reactive protein, and sialic acid in blood). On the other hand, the mediators IFN-γ, C-reactive protein, and total sialic acid were found to be most influential in distinguishing pre- and post-treatment inflammatory response in subjects with APTB without DM. Conclusions Inflammatory mediators analyzed in combination, including IFN-γ, CRP, and total sialic acid, may be useful in evaluating the systemic inflammatory response in subjects with APTB and TBDM before and after anti-tuberculosis treatment. Determining these mediators revealed persistent systemic inflammation in TBDM subjects after six months of standard tuberculosis treatment, despite negative sputum smear microscopy results and good glycemic control. This suggests a need for inflammation-modulating therapies during tuberculosis control. Finally, monitoring sputum smear microscopy results alongside the determination of proposed inflammatory mediators (IFN-γ, CRP, and total sialic acid) are effective in evaluating the response to anti-tuberculosis treatment in APTB subjects without DM, warranting further investigation.

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

The spread of tuberculosis (TB), especially multidrug-resistant TB and extensively drug-resistant TB, has strongly motivated the research and development of new anti-TB drugs. New strategies to facilitate drug combinations, including pharmacokinetics-guided dose optimization and toxicology studies of first- and second-line anti-TB drugs have also been introduced and recommended. Liquid chromatography-mass spectrometry (LC-MS) has arguably become the gold standard in the analysis of both endo- and exo-genous compounds. This technique has been applied successfully not only for therapeutic drug monitoring (TDM) but also for pharmacometabolomics analysis. TDM improves the effectiveness of treatment, reduces adverse drug reactions, and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window. Based on TDM, the dose would be optimized individually to achieve favorable outcomes. Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs, aiding in the discovery of potential biomarkers for TB diagnostics, treatment monitoring, and outcome evaluation. This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades. Besides, we discussed the advantages and disadvantages of this technique in practical use. The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted. Lastly, we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies (pharmacometrics, drug and vaccine developments, machine learning/artificial intelligence, among others) to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.