Urinary biomarkers of mycobacterial load and treatment response in pulmonary tuberculosis

Abstract

BACKGROUND. Control of the tuberculosis (TB) pandemic remains hindered in part by a lack of simple and accurate measures of treatment efficacy, as current gold standard markers rely on sputum-based assays that are slow and challenging to implement. However, previous work identified urinary N 1 , N 12-diacetylspermine (DiAcSpm), neopterin, hydroxykynurenine, Nacetylhexosamine, ureidopropionic acid, sialic acid, and mass-to-charge ratio (m/z) 241.0903 as potential biomarkers of active pulmonary TB (ATB). Here, we evaluated their ability to serve as biomarkers of TB treatment response and mycobacterial load. METHODS. We analyzed urine samples prospectively collected from 2 cohorts with ATB. A total of 34 study participants from African countries treated with first-line TB therapy rifampin, isoniazid, pyrazinamide, and ethambutol (HRZE) were followed for 1 year, and 35 participants from Haiti treated with either HRZE or an experimental drug were followed for 14 days. Blinded samples were analyzed by untargeted HPLC-coupled high-resolution TOF-mass spectrometry. RESULTS. Urinary levels of all 7 molecules significantly decreased by week 26 of successful treatment (P = 0.01 to P < 0.0001) and positively correlated with sputum mycobacterial load (P < 0.0001). Urinary DiAcSpm levels decreased significantly in participants treated with HRZE as early as 14 days (P < 0.0001) but remained unchanged in cases of ineffective therapy (P = 0.14). CONCLUSION. Urinary DiAcSpm, neopterin, hydroxykynurenine, N-acetylhexosamine, ureidopropionic acid, sialic acid, and m/z 241.0903 reductions correlated with successful anti-TB treatment and sputum mycobacterial load. Urinary DiAcSpm levels exhibited reductions capable of differentiating treatment success from failure as early as 2 weeks after the initiation of chemotherapy, advocating its further development as a potentially simple, noninvasive biomarker for assessing treatment response and bacterial load.

Metabolomic changes in Mycobacterium avium subsp. paratuberculosis (MAP) challenged Holstein–Friesian cattle highlight the role of serum amino acids as indicators of immune system activation

“…Differences in N-acetylneuraminate (the predominant sialic acid) levels reinforce these findings. M. tuberculosis infected patients demonstrate positive correlation between sialic acid and mycobacterial load (Xia et al, 2020 ). Moreover, M. tuberculosis , alongside other bacteria, exhibit sialic acid decorated proteins which act as receptors and are capable of masking recognition sites and provide protection from humoral and cellular immune system responses (Bhagavat & Chandra, 2013 ).…”

Urine metabolome of tuberculosis patients receiving intensive phase of treatment show diurnal variations

“…Creatinine level is commonly used as a normalization factor in urine metabolite analysis, but in perturbed conditions like TB, due to muscle mass loss, creatinine level is reported to be higher, so was not considered in this study. 26,33,34 Earlier, we monitored urine metabolites in TB patients just after receiving the first dose of treatment 23 but conditioning the host system needs at least a few weeks before the enzymes responsible for TB drug metabolism gets stabilized. So, we collected urine samples from subjects completing at least 15 days post-therapy.…”

“…Creatinine level is commonly used as a normalization factor in urine metabolite analysis, but in perturbed conditions like TB, due to muscle mass loss, creatinine level is reported to be higher, so was not considered in this study. 26,33,34…”

“…Correlating the total body Mycobacterial burden and urine metabolome has recently yielded interesting conclusions. 34 Diet, physical activity and hormones play major roles in diurnal rhythmicity and are responsible for fluctuations. 42,43 So, maintaining uniformity in time of urine sample collection and hormonal status are critical in comparative metabolomics and epidemiological studies.…”

PROLONG: Penalized Regression for Outcome guided Longitudinal Omics analysis with Network and Group constraints

“…Our work is motivated by a pulmonary tuberculosis study consisting of 4 time point observations for 15 subjects each with measured sputum mycobacterial load, quantified by the time in hours to Mtb culture positivity (TTP), and abundances of up to 915 urinary metabolites. Previous work has been performed on the identification of urinary metabolite-based biomarkers for patients with pulmonary tuberculosis [4] [5] and creating a general methodology for metabolite-based biomarker discovery in settings with longitudinal continuous outcomes.…”