Sputum lipoarabinomannan (LAM) as a biomarker to determine sputum mycobacterial load: exploratory and model-based analyses of integrated data from four cohorts

Abstract

Background: Despite the high global disease burden of tuberculosis (TB), the disease caused by Mycobacterium tuberculosis (Mtb) infection, novel treatments remain an urgent medical need. Development efforts continue to be hampered by the reliance on culture-based methods, which often take weeks to obtain due to the slow growth rate of Mtb. The availability of a "real-time" measure of treatment efficacy could accelerate TB drug development. Sputum lipoarabinomannan (LAM; an Mtb cell wall glycolipid) has promise as a pharmacodynamic biomarker of mycobacterial sputum load.

Methods: The present analysis evaluates LAM as a surrogate for Mtb burden in the sputum samples from 4 cohorts of a total of 776 participants. These include those from 2 cohorts of 558 non-TB and TB participants prior to the initiation of treatment (558 sputum samples), 1 cohort of 178 TB patients under a 14-day bactericidal activity trial with various mono- or multi-TB drug therapies, and 1 cohort of 40 TB patients with data from the first 56-day treatment of a standard 4-drug regimen.

Results: Regression analysis demonstrated that LAM was a predictor of colony-forming unit (CFU)/mL values obtained from the 14-day treatment cohort, with well-estimated model parameters (relative standard error ≤ 22.2%). Moreover, no changes in the relationship between LAM and CFU/mL were observed across the different treatments, suggesting that sputum LAM can be used to reasonably estimate the CFU/mL in the presence of treatment. The integrated analysis showed that sputum LAM also appears to be as good a predictor of time to Mycobacteria Growth Incubator Tube (MGIT) positivity as CFU/mL. As a binary readout, sputum LAM positivity is a strong predictor of solid media or MGIT culture positivity with an area-under-the-curve value of 0.979 and 0.976, respectively, from receiver-operator curve analysis.

Conclusions: Our results indicate that sputum LAM performs as a pharmacodynamic biomarker for rapid measurement of Mtb burden in sputum, and thereby may enable more efficient early phase clinical trial designs (e.g., adaptive designs) to compare candidate anti-TB regimens and streamline dose selection for use in pivotal trials. Trial registration NexGen EBA study (NCT02371681).

Keywords: Biomarker; LAM; Lipoarabinomannan; Mycobacterium; Tuberculosis.

Conflict of interest statement

AB, AGL, AHD, AJ, BK, DA, DH, DHe, JS, KR, LEV, RH, YC, and YL have no competing interests.

GW holds the following 3 patents:

Method for diagnosing tuberculosis: AP/P/2016/009427 (ARIPO), 201580023042.X (China), 15755681.2 (Europe), 201617030869 (India), F/P/2016/258 (Nigeria), 2016/06324 (South Africa).

Serum host biomarkers for tuberculosis disease: PCT/IB2017/052142, due for national filing.

TB diagnostic markers: PCT/IB2013/054377 (USA), host markers in whole blood culture supernatants.

© 2022. The Author(s).

Figures

Fig. 1

Correlation between log10 LAM and log10 CFU concentrations in sputum samples from the same visit. Note: Dashed red, green, and blue lines represent spline for Baseline and Days 7 and 13 Visits, respectively. Solid black line represents spline fit to all data. Pearson Correlation shown in figure represents overall correlation. CFU, colony-forming units; LAM, lipoarabinomannan; log10, 10 logarithm

Fig. 2

Distribution comparison of log10 CFU and LAM concentrations in sputum samples by study visit. Note: Boxes are 25th, 50th, and 75th percentiles, whiskers extend from the hinge to 1.5* inter-quartile range (IQR). Solid black circles are data points outside this range. CFU, colony-forming units; LAM, lipoarabinomannan; log10, 10 logarithm

Fig. 3

Change from baseline correlation between log10 LAM concentrations and log10 CFU concentrations in sputum samples. Note: Red solid line depicts line of unity, blue solid line represents a smoothing spline fit to the observed data, gray shaded area depicts the 95% confidence interval of the spline fit. CFB, change from baseline; CFU, colony-forming units; LAM, lipoarabinomannan; log10, 10 logarithm

Fig. 4

Visual predictive check of the mixed-effects model of log10 LAM concentration and log10 CFU concentration. CFU, colony-forming units; CI, confidence interval; LAM, lipoarabinomannan; log10, 10 logarithm

Fig. 5

Correlation between paired log10 LAM concentration (A) and CFU concentration (B) versus log10 MGIT-TTD. CFU, colony-forming units; LAM, lipoarabinomannan; log10, 10 logarithm; MGIT, Mycobacterium Growth Indicator Tube; TTD, time to detection

Fig. 6

Kaplan–Meier plot of MGIT positivity versus MGIT-TTD, stratified by log10 LAM concentration quartiles. Note: [or] indicates respective endpoint is included in the interval and (or) indicates respective endpoint is not included in the interval. BLQ, below the lower limit of quantitation; LAM, lipoarabinomannan; log10, 10 logarithm; MGIT, Mycobacterium Growth Indicator Tube; TTD, time to detection

Fig. 7

Comparison of log10 LAM concentrations by solid media culture status across samples from all cohorts. Note: Dashed line indicates the LLOQ of 1.176 log10 pg/mL for sputum LAM concentrations. CFU, colony-forming units; LAM, lipoarabinomannan; LLOQ, lower limit of quantitation; log10, base 10 logarithm

Fig. 8

ROCs of LAM and/or MGIT as predictors of CFU-based (A) or MGIT-based culture positivity (B). CFU, colony-forming units; LAM, lipoarabinomannan; MGIT, Mycobacterium Growth Indicator Tube; ROC, receiver operator curve