Tuberculosis biomarkers discovered using Diversity Outbred mice

Abstract

BackgroundBiomarker discovery for pulmonary tuberculosis (TB) may be accelerated by modeling human genotypic diversity and phenotypic responses to Mycobacterium tuberculosis (Mtb). To meet these objectives, we use the Diversity Outbred (DO) mouse population and apply novel classifiers to identify informative biomarkers from multidimensional data sets.MethodTo identify biomarkers, we infected DO mice with aerosolized Mtb confirmed a human-like spectrum of phenotypes, examined gene expression, and inflammatory and immune mediators in the lungs. We measured 11 proteins in 453 Mtb-infected and 29 non-infected mice. We have searched all combinations of six classification algorithms and 239 biomarker subsets and independently validated the selected classifiers. Finally, we selected two mouse lung biomarkers to test as candidate biomarkers of active TB, measuring their diagnostic performance in human sera acquired from the Foundation for Innovative New Diagnostics.FindingsDO mice discovered two translationally relevant biomarkers, CXCL1 and MMP8 that accurately diagnosed active TB in humans with > 90% sensitivity and specificity compared to controls. We identified them through the two classifiers that accurately diagnosed supersusceptible DO mice with early-onset TB: Logistic Regression using MMP8 as a single biomarker, and Gradient Tree Boosting using a panel of 4 biomarkers (CXCL1, CXCL2, TNF, IL-10).InterpretationThis work confirms that the DO population models human responses and can accelerate discovery of translationally relevant TB biomarkers.FundingSupport was provided by NIH R21 AI115038; NIH R01 HL145411; NIH UL1-TR001430; and the American Lung Association Biomedical Research Grant RG-349504.

All that Glitters Is not Gold: Type‐I Error Controlled Variable Selection from Clinical Trial Data

“…Recent work has addressed two additional challenges that are often faced when analyzing clinical trial data, namely missing values and combining data from different sources 46,47 . In our real case scenario in the “Case studies” section, we followed Kormaksson et al 13 .…”

“…If data are missing at random, this approach might compromise power due to a smaller sample size, however, in general, removing patients with missing data can introduce bias. To address missing data in general, one could follow Koyuncu et al ., 46 who have recently shown how missing values can be imputed while preserving the guarantees of the knockoff methods. In our real case scenario, we also present selection results based on pooled data from different, but closely related clinical trials.…”

Prediction of Tuberculosis From Lung Tissue Images of Diversity Outbred Mice Using Jump Knowledge Based Cell Graph Neural Network

“…In the literature, works involved designing a histological categorization system to assess the advancement of pulmonary lesions in TB animal models. This system involved evaluating granulomatus lesions and assigning numerical categories based on the number of inflammatory cells present and the pattern of their infiltration within the tissue [33].In [2], they infected DO mice with aerosolized Mtb, resulting in a range of human-like phenotypes. After examining gene expression and immune responses, they measured 11 proteins in 482 mice (453 infected, 29 non-infected).…”

“…For many years, research on inbred laboratory mice has been instrumental in understanding the host reactions to Mycobacterium tuberculosis ( M. tb ), governed by individual cell types and genes. However, recently, researchers have focused on the introduction of genetically diverse animal models to pinpoint factors influencing lung damage from M.tb in immune-adequate hosts and the adoption of novel techniques to discover biomarkers in line with the World Health Organization’s (WHO) Target Product Profiles [ 2 ]. A new population of mice called Diversity Outbred (DO) mice, which has a level of genetic diversity comparable to that of humans is used in this study.…”

Tuberculosis susceptibility in genetically diverse mice reveals functional diversity of neutrophils

“…Both cohorts have been used for the study of Mtb infection and display a range of disease phenotypes, including enhanced control or susceptibility to infection compared to standard laboratory lines [19][20][21]. Infection of the DO cohort with Mtb revealed correlations between disease pathology and neutrophil influx, recapitulating features seen in human lung infections, in addition to identifying new inflammatory biomarkers that correlate with active human disease [20,22]. Furthermore, these cohorts have been used to identify the genetic basis of disease responses.…”