# Using the Mycobacterium tuberculosis Genome to Predict Tuberculosis Pathology, Drug Resistance Acquisition and Identify Community Transmission Sites

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2020 · $722,155

## Abstract

PROJECT SUMMARY
Peru has the second highest incidence of tuberculosis (TB) disease in the Americas [1]. Despite causing the
largest number of deaths worldwide due to any single agent infectious disease, no study has yet examined the
influence of the pathogen genome on TB pathology as defined by the extent of radiological involvement on the
chest radiograph. Therefore, our first Aim is to combine population level genome sequencing data with
radiological data and linked clinical and demographic metadata to determine using novel multivariate genome
wide association (GWAS) techniques the bacterial genomic biomarkers of TB pathology
More than 80% of TB disease arises following a transmission event that occurs outside the home [2].
Understanding where, when and how frequently transmission events occur in the community is therefore critical
in order to intervene and prevent spread of the disease. Identifying transmission sites, intervening and thereby
preventing transmission is critical to diminishing the spread of primary drug resistance [3]. Therefore, our second
Aim is to use population level whole genome sequencing together with real time GPS monitoring and the latest
in spatial ecology mapping analysis to uncover new sites of TB transmission relative to matched controls
Acquired drug resistance also contributes significantly to the global burden of drug resistance [4]. How TB strain
genotype influences the acquisition of drug resistance remains disputed and insufficiently understood [5–11].
Identifying which genetic background is most associated with the acquisition of drug resistance to specific drugs
would enable patients with drug susceptible TB to receive a personalized treatment regimen that minimizes the
development of drug resistance on that genetic background. Therefore, our third aim is to use a unique set of
>9000 bacterial strains collected in Peru at the population level over 20 years to phylogenetically infer which
genetic background is associated with drug resistance acquisition; then confirm these findings in the laboratory
and on a similar Moldovan dataset collection of >3000 strains.
Preliminary studies have identified a TB bacterial genetic background that is highly associated with drug
resistance [12]. We have also identified new community sites where significant TB transmission occurs [13] as
well as identifying putative bacterial genetic polymorphisms independently associated with pathology in drug
resistant TB. Our proposed study could help to diminish TB transmission in the region, identify new biomarkers
of pathology, uncover new sites of TB transmission, and identify the bacterial genetic associations with drug
resistance acquisition.

## Key facts

- **NIH application ID:** 9971780
- **Project number:** 1R01AI146338-01A1
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** ROBERT H GILMAN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $722,155
- **Award type:** 1
- **Project period:** 2020-04-15 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9971780

## Citation

> US National Institutes of Health, RePORTER application 9971780, Using the Mycobacterium tuberculosis Genome to Predict Tuberculosis Pathology, Drug Resistance Acquisition and Identify Community Transmission Sites (1R01AI146338-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9971780. Licensed CC0.

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