# Harnessing the Host Response to Leptosporisis for Diagnosis and Prognosis

> **NIH NIH P01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2023 · $967,771

## Abstract

Abstract: Project 4, Duke University
Leptospirosis is a common, potentially life-threatening infection of global significance. The bacteria spread from
a variety of different host animals to humans typically through contact with infected urine. As a result,
leptospirosis is a leading cause of fever in the tropics. Leptospirosis can cause severe disease resulting in organ
failure and death. Although the infection is responsive to antibiotics, treatment is often delayed due to similarities
with other causes of fever (e.g., dengue) and limitations of current diagnostic tests. Leptospira spp. do not grow
in standard culture media, molecular pathogen detection methods suffer from insufficient sensitivity throughout
the course of the disease, and acute-phase serology is both insensitive and non-specific. Paired (acute and
convalescent) sera can confirm acute infection retrospectively, but convalescent follow-up is infrequent. A
growing body of evidence supports the potential for the development of molecular biomarkers based on the
human immune response to the infection to not only detect infectious pathogen but also predict disease severity
in infectious diseases.
The development and validation of these “host response” diagnostic tests requires rigorous prospective studies
of leptospirosis in diverse locations where different strains of the bacteria are common in people of different
ancestral backgrounds. Our research team has 20 years of experience conducting such studies on 3 continents:
Sri Lanka (Galle), Nicaragua (Leon), and Tanzania (Moshi) where the epidemiology of leptospirosis is well
established. In addition to being relatively common, severe disease is well documented in Nicaragua and Sri
Lanka to support development of diagnostics predictive of disease progression. Our team has extensive
experience in generating the relevant molecular data (gene and protein expression) and the analytical, machine-
learning tools for developing multi-analyte host response classifiers for pathogen differentiation across the
course of infection which can be applied to identify and predict the severity of leptospirosis. The team also has
experience translating these sets of biomarkers onto existing diagnostic platforms. In this project, we will add to
our existing biorepository of samples from three geographically diverse locations to support the development of
leptospirosis-specific molecular classifiers for both diagnosis and prediction of disease severity. Importantly,
critical preliminary data and an unparalleled biorepository of samples and clinical data support Project 4 and
synergize with Projects 1-3 in the proposed research program. Project 4 will be led by Megan E. Reller, MD,
PhD, MPH.

## Key facts

- **NIH application ID:** 10643293
- **Project number:** 1P01AI168148-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Megan Elizabeth Reller
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $967,771
- **Award type:** 1
- **Project period:** 2023-05-16 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10643293

## Citation

> US National Institutes of Health, RePORTER application 10643293, Harnessing the Host Response to Leptosporisis for Diagnosis and Prognosis (1P01AI168148-01A1). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10643293. Licensed CC0.

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