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Each month, the OVPR highlights the past month’s sponsored research funding awarded to Tufts’ investigators, including both a list of funded awards and one or more featured project abstracts.

You can download the list of January’s awardees by clicking the button below. In January, Tufts researchers received 41 awards for extramural funding from federal, foundation, and corporate sponsors.

To submit a recent award to be highlighted, please use the "nominate a project" button below.


This month we are highlighting Dr. Gillian Beamer, for her NIH funded proposal “Predicting tuberculosis outcomes using genotypic and biomarker signatures.” Please see the abstract for this proposal below.

PI: Gillian Beamer
Funder: National Institues of Health
Title: Predicting tuberculosis outcomes using genotypic and biomarker signatures
Abstract: Tuberculosis (TB) is caused by an infectious pathogen, Mycobacterium tuberculosis (M.tb) in susceptible individuals, but we cannot yet classify or predict outcomes in those prone to pulmonary TB disease versus those prone to resistance. In part, this reflects knowledge gaps regarding genotypes that may increase susceptibility, and in validated disease correlates (e.g. serum of lung protein biomarkers) measured individually, or combined signatures. We address these knowledge gaps by using Diversity Outbred (DO) mice, a population with abundant genetic diversity and heterozygosity, like the human population. Also, like humans, a low dose M.tb infection of DO mice produces a spectrum of outcomes, from highly susceptible to highly resistant, and many intermediate outcomes. In this proposal, we use the DO population to: 1) Identify and test the capacity of genotypic (alleles and statistically significant loci) to predict outcomes such as diagnostic category (class); and 2) To identify and test lung and serum biomarker (protein) and granuloma signatures to determine diagnostic category (class); and 3) To identify and test serum biomarker (protein) signatures that can forecast disease onset, within a 3-week window before illness manifests clinically. The best performing signatures will be tested using samples from humans. Collectively, results from these studies will generate new translatable knowledge regarding correlates of pulmonary TB (useful for diagnostics), and genotypic and serum protein signatures (useful for prognostics).