Imperial College London

ProfessorJonFriedland

Faculty of MedicineDepartment of Infectious Disease

Visiting Professor
 
 
 
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Contact

 

+44 (0)20 3313 8521j.friedland Website

 
 
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Assistant

 

Ms Teyanna Gaeta +44 (0)20 3313 1943

 
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Location

 

8N21ACommonwealth BuildingHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Sandhu:2012:10.1371/journal.pone.0038080,
author = {Sandhu, G and Battaglia, F and Ely, BK and Athanasakis, D and Montoya, R and Valencia, T and Gilman, RH and Evans, CA and Friedland, JS and Fernandez-Reyes, D and Agranoff, DD},
doi = {10.1371/journal.pone.0038080},
journal = {PLOS One},
title = {Discriminating Active from Latent Tuberculosis in Patients Presenting to Community Clinics},
url = {http://dx.doi.org/10.1371/journal.pone.0038080},
volume = {7},
year = {2012}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Background: Because of the high global prevalence of latent TB infection (LTBI), a key challenge in endemic settings isdistinguishing patients with active TB from patients with overlapping clinical symptoms without active TB but with coexistingLTBI. Current methods are insufficiently accurate. Plasma proteomic fingerprinting can resolve this difficulty byproviding a molecular snapshot defining disease state that can be used to develop point-of-care diagnostics.Methods: Plasma and clinical data were obtained prospectively from patients attending community TB clinics in Peru andfrom household contacts. Plasma was subjected to high-throughput proteomic profiling by mass spectrometry. Statisticalpattern recognition methods were used to define mass spectral patterns that distinguished patients with active TB fromsymptomatic controls with or without LTBI.Results: 156 patients with active TB and 110 symptomatic controls (patients with respiratory symptoms without active TB)were investigated. Active TB patients were distinguishable from undifferentiated symptomatic controls with accuracy of87% (sensitivity 84%, specificity 90%), from symptomatic controls with LTBI (accuracy of 87%, sensitivity 89%, specificity82%) and from symptomatic controls without LTBI (accuracy 90%, sensitivity 90%, specificity 92%).Conclusions: We show that active TB can be distinguished accurately from LTBI in symptomatic clinic attenders usinga plasma proteomic fingerprint. Translation of biomarkers derived from this study into a robust and affordable point-of-careformat will have significant implications for recognition and control of active TB in high prevalence settings.
AU - Sandhu,G
AU - Battaglia,F
AU - Ely,BK
AU - Athanasakis,D
AU - Montoya,R
AU - Valencia,T
AU - Gilman,RH
AU - Evans,CA
AU - Friedland,JS
AU - Fernandez-Reyes,D
AU - Agranoff,DD
DO - 10.1371/journal.pone.0038080
PY - 2012///
SN - 1932-6203
TI - Discriminating Active from Latent Tuberculosis in Patients Presenting to Community Clinics
T2 - PLOS One
UR - http://dx.doi.org/10.1371/journal.pone.0038080
UR - http://hdl.handle.net/10044/1/30571
VL - 7
ER -