Farhat MR, Loring SH, Riskind P, and Weinhouse G. 2013. “Disturbance of respiratory muscle control in a patient with early-stage multiple sclerosis.” Eur Respir J, 41, 6, Pp. 1454-6.
Farhat MR, Shapiro BJ, Kieser KJ, Sultana R, Jacobson KR, Victor TC, Warren RM, Streicher EM, Calver A, Sloutsky A, Kaur D, Posey JE, Plikaytis B, Oggioni MR, Gardy JL, Johnston JC, Rodrigues M, Tang PKC, Kato-Maeda M, Borowsky ML, Muddukrishna B, Kreiswirth BN, Kurepina N, Galagan J, Gagneux S, Birren B, Eric JR, Lander ES, Sabeti PC, and Murray M. 2013. “Genomic analysis identifies targets of convergent positive selection in drug-resistant Mycobacterium tuberculosis.” Nat Genet, 45, 10, Pp. 1183-9.Abstract
M. tuberculosis is evolving antibiotic resistance, threatening attempts at tuberculosis epidemic control. Mechanisms of resistance, including genetic changes favored by selection in resistant isolates, are incompletely understood. Using 116 newly sequenced and 7 previously sequenced M. tuberculosis whole genomes, we identified genome-wide signatures of positive selection specific to the 47 drug-resistant strains. By searching for convergent evolution--the independent fixation of mutations in the same nucleotide position or gene--we recovered 100% of a set of known resistance markers. We also found evidence of positive selection in an additional 39 genomic regions in resistant isolates. These regions encode components in cell wall biosynthesis, transcriptional regulation and DNA repair pathways. Mutations in these regions could directly confer resistance or compensate for fitness costs associated with resistance. Functional genetic analysis of mutations in one gene, ponA1, demonstrated an in vitro growth advantage in the presence of the drug rifampicin.
Farhat M. 2011. “Chapter 47: Lung Cancer.” In Respiratory care: Principles and Practice, 2nd ed., Pp. 971. Burlington, MA: Jones & Bartlett Learning.
Karvellas CJ, Farhat MR, Sajjad I, Mogensen SS, Leung AA, Wald R, and Bagshaw SM. 2011. “A comparison of early versus late initiation of renal replacement therapy in critically ill patients with acute kidney injury: a systematic review and meta-analysis.” Crit Care, 15, 1, Pp. R72.Abstract
INTRODUCTION: Our aim was to investigate the impact of early versus late initiation of renal replacement therapy (RRT) on clinical outcomes in critically ill patients with acute kidney injury (AKI). METHODS: Systematic review and meta-analysis were used in this study. PUBMED, EMBASE, SCOPUS, Web of Science and Cochrane Central Registry of Controlled Clinical Trials, and other sources were searched in July 2010. Eligible studies selected were cohort and randomised trials that assessed timing of initiation of RRT in critically ill adults with AKI. RESULTS: We identified 15 unique studies (2 randomised, 4 prospective cohort, 9 retrospective cohort) out of 1,494 citations. The overall methodological quality was low. Early, compared with late therapy, was associated with a significant improvement in 28-day mortality (odds ratio (OR) 0.45; 95% confidence interval (CI), 0.28 to 0.72). There was significant heterogeneity among the 15 pooled studies (I(2) = 78%). In subgroup analyses, stratifying by patient population (surgical, n = 8 vs. mixed, n = 7) or study design (prospective, n = 10 vs. retrospective, n = 5), there was no impact on the overall summary estimate for mortality. Meta-regression controlling for illness severity (Acute Physiology And Chronic Health Evaluation II (APACHE II)), baseline creatinine and urea did not impact the overall summary estimate for mortality. Of studies reporting secondary outcomes, five studies (out of seven) reported greater renal recovery, seven (out of eight) studies showed decreased duration of RRT and five (out of six) studies showed decreased ICU length of stay in the early, compared with late, RRT group. Early RRT did not; however, significantly affect the odds of dialysis dependence beyond hospitalization (OR 0.62 0.34 to 1.13, I(2) = 69.6%). CONCLUSIONS: Earlier institution of RRT in critically ill patients with AKI may have a beneficial impact on survival. However, this conclusion is based on heterogeneous studies of variable quality and only two randomised trials. In the absence of new evidence from suitably-designed randomised trials, a definitive treatment recommendation cannot be made.
Colijn C, Brandes A, Zucker J, Lun DS, Weiner B, Farhat MR, Cheng T-Y, Moody DB, Murray M, and Galagan JE. 2009. “Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production.” PLoS Comput Biol, 5, 8, Pp. e1000489.Abstract
Metabolism is central to cell physiology, and metabolic disturbances play a role in numerous disease states. Despite its importance, the ability to study metabolism at a global scale using genomic technologies is limited. In principle, complete genome sequences describe the range of metabolic reactions that are possible for an organism, but cannot quantitatively describe the behaviour of these reactions. We present a novel method for modeling metabolic states using whole cell measurements of gene expression. Our method, which we call E-Flux (as a combination of flux and expression), extends the technique of Flux Balance Analysis by modeling maximum flux constraints as a function of measured gene expression. In contrast to previous methods for metabolically interpreting gene expression data, E-Flux utilizes a model of the underlying metabolic network to directly predict changes in metabolic flux capacity. We applied E-Flux to Mycobacterium tuberculosis, the bacterium that causes tuberculosis (TB). Key components of mycobacterial cell walls are mycolic acids which are targets for several first-line TB drugs. We used E-Flux to predict the impact of 75 different drugs, drug combinations, and nutrient conditions on mycolic acid biosynthesis capacity in M. tuberculosis, using a public compendium of over 400 expression arrays. We tested our method using a model of mycolic acid biosynthesis as well as on a genome-scale model of M. tuberculosis metabolism. Our method correctly predicts seven of the eight known fatty acid inhibitors in this compendium and makes accurate predictions regarding the specificity of these compounds for fatty acid biosynthesis. Our method also predicts a number of additional potential modulators of TB mycolic acid biosynthesis. E-Flux thus provides a promising new approach for algorithmically predicting metabolic state from gene expression data.
D Menzies, G Gardiner, M Farhat, C Greenaway, and M Pai. 2008. “Thinking in three dimensions: a web-based algorithm to aid the interpretation of tuberculin skin test results.” Int J Tuberc Lung Dis, 12, 5, Pp. 498-505.Abstract
BACKGROUND: The tuberculin skin test (TST) is the most widely used test for detecting tuberculosis (TB) infection. Accurate interpretation of TST requires consideration of three dimensions-the size of the skin reaction, the positive predictive value (PPV) and risk of disease. METHODS: We developed a web-based algorithm incorporating epidemiological, medical and radiographic risk factors to help in the interpretation of positive TST results in adults ( TST Calculator/homeE.htm). We used summary estimates from published reviews on the prevalence of latent TB infection, the likelihood of false-positive TST and risk of active TB disease. RESULTS: The algorithm calculations show that the most important determinants of risk of active disease are the presence of medical and radiographic risk factors, while the size of the reaction is of modest importance. In persons who have received bacille Calmette-Guérin vaccination after infancy, the algorithm calculations show that the PPV will be low. In such persons, the risk of disease is predicted to be very low, unless there are medical or radiographic risk factors that increase the risk of reactivation. CONCLUSIONS: Our web-based algorithm can generate clinically useful estimates of the annual and cumulative lifetime risk of developing TB in adults with a positive TST.
Bazari H, Jaff MR, Mannstadt M, and Yan S. 2007. “Case records of the Massachusetts General Hospital. Case 7-2007. A 59-year-old woman with diabetic renal disease and nonhealing skin ulcers.” N Engl J Med, 356, 10, Pp. 1049-57.
FGJ Cobelens, D Menzies, and MR Farhat. 2007. “False-positive tuberculin reactions due to non-tuberculous mycobacterial infections.” Int J Tuberc Lung Dis, 11, 8, Pp. 934-5;author reply 935.
Farhat M, Greenaway C, Pai M, and Menzies D. 11/2006. “False-positive tuberculin reactions due to non-tuberculous mycobacterial infections.” Int J Tuberc Lung Disease, 10, 11, Pp. 1192-1204. Publisher's VersionAbstract


Despite certain drawbacks, the tuberculin skin test (TST) remains in widespread use. Important advantages of the TST are its low cost, simplicity and interpretation based on extensive published literature. However, TST specificity is reduced by bacille Calmette-Guérin (BCG) vaccination and exposure to non-tuberculous mycobacteria (NTM).


To estimate TST specificity, we reviewed the published literature since 1966 regarding the effect of BCG vaccination and NTM infection on TST. Studies selected included healthy subjects with documented BCG vaccination status, including age at vaccination. Studies of NTM effect had used standardised NTM antigens in healthy subjects.


In 24 studies involving 240,203 subjects BCG-vaccinated as infants, 20,406 (8.5%) had a TST of 10+ mm attributable to BCG, but only 56/5639 (1%) were TST-positive if tested > or =10 years after BCG. In 12 studies of 12,728 subjects vaccinated after their first birthday, 5314 (41.8%) had a false-positive TST of 10+ mm, and 191/898 (21.2%) after 10 years. Type of tuberculin test did not modify these results. In 18 studies involving 1,169,105 subjects, the absolute prevalence of false-positive TST from NTM cross-reactivity ranged from 0.1% to 2.3% in different regions.


The effect on TST of BCG received in infancy is minimal, especially > or =10 years after vaccination. BCG received after infancy produces more frequent, more persistent and larger TST reactions. NTM is not a clinically important cause of false-positive TST, except in populations with a high prevalence of NTM sensitisation and a very low prevalence of TB infection.