Publications by authors named "Maha R Farhat"

29 Publications

  • Page 1 of 1

Fecal microbiota transplantation and Clostridioides difficile infection among privately insured patients in the United States.

J Gastroenterol 2021 Sep 8. Epub 2021 Sep 8.

Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street #307, Boston, MA, 02115, USA.

Background: Clostridioides difficile infection (CDI) may be rising in severity in the US over the past decade and its treatment landscape is changing given the recent adoption of fecal microbiota transplantation (FMT) METHODS: We built a retrospective observational cohort using a database of a national care-plan containing medical claims of over 50 million individuals between 2008 and 2019. We used International Classification of Disease (ICD) and prescription data to identify patients with CDI. We estimated trends in disease burden and FMT use, and evaluated complications post FMT using a phenome-wide association approach.

Results: We identified 38,396 patients with CDI; the median age was 60 years (IQR 45-74) and 60% were female (n = 23,374). The rate of CDI increased from 33.4 to 69.46 cases per 100,000 person-years between 2008 and 2015, and stabilized from 2015 to 2019 (increase of 4.77 cases per 100,000 person-years per year, 95% CI 3.55-5.98 prior to 2015 vs. 2.01 95% CI - 10.16 to 14.18 after 2015). Of the 7715 patients with recurrent CDI, 407 patients (5%) underwent FMT. Gastrointestinal complications were increased within 1 month post FMT (OR 99.60, p < 0.001). Sepsis was identified in two individuals (0.49% 95% CI 0.05-1.7%) within the first month post FMT. The risk of CDI recurrence significantly decreased post FMT compared with anti-CDI antibiotics in the multivariable model (raw-recurrence rate 9.8% vs 36%, aOR = 0.21, 95% CI 0.12-0.53, p < 0.001).

Conclusion: We show that FMT is strongly associated with a decrease in CDI recurrence compared with the usual care with generally mild complications for up to 2 years.
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http://dx.doi.org/10.1007/s00535-021-01822-yDOI Listing
September 2021

GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning.

Genome Med 2021 Aug 30;13(1):138. Epub 2021 Aug 30.

Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.

Background: Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly and accurate resistance prediction tools are needed to enable public health and clinical practitioners to rapidly diagnose resistance and inform treatment regimens.

Results: We present Translational Genomics platform for Tuberculosis (GenTB), a free and open web-based application to predict antibiotic resistance from next-generation sequence data. The user can choose between two potential predictors, a Random Forest (RF) classifier and a Wide and Deep Neural Network (WDNN) to predict phenotypic resistance to 13 and 10 anti-tuberculosis drugs, respectively. We benchmark GenTB's predictive performance along with leading TB resistance prediction tools (Mykrobe and TB-Profiler) using a ground truth dataset of 20,408 isolates with laboratory-based drug susceptibility data. All four tools reliably predicted resistance to first-line tuberculosis drugs but had varying performance for second-line drugs. The mean sensitivities for GenTB-RF and GenTB-WDNN across the nine shared drugs were 77.6% (95% CI 76.6-78.5%) and 75.4% (95% CI 74.5-76.4%), respectively, and marginally higher than the sensitivities of TB-Profiler at 74.4% (95% CI 73.4-75.3%) and Mykrobe at 71.9% (95% CI 70.9-72.9%). The higher sensitivities were at an expense of ≤ 1.5% lower specificity: Mykrobe 97.6% (95% CI 97.5-97.7%), TB-Profiler 96.9% (95% CI 96.7 to 97.0%), GenTB-WDNN 96.2% (95% CI 96.0 to 96.4%), and GenTB-RF 96.1% (95% CI 96.0 to 96.3%). Averaged across the four tools, genotypic resistance sensitivity was 11% and 9% lower for isoniazid and rifampicin respectively, on isolates sequenced at low depth (< 10× across 95% of the genome) emphasizing the need to quality control input sequence data before prediction. We discuss differences between tools in reporting results to the user including variants underlying the resistance calls and any novel or indeterminate variants CONCLUSIONS: GenTB is an easy-to-use online tool to rapidly and accurately predict resistance to anti-tuberculosis drugs. GenTB can be accessed online at https://gentb.hms.harvard.edu , and the source code is available at https://github.com/farhat-lab/gentb-site .
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http://dx.doi.org/10.1186/s13073-021-00953-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8407037PMC
August 2021

The role of epistasis in amikacin, kanamycin, bedaquiline, and clofazimine resistance in complex.

Antimicrob Agents Chemother 2021 Aug 30:AAC0116421. Epub 2021 Aug 30.

Department of Biomedical Informatics, Harvard Medical School, Boston, USA.

Antibiotic resistance among bacterial pathogens poses a major global health threat. complex (MTBC) is estimated to have the highest resistance rates of any pathogen globally. Given the slow growth rate and the need for a biosafety level 3 laboratory, the only realistic avenue to scale up drug susceptibility testing (DST) for this pathogen is to rely on genotypic techniques. This raises the fundamental question of whether a mutation is a reliable surrogate for phenotypic resistance or whether the presence of a second mutation can completely counteract its effect, resulting in major diagnostic errors (i.e. systematic false resistance results). To date, such epistatic interactions have only been reported for streptomycin that is now rarely used. By analyzing more than 31,000 MTBC genomes, we demonstrated that the C-14T promoter mutation, which is interrogated by several genotypic DST assays endorsed by the World Health Organization, cannot confer resistance to amikacin and kanamycin if it coincides with loss-of-function (LoF) mutations in the coding region of . To our knowledge, this represents the first definitive example of antibiotic reversion in MTBC. Moreover, we raise the possibility that () mutations are not valid markers of resistance to bedaquiline and clofazimine if these coincide with a LoF mutation in the efflux pump encoded by () and ().
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http://dx.doi.org/10.1128/AAC.01164-21DOI Listing
August 2021

Association Between NEDD4L Variation and the Genetic Risk of Acute Appendicitis: A Multi-institutional Genome-Wide Association Study.

JAMA Surg 2021 Oct;156(10):917-923

Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts.

Importance: The familial aspect of acute appendicitis (AA) has been proposed, but its hereditary basis remains undetermined.

Objective: To identify genomic variants associated with AA.

Design, Setting, And Participants: This genome-wide association study, conducted from June 21, 2019, to February 4, 2020, used a multi-institutional biobank to retrospectively identify patients with AA across 8 single-nucleotide variation (SNV) genotyping batches. The study also examined differential gene expression in appendiceal tissue samples between patients with AA and controls using the GSE9579 data set in the National Institutes of Health's Gene Expression Omnibus repository. Statistical analysis was conducted from October 1, 2019, to February 4, 2020.

Main Outcomes And Measures: Single-nucleotide variations with a minor allele frequency of 5% or higher were tested for association with AA using a linear mixed model. The significance threshold was set at P = 5 × 10-8.

Results: A total of 29 706 patients (15 088 women [50.8%]; mean [SD] age at enrollment, 60.1 [17.0] years) were included, 1743 of whom had a history of AA. The genomic inflation factor for the cohort was 1.003. A previously unknown SNV at chromosome 18q was found to be associated with AA (rs9953918: odds ratio, 0.99; 95% CI, 0.98-1.00; P = 4.48 × 10-8). This SNV is located in an intron of the NEDD4L gene. The heritability of appendicitis was estimated at 30.1%. Gene expression data from appendiceal tissue donors identified NEDD4L to be among the most differentially expressed genes (14 of 22 216 genes; β [SE] = -2.71 [0.44]; log fold change = -1.69; adjusted P = .04).

Conclusions And Relevance: This study identified SNVs within the NEDD4L gene as being associated with AA. Nedd4l is involved in the ubiquitination of intestinal ion channels and decreased Nedd4l activity may be implicated in the pathogenesis of AA. These findings can improve the understanding of the genetic predisposition to and pathogenesis of AA.
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http://dx.doi.org/10.1001/jamasurg.2021.3303DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319828PMC
October 2021

Globally diverse resistance acquisition: a retrospective geographical and temporal analysis of whole genome sequences.

Lancet Microbe 2021 Mar 27;2(3):e96-e104. Epub 2021 Jan 27.

Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.

Background: whole genome sequencing (WGS) data can provide insights into temporal and geographical trends in resistance acquisition and inform public health interventions. We aimed to use a large clinical collection of WGS and resistance phenotype data to study how, when, and where resistance was acquired on a global scale.

Methods: We did a retrospective analysis of WGS data. We curated a set of clinical isolates with high-quality sequencing and culture-based drug susceptibility data (spanning four lineages and 52 countries in Africa, Asia, the Americas, and Europe) using public databases and literature curation. For inclusion, sequence quality criteria and country of origin data were required. We constructed geographical and lineage specific phylogenies and used Bayesian molecular dating with BEAST, version 1.10.4, to infer the most recent common susceptible ancestor age for 4869 instances of resistance to ten drugs.

Findings: Between Jan 1, 1987, and Sept 12, 2014, of 10 299 clinical isolates, 8550 were curated, of which 6099 (71%) from 15 countries met criteria for molecular dating. The number of independent resistance acquisition events was lower than the number of resistant isolates across all countries, suggesting ongoing transmission of drug resistance. Ancestral age distributions supported the presence of old resistance, 20 years or more before, in most countries. A consistent order of resistance acquisition was observed globally starting with resistance to isoniazid, but resistance ancestral age varied by country. We found a direct correlation between gross domestic product per capita and resistance age ( =0·47; p=0·014). Amplification of fluoroquinolone and second-line injectable resistance among multidrug-resistant isolates is estimated to have occurred very recently (median ancestral age 4·7 years [IQR 1·9-9·8] before sample collection). We found the sensitivity of commercial molecular diagnostics for second-line resistance to vary significantly by country (p<0·0003).

Interpretation: Our results highlight that both resistance transmission and amplification are contributing to disease burden globally but vary by country. The observation that wealthier nations are more likely to have old resistance (most recent common susceptible ancestor >20 years before isolation) suggests that programmatic improvements can reduce resistance amplification, but that fit resistant strains can circulate for decades subsequently implies the need for continued surveillance.
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http://dx.doi.org/10.1016/s2666-5247(20)30195-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8078851PMC
March 2021

Multisystem outcomes and predictors of mortality in critically ill patients with COVID-19: Demographics and disease acuity matter more than comorbidities or treatment modalities.

J Trauma Acute Care Surg 2021 05;90(5):880-890

From the Division of Trauma, Emergency Surgery and Surgical Critical Care (O.A., A.M., L.N., K.L., K.A.B., M.E.M., C.K., A.G., M.A.C., L.R.M., H.M., B.B.-K., J.P., J.F., N.S., A.M., C.P., P.F., D.K., J.L., G.C.V., H.M.A.K.), and Division of Pulmonary Critical Care (M.R.F.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.

Background: We sought to describe characteristics, multisystem outcomes, and predictors of mortality of the critically ill COVID-19 patients in the largest hospital in Massachusetts.

Methods: This is a prospective cohort study. All patients admitted to the intensive care unit (ICU) with reverse-transcriptase-polymerase chain reaction-confirmed severe acute respiratory syndrome coronavirus 2 infection between March 14, 2020, and April 28, 2020, were included; hospital and multisystem outcomes were evaluated. Data were collected from electronic records. Acute respiratory distress syndrome (ARDS) was defined as PaO2/FiO2 ratio of ≤300 during admission and bilateral radiographic pulmonary opacities. Multivariable logistic regression analyses adjusting for available confounders were performed to identify predictors of mortality.

Results: A total of 235 patients were included. The median (interquartile range [IQR]) Sequential Organ Failure Assessment score was 5 (3-8), and the median (IQR) PaO2/FiO2 was 208 (146-300) with 86.4% of patients meeting criteria for ARDS. The median (IQR) follow-up was 92 (86-99) days, and the median ICU length of stay was 16 (8-25) days; 62.1% of patients were proned, 49.8% required neuromuscular blockade, and 3.4% required extracorporeal membrane oxygenation. The most common complications were shock (88.9%), acute kidney injury (AKI) (69.8%), secondary bacterial pneumonia (70.6%), and pressure ulcers (51.1%). As of July 8, 2020, 175 patients (74.5%) were discharged alive (61.7% to skilled nursing or rehabilitation facility), 58 (24.7%) died in the hospital, and only 2 patients were still hospitalized, but out of the ICU. Age (odds ratio [OR], 1.08; 95% confidence interval [CI], 1.04-1.12), higher median Sequential Organ Failure Assessment score at ICU admission (OR, 1.24; 95% CI, 1.06-1.43), elevated creatine kinase of ≥1,000 U/L at hospital admission (OR, 6.64; 95% CI, 1.51-29.17), and severe ARDS (OR, 5.24; 95% CI, 1.18-23.29) independently predicted hospital mortality.Comorbidities, steroids, and hydroxychloroquine treatment did not predict mortality.

Conclusion: We present here the outcomes of critically ill patients with COVID-19. Age, acuity of disease, and severe ARDS predicted mortality rather than comorbidities.

Level Of Evidence: Prognostic, level III.
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http://dx.doi.org/10.1097/TA.0000000000003085DOI Listing
May 2021

Measuring health-care delays among privately insured patients with tuberculosis in the USA: an observational cohort study.

Lancet Infect Dis 2021 08 23;21(8):1175-1183. Epub 2021 Mar 23.

Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA. Electronic address:

Background: A high index of suspicion is needed to initiate appropriate testing for tuberculosis due to its protean symptoms, yet health-care providers in low-incidence settings are becoming less familiar with the disease as rates decline. We aimed to estimate delays in tuberculosis diagnosis and treatment at the US national level between 2008 and 2016.

Methods: In this retrospective observational cohort study, we repurposed private insurance claims data provided by Aetna (Connecticut, USA), to measure health-care delays in tuberculosis diagnosis in the USA in 2008-16. Active tuberculosis was determined by diagnosis codes and the filling of anti-tuberculosis treatment prescriptions. Health-care delays were defined as the duration between the first health-care visit for a tuberculosis symptom and the initiation of anti-tuberculosis treatment. We assessed if delays varied over time, and by patient and system variables, using multivariable regression. We estimated household tuberculosis transmission and respiratory complications after treatment initiation.

Findings: We confirmed 738 active tuberculosis cases (incidence 1·45 per 100 000 person-years) with a median health-care delay of 24 days (IQR 10-45). Multivariable regression analysis showed that longer delays were associated with older age (8·4% per 10 year increase [95% CI 4·0 to 13·1]; p<0·0086) and non-HIV immunosuppression (19·2% [15·1 to 60·0]; p=0·0432). Presenting with three or more symptoms was associated with a shorter delay (-22·5% [-39·1 to -2·0]; p=0·0415), relative to presenting with one symptom, as did use of chest imaging (-24·9% [-37·9 to -8·9]; p<0·0098), tuberculosis nucleic acid amplification tests (-19·2% [-32·7 to -3·1]; p=0·0241), and care by a tuberculosis specialist provider (-17·2% [-33·1 to -22·3]; p<0·0087). Longer delays were associated with an increased rate of respiratory complications even after controlling for patient characteristics, and an increased rate of secondary tuberculosis among dependents.

Interpretation: In the USA, the median health-care delay for privately insured patients with tuberculosis exceeds WHO-recommended levels of 21 days (3 weeks). The results suggest the need for health-care provider education on best practices in tuberculosis diagnosis, including the use of molecular tests and the maintenance of a high index of suspicion for the disease.

Funding: US National Institutes of Health.
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http://dx.doi.org/10.1016/S1473-3099(20)30732-5DOI Listing
August 2021

Mentorship at a distance.

Science 2020 Oct;370(6515):494

Naomi Rankin is an undergrad at Howard University. Matthias Gröschel is a postdoc and Maha Farhat an assistant professor at Harvard Medical School. Farhat is also an attending pulmonologist at Massachusetts General Hospital. Send your career story to

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http://dx.doi.org/10.1126/science.370.6515.494DOI Listing
October 2020

The phylogenetic landscape and nosocomial spread of the multidrug-resistant opportunist Stenotrophomonas maltophilia.

Nat Commun 2020 04 27;11(1):2044. Epub 2020 Apr 27.

Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany.

Recent studies portend a rising global spread and adaptation of human- or healthcare-associated pathogens. Here, we analyse an international collection of the emerging, multidrug-resistant, opportunistic pathogen Stenotrophomonas maltophilia from 22 countries to infer population structure and clonality at a global level. We show that the S. maltophilia complex is divided into 23 monophyletic lineages, most of which harbour strains of all degrees of human virulence. Lineage Sm6 comprises the highest rate of human-associated strains, linked to key virulence and resistance genes. Transmission analysis identifies potential outbreak events of genetically closely related strains isolated within days or weeks in the same hospitals.
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http://dx.doi.org/10.1038/s41467-020-15123-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7184733PMC
April 2020

Identification of a new genetic variant associated with cholecystitis: A multicenter genome-wide association study.

J Trauma Acute Care Surg 2020 07;89(1):173-178

From the Division of Trauma (A.B., A.G., K.B., M.E.H., C.N., M.C., N.K., A.M., G.V., H.M.A.K.), Emergency Surgery and Surgical Critical Care, Massachusetts General Hospital, Boston, Massachusetts; Department of Anesthesia (A.B., M.C., M.S.), Center of Head and Orthopedics, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark; Department of Biomedical Informatics (M.R.F.), Harvard Medical School; and Pulmonary and Critical Care Medicine (M.R.F.), Massachusetts General Hospital, Boston, Massachusetts.

Background: The genomic landscape of gallbladder disease remains poorly understood. We sought to examine the association between genetic variants and the development of cholecystitis.

Methods: The Biobank of a large multi-institutional health care system was used. All patients with cholecystitis were identified using International Statistical Classification of Diseases, 10th Revision, codes and genotyped across six batches. To control for population stratification, data were restricted to that from individuals of European genomic ancestry using a multidimensional scaling approach. The association between single nucleotide polymorphisms and cholecystitis was evaluated with a mixed linear model-based analysis, controlling for age, sex, and obesity. The threshold for significance was set at 5 × 10.

Results: Of 24,635 patients (mean ± SD age, 60.1 ± 16.7 years; 13,022 females [52.9%]), 900 had cholecystitis (mean ± SD age, 65.4 ± 14.3 years; 496 females [55.1%]). After meta-analysis, three single nucleotide polymorphisms on chromosome 5p15 exceeded the threshold for significance (p < 5 × 10). The phenotypic variance of cholecystitis explained by genetics and controlling for sex and obesity was estimated to be 17.9%.

Conclusion: Using a multi-institutional genomic Biobank, we report that a region on chromosome 5p15 is associated with the development of cholecystitis that can be used to identify patients at risk.

Level Of Evidence: Prognostic and epidemiological, Level III.
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http://dx.doi.org/10.1097/TA.0000000000002647DOI Listing
July 2020

Antibiotic treatment and selection for mutations in patients with active tuberculosis disease.

Proc Natl Acad Sci U S A 2020 02 19;117(8):3910-3912. Epub 2020 Feb 19.

Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115.

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http://dx.doi.org/10.1073/pnas.1920788117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7049102PMC
February 2020

Antibiotic resistance prediction for from genome sequence data with Mykrobe.

Wellcome Open Res 2019 2;4:191. Epub 2019 Dec 2.

European Bioinformatics Institute, Cambridge, UK.

Two billion people are infected with , leading to 10 million new cases of active tuberculosis and 1.5 million deaths annually. Universal access to drug susceptibility testing (DST) has become a World Health Organization priority. We previously developed a software tool, , which provided offline species identification and drug resistance predictions for from whole genome sequencing (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations.  Here we present a new tool, , which provides the same functionality based on a new software implementation. Improvements include i) an updated mutation catalogue giving greater sensitivity to detect pyrazinamide resistance, ii) support for user-defined resistance catalogues, iii) improved identification of non-tuberculous mycobacterial species, and iv) an updated statistical model for Oxford Nanopore Technologies sequencing data. is released under MIT license at https://github.com/mykrobe-tools/mykrobe. We incorporate mutation catalogues from the CRyPTIC consortium et al. (2018) and from Walker et al. (2015), and make improvements based on performance on an initial set of 3206 and an independent set of 5845 Illumina sequences. To give estimates of error rates, we use a prospectively collected dataset of 4362 . Using culture based DST as the reference, we estimate to be 100%, 95%, 82%, 99% sensitive and 99%, 100%, 99%, 99% specific for rifampicin, isoniazid, pyrazinamide and ethambutol resistance prediction respectively. We benchmark against four other tools on 10207 (=5845+4362) samples, and also show that gives concordant results with nanopore data.  We measure the ability of -based DST to guide personalized therapeutic regimen design in the context of complex drug susceptibility profiles, showing 94% concordance of implied regimen with that driven by phenotypic DST, higher than all other benchmarked tools.
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http://dx.doi.org/10.12688/wellcomeopenres.15603.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7004237PMC
December 2019

Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues.

Nat Rev Microbiol 2019 09;17(9):533-545

Foundation for Innovative New Diagnostics, Geneva, Switzerland.

Whole genome sequencing (WGS) of Mycobacterium tuberculosis has rapidly progressed from a research tool to a clinical application for the diagnosis and management of tuberculosis and in public health surveillance. This development has been facilitated by drastic drops in cost, advances in technology and concerted efforts to translate sequencing data into actionable information. There is, however, a risk that, in the absence of a consensus and international standards, the widespread use of WGS technology may result in data and processes that lack harmonization, comparability and validation. In this Review, we outline the current landscape of WGS pipelines and applications, and set out best practices for M. tuberculosis WGS, including standards for bioinformatics pipelines, curated repositories of resistance-causing variants, phylogenetic analyses, quality control and standardized reporting.
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http://dx.doi.org/10.1038/s41579-019-0214-5DOI Listing
September 2019

GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions.

Nat Commun 2019 05 13;10(1):2128. Epub 2019 May 13.

Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA.

Drug resistance diagnostics that rely on the detection of resistance-related mutations could expedite patient care and TB eradication. We perform minimum inhibitory concentration testing for 12 anti-TB drugs together with Illumina whole-genome sequencing on 1452 clinical Mycobacterium tuberculosis (MTB) isolates. We evaluate genome-wide associations between mutations in MTB genes or non-coding regions and resistance, followed by validation in an independent data set of 792 patient isolates. We confirm associations at 13 non-canonical loci, with two involving non-coding regions. Promoter mutations are measured to have smaller average effects on resistance than gene body mutations. We estimate the heritability of the resistance phenotype to 11 anti-TB drugs and identify a lower than expected contribution from known resistance genes. This study highlights the complexity of the genomic mechanisms associated with the MTB resistance phenotype, including the relatively large number of potentially causal loci, and emphasizes the contribution of the non-coding portion of the genome.
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http://dx.doi.org/10.1038/s41467-019-10110-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6513847PMC
May 2019

Whole genome sequencing identifies bacterial factors affecting transmission of multidrug-resistant tuberculosis in a high-prevalence setting.

Sci Rep 2019 04 3;9(1):5602. Epub 2019 Apr 3.

Harvard Medical School, Boston, MA, USA.

Whole genome sequencing (WGS) can elucidate Mycobacterium tuberculosis (Mtb) transmission patterns but more data is needed to guide its use in high-burden settings. In a household-based TB transmissibility study in Peru, we identified a large MIRU-VNTR Mtb cluster (148 isolates) with a range of resistance phenotypes, and studied host and bacterial factors contributing to its spread. WGS was performed on 61 of the 148 isolates. We compared transmission link inference using epidemiological or genomic data and estimated the dates of emergence of the cluster and antimicrobial drug resistance (DR) acquisition events by generating a time-calibrated phylogeny. Using a set of 12,032 public Mtb genomes, we determined bacterial factors characterizing this cluster and under positive selection in other Mtb lineages. Four of the 61 isolates were distantly related and the remaining 57 isolates diverged ca. 1968 (95%HPD: 1945-1985). Isoniazid resistance arose once and rifampin resistance emerged subsequently at least three times. Emergence of other DR types occurred as recently as within the last year of sampling. We identified five cluster-defining SNPs potentially contributing to transmissibility. In conclusion, clusters (as defined by MIRU-VNTR typing) may be circulating for decades in a high-burden setting. WGS allows for an enhanced understanding of transmission, drug resistance, and bacterial fitness factors.
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http://dx.doi.org/10.1038/s41598-019-41967-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6447560PMC
April 2019

Rifampicin and rifabutin resistance in 1003 Mycobacterium tuberculosis clinical isolates.

J Antimicrob Chemother 2019 06;74(6):1477-1483

Department of Global Health and Social Medicine, Harvard Medical School, 641 Huntington Avenue, Boston, MA, USA.

Objectives: Drug-resistant TB remains a public health challenge. Rifamycins are among the most potent anti-TB drugs. They are known to target the RpoB subunit of RNA polymerase; however, our understanding of how rifamycin resistance is genetically encoded remains incomplete. Here we investigated rpoB genetic diversity and cross-resistance between the two rifamycin drugs rifampicin and rifabutin.

Methods: We performed WGS of 1003 Mycobacterium tuberculosis clinical isolates and determined MICs of both rifamycin agents on 7H10 agar using the indirect proportion method. We generated rpoB mutants in a laboratory strain and measured their antibiotic susceptibility using the alamarBlue reduction assay.

Results: Of the 1003 isolates, 766 were rifampicin resistant and 210 (27%) of these were rifabutin susceptible; 102/210 isolates had the rpoB mutation D435V (Escherichia coli D516V). Isolates with discordant resistance were 17.2 times more likely to harbour a D435V mutation than those resistant to both agents (OR 17.2, 95% CI 10.5-27.9, P value <10-40). Compared with WT, the D435V in vitro mutant had an increased IC50 of both rifamycins; however, in both cases to a lesser degree than the S450L (E. coli S531L) mutation.

Conclusions: The observation that the rpoB D435V mutation produces an increase in the IC50 of both drugs contrasts with findings from previous smaller studies that suggested that isolates with the D435V mutation remain rifabutin susceptible despite being rifampicin resistant. Our finding thus suggests that the recommended critical testing concentration for rifabutin should be revised.
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http://dx.doi.org/10.1093/jac/dkz048DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6524487PMC
June 2019

Genome-wide discovery of epistatic loci affecting antibiotic resistance in Neisseria gonorrhoeae using evolutionary couplings.

Nat Microbiol 2019 02 3;4(2):328-338. Epub 2018 Dec 3.

Department of Systems Biology, Harvard Medical School, Boston, MA, USA.

Genome analysis should allow the discovery of interdependent loci that together cause antibiotic resistance. In practice, however, the vast number of possible epistatic interactions erodes statistical power. Here, we extend an approach that has been successfully used to identify epistatic residues in proteins to infer genomic loci that are strongly coupled. This approach reduces the number of tests required for an epistatic genome-wide association study of antibiotic resistance and increases the likelihood of identifying causal epistasis. We discovered 38 loci and 240 epistatic pairs that influence the minimum inhibitory concentrations of 5 different antibiotics in 1,102 isolates of Neisseria gonorrhoeae that were confirmed in a second dataset of 495 isolates. Many known resistance-affecting loci were recovered; however, the majority of associations occurred in unreported genes, such as murE. About half of the discovered epistasis involved at least one locus previously associated with antibiotic resistance, including interactions between gyrA and parC. Still, many combinations involved unreported loci and genes. While most variation in minimum inhibitory concentrations could be explained by identified loci, epistasis substantially increased explained phenotypic variance. Our work provides a systematic identification of epistasis affecting antibiotic resistance in N. gonorrhoeae and a generalizable approach for epistatic genome-wide association studies.
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http://dx.doi.org/10.1038/s41564-018-0309-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6663919PMC
February 2019

Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing.

N Engl J Med 2018 10 26;379(15):1403-1415. Epub 2018 Sep 26.

Background: The World Health Organization recommends drug-susceptibility testing of Mycobacterium tuberculosis complex for all patients with tuberculosis to guide treatment decisions and improve outcomes. Whether DNA sequencing can be used to accurately predict profiles of susceptibility to first-line antituberculosis drugs has not been clear.

Methods: We obtained whole-genome sequences and associated phenotypes of resistance or susceptibility to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and pyrazinamide for isolates from 16 countries across six continents. For each isolate, mutations associated with drug resistance and drug susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These profiles were predicted to be susceptible to all four drugs (i.e., pansusceptible) if they were predicted to be susceptible to isoniazid and to the other drugs or if they contained mutations of unknown association in genes that affect susceptibility to the other drugs. We simulated the way in which the negative predictive value changed with the prevalence of drug resistance.

Results: A total of 10,209 isolates were analyzed. The largest proportion of phenotypes was predicted for rifampin (9660 [95.4%] of 10,130) and the smallest was predicted for ethambutol (8794 [89.8%] of 9794). Resistance to isoniazid, rifampin, ethambutol, and pyrazinamide was correctly predicted with 97.1%, 97.5%, 94.6%, and 91.3% sensitivity, respectively, and susceptibility to these drugs was correctly predicted with 99.0%, 98.8%, 93.6%, and 96.8% specificity. Of the 7516 isolates with complete phenotypic drug-susceptibility profiles, 5865 (78.0%) had complete genotypic predictions, among which 5250 profiles (89.5%) were correctly predicted. Among the 4037 phenotypic profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted.

Conclusions: Genotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.).
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http://dx.doi.org/10.1056/NEJMoa1800474DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6121966PMC
October 2018

Fluoroquinolone Resistance Mutation Detection Is Equivalent to Culture-Based Drug Sensitivity Testing for Predicting Multidrug-Resistant Tuberculosis Treatment Outcome: A Retrospective Cohort Study.

Clin Infect Dis 2017 Oct;65(8):1364-1370

Department of Global Health and Social Medicine, Harvard Medical School.

Background: Molecular diagnostics that rapidly and accurately predict fluoroquinolone (FQ) resistance promise to improve treatment outcomes for individuals with multidrug-resistant (MDR) tuberculosis (TB). Mutations in the gyr genes, though, can cause variable levels of in vitro FQ resistance, and some in vitro resistance remains unexplained by gyr mutations alone, but the implications of these discrepancies for treatment outcome are unknown.

Methods: We performed a retrospective cohort study of 172 subjects with MDR/extensively drug-resistant TB subjects and sequenced the full gyrA and gyrB open reading frames in their respective sputum TB isolates. The gyr mutations were classified into 2 categories: a set of mutations that encode high-level FQ resistance and a second set that encodes intermediate resistance levels. We constructed a Cox proportional model to assess the effect of the gyr mutation type on the time to death or treatment failure and compared this with in vitro FQ resistance, controlling for host and treatment factors.

Results: Controlling for other host and treatment factors and compared with patients with isolates without gyr resistance mutations, "high-level" gyr mutations significantly predict poor treatment outcomes with a hazard ratio of 2.6 (1.2-5.6). We observed a hazard of death and treatment failure with "intermediate-level" gyr mutations of 1.3 (0.6-3.1), which did not reach statistical significance. The gyr mutations were not different than culture-based FQ drug susceptibility testing in predicting the hazard of death or treatment failure and may be superior.

Conclusions: FQ molecular-based diagnostic tests may better predict treatment response than traditional drug susceptibility testing and open avenues for personalizing TB therapy.
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http://dx.doi.org/10.1093/cid/cix556DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5850426PMC
October 2017

Transmissible Mycobacterium tuberculosis Strains Share Genetic Markers and Immune Phenotypes.

Am J Respir Crit Care Med 2017 06;195(11):1519-1527

1 National Institute for Public Health and the Environment, Bilthoven, the Netherlands.

Rationale: Successful transmission of tuberculosis depends on the interplay of human behavior, host immune responses, and Mycobacterium tuberculosis virulence factors. Previous studies have been focused on identifying host risk factors associated with increased transmission, but the contribution of specific genetic variations in mycobacterial strains themselves are still unknown.

Objectives: To identify mycobacterial genetic markers associated with increased transmissibility and to examine whether these markers lead to altered in vitro immune responses.

Methods: Using a comprehensive tuberculosis registry (n = 10,389) and strain collection in the Netherlands, we identified a set of 100 M. tuberculosis strains either least or most likely to be transmitted after controlling for host factors. We subjected these strains to whole-genome sequencing and evolutionary convergence analysis, and we repeated this analysis in an independent validation cohort. We then performed immunological experiments to measure in vitro cytokine production and neutrophil responses to a subset of the original strains with or without the identified mutations associated with increased transmissibility.

Measurements And Main Results: We identified the loci espE, PE-PGRS56, Rv0197, Rv2813-2814c, and Rv2815-2816c as targets of convergent evolution among transmissible strains. We validated four of these regions in an independent set of strains, and we demonstrated that mutations in these targets affected in vitro monocyte and T-cell cytokine production, neutrophil reactive oxygen species release, and apoptosis.

Conclusions: In this study, we identified genetic markers in convergent evolution of M. tuberculosis toward enhanced transmissibility in vivo that are associated with altered immune responses in vitro.
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http://dx.doi.org/10.1164/rccm.201605-1042OCDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5803666PMC
June 2017

Genetic Determinants of Drug Resistance in Mycobacterium tuberculosis and Their Diagnostic Value.

Am J Respir Crit Care Med 2016 09;194(5):621-30

2 Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts.

Rationale: The development of molecular diagnostics that detect both the presence of Mycobacterium tuberculosis in clinical samples and drug resistance-conferring mutations promises to revolutionize patient care and interrupt transmission by ensuring early diagnosis. However, these tools require the identification of genetic determinants of resistance to the full range of antituberculosis drugs.

Objectives: To determine the optimal molecular approach needed, we sought to create a comprehensive catalog of resistance mutations and assess their sensitivity and specificity in diagnosing drug resistance.

Methods: We developed and validated molecular inversion probes for DNA capture and deep sequencing of 28 drug-resistance loci in M. tuberculosis. We used the probes for targeted sequencing of a geographically diverse set of 1,397 clinical M. tuberculosis isolates with known drug resistance phenotypes. We identified a minimal set of mutations to predict resistance to first- and second-line antituberculosis drugs and validated our predictions in an independent dataset. We constructed and piloted a web-based database that provides public access to the sequence data and prediction tool.

Measurements And Main Results: The predicted resistance to rifampicin and isoniazid exceeded 90% sensitivity and specificity but was lower for other drugs. The number of mutations needed to diagnose resistance is large, and for the 13 drugs studied it was 238 across 18 genetic loci.

Conclusions: These data suggest that a comprehensive M. tuberculosis drug resistance diagnostic will need to allow for a high dimension of mutation detection. They also support the hypothesis that currently unknown genetic determinants, potentially discoverable by whole-genome sequencing, encode resistance to second-line tuberculosis drugs.
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http://dx.doi.org/10.1164/rccm.201510-2091OCDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5027209PMC
September 2016

Gyrase Mutations Are Associated with Variable Levels of Fluoroquinolone Resistance in Mycobacterium tuberculosis.

J Clin Microbiol 2016 Mar 13;54(3):727-33. Epub 2016 Jan 13.

Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA.

Molecular diagnostics that rapidly and accurately predict resistance to fluoroquinolone drugs and especially later-generation agents promise to improve treatment outcomes for patients with multidrug-resistant tuberculosis and prevent the spread of disease. Mutations in the gyr genes are known to confer most fluoroquinolone resistance, but knowledge about the effects of gyr mutations on susceptibility to early- versus later-generation fluoroquinolones and about the role of mutation-mutation interactions is limited. Here, we sequenced the full gyrA and gyrB open reading frames in 240 multidrug-resistant and extensively drug-resistant tuberculosis strains and quantified their ofloxacin and moxifloxacin MIC by testing growth at six concentrations for each drug. We constructed a multivariate regression model to assess both the individual mutation effects and interactions on the drug MICs. We found that gyrB mutations contribute to fluoroquinolone resistance both individually and through interactions with gyrA mutations. These effects were statistically significant. In these clinical isolates, several gyrA and gyrB mutations conferred different levels of resistance to ofloxacin and moxifloxacin. Consideration of gyr mutation combinations during the interpretation of molecular test results may improve the accuracy of predicting the fluoroquinolone resistance phenotype. Further, the differential effects of gyr mutations on the activity of early- and later-generation fluoroquinolones requires further investigation and could inform the selection of a fluoroquinolone for treatment.
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http://dx.doi.org/10.1128/JCM.02775-15DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4767988PMC
March 2016

The nature, patterns, clinical outcomes, and financial impact of intraoperative adverse events in emergency surgery.

Am J Surg 2016 Jul 24;212(1):16-23. Epub 2015 Oct 24.

Division of Trauma, Emergency Surgery, and Surgical Critical Care, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge Street Suite 810, Boston, MA, 02114, USA. Electronic address:

Background: Little is known about intraoperative adverse events (iAEs) in emergency surgery (ES). We sought to describe iAEs in ES and to investigate their clinical and financial impact.

Methods: The 2007 to 2012 administrative and American College of Surgeons-National Surgical Quality Improvement Program databases at our tertiary academic center were: (1) linked, (2) queried for all ES procedures, and then (3) screened for iAEs using the ICD-9-CM-based Patient Safety Indicator "accidental puncture/laceration". Flagged cases were systematically reviewed to: (1) confirm or exclude the occurrence of iAEs (defined as inadvertent injuries during the operation) and (2) extract additional variables such as procedure type, approach, complexity (measured by relative value units), need for adhesiolysis, and extent of repair. Univariate and multivariate analyses were performed to assess the independent impact of iAEs on 30-day morbidity, mortality, and hospital charges.

Results: Of a total of 9,288 patients, 1,284 (13.8%) patients underwent ES, of which 23 had iAEs (1.8%); 18 of 23 (78.3%) of the iAEs involved the small bowel or spleen, 10 of 23 (43.5%) required suture repair, and 8 of 23 (34.8%) required tissue or organ resection. Compared with those without iAEs, patients with iAEs were older (median age 62 vs 50; P = .04); their procedures were more complex (total relative value unit 46.7, interquartile range [27.5 to 52.6] vs 14.5 [.5 to 30.2]; P < .001), longer in duration (>3 hours: 52% vs 8%; P < .001), and more often required adhesiolysis (39.1% vs 13.5% P = .001). Patients with iAEs had increased total charges ($31,080 vs $11,330, P < .001), direct charges ($20,030 vs $7,387, P < .001), and indirect charges ($11,460 vs $4,088, P < .001). On multivariable analyses, iAEs were independently associated with increased 30-day morbidity (odds ratio, 3.56 [CI, 1.10 to 11.54]; P = .03) and prolonged postoperative length of stay (LOS; LOS >7 days; odds ratio, 5.60 [1.54 to 20.35]; P = .01]. A trend toward increased mortality did not reach statistical significance.

Conclusions: In ES, iAEs are independently associated with significantly higher postoperative morbidity and prolonged LOS.
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http://dx.doi.org/10.1016/j.amjsurg.2015.07.023DOI Listing
July 2016

A phylogeny-based sampling strategy and power calculator informs genome-wide associations study design for microbial pathogens.

Genome Med 2014 15;6(11):101. Epub 2014 Nov 15.

Department of Global Health and Social Medicine, Harvard Medical School, 641 Huntington Avenue Suite 4A, Boston, MA 02115 USA ; Department of Epidemiology, Harvard School of Public Health, Boston, MA USA.

Whole genome sequencing is increasingly used to study phenotypic variation among infectious pathogens and to evaluate their relative transmissibility, virulence, and immunogenicity. To date, relatively little has been published on how and how many pathogen strains should be selected for studies associating phenotype and genotype. There are specific challenges when identifying genetic associations in bacteria which often comprise highly structured populations. Here we consider general methodological questions related to sampling and analysis focusing on clonal to moderately recombining pathogens. We propose that a matched sampling scheme constitutes an efficient study design, and provide a power calculator based on phylogenetic convergence. We demonstrate this approach by applying it to genomic datasets for two microbial pathogens: Mycobacterium tuberculosis and Campylobacter species.
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http://dx.doi.org/10.1186/s13073-014-0101-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4256898PMC
December 2014

Systematic review of allelic exchange experiments aimed at identifying mutations that confer drug resistance in Mycobacterium tuberculosis.

J Antimicrob Chemother 2014 Feb 20;69(2):331-42. Epub 2013 Sep 20.

Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA.

Background: Improving our understanding of the relationship between the genotype and the drug resistance phenotype of Mycobacterium tuberculosis will aid the development of more accurate molecular diagnostics for drug-resistant tuberculosis. Studies that use direct genetic manipulation to identify the mutations that cause M. tuberculosis drug resistance are superior to associational studies in elucidating an individual mutation's contribution to the drug resistance phenotype.

Methods: We systematically reviewed the literature for publications reporting allelic exchange experiments in any of the resistance-associated M. tuberculosis genes. We included studies that introduced single point mutations using specialized linkage transduction or site-directed/in vitro mutagenesis and documented a change in the resistance phenotype.

Results: We summarize evidence supporting the causal relationship of 54 different mutations in eight genes (katG, inhA, kasA, embB, embC, rpoB, gyrA and gyrB) and one intergenic region (furA-katG) with resistance to isoniazid, the rifamycins, ethambutol and fluoroquinolones. We observed a significant role for the strain genomic background in modulating the resistance phenotype of 21 of these mutations and found examples of where the same drug resistance mutations caused varying levels of resistance to different members of the same drug class.

Conclusions: This systematic review highlights those mutations that have been shown to causally change phenotypic resistance in M. tuberculosis and brings attention to a notable lack of allelic exchange data for several of the genes known to be associated with drug resistance.
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http://dx.doi.org/10.1093/jac/dkt358DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886931PMC
February 2014

Genomic analysis identifies targets of convergent positive selection in drug-resistant Mycobacterium tuberculosis.

Nat Genet 2013 Oct 1;45(10):1183-9. Epub 2013 Sep 1.

1] Pulmonary and Critical Care Division, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. [2].

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.
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http://dx.doi.org/10.1038/ng.2747DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3887553PMC
October 2013

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 2011 25;15(1):R72. Epub 2011 Feb 25.

Division of Critical Care Medicine, University of Alberta, 3C1,12 Walter C, Mackenzie Centre, 8440-122 Street, Edmonton, AB T6G2B7, Canada.

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.
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http://dx.doi.org/10.1186/cc10061DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3222005PMC
December 2011

Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production.

PLoS Comput Biol 2009 Aug 28;5(8):e1000489. Epub 2009 Aug 28.

Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.

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.
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http://dx.doi.org/10.1371/journal.pcbi.1000489DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2726785PMC
August 2009
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