A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simple diagnostic test. Adult case-control cohorts were established in South Africa and Malawi of HIV-infected or -uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB] from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differential diagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized into training (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantly differentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcript signature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, we used a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on this score was first evaluated in the test cohort, and then validated in an independent publically available dataset (GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87–100]; specificity 90%, 95% CI [80–97]) and TB from OD (sensitivity 93%, 95% CI [83–100]; specificity 88%, 95% CI [74–97]). In the independent validation cohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85–100]; specificity 94%, 95% CI [84–100]) and OD patients (sensitivity 100%, 95% CI [100–100]; specificity 96%, 95% CI [93–100]). Limitations of our study include the use of only culture confirmed TB patients, and the potential that TB may have been misdiagnosed in a small proportion of OD patients despite the extensive clinical investigation used to assign each patient to their diagnostic group. In our study, blood transcriptional signatures distinguished TB from other conditions prevalent in HIV-infected and -uninfected African adults. Our DRS, based on these signatures, could be developed as a test for TB suitable for use in HIV endemic countries. Further evaluation of the performance of the signatures and DRS in prospective populations of patients with symptoms consistent with TB will be needed to define their clinical value under operational conditions. Please see later in the article for the Editors' Summary Tuberculosis (TB), caused by Mycobacterium tuberculosis, is curable and preventable, but according to the World Health Organization (WHO), in 2011, 8.7 million people had symptoms of TB (usually a productive cough and fever) and 1.4 million people—95% from low- and middle-income countries—died from this infection. Worldwide, TB is also the leading cause of death in people with HIV. For over a century, diagnosis of TB has relied on clinical and radiological features, sputum microscopy, and tuberculin skin testing but all of these tests have major disadvantages, especially in people who are also infected with HIV (HIV/TB co-infection) in whom results are often atypical or falsely negative. Furthermore, current tests cannot distinguish between inactive (latent) and active TB infection. Therefore, there is a need to identify biomarkers that can differentiate TB from other diseases common to African populations, where the burden of the HIV/TB pandemic is greatest. Previous studies have suggested that TB may be associated with specific transcriptional profiles (identified by microarray analysis) in the blood of the infected patient (host), which might make it possible to differentiate TB from other conditions. However, these studies have not included people co-infected with HIV and have included in the differential diagnosis diseases that are unrepresentative of the range of conditions common to African patients. In this study of patients from Malawi and South Africa, the researchers investigated whether blood RNA expression could distinguish TB from other conditions prevalent in African populations and form the basis of a diagnostic test for TB (through a process using transcription signatures). The researchers recruited patients with suspected TB attending one clinic in Cape Town, South Africa between 2007 and 2010 and in one hospital in Karonga district, Malawi between 2007 and 2009 (the training and test cohorts). Each patient underwent a series of tests for TB (and had a blood test for HIV) and was diagnosed as having TB if there was microbiological evidence confirming the presence of Mycobacterium tuberculosis. At recruitment, each patient also had blood taken for microarray analysis and following this assessment, the researchers selected minimal transcript sets that distinguished TB from latent TB infection and TB from other diseases, even in HIV-infected individuals. In order to help form the basis of a simple, low cost, diagnostic test, the researchers then developed a statistical method for the translation of multiple transcript RNA signatures into a disease risk score, which the researchers then checked using a separate cohort of South African patients (the independent validation cohort). Using these methods, after screening 437 patients in Malawi and 314 in South Africa, the researchers recruited 273 patients to the Malawi cohort and 311 adults to the South African cohort (the training and test cohorts). Following technical failures, 536 microarray samples were available for analysis. The researchers identified a set of 27 transcripts that could distinguish between TB and latent TB and a set of 44 transcripts that could distinguish TB from other diseases. These multi-transcript signatures were then used to calculate a single value disease risk score for every patient. In the test cohorts, the disease risk score had a high sensitivity (95%) and specificity (90%) for distinguishing TB from latent TB infection (sensitivity is a measure of true positives, correctly identified as such and specificity is a measure of true negatives, correctly identified as such) and for distinguishing TB from other diseases (sensitivity 93% and specificity 88%). In the independent validation cohort, the researchers found that patients with TB could be distinguished from patients with latent TB infection (sensitivity 95% and specificity 94%) and also from patients with other diseases (sensitivity 100% and specificity 96%). These findings suggest that a distinctive set of RNA transcriptional signatures forming a disease risk score might provide the basis of a diagnostic test that can distinguish active TB from latent TB infection (27 signatures) and also from other diseases (44 signatures), such as pneumonia, that are prevalent in African populations. There is a concern that using transcriptional signatures as a clinical diagnostic tool in resource poor settings might not be feasible because they are complex and costly. The relatively small number of transcripts in the signatures described here may increase the potential for using this approach (transcriptional profiling) as a clinical diagnostic tool using a single blood test. In order to make most use of these findings, there is an urgent need for the academic research community and for industry to develop innovative methods to translate multi-transcript signatures into simple, cheap tests for TB suitable for use in African health facilities. Please access these websites via the online version of this summary at http://dx.doi.org/ 10.1371/journal.pmed.1001538.

Improved diagnostic tests for tuberculosis in children are needed. We hypothesized that transcriptional signatures of host blood could be used to distinguish tuberculosis from other diseases in African children who either were or were not infected with the human immunodeficiency virus (HIV). The study population comprised prospective cohorts of children who were undergoing evaluation for suspected tuberculosis in South Africa (655 children), Malawi (701 children), and Kenya (1599 children). Patients were assigned to groups according to whether the diagnosis was culture-confirmed tuberculosis, culture-negative tuberculosis, diseases other than tuberculosis, or latent tuberculosis infection. Diagnostic signatures distinguishing tuberculosis from other diseases and from latent tuberculosis infection were identified from genomewide analysis of RNA expression in host blood. We identified a 51-transcript signature distinguishing tuberculosis from other diseases in the South African and Malawian children (the discovery cohort). In the Kenyan children (the validation cohort), a risk score based on the signature for tuberculosis and for diseases other than tuberculosis showed a sensitivity of 82.9% (95% confidence interval [CI], 68.6 to 94.3) and a specificity of 83.6% (95% CI, 74.6 to 92.7) for the diagnosis of culture-confirmed tuberculosis. Among patients with cultures negative for Mycobacterium tuberculosis who were treated for tuberculosis (those with highly probable, probable, or possible cases of tuberculosis), the estimated sensitivity was 62.5 to 82.3%, 42.1 to 80.8%, and 35.3 to 79.6%, respectively, for different estimates of actual tuberculosis in the groups. In comparison, the sensitivity of the Xpert MTB/RIF assay for molecular detection of M. tuberculosis DNA in cases of culture-confirmed tuberculosis was 54.3% (95% CI, 37.1 to 68.6), and the sensitivity in highly probable, probable, or possible cases was an estimated 25.0 to 35.7%, 5.3 to 13.3%, and 0%, respectively; the specificity of the assay was 100%. RNA expression signatures provided data that helped distinguish tuberculosis from other diseases in African children with and those without HIV infection. (Funded by the European Union Action for Diseases of Poverty Program and others).

The majority of febrile children have self-resolving viral infection, but a small proportion have life-threatening bacterial infections. Although culture of bacteria from normally sterile sites remains the gold standard for confirming bacterial infection, culture results may take several days and are frequently negative when infection resides in inaccessible sites or when antibiotics have been previously administered.^1-3 Current practice is to admit ill-appearing febrile children to the hospital and administer parenteral antibiotics while awaiting culture results.^4-6 Because only a minority of febrile children are ultimately proven to have bacterial infection, the process of ruling out bacterial infection results in a major burden on health care resources and in inappropriate antibiotic prescription.⁷

Kawasaki disease (KD) is a pediatric vasculitis that damages the coronary arteries in 25% of untreated and approximately 5% of treated children. Epidemiologic data suggest that KD is triggered by unidentified infection(s) in genetically susceptible children. To investigate genetic determinants of KD susceptibility, we performed a genome-wide association study (GWAS) in 119 Caucasian KD cases and 135 matched controls with stringent correction for possible admixture, followed by replication in an independent cohort and subsequent fine-mapping, for a total of 893 KD cases plus population and family controls. Significant associations of 40 SNPs and six haplotypes, identifying 31 genes, were replicated in an independent cohort of 583 predominantly Caucasian KD families, with NAALADL2 (rs17531088, p_combined = 1.13×10⁻⁶) and ZFHX3 (rs7199343, p_combined = 2.37×10⁻⁶) most significantly associated. Sixteen associated variants with a minor allele frequency of >0.05 that lay within or close to known genes were fine-mapped with HapMap tagging SNPs in 781 KD cases, including 590 from the discovery and replication stages. Original or tagging SNPs in eight of these genes replicated the original findings, with seven genes having further significant markers in adjacent regions. In four genes (ZFHX3, NAALADL2, PPP1R14C, and TCP1), the neighboring markers were more significantly associated than the originally associated variants. Investigation of functional relationships between the eight fine-mapped genes using Ingenuity Pathway Analysis identified a single functional network (p = 10⁻¹³) containing five fine-mapped genes—LNX1, CAMK2D, ZFHX3, CSMD1, and TCP1—with functional relationships potentially related to inflammation, apoptosis, and cardiovascular pathology. Pair-wise blood transcript levels were measured during acute and convalescent KD for all fine-mapped genes, revealing a consistent trend of significantly reduced transcript levels prior to treatment. This is one of the first GWAS in an infectious disease. We have identified novel, plausible, and functionally related variants associated with KD susceptibility that may also be relevant to other cardiovascular diseases. Kawasaki disease is an inflammatory pediatric condition that damages the coronary arteries in a quarter of untreated patients and is the commonest cause of childhood acquired heart disease in developed countries. While the infectious trigger(s) remain unknown, epidemiologic evidence suggests that human genetic variation underlies the susceptibility. In order to identify novel mechanisms that may predispose to this disease, we undertook a genome-wide association study, which investigates genetic determinants without prior supposition regarding the loci of interest. This was amongst the first complex infectious diseases to be studied in this way and one of the largest genetic studies of Kawasaki disease with 893 cases. We identified and confirmed 40 SNPs and six haplotypes, identifying 31 genes, in an international cohort of Caucasian patients. We followed up 16 SNPs where the associated genetic variant was more common and was situated within a gene, confirming eight SNPs by fine-mapping across the entire gene. Of these eight genes, seven were expressed in blood and five showed significantly different gene expression in paired patient samples taken during acute and convalescent Kawasaki disease. Five of the eight genes also appear to be involved in a single putative functional network of interacting genes. These novel genes and pathways may ultimately lead to novel diagnostics and treatment for Kawasaki disease.

Background: Global gene expression profiling can provide insight into the underlying pathophysiology of disease processes. Kawasaki disease (KD) is an acute, self-limited vasculitis whose etiology remains unknown. Although the clinical illness shares certain features with other pediatric infectious diseases, the occurrence of coronary artery aneurysms in 25% of untreated patients is unique to KD. Methods: To gain further insight into the molecular mechanisms underlying KD, we investigated the acute and convalescent whole blood transcriptional profiles of 146 KD subjects and compared them with the transcriptional profiles of pediatric patients with confirmed bacterial or viral infection, and with healthy control children. We also investigated the transcript abundance in patients with different intravenous immunoglobulin treatment responses and different coronary artery outcomes. Results: The overwhelming signature for acute KD involved signaling pathways of the innate immune system. Comparison with other acute pediatric infections highlighted the importance of pathways involved in cell motility including paxillin, relaxin, actin, integrins, and matrix metalloproteinases. Most importantly, the IL1β pathway was identified as a potential therapeutic target. Conclusion: Our study revealed the importance of the IL-1 signaling pathway and a prominent signature of innate immunity and cell migration in the acute phase of the illness.