Integrated genetic, epigenetic, and immune landscape of TP53 mutant AML and higher risk MDS treated with azacitidine.

Background: TP53 mutations are associated with an adverse prognosis in acute myeloid leukemia (AML) and higher-risk myelodysplastic syndromes (HR-MDS). However, the integrated genetic, epigenetic, and immunologic landscape of TP53-mutated AML/HR-MDS is not well defined. Objectives: To define the genetic, epigenetic, and immunologic landscape of TP53-mutant and TP53 wild-type AML and HR-MDS patients. Design: Post hoc analysis of TP53-mutant and TP53 wild-type patients treated on the randomized FUSION trial with azacitidine ± the anti-PD-L1 antibody durvalumab. Methods: We performed extensive molecular, epigenetic, and immunologic assays on a well-annotated clinical trial dataset of 61 patients with TP53-mutated disease (37 AML, 24 MDS) and 144 TP53 wild-type (89 AML, 55 MDS) patients, all of whom received azacitidine-based therapy. A 38 gene-targeted myeloid mutation analysis from screening bone marrow (BM) was performed. DNA methylation arrays, immunophenotyping and immune checkpoint expression by flow cytometry, and gene expression profiles by bulk RNA sequencing were assessed at baseline and serially during the trial. Results: Global DNA methylation from peripheral blood was independent of TP53 mutation and allelic status. AZA therapy led to a statistically significant decrease in global DNA methylation scores independent of TP53 mutation status. In BM from TP53-mutant patients, we found both a higher T-cell population and upregulation of inhibitory immune checkpoint proteins such as PD-L1 compared to TP53 wild-type. RNA sequencing analyses revealed higher expression of the myeloid immune checkpoint gene LILRB3 in TP53-mutant samples suggesting a novel therapeutic target. Conclusion: This integrated analysis of the genetic, epigenetic, and immunophenotypic landscape of TP53 mutant AML/HR-MDS suggests that differences in the immune landscape resulting in an immunosuppressive microenvironment rather than epigenetic differences contribute to the poor prognosis of TP53-mutant AML/HR-MDS with mono- or multihit TP53 mutation status. Trial registration: FUSION trial (NCT02775903).

Linkage Mapping and Genome-Wide Association Study Identified Two Peanut Late Leaf Spot Resistance Loci, PLLSR-1 and PLLSR-2, Using Nested Association Mapping.

Identification of candidate genes and molecular markers for late leaf spot (LLS) disease resistance in peanut (Arachis hypogaea) has been a focus of molecular breeding for the U.S. industry-funded peanut genome project. Efforts have been hindered by limited mapping resolution due to low levels of genetic recombination and marker density available in traditional biparental mapping populations. To address this, a multi-parental nested association mapping population has been genotyped with the peanut 58K single-nucleotide polymorphism (SNP) array and phenotyped for LLS severity in the field for 3 years. Joint linkage-based quantitative trait locus (QTL) mapping identified nine QTLs for LLS resistance with significant phenotypic variance explained up to 47.7%. A genome-wide association study identified 13 SNPs consistently associated with LLS resistance. Two genomic regions harboring the consistent QTLs and SNPs were identified from 1,336 to 1,520 kb (184 kb) on chromosome B02 and from 1,026.9 to 1,793.2 kb (767 kb) on chromosome B03, designated as peanut LLS resistance loci, PLLSR-1 and PLLSR-2, respectively. PLLSR-1 contains 10 nucleotide-binding site leucine-rich repeat disease resistance genes. A nucleotide-binding site leucine-rich repeat disease resistance gene, Arahy.VKVT6A, was also identified on homoeologous chromosome A02. PLLSR-2 contains five significant SNPs associated with five different genes encoding callose synthase, pollen defective in guidance protein, pentatricopeptide repeat, acyl-activating enzyme, and C2 GRAM domains-containing protein. This study highlights the power of multi-parent populations such as nested association mapping for genetic mapping and marker-trait association studies in peanuts. Validation of these two LLS resistance loci will be needed for marker-assisted breeding.

Nonequilibrium sensing of volatile compounds using active and passive analyte delivery.

Although sensor technologies have allowed us to outperform the human senses of sight, hearing, and touch, the development of artificial noses is significantly behind their biological counterparts. This largely stems from the sophistication of natural olfaction, which relies on both fluid dynamics within the nasal anatomy and the response patterns of hundreds to thousands of unique molecular-scale receptors. We designed a sensing approach to identify volatiles inspired by the fluid dynamics of the nose, allowing us to extract information from a single sensor (here, the reflectance spectra from a mesoporous one-dimensional photonic crystal) rather than relying on a large sensor array. By accentuating differences in the nonequilibrium mass-transport dynamics of vapors and training a machine learning algorithm on the sensor output, we clearly identified polar and nonpolar volatile compounds, determined the mixing ratios of binary mixtures, and accurately predicted the boiling point, flash point, vapor pressure, and viscosity of a number of volatile liquids, including several that had not been used for training the model. We further implemented a bioinspired active sniffing approach, in which the analyte delivery was performed in well-controlled 'inhale-exhale' sequences, enabling an additional modality of differentiation and reducing the duration of data collection and analysis to seconds. Our results outline a strategy to build accurate and rapid artificial noses for volatile compounds that can provide useful information such as the composition and physical properties of chemicals, and can be applied in a variety of fields, including disease diagnosis, hazardous waste management, and healthy building monitoring.

Neutrophil degranulation, NETosis and platelet degranulation pathway genes are co-induced in whole blood up to six months before tuberculosis diagnosis.

Mycobacterium tuberculosis (M.tb) causes tuberculosis (TB) and remains one of the leading causes of mortality due to an infectious pathogen. Host immune responses have been implicated in driving the progression from infection to severe lung disease. We analyzed longitudinal RNA sequencing (RNAseq) data from the whole blood of 74 TB progressors whose samples were grouped into four six-month intervals preceding diagnosis (the GC6-74 study). We additionally analyzed RNAseq data from an independent cohort of 90 TB patients with positron emission tomography-computed tomography (PET-CT) scan results which were used to categorize them into groups with high and low levels of lung damage (the Catalysis TB Biomarker study). These groups were compared to non-TB controls to obtain a complete whole blood transcriptional profile for individuals spanning from early stages of M.tb infection to TB diagnosis. The results revealed a steady increase in the number of genes that were differentially expressed in progressors at time points closer to diagnosis with 278 genes at 13-18 months, 742 at 7-12 months and 5,131 detected 1-6 months before diagnosis and 9,205 detected in TB patients. A total of 2,144 differentially expressed genes were detected when comparing TB patients with high and low levels of lung damage. There was a large overlap in the genes upregulated in progressors 1-6 months before diagnosis (86%) with those in TB patients. A comprehensive pathway analysis revealed a potent activation of neutrophil and platelet mediated defenses including neutrophil and platelet degranulation, and NET formation at both time points. These pathways were also enriched in TB patients with high levels of lung damage compared to those with low. These findings suggest that neutrophils and platelets play a critical role in TB pathogenesis, and provide details of the timing of specific effector mechanisms that may contribute to TB lung pathology.

A randomized phase 2 trial of azacitidine with or without durvalumab as first-line therapy for higher-risk myelodysplastic syndromes.

Azacitidine-mediated hypomethylation promotes tumor cell immune recognition but may increase the expression of inhibitory immune checkpoint molecules. We conducted the first randomized phase 2 study of azacitidine plus the immune checkpoint inhibitor durvalumab vs azacitidine monotherapy as first-line treatment for higher-risk myelodysplastic syndromes (HR-MDS). In all, 84 patients received 75 mg/m2 subcutaneous azacitidine (days 1-7 every 4 weeks) combined with 1500 mg intravenous durvalumab on day 1 every 4 weeks (Arm A) for at least 6 cycles or 75 mg/m² subcutaneous azacitidine alone (days 1-7 every 4 weeks) for at least 6 cycles (Arm B). After a median follow-up of 15.25 months, 8 patients in Arm A and 6 in Arm B remained on treatment. Patients in Arm A received a median of 7.9 treatment cycles and those in Arm B received a median of 7.0 treatment cycles with 73.7% and 65.9%, respectively, completing ≥4 cycles. The overall response rate (primary end point) was 61.9% in Arm A (26 of 42) and 47.6% in Arm B (20 of 42; P = .18), and median overall survival was 11.6 months (95% confidence interval, 9.5 months to not evaluable) vs 16.7 months (95% confidence interval, 9.8-23.5 months; P = .74). Durvalumab-related adverse events (AEs) were reported by 71.1% of patients; azacitidine-related AEs were reported by 82% (Arm A) and 81% (Arm B). Grade 3 or 4 hematologic AEs were reported in 89.5% (Arm A) vs 68.3% (Arm B) of patients. Patients with TP53 mutations tended to have a worse response than patients without these mutations. Azacitidine increased programmed cell death ligand 1 (PD-L1 [CD274]) surface expression on bone marrow granulocytes and monocytes, but not blasts, in both arms. In summary, combining azacitidine with durvalumab in patients with HR-MDS was feasible but with more toxicities and without significant improvement in clinical outcomes over azacitidine alone. This trial was registered at www.clinicaltrials.gov as #NCT02775903.

A randomized phase 2 trial of azacitidine with or without durvalumab as first-line therapy for older patients with AML.

Evidence suggests that combining immunotherapy with hypomethylating agents may enhance antitumor activity. This phase 2 study investigated the activity and safety of durvalumab, a programmed death-ligand 1 (PD-L1) inhibitor, combined with azacitidine for patients aged ≥65 years with acute myeloid leukemia (AML), including analyses to identify biomarkers of treatment response. Patients were randomized to first-line therapy with azacitidine 75 mg/m2 on days 1 through 7 with (Arm A, n = 64) or without (Arm B, n = 65) durvalumab 1500 mg on day 1 every 4 weeks. Overall response rate (complete response [CR] + CR with incomplete blood recovery) was similar in both arms (Arm A, 31.3%; Arm B, 35.4%), as were overall survival (Arm A, 13.0 months; Arm B, 14.4 months) and duration of response (Arm A, 24.6 weeks; Arm B, 51.7 weeks; P = .0765). No new safety signals emerged with combination treatment. The most frequently reported treatment-emergent adverse events were constipation (Arm A, 57.8%; Arm B, 53.2%) and thrombocytopenia (Arm A, 42.2%; Arm B, 45.2%). DNA methylation, mutational status, and PD-L1 expression were not associated with response to treatment. In this study, first-line combination therapy with durvalumab and azacitidine in older patients with AML was feasible but did not improve clinical efficacy compared with azacitidine alone. ClinicalTrials.gov: NCT02775903.

Sox2 Is an Oncogenic Driver of Small-Cell Lung Cancer and Promotes the Classic Neuroendocrine Subtype.

Although many cancer prognoses have improved in the past 50 years due to advancements in treatments, there has been little improvement in therapies for small-cell lung cancer (SCLC). One promising avenue to improve treatment for SCLC is to understand its underlying genetic alterations that drive its formation, growth, and cellular heterogeneity. RB1 loss is one key driver of SCLC, and RB1 loss has been associated with an increase in pluripotency factors such as SOX2. SOX2 is highly expressed and amplified in SCLC and has been associated with SCLC growth. Using a genetically engineered mouse model, we have shown that Sox2 is required for efficient SCLC formation. Furthermore, genome-scale binding assays have indicated that SOX2 can regulate key SCLC pathways such as NEUROD1 and MYC. These data suggest that SOX2 can be associated with the switch of SCLC from an ASCL1 subtype to a NEUROD1 subtype. Understanding this genetic switch is key to understanding such processes as SCLC progression, cellular heterogeneity, and treatment resistance. IMPLICATIONS: Understanding the molecular mechanisms of SCLC initiation and development are key to opening new potential therapeutic options for this devastating disease.

Immunomodulation by durvalumab and pomalidomide in patients with relapsed/refractory multiple myeloma.

This study sought to understand how the programmed death ligand 1 (PD-L1) inhibitor durvalumab and the immunomodulatory agent pomalidomide regulate immune cell activation and function in patients with relapsed/refractory (RR) multiple myeloma (MM). Immunologic changes in peripheral blood and bone marrow of patients treated with durvalumab as monotherapy or in combination with pomalidomide with/without dexamethasone were characterized by assessing subsets of immune cells and gene signatures to understand the immunomodulatory effect of the treatment. Soluble PD-L1 levels were elevated at screening in patients with RRMM but did not correlate with response to durvalumab combination therapy. Immune cell subsets were increased in peripheral blood during treatment with durvalumab and pomalidomide, and combination therapy induced significant gene expression changes in the MM tumor microenvironment versus durvalumab alone. Estimation of cell populations based on RNA sequencing data revealed increased monocytes, neutrophils, and natural killer cells with the combination therapy, but not with durvalumab alone. Additionally, multiplex immunofluorescence of bone marrow demonstrated that immune populations were different in responders versus nonresponders to durvalumab plus pomalidomide with dexamethasone therapy. Overall, durvalumab effectively blocked soluble PD-L1; however, durvalumab monotherapy was not associated with immunologic changes, which were observed with combination therapy.

The Ratiometric Transcript Signature MX2/GPR183 Is Consistently Associated With RTS,S-Mediated Protection Against Controlled Human Malaria Infection.

The RTS,S/AS01 vaccine provides partial protection against Plasmodium falciparum infection but determinants of protection and/or disease are unclear. Previously, anti-circumsporozoite protein (CSP) antibody titers and blood RNA signatures were associated with RTS,S/AS01 efficacy against controlled human malaria infection (CHMI). By analyzing host blood transcriptomes from five RTS,S vaccination CHMI studies, we demonstrate that the transcript ratio MX2/GPR183, measured 1 day after third immunization, discriminates protected from non-protected individuals. This ratiometric signature provides information that is complementary to anti-CSP titer levels for identifying RTS,S/AS01 immunized people who developed protective immunity and suggests a role for interferon and oxysterol signaling in the RTS,S mode of action.

RISK6, a 6-gene transcriptomic signature of TB disease risk, diagnosis and treatment response.

Improved tuberculosis diagnostics and tools for monitoring treatment response are urgently needed. We developed a robust and simple, PCR-based host-blood transcriptomic signature, RISK6, for multiple applications: identifying individuals at risk of incident disease, as a screening test for subclinical or clinical tuberculosis, and for monitoring tuberculosis treatment. RISK6 utility was validated by blind prediction using quantitative real-time (qRT) PCR in seven independent cohorts. Prognostic performance significantly exceeded that of previous signatures discovered in the same cohort. Performance for diagnosing subclinical and clinical disease in HIV-uninfected and HIV-infected persons, assessed by area under the receiver-operating characteristic curve, exceeded 85%. As a screening test for tuberculosis, the sensitivity at 90% specificity met or approached the benchmarks set out in World Health Organization target product profiles for non-sputum-based tests. RISK6 scores correlated with lung immunopathology activity, measured by positron emission tomography, and tracked treatment response, demonstrating utility as treatment response biomarker, while predicting treatment failure prior to treatment initiation. Performance of the test in capillary blood samples collected by finger-prick was noninferior to venous blood collected in PAXgene tubes. These results support incorporation of RISK6 into rapid, capillary blood-based point-of-care PCR devices for prospective assessment in field studies.

Counterflow Gradient Focusing in Free-Flow Electrophoresis for Protein Fractionation.

With its ability to continuously separate and collect charged analytes, free-flow electrophoresis (FFE) has become a useful tool for the purification and real-time analysis of biological mixtures. This work presents a new free-flow counterflow gradient focusing (FF-CGF) mechanism that uses a novel velocity gradient to counterbalance electrophoretic migration. This counterflow gradient is created by simply introducing fluid flow through the sidewalls of the FFE chamber. The theoretical foundation and device design for FF-CGF are provided in this work, followed by implementation and validation, with a detailed discussion on future opportunities and challenges. Initial results show promise, with the potential to improve FFE resolution and offer versatility. Compared to existing focusing techniques, such as free-flow isotachophoresis and isoelectric focusing, no complex buffer compositions are required.

The Peripheral Blood Transcriptome Is Correlated With PET Measures of Lung Inflammation During Successful Tuberculosis Treatment.

Pulmonary tuberculosis (PTB) is characterized by lung granulomas, inflammation and tissue destruction. Here we used within-subject peripheral blood gene expression over time to correlate with the within-subject lung metabolic activity, as measured by positron emission tomography (PET) to identify biological processes and pathways underlying overall resolution of lung inflammation. We used next-generation RNA sequencing and [18F]FDG PET-CT data, collected at diagnosis, week 4, and week 24, from 75 successfully cured PTB patients, with the [18F]FDG activity as a surrogate for lung inflammation. Our linear mixed-effects models required that for each individual the slope of the line of [18F]FDG data in the outcome and the slope of the peripheral blood transcript expression data correlate, i.e., the slopes of the outcome and explanatory variables had to be similar. Of 10,295 genes that changed as a function of time, we identified 639 genes whose expression profiles correlated with decreasing [18F]FDG uptake levels in the lungs. Gene enrichment over-representation analysis revealed that numerous biological processes were significantly enriched in the 639 genes, including several well known in TB transcriptomics such as platelet degranulation and response to interferon gamma, thus validating our novel approach. Others not previously associated with TB pathobiology included smooth muscle contraction, a set of pathways related to mitochondrial function and cell death, as well as a set of pathways connecting transcription, translation and vesicle formation. We observed up-regulation in genes associated with B cells, and down-regulation in genes associated with platelet activation. We found 254 transcription factor binding sites to be enriched among the 639 gene promoters. In conclusion, we demonstrated that of the 10,295 gene expression changes in peripheral blood, only a subset of 639 genes correlated with inflammation in the lungs, and the enriched pathways provide a description of the biology of resolution of lung inflammation as detectable in peripheral blood. Surprisingly, resolution of PTB inflammation is positively correlated with smooth muscle contraction and, extending our previous observation on mitochondrial genes, shows the presence of mitochondrial stress. We focused on pathway analysis which can enable therapeutic target discovery and potential modulation of the host response to TB.

Correction: Discovery and validation of a prognostic proteomic signature for tuberculosis progression: A prospective cohort study.

[This corrects the article DOI: 10.1371/journal.pmed.1002781.].

Detection of Tuberculosis Recurrence, Diagnosis and Treatment Response by a Blood Transcriptomic Risk Signature in HIV-Infected Persons on Antiretroviral Therapy.

HIV-infected individuals are at high risk of tuberculosis disease and those with prior tuberculosis episodes are at even higher risk of disease recurrence. A non-sputum biomarker that identifies individuals at highest tuberculosis risk would allow targeted microbiological testing and appropriate treatment and also guide need for prolonged therapy. We determined the utility of a previously developed whole blood transcriptomic correlate of risk (COR) signature for (1) predicting incident recurrent tuberculosis, (2) tuberculosis diagnosis and (3) its potential utility for tuberculosis treatment monitoring in HIV-infected individuals. We retrieved cryopreserved blood specimens from three previously completed clinical studies and measured the COR signature by quantitative microfluidic real-time-PCR. The signature differentiated recurrent tuberculosis progressors from non-progressors within 3 months of diagnosis with an area under the Receiver-operating characteristic (ROC) curve (AUC) of 0.72 (95% confidence interval (CI), 0.58-0.85) amongst HIV-infected individuals on antiretroviral therapy (ART). Twenty-five of 43 progressors (58%) were asymptomatic at microbiological diagnosis and thus had subclinical disease. The signature showed excellent diagnostic discrimination between HIV-uninfected tuberculosis cases and controls (AUC 0.97; 95%CI 0.94-1). Performance was lower in HIV-infected individuals (AUC 0.83; 95%CI 0.81-0.96) and signature scores were directly associated with HIV viral loads. Tuberculosis treatment response in HIV-infected individuals on ART with a new recurrent tuberculosis diagnosis was also assessed. Signature scores decreased significantly during treatment. However, pre-treatment scores could not differentiate between those who became sputum negative before and after 2 months. Direct application of the unmodified blood transcriptomic COR signature detected subclinical and active tuberculosis by blind validation in HIV-infected individuals. However, prognostic performance for recurrent tuberculosis, and performance as diagnostic and as treatment monitoring tool in HIV-infected persons was inferior to published results from HIV-negative cohorts. Our results suggest that performance of transcriptomic signatures comprising interferon stimulated genes are negatively affected in HIV-infected individuals, especially in those with incompletely suppressed viral loads.

Multinomial modelling of TB/HIV co-infection yields a robust predictive signature and generates hypotheses about the HIV+TB+ disease state.

BACKGROUND: Current diagnostics are inadequate to meet the challenges presented by co-infection with Mycobacterium tuberculosis (Mtb) and HIV, the leading cause of death for HIV-infected individuals. Improved characterization of Mtb/HIV coinfection as a distinct disease state may lead to better identification and treatment of affected individuals. METHODS: Four previously-published TB and HIV co-infection related datasets were used to train and validate multinomial machine learning classifiers that simultaneously predict TB and HIV status. Classifier predictive performance was measured using leave-one-out cross validation on the training set and blind predictive performance on multiple test sets using area under the ROC curve (AUC) as the performance metric. Linear modelling of signature gene expression was applied to systematically classify genes as TB-only, HIV-only or combined TB/HIV. RESULTS: The optimal signature discovered was a 10-gene random forest multinomial signature that robustly discriminated active tuberculosis (TB) from other non-TB disease states with improved performance compared with previously published signatures (AUC: 0.87), and specifically discriminated active TB/HIV co-infection from all other conditions (AUC: 0.88). Signature genes exhibited a variety of transcriptional patterns including both TB-only and HIV-only response genes and genes with expression patterns driven by interactions between HIV and TB infection states, including the CD8+ T-cell receptor LAG3 and the apoptosis-related gene CERKL. CONCLUSIONS: By explicitly including distinct disease states within the machine learning analysis framework, we developed a compact and highly diagnostic signature that simultaneously discriminates multiple disease states associated with Mtb/HIV co-infection. Examination of the expression patterns of signature genes suggests mechanisms underlying the unique inflammatory conditions associated with active TB in the presence of HIV. In particular, we observed that dysregulation of CD8+ effector T-cell and NK-cell associated genes may be an important feature of Mtb/HIV co-infection.

Immunometabolic Signatures Predict Risk of Progression to Active Tuberculosis and Disease Outcome.

There remains a pressing need for biomarkers that can predict who will progress to active tuberculosis (TB) after exposure to Mycobacterium tuberculosis (MTB) bacterium. By analyzing cohorts of household contacts of TB index cases (HHCs) and a stringent non-human primate (NHP) challenge model, we evaluated whether integration of blood transcriptional profiling with serum metabolomic profiling can provide new understanding of disease processes and enable improved prediction of TB progression. Compared to either alone, the combined application of pre-existing transcriptome- and metabolome-based signatures more accurately predicted TB progression in the HHC cohorts and more accurately predicted disease severity in the NHPs. Pathway and data-driven correlation analyses of the integrated transcriptional and metabolomic datasets further identified novel immunometabolomic signatures significantly associated with TB progression in HHCs and NHPs, implicating cortisol, tryptophan, glutathione, and tRNA acylation networks. These results demonstrate the power of multi-omics analysis to provide new insights into complex disease processes.

Discovery and validation of a prognostic proteomic signature for tuberculosis progression: A prospective cohort study.

BACKGROUND: A nonsputum blood test capable of predicting progression of healthy individuals to active tuberculosis (TB) before clinical symptoms manifest would allow targeted treatment to curb transmission. We aimed to develop a proteomic biomarker of risk of TB progression for ultimate translation into a point-of-care diagnostic. METHODS AND FINDINGS: Proteomic TB risk signatures were discovered in a longitudinal cohort of 6,363 Mycobacterium tuberculosis-infected, HIV-negative South African adolescents aged 12-18 years (68% female) who participated in the Adolescent Cohort Study (ACS) between July 6, 2005 and April 23, 2007, through either active (every 6 months) or passive follow-up over 2 years. Forty-six individuals developed microbiologically confirmed TB disease within 2 years of follow-up and were selected as progressors; 106 nonprogressors, who remained healthy, were matched to progressors. Over 3,000 human proteins were quantified in plasma with a highly multiplexed proteomic assay (SOMAscan). Three hundred sixty-one proteins of differential abundance between progressors and nonprogressors were identified. A 5-protein signature, TB Risk Model 5 (TRM5), was discovered in the ACS training set and verified by blind prediction in the ACS test set. Poor performance on samples 13-24 months before TB diagnosis motivated discovery of a second 3-protein signature, 3-protein pair-ratio (3PR) developed using an orthogonal strategy on the full ACS subcohort. Prognostic performance of both signatures was validated in an independent cohort of 1,948 HIV-negative household TB contacts from The Gambia (aged 15-60 years, 66% female), longitudinally followed up for 2 years between March 5, 2007 and October 21, 2010, sampled at baseline, month 6, and month 18. Amongst these contacts, 34 individuals progressed to microbiologically confirmed TB disease and were included as progressors, and 115 nonprogressors were included as controls. Prognostic performance of the TRM5 signature in the ACS training set was excellent within 6 months of TB diagnosis (area under the receiver operating characteristic curve [AUC] 0.96 [95% confidence interval, 0.93-0.99]) and 6-12 months (AUC 0.76 [0.65-0.87]) before TB diagnosis. TRM5 validated with an AUC of 0.66 (0.56-0.75) within 1 year of TB diagnosis in the Gambian validation cohort. The 3PR signature yielded an AUC of 0.89 (0.84-0.95) within 6 months of TB diagnosis and 0.72 (0.64-0.81) 7-12 months before TB diagnosis in the entire South African discovery cohort and validated with an AUC of 0.65 (0.55-0.75) within 1 year of TB diagnosis in the Gambian validation cohort. Signature validation may have been limited by a systematic shift in signal magnitudes generated by differences between the validation assay when compared to the discovery assay. Further validation, especially in cohorts from non-African countries, is necessary to determine how generalizable signature performance is. CONCLUSIONS: Both proteomic TB risk signatures predicted progression to incident TB within a year of diagnosis. To our knowledge, these are the first validated prognostic proteomic signatures. Neither meet the minimum criteria as defined in the WHO Target Product Profile for a progression test. More work is required to develop such a test for practical identification of individuals for investigation of incipient, subclinical, or active TB disease for appropriate treatment and care.

Metabolite changes in blood predict the onset of tuberculosis.

New biomarkers of tuberculosis (TB) risk and disease are critical for the urgently needed control of the ongoing TB pandemic. In a prospective multisite study across Subsaharan Africa, we analyzed metabolic profiles in serum and plasma from HIV-negative, TB-exposed individuals who either progressed to TB 3-24 months post-exposure (progressors) or remained healthy (controls). We generated a trans-African metabolic biosignature for TB, which identifies future progressors both on blinded test samples and in external data sets and shows a performance of 69% sensitivity at 75% specificity in samples within 5 months of diagnosis. These prognostic metabolic signatures are consistent with development of subclinical disease prior to manifestation of active TB. Metabolic changes associated with pre-symptomatic disease are observed as early as 12 months prior to TB diagnosis, thus enabling timely interventions to prevent disease progression and transmission.

A Serum Circulating miRNA Signature for Short-Term Risk of Progression to Active Tuberculosis Among Household Contacts.

Biomarkers that predict who among recently Mycobacterium tuberculosis (MTB)-exposed individuals will progress to active tuberculosis are urgently needed. Intracellular microRNAs (miRNAs) regulate the host response to MTB and circulating miRNAs (c-miRNAs) have been developed as biomarkers for other diseases. We performed machine-learning analysis of c-miRNA measurements in the serum of adult household contacts (HHCs) of TB index cases from South Africa and Uganda and developed a c-miRNA-based signature of risk for progression to active TB. This c-miRNA-based signature significantly discriminated HHCs within 6 months of progression to active disease from HHCs that remained healthy in an independent test set [ROC area under the ROC curve (AUC) 0.74, progressors < 6 Mo to active TB and ROC AUC 0.66, up to 24 Mo to active TB], and complements the predictions of a previous cellular mRNA-based signature of TB risk.