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.].

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.

Trisomy 21 causes changes in the circulating proteome indicative of chronic autoinflammation.

Trisomy 21 (T21) causes Down syndrome (DS), but the mechanisms by which T21 produces the different disease spectrum observed in people with DS are unknown. We recently identified an activated interferon response associated with T21 in human cells of different origins, consistent with overexpression of the four interferon receptors encoded on chromosome 21, and proposed that DS could be understood partially as an interferonopathy. However, the impact of T21 on systemic signaling cascades in living individuals with DS is undefined. To address this knowledge gap, we employed proteomics approaches to analyze blood samples from 263 individuals, 165 of them with DS, leading to the identification of dozens of proteins that are consistently deregulated by T21. Most prominent among these proteins are numerous factors involved in immune control, the complement cascade, and growth factor signaling. Importantly, people with DS display higher levels of many pro-inflammatory cytokines (e.g. IL-6, MCP-1, IL-22, TNF-α) and pronounced complement consumption, resembling changes seen in type I interferonopathies and other autoinflammatory conditions. Therefore, these results are consistent with the hypothesis that increased interferon signaling caused by T21 leads to chronic immune dysregulation, and justify investigations to define the therapeutic value of immune-modulatory strategies in DS.

Discovery and Validation of a Six-Marker Serum Protein Signature for the Diagnosis of Active Pulmonary Tuberculosis.

New non-sputum biomarker tests for active tuberculosis (TB) diagnostics are of the highest priority for global TB control. We performed in-depth proteomic analysis using the 4,000-plex SOMAscan assay on 1,470 serum samples from seven countries where TB is endemic. All samples were from patients with symptoms and signs suggestive of active pulmonary TB that were systematically confirmed or ruled out for TB by culture and clinical follow-up. HIV coinfection was present in 34% of samples, and 25% were sputum smear negative. Serum protein biomarkers were identified by stability selection using L1-regularized logistic regression and by Kolmogorov-Smirnov (KS) statistics. A naive Bayes classifier using six host response markers (HR6 model), including SYWC, kallistatin, complement C9, gelsolin, testican-2, and aldolase C, performed well in a training set (area under the sensitivity-specificity curve [AUC] of 0.94) and in a blinded verification set (AUC of 0.92) to distinguish TB and non-TB samples. Differential expression was also highly significant (P < 10-20) for previously described TB markers, such as IP-10, LBP, FCG3B, and TSP4, and for many novel proteins not previously associated with TB. Proteins with the largest median fold changes were SAA (serum amyloid protein A), NPS-PLA2 (secreted phospholipase A2), and CA6 (carbonic anhydrase 6). Target product profiles (TPPs) for a non-sputum biomarker test to diagnose active TB for treatment initiation (TPP#1) and for a community-based triage or referral test (TPP#2) have been published by the WHO. With 90% sensitivity and 80% specificity, the HR6 model fell short of TPP#1 but reached TPP#2 performance criteria. In conclusion, we identified and validated a six-marker signature for active TB that warrants diagnostic development on a patient-near platform.

Potential of High-Affinity, Slow Off-Rate Modified Aptamer Reagents for Mycobacterium tuberculosis Proteins as Tools for Infection Models and Diagnostic Applications.

Direct pathogen detection in blood to diagnose active tuberculosis (TB) has been difficult due to low levels of circulating antigens or due to the lack of specific, high-affinity binding reagents and reliable assays with adequate sensitivity. We sought to determine whether slow off-rate modified aptamer (SOMAmer) reagents with subnanomolar affinity for Mycobacterium tuberculosis proteins (antigens 85A, 85B, 85C, GroES, GroEL2, DnaK, CFP10, KAD, CFP2, RplL, and Tpx) could be useful to diagnose tuberculosis. When incorporated into the multiplexed, array-based proteomic SOMAscan assay, limits of detection reached the subpicomolar range in 40% serum. Binding to native M. tuberculosis proteins was confirmed by using M. tuberculosis culture filtrate proteins and fractions from infected macrophages and via affinity capture assays and subsequent mass spectrometry. Comparison of serum from culture-positive pulmonary TB patients and TB suspects systematically ruled out for TB revealed small but statistically significant (P < 0.0001) differences in the median M. tuberculosis signals and in specific pathogen markers, such as antigen 85B. Samples where many M. tuberculosis aptamers produced high signals were rare exceptions. In concentrated, protein-normalized urine from TB patients and non-TB controls, the CFP10 (EsxB) SOMAmer yielded the most significant differential signals (P < 0.0276), particularly in TB patients with HIV coinfection. In conclusion, direct M. tuberculosis antigen detection proved difficult even with a sensitive method such as SOMAscan, likely due to their very low, subpicomolar abundance. The observed differences between cases and controls had limited diagnostic utility in serum and urine, but further evaluation of M. tuberculosis SOMAmers using other platforms and sample types is warranted.

Highly Multiplexed Proteomic Analysis of Quantiferon Supernatants To Identify Biomarkers of Latent Tuberculosis Infection.

The tests for diagnosing latent tuberculosis infection (LTBI) are limited by a poor predictive value for identifying people at the highest risk for progressing to active tuberculosis (TB) and have various sensitivities and specificities in different populations. Identifying a more robust signature for LTBI is important for TB prevention and elimination. A pilot study was conducted with samples from immigrants to the United States that were screened for LTBI by the three commercially approved tests, namely, the tuberculin skin test (TST), the Quantiferon-TB Gold in-tube (QFT-GIT), and the T-SPOT.TB (T-SPOT). QFT-GIT supernatants from 13 people with concordant positive results and 26 people with concordant negative results were analyzed via the highly multiplexed SOMAscan proteomic assay. The proteins in the stimulated supernatants that distinguished LTBI from controls included interleukin-2 (IL-2), monocyte chemotactic protein 2 (MCP-2), interferon gamma inducible protein-10 (IP-10), interferon gamma (IFN-γ), tumor necrosis factor superfamily member 14 (TNFSF14, also known as LIGHT), monokine induced by gamma interferon (MIG), and granzyme B (P <0.00001). In addition, antigen stimulation increased the expression of heparin-binding EGF-like growth factor (HB-EGF) and activin AB in LTBI samples. In nil tubes, LIGHT was the most significant marker (P <0.0001) and was elevated in LTBI subjects. Other prominent markers in nonstimulated QFT-GIT supernatants were the complement-3 components C3b, iC3b, and C3d, which were upregulated in LTBI and markedly decreased upon stimulation. We found known and novel proteins that warrant further studies for developing improved tests for LTBI, for predicting progression to active disease, and for discriminating LTBI from active TB.

Decreases in Gap Junction Coupling Recovers Ca2+ and Insulin Secretion in Neonatal Diabetes Mellitus, Dependent on Beta Cell Heterogeneity and Noise.

Diabetes is caused by dysfunction to ß-cells in the islets of Langerhans, disrupting insulin secretion and glucose homeostasis. Gap junction-mediated electrical coupling between ß-cells in the islet plays a major role in coordinating a pulsatile secretory response at elevated glucose and suppressing insulin secretion at basal glucose. Previously, we demonstrated that a critical number of inexcitable cells can rapidly suppress the overall islet response, as a result of gap junction coupling. This was demonstrated in a murine model of Neonatal Diabetes Mellitus (NDM) involving expression of ATP-insensitive KATP channels, and by a multi-cellular computational model of islet electrical activity. Here we examined the mechanisms by which gap junction coupling contributes to islet dysfunction in NDM. We first verified the computational model against [Ca2+] and insulin secretion measurements in islets expressing ATP-insensitive KATP channels under different levels of gap junction coupling. We then applied this model to predict how different KATP channel mutations found in NDM suppress [Ca2+], and the role of gap junction coupling in this suppression. We further extended the model to account for stochastic noise and insulin secretion dynamics. We found experimentally and in the islet model that reductions in gap junction coupling allow progressively greater glucose-stimulated [Ca2+] and insulin secretion following expression of ATP-insensitive KATP channels. The model demonstrated good correspondence between suppression of [Ca2+] and clinical presentation of different NDM mutations. Significant recoveries in [Ca2+] and insulin secretion were predicted for many mutations upon reductions in gap junction coupling, where stochastic noise played a significant role in the recoveries. These findings provide new understanding how the islet functions as a multicellular system and for the role of gap junction channels in exacerbating the effects of decreased cellular excitability. They further suggest novel therapeutic options for NDM and other monogenic forms of diabetes.

Phase transitions in the multi-cellular regulatory behavior of pancreatic islet excitability.

The pancreatic islets of Langerhans are multicellular micro-organs integral to maintaining glucose homeostasis through secretion of the hormone insulin. ß-cells within the islet exist as a highly coupled electrical network which coordinates electrical activity and insulin release at high glucose, but leads to global suppression at basal glucose. Despite its importance, how network dynamics generate this emergent binary on/off behavior remains to be elucidated. Previous work has suggested that a small threshold of quiescent cells is able to suppress the entire network. By modeling the islet as a Boolean network, we predicted a phase-transition between globally active and inactive states would emerge near this threshold number of cells, indicative of critical behavior. This was tested using islets with an inducible-expression mutation which renders defined numbers of cells electrically inactive, together with pharmacological modulation of electrical activity. This was combined with real-time imaging of intracellular free-calcium activity [Ca2+]i and measurement of physiological parameters in mice. As the number of inexcitable cells was increased beyond ∼15%, a phase-transition in islet activity occurred, switching from globally active wild-type behavior to global quiescence. This phase-transition was also seen in insulin secretion and blood glucose, indicating physiological impact. This behavior was reproduced in a multicellular dynamical model suggesting critical behavior in the islet may obey general properties of coupled heterogeneous networks. This study represents the first detailed explanation for how the islet facilitates inhibitory activity in spite of a heterogeneous cell population, as well as the role this plays in diabetes and its reversal. We further explain how islets utilize this critical behavior to leverage cellular heterogeneity and coordinate a robust insulin response with high dynamic range. These findings also give new insight into emergent multicellular dynamics in general which are applicable to many coupled physiological systems, specifically where inhibitory dynamics result from coupled networks.

Decreasing cx36 gap junction coupling compensates for overactive KATP channels to restore insulin secretion and prevent hyperglycemia in a mouse model of neonatal diabetes.

Mutations to the ATP-sensitive K(+) channel (KATP channel) that reduce the sensitivity of ATP inhibition cause neonatal diabetes mellitus via suppression of ß-cell glucose-stimulated free calcium activity ([Ca(2+)]i) and insulin secretion. Connexin-36 (Cx36) gap junctions also regulate islet electrical activity; upon knockout of Cx36, ß-cells show [Ca(2+)]i elevations at basal glucose. We hypothesized that in the presence of overactive ATP-insensitive KATP channels, a reduction in Cx36 would allow elevations in glucose-stimulated [Ca(2+)]i and insulin secretion to improve glucose homeostasis. To test this, we introduced a genetic knockout of Cx36 into mice that express ATP-insensitive KATP channels and measured glucose homeostasis and islet metabolic, electrical, and insulin secretion responses. In the normal presence of Cx36, after expression of ATP-insensitive KATP channels, blood glucose levels rapidly rose to >500 mg/dL. Islets from these mice showed reduced glucose-stimulated [Ca(2+)]i and no insulin secretion. In mice lacking Cx36 after expression of ATP-insensitive KATP channels, normal glucose levels were maintained. Islets from these mice had near-normal glucose-stimulated [Ca(2+)]i and insulin secretion. We therefore demonstrate a novel mechanism by which islet function can be recovered in a monogenic model of diabetes. A reduction of gap junction coupling allows sufficient glucose-stimulated [Ca(2+)]i and insulin secretion to prevent the emergence of diabetes.

Dimensionality and size scaling of coordinated Ca(2+) dynamics in MIN6 ß-cell clusters.

Pancreatic islets of Langerhans regulate blood glucose homeostasis by the secretion of the hormone insulin. Like many neuroendocrine cells, the coupling between insulin-secreting ß-cells in the islet is critical for the dynamics of hormone secretion. We have examined how this coupling architecture regulates the electrical dynamics that underlie insulin secretion by utilizing a microwell-based aggregation method to generate clusters of a ß-cell line with defined sizes and dimensions. We measured the dynamics of free-calcium activity ([Ca(2+)]i) and insulin secretion and compared these measurements with a percolating network model. We observed that the coupling dimension was critical for regulating [Ca(2+)]i dynamics and insulin secretion. Three-dimensional coupling led to size-invariant suppression of [Ca(2+)]i at low glucose and robust synchronized [Ca(2+)]i oscillations at elevated glucose, whereas two-dimensional coupling showed poor suppression and less robust synchronization, with significant size-dependence. The dimension- and size-scaling of [Ca(2+)]i at high and low glucose could be accurately described with the percolating network model, using similar network connectivity. As such this could explain the fundamentally different behavior and size-scaling observed under each coupling dimension. This study highlights the dependence of proper ß-cell function on the coupling architecture that will be important for developing therapeutic treatments for diabetes such as islet transplantation techniques. Furthermore, this will be vital to gain a better understanding of the general features by which cellular interactions regulate coupled multicellular systems.