Gender-dependent differences in plasma matrix metalloproteinase-8 elevated in pulmonary tuberculosis.

Tuberculosis (TB) remains a global health pandemic and greater understanding of underlying pathogenesis is required to develop novel therapeutic and diagnostic approaches. Matrix metalloproteinases (MMPs) are emerging as key effectors of tissue destruction in TB but have not been comprehensively studied in plasma, nor have gender differences been investigated. We measured the plasma concentrations of MMPs in a carefully characterised, prospectively recruited clinical cohort of 380 individuals. The collagenases, MMP-1 and MMP-8, were elevated in plasma of patients with pulmonary TB relative to healthy controls, and MMP-7 (matrilysin) and MMP-9 (gelatinase B) were also increased. MMP-8 was TB-specific (p<0.001), not being elevated in symptomatic controls (symptoms suspicious of TB but active disease excluded). Plasma MMP-8 concentrations inversely correlated with body mass index. Plasma MMP-8 concentration was 1.51-fold higher in males than females with TB (p<0.05) and this difference was not due to greater disease severity in men. Gender-specific analysis of MMPs demonstrated consistent increase in MMP-1 and -8 in TB, but MMP-8 was a better discriminator for TB in men. Plasma collagenases are elevated in pulmonary TB and differ between men and women. Gender must be considered in investigation of TB immunopathology and development of novel diagnostic markers.

Mycobacterium tuberculosis upregulates microglial matrix metalloproteinase-1 and -3 expression and secretion via NF-kappaB- and Activator Protein-1-dependent monocyte networks.

Inflammatory tissue destruction is central to pathology in CNS tuberculosis (TB). We hypothesized that microglial-derived matrix metalloproteinases (MMPs) have a key role in driving such damage. Analysis of all of the MMPs demonstrated that conditioned medium from Mycobacterium tuberculosis-infected human monocytes (CoMTb) stimulated greater MMP-1, -3, and -9 gene expression in human microglial cells than direct infection. In patients with CNS TB, MMP-1/-3 immunoreactivity was demonstrated in the center of brain granulomas. Concurrently, CoMTb decreased expression of the inhibitors, tissue inhibitor of metalloproteinase-2, -3, and -4. MMP-1/-3 secretion was significantly inhibited by dexamethasone, which reduces mortality in CNS TB. Surface-enhanced laser desorption ionization time-of-flight analysis of CoMTb showed that TNF-alpha and IL-1beta are necessary but not sufficient for upregulating MMP-1 secretion and act synergistically to drive MMP-3 secretion. Chemical inhibition and promoter-reporter analyses showed that NF-kappaB and AP-1 c-Jun/FosB heterodimers regulate CoMTb-induced MMP-1/-3 secretion. Furthermore, NF-kappaB p65 and AP-1 c-Jun subunits were upregulated in biopsy granulomas from patients with cerebral TB. In summary, functionally unopposed, network-dependent microglial MMP-1/-3 gene expression and secretion regulated by NF-kappaB and AP-1 subunits were demonstrated in vitro and, for the first time, in CNS TB patients. Dexamethasone suppression of MMP-1/-3 gene expression provides a novel mechanism explaining the benefit of steroid therapy in these patients.

Association of mannose-binding lectin deficiency with acute invasive aspergillosis in immunocompromised patients.

BACKGROUND: Invasive aspergillosis is a devastating infection with attributable mortality of 40% despite antifungal therapy. In animal models of aspergillosis, deficiency of mannose-binding lectin (MBL), a pattern recognition receptor that activates complement, is a susceptibility factor. MBL deficiency occurs in 20%-30% of the population. We hypothesized that MBL deficiency may be a susceptibility factor for invasive aspergillosis in humans. METHODS: Serum MBL concentrations were measured by enzyme-linked immunosorbent assay in 65 patients with proven or probable acute invasive aspergillosis and 78 febrile immunocompromised control subjects. MBL concentrations and the frequency of MBL deficiency were compared. RESULTS: The median serum MBL level was significantly lower in patients with aspergillosis than in control subjects (281 ng/mL vs 835 ng/mL; P = .007). MBL deficiency (MBL concentration, <500 ng/mL) was significantly more common in patients with aspergillosis than control subjects (62% vs 32%; P < .001). Frequency of MBL deficiency was similar among patients with aspergillosis irrespective of response to antifungal therapy (P = .10). CONCLUSIONS: This study is the first, to our knowledge, to show an association between MBL deficiency and acute invasive aspergillosis in humans. Further study is required to investigate the causal nature of this association and to define whether diagnosis of MBL deficiency may identify immunocompromised patients at increased risk of invasive aspergillosis.

Pooling serum samples may lead to loss of potential biomarkers in SELDI-ToF MS proteomic profiling.

BACKGROUND: High throughput proteomic technology offers promise for the detection of disease biomarkers and proteomic signature patterns but biomarker discovery studies can be limited by cost factors when large sample size numbers are required. Pooling sera or plasma samples from disease cases potentially offers a solution to cost implications by reducing the standard errors of mass to charge values. Surface enhanced laser desorption/ionization time of flight (SELDI-ToF) mass spectra obtained from individual and pooled sera from invasive aspergillosis cases and controls were compared. RESULTS: Pooling resulted in 50% loss of peak clusters detected in individual samples. Overall, loss was greatest for low intensity clusters. Peak intensities and case:control intensity ratios, among clusters not lost, demonstrated good reproducibility. CONCLUSION: Pooling sera results in significant potential biomarker loss when using SELDI-ToF MS.

Estimation of relevant variables on high-dimensional biological patterns using iterated weighted kernel functions.

BACKGROUND: The analysis of complex proteomic and genomic profiles involves the identification of significant markers within a set of hundreds or even thousands of variables that represent a high-dimensional problem space. The occurrence of noise, redundancy or combinatorial interactions in the profile makes the selection of relevant variables harder. METHODOLOGY/PRINCIPAL FINDINGS: Here we propose a method to select variables based on estimated relevance to hidden patterns. Our method combines a weighted-kernel discriminant with an iterative stochastic probability estimation algorithm to discover the relevance distribution over the set of variables. We verified the ability of our method to select predefined relevant variables in synthetic proteome-like data and then assessed its performance on biological high-dimensional problems. Experiments were run on serum proteomic datasets of infectious diseases. The resulting variable subsets achieved classification accuracies of 99% on Human African Trypanosomiasis, 91% on Tuberculosis, and 91% on Malaria serum proteomic profiles with fewer than 20% of variables selected. Our method scaled-up to dimensionalities of much higher orders of magnitude as shown with gene expression microarray datasets in which we obtained classification accuracies close to 90% with fewer than 1% of the total number of variables. CONCLUSIONS: Our method consistently found relevant variables attaining high classification accuracies across synthetic and biological datasets. Notably, it yielded very compact subsets compared to the original number of variables, which should simplify downstream biological experimentation.

Early risk assessment for viral haemorrhagic fever: experience at the Hospital for Tropical Diseases, London, UK.

OBJECTIVES: To implement a policy of systematic screening for viral haemorrhagic fever (VHF) among travellers returning from African countries with fever, commencing at initial clinical contact. METHODS: A protocol based on UK Advisory Committee on Dangerous Pathogens guidance was developed collaboratively by medical, nursing and laboratory staff. Audit was carried out to quantify resource demands and effects on time to diagnose malaria, the main differential diagnosis. RESULTS: A protocol is now implemented for all patients presenting to HTD with fever, with clear guidelines for interaction with clinical and laboratory staff at each stage. The protocol required moderate amounts of clinical and laboratory staff time and resulted in some additional hospital admissions. The time to a diagnosis of malaria increased from a median of 90 (range 50-125) min in patients without VHF risk to a median of 140 (range 101-225) min (p=0.0025) in those assessed as at risk. CONCLUSIONS: Although all acute medical services need to have robust procedures for early detection of patients with serious transmissible conditions, few implement such a policy. Our protocol requires increased human and other resources but has no important impact on the rapidity of diagnosis of malaria, and is now embedded in local practice.

Identification of diagnostic markers for tuberculosis by proteomic fingerprinting of serum.

BACKGROUND: We investigated the potential of proteomic fingerprinting with mass spectrometric serum profiling, coupled with pattern recognition methods, to identify biomarkers that could improve diagnosis of tuberculosis. METHODS: We obtained serum proteomic profiles from patients with active tuberculosis and controls by surface-enhanced laser desorption ionisation time of flight mass spectrometry. A supervised machine-learning approach based on the support vector machine (SVM) was used to obtain a classifier that distinguished between the groups in two independent test sets. We used k-fold cross validation and random sampling of the SVM classifier to assess the classifier further. Relevant mass peaks were selected by correlational analysis and assessed with SVM. We tested the diagnostic potential of candidate biomarkers, identified by peptide mass fingerprinting, by conventional immunoassays and SVM classifiers trained on these data. FINDINGS: Our SVM classifier discriminated the proteomic profile of patients with active tuberculosis from that of controls with overlapping clinical features. Diagnostic accuracy was 94% (sensitivity 93.5%, specificity 94.9%) for patients with tuberculosis and was unaffected by HIV status. A classifier trained on the 20 most informative peaks achieved diagnostic accuracy of 90%. From these peaks, two peptides (serum amyloid A protein and transthyretin) were identified and quantitated by immunoassay. Because these peptides reflect inflammatory states, we also quantitated neopterin and C reactive protein. Application of an SVM classifier using combinations of these values gave diagnostic accuracies of up to 84% for tuberculosis. Validation on a second, prospectively collected testing set gave similar accuracies using the whole proteomic signature and the 20 selected peaks. Using combinations of the four biomarkers, we achieved diagnostic accuracies of up to 78%. INTERPRETATION: The potential biomarkers for tuberculosis that we identified through proteomic fingerprinting and pattern recognition have a plausible biological connection with the disease and could be used to develop new diagnostic tests.

Proteomic fingerprinting for the diagnosis of human African trypanosomiasis.

Papadopoulos et al. recently reported the discovery of a diagnostic serum proteomic signature for human African trypanosomiasis (HAT), using a combination of surface-enhanced laser desorption-ionization time-of-flight (SELDI-TOF) mass spectrometry and data-mining algorithms. This novel approach, coupled with biochemical characterization of the proteins that contribute to the signature, provides powerful new tools for the development of improved diagnostic tests, disease staging and identification of potential novel drug targets in HAT.

A novel and accurate diagnostic test for human African trypanosomiasis.

INTRODUCTION: Human African trypanosomiasis (sleeping sickness) affects up to half a million people every year in sub-Saharan Africa. Because current diagnostic tests for the disease have low accuracy, we sought to develop a novel test that can diagnose human African trypanosomiasis with high sensitivity and specificity. METHODS: We applied serum samples from 85 patients with African trypanosomiasis and 146 control patients who had other parasitic and non-parasitic infections to a weak cation exchange chip, and analysed with surface-enhanced laser desorption-ionisation time-of-flight mass spectrometry. Mass spectra were then assessed with three powerful data-mining tools: a tree classifier, a neural network, and a genetic algorithm. FINDINGS: Spectra (2-100 kDa) were grouped into training (n=122) and testing (n=109) sets. The training set enabled data-mining software to identify distinct serum proteomic signatures characteristic of human African trypanosomiasis among 206 protein clusters. Sensitivity and specificity, determined with the testing set, were 100% and 98.6%, respectively, when the majority opinion of the three algorithms was considered. This novel approach is much more accurate than any other diagnostic test. INTERPRETATION: Our report of the accurate diagnosis of an infection by use of proteomic signature analysis could form the basis for diagnostic tests for the disease, monitoring of response to treatment, and for improving the accuracy of patient recruitment in large-scale epidemiological studies.

Case report: rapid ante-mortem diagnosis of a human case of rabies imported into the UK from the Philippines.

The United Kingdom is free from rabies, with the last human death from indigenous rabies recorded in 1902. However, between 1946 and 2000, 20 deaths were reported in the United Kingdom in people who were bitten and infected while abroad in rabies endemic areas. The rapid diagnosis of suspected human rabies cases influences the use of anti-rabies post-exposure prophylaxis for potential contacts with the victim. In addition, the occurrence of a human rabies case requires urgent investigation to support patient management policies. In May 2001, a case of human rabies imported into the United Kingdom from the Philippines was identified. A 55-year-old man was admitted to University College Hospital, London, with clinical symptoms and a history consistent with exposure to rabies. Saliva, cerebrospinal fluid), and skin biopsies (from the wound site and nape of the neck) were submitted for conventional ante-mortem diagnostic techniques. Established diagnostic techniques, including the fluorescent antibody test (FAT), mouse inoculation test, (MIT) and the rabies tissue culture inoculation test (RTCIT), failed to detect the virus. In contrast, hemi-nested reverse transcription-polymerase chain reaction (RT-PCR), followed by automated sequencing confirmed the presence of classical rabies virus (genotype 1) in both the saliva and skin specimens within 36 hr of sample submission. Subsequent phylogenetic analysis demonstrated that this isolate was closely related to that of canine variants currently circulating in the Philippines.

African trypanosomiasis in travelers returning to the United Kingdom.

Two returning safari tourists with African trypanosomiasis were admitted to the Hospital for Tropical Diseases, London, in a 3-day period, compared with six cases in the previous 14 years. We describe the clinical features, diagnosis, and problems encountered in accessing appropriate therapy, and discuss the potential for emergence of this disease in increasingly adventurous international travelers.