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Biomarkers for diagnosing and/or monitoring tuberculosis

A biomarker, tuberculosis technology, applied in disease diagnosis, biomaterial analysis, measurement devices, etc.

Inactive Publication Date: 2015-08-05
PROTEINLOGIC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, partial adherence to treatment can lead to suboptimal therapeutic levels of antimicrobials and microevolution of antibiotic resistance mutations
Therefore, patients may remain infectious for a longer period and the frequency of transmission increases

Method used

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  • Biomarkers for diagnosing and/or monitoring tuberculosis
  • Biomarkers for diagnosing and/or monitoring tuberculosis
  • Biomarkers for diagnosing and/or monitoring tuberculosis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0175] Example 1: Validity of IFN-γ and TNF-α as TB Biomarkers

[0176] The use of IFN-[gamma], TNF-[alpha] and additional CD for the effectiveness of discriminating different sample types (healthy, latent TB, active TB, disease) was evaluated.

[0177] 1. The combination of IFN-γ and TNF-α consistently produces better discriminative signals than these antigens alone.

[0178] 2. Additional CDs were identified, which further improved predictive characteristics for certain predictive tasks.

[0179] The study was performed on n = 92 human samples to identify potential markers capable of distinguishing TB-disease subjects from TB-free control subjects.

[0180] The demographics of each patient are summarized in Table 1:

[0181] Table 1: Demographic and patient data for each sample analyzed

[0182] group grouping Diagnostic classification BCG history? TB position age gender comorbidity A 4C yes N / A 52 male psoriasis A ...

Embodiment 2

[0235] Example 2: Effectiveness of Additional Biomarkers in Combination with IFN-γ and TNF-α

[0236] Additional antigens were identified that may complement the pattern of discrimination observed for IFN-γ and TNF-α. first, Figure 1-3 Scatterplots are shown for all antigens that were significantly differentially expressed (pv=0.05) between at least two considered sample types (healthy, active, latent, disease). Several sCDs appear to add an additional axis of discrimination between sample types, complementing IFN-γ and TNF-α. Table 3 summarizes the predicted performance of these CDs when combined with TNF-α and IFN-γ. This "joint" predictor performed at least as well as IFN-γ and TNF-α and generally improved the results obtained with the two antigen models for the prediction tasks Health / TB and Health / Latency.

[0237] Table 3: Predictive performance of different combinations of antigens for the alternative classification task

[0238]

[0239]Table 3 shows the area...

Embodiment 3

[0241] Example 3: Replication of the Activity / Latency Model Using Increasing Patient Sample Sizes

[0242] The purpose of this experiment was to validate the activity / latency predictive features identified in the initial screen and providing the results described in Example 1 and Example 2. For this purpose, unrelated samples were obtained from Imperial College London. These include the following numbers of active and latent TB cases:

[0243] Active TB: 94 samples (51: IGRA positive)

[0244] Latent TB: 89 samples (45: IGRA positive)

[0245] Table 4: Demographic and patient data for each sample analyzed

[0246] gender age BCG? IGRA diagnosis Diagnostic classification group Female 56 Y QFT+ Lung + uveitis TB 2 ATB Female 51 N QFT- LTBI 4B LTBI Female 21 Y NT lymph node TB 1 ATB male 21 Y QFT- LTBI 4A LTBI Female 49 Y QFT+ Skin TB 2 ATB Female 33 Y QFT+ ...

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Abstract

The invention relates to biomarkers for diagnosing and / or monitoring tuberculosisin both immunocompetent and immunocompromised individuals, monitoring the responses of individuals to anti-mycobacterial chemotherapy, monitoring the progression of latent tuberculosis to active tuberculosis, differentiating active tuberculosis from latent tuberculosis, and from other clinical conditions that mimic tuberculosis (TB). The invention also relates to methods for diagnosing, treating and monitoring tuberculosis using said biomarkers. The above pertain in all aspects both to pulmonary and extrapulmonary Mycobacterium.tuberculosis infections, with Mycobacterium.tuberculosis being the causative organism in tuberculosis.

Description

field of invention [0001] The present invention relates to biomarkers for diagnosing and / or monitoring tuberculosis in both immunocompetent and immunocompromised individuals, monitoring individual response to antimycobacterial chemotherapy, monitoring latent tuberculosis to active tuberculosis to distinguish active tuberculosis from latent tuberculosis and other clinical conditions resembling tuberculosis (TB). The invention also relates to methods of using said biomarkers for diagnosis, treatment and monitoring of tuberculosis. The above relates in all respects to both pulmonary and extrapulmonary Mycobacterium tuberculosis infection, the causative organism of tuberculosis. Background of the invention [0002] Mycobacterium tuberculosis is arguably one of the most successful pathogenic microorganisms worldwide and is the causative agent of the potentially fatal infectious disease tuberculosis. It is also the leading cause of death from potentially curable infectious ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/569
CPCG01N2800/52G01N33/6869G01N2800/26G01N33/6866G01N33/6863G01N33/6872G01N33/6893G01N33/5695G01N2333/57G01N2800/56G01N2333/70596
Inventor J.库宁汉A.贝茨O.斯特格尔A.利尔瓦尼
Owner PROTEINLOGIC
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