Detection of (1→3)-𝝱-D-glucan as a Marker of Invasive Fungal Disease

Expires: September 9, 2022

Image of Elitza Theel, Ph.D.Presenter

Elitza Theel, Ph.D., is the Director of Infectious Diseases Serology for Clinical Microbiology in the Department of Laboratory Medicine and Pathology. She holds the academic rank of Associate Professor of Laboratory Medicine and Pathology.

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Transcript and References

Introduction

Hi, I’m Bobbi Pritt, Director of the Clinical Parasitology Lab and Vice Chair of Education in the Department of Laboratory Medicine and Pathology at Mayo Clinic. Diagnosis of invasive fungal infections, including invasive aspergillosis can be a challenge, particularly in immunocompromised hosts. In this “Hot Topic,” my colleague, Dr. Elli Theel, will discuss detection of beta-(1,3)-D-glucan or BDG in serum as a biomarker for the presence of such invasive fungal infections.  As Dr. Theel will discuss, BDG is a cell wall component of many clinically relevant fungi, including Aspergillus sp, Fusarium sp. and Pneumocystis among others. I hope you enjoy this month’s Hot Topic, and I want to personally thank you for allowing Mayo Clinic the opportunity to be a partner in your patient’s health care.

Thank you for the introduction and to the listeners for joining us today to talk about testing for the fungal antigen, 1-3 beta-d-glucan.

Disclosure

Before we begin, just a note that I do not have any relevant financial disclosures to share.

Invasive Fungal Disease (IFD)

Broadly speaking, invasive fungal disease is defined as a fungal infection of an otherwise sterile site, such as the bloodstream or deep tissues.

While both opportunistic and endemic fungal pathogens can cause invasive disease in the right host, some of the most common fungal pathogens causing invasive fungal infections include Candida species., Aspergillus species., Pneumocystis and Cryptococcus species., and while the overall incidence of invasive fungal disease can vary somewhat from region to region, in higher income countries, the incidence ranges from approximately 14 to 27 cases per 100,000 patients per year.

Those at highest risk of IFDs include individuals having recently received a hematopoeitic stem cell transplant, a solid organ transplant, those that have significant and prolonged neutropenia and others that are significantly immunosuppressed due to malignancy, receipt of chemotherapy or on treatment with certain biologic agents.

Importantly, IFDs are associated with significant morbidity and mortality, particularly in situations where diagnosis and initiation of appropriate antifungal therapy is delayed.

Challenges Associated with Diagnosis of IFDs

The diagnosis of IFDs is challenging for multiple reasons, including the fact that symptoms are largely non-specific, and so a combined diagnostic approach is typically required. This includes imaging studies, and while certain classic radiologic signs like the halo or crescent sign on chest imaging have been well described, these are infrequently observed. 

With regards to laboratory testing, the gold standard remains histopathologic examination of biopsy material from affected tissues alongside culture, however invasive specimen collection procedures may be contraindicated particularly in patients with significant respiratory insufficiency. Routine fungal culture can be helpful, however results may also be confounding.  Sensitivity of culture is generally low and is largely dependent on the quality of the specimen submitted.  Additionally, some fungal pathogens require prolonged incubation, which can further delay diagnosis.

Because of these limitations, significant effort has gone into developing additional or alternative diagnostic assays for detection of IFDs, including both molecular testing and identification of fungal biomarkers, including detection of the pan-fungal biomarker 1-3 beta-d-glucan or BDG, which is the focus of today’s presentation.

(1→3)-β-D-Glucan (BDG)

BDG is a polysaccharide composed of glucose monomers linked by beta 1-3 glucosidic bonds and is found in high abundance in cellulose containing plants, and it also makes up a significant proportion of the cell wall of many fungi, including clinically important fungi like Aspergillus, Candida, Fusarium, and others.  It is actually easier to remember which organisms lack BDG or produce it in low amounts, which include the Mucorales agents, such as Mucor species and Absidia species, and also Cryptococcus species and Blastomyces dermatitidis.

There are at least five commercially available assays for detection of BDG, however only the Fungitell assay from the Associates of Cape Cod is FDA-approved for detection of BDG in serum, with the intended use as an aid in the diagnosis of deep-seated IFDs.  It is also important to remember that results from this assay need to be used in conjunction with the other diagnostic procedures previously mentioned, including imaging studies, culture and histopathologic examination of biopsy material as available.

The Fungitell BDG Assay: How Does It Work?

The Fungitell BDG assay is a chromogenic, quantitative EIA based on the clotting cascade of the Limulus or horseshoe crab. Briefly, horseshoe crab amebocytes are isolated and lysed to release components of the crab clotting cascade and it is this lysate that is used for the Fungitell assay.  This clotting cascade can be stimulated by two different molecules, either by the presence of bacterial endotoxin or by BDG, as shown here.  In order to make this assay specific for detection of BDG, factor C has been eliminated by the manufacturer, which is the component that activates the clotting cascade in the presence of endotoxin.  So with this modification, in the presence of BDG, Factor G, a serine protease zymogen, is activated, which activates the clotting enzyme which can then cleave this externally added chromogenic peptide substrate to release para-nitroaniline or pNA, which is excited at a specific wavelength.  Unlike most other standard ELISAs, this assay is a kinetic ELISA, meaning that each well for each patient sample, which is run in duplicate, is read and optical density or OD values recorded every 30 seconds over a 40 minute period.

As an example, this is what a single patient run looks like after completion. Each run has BDG standards run in duplicate, alongside patient sera, also run in duplicate. The OD values are collected at each 30 sec interval and are plotted over the 40 minute time frame to generate a curve. Interpretation of results involves both analysis of the curve shape as well as software analysis to establish the mean rate of change in the OD, which is then used to determine the final BDG concentration value in pg/mL using the standard curve. 

Without going into details, positive patient results typically have ‘hockey stick’ shaped curves with a notable increase in OD levels over time.  This is in comparison to samples with negative results which typically have straight curves and a negligible change in OD values over the 40 minute period. Additionally, some samples may be reported as ‘uninterpretable due to optical artifact’. In these samples, although there is a significant change in the OD values over time, the associated curves are aberrant as shown in this example.  Various factors may lead to such a result, and repeat testing of a new specimen may be helpful.

Finally, the quantitative range of the Fungitell assay is 31 to 500 pg/mL, with qualitative interpretive cut-offs of 80 pg/mL or greater considered positive, 59 pg/mL or less considered negative and indeterminate results range in value from 60 to 79 pg/mL.

BDG as a Biomarker for IFD

The performance characteristics of BDG assays for detection of IFDs vary significantly in the literature, and importantly multiple studies and meta-analyses have shown that these assays perform best in patients that are at high risk for the presence of IFDs as indicated here.  Findings from 4 different meta-analyses performed over the years are summarized in the table below and show that in patients at high-risk of IFD, single time point beta-d-glucan testing is associated with a sensitivity and specificity generally ranging between 60 and 90%.

Interestingly, multiple studies, performed primarily in patients with hematologic malignancies, have shown that the presence of two consecutively positive BDG results increase specificity of the assay to almost 99%, suggesting that these results may be used as a diagnostic marker for the presence of an IFD.

Additionally, it is important to remember that the absence of BDG antigenemia should be interpreted with caution as a single negative result may not be used to rule out IFD, and this is true for most fungal pathogens with the notable exception of IFD due to Pneumocystis

BDG as a Biomarker for Pneumocystis Pneumonia

Very briefly, as you’ll remember, Pneumocystis jirovecii is a fungus, which notably does not respond to antifungals, and is associated with significant mortality in immunosuppressed patients. Similar to other fungal infections, diagnosis of Pneumocystis can be challenging, which is further hampered by its inability to be grown in culture.

Notably however, BDG is a major component of the Pneumocystis cell wall, and an 11 study meta-analysis performed in 2013 showed that the overall sensitivity and specificity of the Fungitell assay in patients with Pneumocystis pneumonia was 95% and 86% respectively.  Importantly, the authors also found that the negative likelihood ratio associated with a negative result was 0.06, collectively indicating that a negative BDG result can reasonably be used to exclude the diagnosis of Pneumocystis pneumonia.

BDG Test Utilization Pearls

To conclude, there are a few additional test utilization pearls to remain cognizant of when considering beta-d-glucan testing. 

First, beta-d-glucan may be detected in patients prior to symptom onset and in some cases as early as one week in advance of symptoms. Therefore, a single positive BDG result in at risk patients does warrant close monitoring and/or further targeted evaluation for an invasive fungal process.

Additionally, although some studies support the trending of BDG levels as a means to monitor response to therapy, other studies have shown contradictory data. So, while decreasing titers may be associated with clinical improvement in cases of invasive candidiasis for example, increasing beta-d-glucan levels may not necessarily mean worsening disease and results should be interpreted with caution by clinicians.

Finally, it is important to remember that there are certain treatments and conditions that may lead to detection of beta-d-glucan in patients without IFD. These include recent infusion of IVIG or albumin, which are frequently filtered through cellulose containing filters.  Also, gauze packing during surgery and hemodialysis using cellulose containing membranes may lead to leaching of beta-d-glucan into the bloodstream. Certain antibiotics have been implicated with leading to elevated beta-d-glucan levels as a result of how the antibiotics are prepared, and finally, elevated beta-d-glucan levels have been documented in bacteremic patients, and in those with severe mucositis and mucosal colonization with Candida.

Therefore, as a result of all of these caveats, it is of critical importance that beta-d-glucan testing be restricted only to patients at high risk of IFDs and that results be interpreted alongside other clinical and laboratory findings.

References

  1. Webb BJ, Ferraro JP, Rea S, et. al. Epidemiology and Clincial Features of Invasive Fungal Infection in a US Health Care Network.  Open Forum Infect Dis. 2018;5(8):187-192
  2. Theel ES, Doern CD. β-D-Glucan Testing is Important for Diagnosis of Invasive Fungal Infections. J Clin Micro. 2013;51(11):3478-3783
  3. White SK, Walker BS, Hanson KE, et. al. Diagnostic Accurayc of β-D-Glucan (Fungitell) Testing Among Patients with Hematologic Malignancies or Solid Organ Tumors.  A systematic review and Meta-Analysis. Am J Clin Pathol. 2019;151:275-285.
  4. Karageorgopoulos DE, Vouloumanou EK, Ntziora F, et. al. β-D-Glucan  assay for the diagnosis of invasive fungal infections: a meta-analysis. Clin Infect Dis. 2011;52:750-770.
  5. Karageorgopoulos DE, Qu Jm, Korbila IP, et. al. Accuracy of β-D-Glucan  for the diagnosis of Pneumocystis jirovecii pneumonia: a meta-analysis. Clin Microbiol Infect. 2013;19(1):39-49
  6. Lu Y, Chen YQ, Guo YL, et. al. Diagnosis of invasive fungal disease using serum (1-3)- β-D-Glucan: a bivariate meta-analysis. Intern Med. 2011;50:2783-2791
  7. He S, Hang JP, Zhang L, et. al. A systematic review and meta-analysis of diagnostic accuracy of serum 1,3- β-D-Glucan for invasive fungal infection: Focus on cutoff levels. J Microbiol Immunol Infect. 2015:48:351-361
  8. Thomas CF, Limper AH. Current insights into the biology and pathogenesis of Pneumocystis pneumonia. Nat Rev Microbiol. 2007;5(4):298-308
  9. Fabre V, Markou T, DeMallie K, et. al. Single Academic Center Experience of Unrestricted β-D-Glucan  Implementation. Open Forum Infect Dis. 2018;5(9)
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