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Archive for category: Featured Articles

Featured Articles

p43

Electronic alerts for acute kidney injury: the role of the laboratory

, 26 August 2020/in Featured Articles /by 3wmedia

Acute kidney injury is a common and serious complication of many hospital admissions, yet there are often delays in recognizing its development. The laboratory can play a key role in ensuring large increases in serum creatinine do not go unnoticed so that deteriorating patients receive prompt medical attention.

by Nick Flynn

Introduction
Acute kidney injury (AKI) is a sudden decline in renal function, generally occurring over hours or days. AKI is increasingly recognized as a common healthcare problem associated with poor outcomes such as increased mortality and progression of chronic kidney disease [1], prolonged hospital stay and increased healthcare costs [2]. There is also evidence that management of patients with AKI is sometimes poor: in the UK, a National Confidential Enquiry into Patient Outcomes and Death (NCEPOD) report found severe deficiencies of care in a cohort of patients who died with a primary diagnosis of AKI [3]. For example, there was often a delay in recognizing post-admission AKI. This has prompted some hospitals to implement electronic alerts (e-alerts) to systematically detect and highlight cases of AKI. As current definitions of AKI are based mainly upon changes in serum creatinine, laboratories are well placed to implement these systems (Table 1) [4]. This review will briefly discuss options for e-alerts, some considerations for their implementation, and the evidence base for their use.

AKI e-alerts
The aim of AKI e-alert systems is to improve the outcomes of patients by facilitating earlier recognition and treatment of AKI. E-alerts may be triggered by a variety of different criteria, ranging from a single threshold creatinine value to full application of AKI diagnostic criteria. This may result in an automated comment being appended to the creatinine result, a phone call, email or text message to the requesting doctor, nephrologist or critical care outreach team, or a combination of the above. The intention is for the alert to prompt medical attention for these high-risk deteriorating patients, with a resulting improvement in patient outcomes (Fig. 1). The most successful e-alert systems are therefore likely to combine the alert with a clinical protocol for AKI management, and should be developed in collaboration with clinical colleagues.

Choosing alert criteria
Although a single threshold creatinine (for example, 300 µmol/L) is the simplest approach, this lacks both sensitivity and specificity for AKI. Creatinine may need to rise significantly before reaching the threshold, so the speed at which AKI is recognized may not be improved. In addition, depending on the population served by the laboratory, a large number of elevated creatinine results are likely to be from patients with stable chronic kidney disease, rather than AKI.
Accuracy can be improved by applying a ‘delta check’ to flag an absolute or percentage increase in creatinine, for example, a 75% increase in creatinine [5]. It is usually within the realms of most modern laboratory information management systems to offer one delta check for creatinine, and it is also sometimes possible to run multiple checks with different criteria. Finally, some systems aim to fully apply current definitions, such as those recommended by KDIGO (Table 1) [4].

Accurately estimating baseline creatinine is difficult
A problem faced both by simple delta checks and e-alerts based on AKI definitions is the difficulty in reliably estimating baseline creatinine. A system employing manual estimation of baseline by clinical biochemists at the Royal Derby Hospital has been shown to have good diagnostic accuracy for detection of AKI with a false negative rate of 0.2% and a false positive rate of 1.7% [6]. However, this approach is limited to normal working hours and many laboratories do not have the resources to replicate this labour intensive system. Instead, automatic surrogate estimation methods are used, such as the lowest, most recent or median creatinine value within a certain timeframe, such as the previous three months. Laboratories should be aware of the limitations of some of these estimation methods; for example, the lowest creatinine result has been shown to be a particularly poor estimate of baseline creatinine that can lead to high rates of potential AKI misclassification [7].

Should every case fulfilling AKI criteria be highlighted?
When choosing criteria for an e-alert system, it may seem sensible to use current definitions for AKI. However, there are arguments against this approach. The KDIGO definition of AKI relies on small changes in serum creatinine based on epidemiological studies which show that even these small increases are associated with an increase in mortality risk in large populations [2]. However, in many cases an increase of 0.3 mg/dl (≥26.5 µmol/L) is within the realms of normal biological variation, particularly amongst patients with chronic kidney disease. As an illustrative example, creatinine increased by between 69% and 129% after the consumption of 300 g of animal protein in healthy volunteers, even with creatinine measurement using a specific enzymatic method [8]. The limitations of the more widely used Jaffe method for serum creatinine are well known amongst laboratory professionals, and any of a wide range of non-creatinine chromogens may cause an increased result in the absence of renal disease. When KDIGO criteria are combined with a poor method of baseline estimation (lowest previous creatinine), the proportion of creatinine results causing an AKI e-alert can approach 10%; this is unlikely to be helpful. Strict application of current AKI definitions could therefore lead to annoyance and unresponsiveness amongst clinicians alerted to minor creatinine elevations, unnecessary interventions, anxiety for patients and families, and diversion of limited healthcare resources to a large and relatively low risk group.  It is therefore important for laboratories to consider both local IT and resource capabilities and the relative benefit and harm of different criteria for e-alerts before implementation.

Evidence base
A small number of studies have investigated the effect of AKI e-alerts on clinician behaviour or patient outcomes. For example, a real-time alert of worsening AKI stage through a text message sent to the clinician’s telephone was found to increase the number of early therapeutic interventions in an ICU in Belgium [9]. There was also an increase in the proportion of patients who recovered their renal function within 8 hours after an alert indicating less severe AKI, but not amongst those with more severe AKI. There was no significant effect on renal replacement therapy, ICU length of stay, mortality, maximum creatinine or maximum AKI stage. Importantly, 9 out of 10 AKI alerts were based on urine volume criteria, so the applicability of these findings to creatinine based e-alerts is questionable.
Hospitals that have already implemented AKI e-alerts have noted improved outcomes following their introduction. For example, a hospital-wide e-alert system based on changes in serum creatinine at the Royal Derby Hospital, led to a progressive reduction in 30 day mortality over consecutive 6 month periods (23.7%, 20.8%, 20.8%, 19.5%, chi-square for trend P=0.006) [10]. This improvement in survival was maintained after adjustment for age, co-morbid conditions, severity of AKI, elective/non-elective admission and baseline renal function. However, the e-alert was introduced as part of a range of educational interventions so it is difficult to determine the contribution made by the e-alert component.
The evidence base for AKI e-alerts is therefore not strong, and would benefit from further studies to demonstrate that this approach can lead to measurable improvements in patient outcomes.

Conclusions
E-alerts represent an opportunity for the laboratory to assist in the early detection of acute kidney injury. This could improve the outcomes of patients with this life threatening condition. Aside from AKI, there are undoubtedly many other opportunities for the laboratory to optimize existing resources by helping clinicians to digest the large amount of laboratory data produced on a daily basis, to highlight trends and to ensure that important changes are recognized and acted upon. The laboratory can play a key role to ensure that these systems are implemented, that they are effective in selectively capturing a high risk population, and that evidence is gathered to justify their continued use.

References
1. Coca SG, et al. Long-term risk of mortality and other adverse outcomes after acute kidney injury: a systematic review and meta-analysis. Am J Kidney Dis. 2009; 53(6): 961–973.
2. Chertow GM, et al. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol. 2005; 16: 3365–3370.
3. Stewart J, et al. Adding Insult to Injury: a review of the care of patients who died in hospital with a primary diagnosis of acute kidney injury (acute renal failure). A report by the National Confidential Enquiry into Patient Outcome and Death. London: NCEPOD, 2009. www.ncepod.org.uk/2009report1/Downloads/AKI_report.pdf
4. Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney Int. Suppl. 2012; 2: 1–138.
5. Thomas M, et al. The initial development and assessment of an automatic alert warning of acute kidney injury. Nephrol Dial Transplant 2011; 26: 2161–2168.
6. Selby N, et al. Use of electronic results reporting to diagnose and monitor aki in hospitalized patients. Clin J Am Soc Nephrol. 2012; 7: 533–540.
7. Siew ED, et al. Estimating baseline kidney function in hospitalized patients with impaired kidney function. Clin J Am Soc Nephrol. 2012; 7: 712-719.
8. Butani L, et al. Dietary protein significantly affects the serum creatinine concentration. Kidney Int. 2002; 61: 1907.
9. Colpaert K, et al. Impact of real-time electronic alerting of acute kidney injury on therapeutic intervention and progression of RIFLE class. Crit Care Med. 2012; 40: 1164–1170.
10. Kohle N, et al. Impact of a combined, hospital-wide improvement strategy on the outcomes of patients with acute kidney injury (AKI) [abstract]. Joint Congress of the British Transplantation Society & Renal Association, 2013. Bournemouth. Abstract O30. www.btsra2013.com/

The author
Nick Flynn, Pre-registration clinical scientist
Department of Clinical Biochemistry, University College London Hospitals, London, UK
E-mail: nick.flynn@nhs.net

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p20 02

NGAL as a biomarker of acute kidney injury

, 26 August 2020/in Featured Articles /by 3wmedia

The diagnosis of acute kidney injury (AKI) is often hindered by the reliance on serum creatinine as a marker of kidney function, which can delay detection. Neutrophil gelatinase-associated lipocalin is a promising biomarker which increases within hours of kidney damage and could therefore improve the early diagnosis of AKI.

by Dr Ashley Garner

Clinical background
Acute kidney injury (AKI) is a common condition associated with significant morbidity and mortality. It is currently diagnosed using serum creatinine and urinary output as markers of kidney function, as defined in the recent KDIGO criteria [Fig. 1][1]. However, these are relatively late markers of AKI since they mainly reflect a decrease in glomerular filtration rate and the time required for serum creatinine to accumulate can delay diagnosis. Biomarkers that can detect structural injury to the kidney rather than a loss of function may allow better and earlier detection of AKI. Earlier diagnosis of AKI could facilitate earlier intervention, potentially reduce the risk of irreversible kidney damage and improve patient outcomes. Much research in recent years has therefore focused on the discovery of improved biomarkers for AKI and neutrophil gelatinase-associated lipocalin (NGAL) is one of the most promising candidates [2].

Pathophysiology of NGAL

NGAL is a small 25kDa protein which belongs to the superfamily of lipocalins. It is expressed in many cells including neutrophils, hepatocytes and renal tubular cells and is induced in response to pathological stimuli including infection, inflammation, ischemia and malignancy. NGAL has a functional role in the innate immune system as a bacteriostatic agent, depleting iron-binding siderophores and thereby preventing bacterial iron acquisition. The iron-binding properties of NGAL are also proposed to provide protection from oxidative stress. There is growing evidence that NGAL also acts as a growth factor in some tissues including renal epithelial cells where it modulates cell proliferation, differentiation and apoptosis and may provide protection against renal tubular damage in AKI [3].

Animal studies of AKI induced by ischemia or nephrotoxicity have shown that NGAL is one of the most upregulated proteins in the kidney and is detectable in the urine within 2–3 h. It has been reported that urine NGAL concentrations increase 25–100 fold and plasma NGAL increases 7–16 fold following AKI. Unlike serum creatinine, NGAL is not increased when there is impaired glomerular filtration without renal tubular damage, often termed ‘pre-renal’ uraemia.
Low plasma concentrations of NGAL are found in health as it is expressed at a low constant rate from various tissues. NGAL is then freely filtered at the kidney and the majority is reabsorbed in the proximal tubule, resulting in low NGAL concentrations in the urine. Following AKI, NGAL is greatly upregulated in the cells lining the ascending loop of Henle and collecting ducts of the kidney and is then excreted in the urine. The origin of the increase in plasma NGAL following AKI is less clear and there is evidence to suggest that NGAL expression is increased in other organs such as the lungs and liver following kidney injury.

Since NGAL can be produced by different tissues in response to various stimuli, it is not specific to AKI. Other common conditions that can cause elevated NGAL, and therefore complicate the interpretation of results, include sepsis, heart failure, chronic kidney disease (CKD), malignancy and urinary tract infections.

NGAL assays
Commercial CE marked assays are available for measuring NGAL in plasma, whole blood and urine. It is not clear from the literature whether any of these sample types are preferred or have better diagnostic performance but there are limiting factors for each that may require consideration. Plasma and whole blood samples are invasive and may be contaminated by haemolysis releasing NGAL from neutrophils. Urine NGAL may theoretically be more sensitive for AKI due to greater induction in renal tubular cells but can be falsely elevated in urinary tract infections due to leukocyturia and it is still unclear whether the NGAL should be corrected for urine concentration effects or whether this is unnecessary or even misleading in AKI. Although non-invasive, urine samples may be more difficult to obtain especially at specific time points or if the patient has reduced urine output.

NGAL exists in monomeric, dimeric and heterodimeric or complexed forms. It has been reported that the monomer is the predominant form produced by renal tubular cells and the homodimer is predominantly released by neutrophils. The relevance of these different forms of NGAL will depend on the extent to which NGAL assays detect them and the sample type used. Even though the monomer form may be most relevant for urine NGAL the origin of plasma NGAL in AKI is less clear and may therefore include the other forms. This variation in NGAL assays and sample types makes it difficult to directly compare study results and derive clinically relevant cut-off values. Standardization of NGAL assays using an internationally approved reference material would greatly improve this variation but this is not currently available and would require agreement on what forms of NGAL should be measured.

Research from large heterogeneous populations suggests that urine NGAL concentrations are dependent on gender, age and ethnicity. Biological variation for urine NGAL has also been reported to be as high as 84%. These factors will need to be taken into account when establishing reference intervals for NGAL although they may not be clinically significant if a cut-off value is used to diagnose AKI, especially if it greatly exceeds the expected reference intervals in health.

Clinical utility of NGAL in AKI

There is evidence that NGAL could be useful as an early diagnostic and prognostic biomarker for AKI. Many studies have demonstrated that NGAL rises 24–72 h before creatinine in patients with AKI and is associated with poorer outcomes. It is difficult to determine the diagnostic performance of NGAL for AKI in terms of clinical sensitivity and specificity however, due to the limitations of using serum creatinine as the gold standard comparator. For example, the rise in creatinine caused by pre-renal uraemia will not be associated with a raised NGAL. In addition, a multicentre pooled analysis of prospective studies has shown that patients who have raised NGAL without increases in serum creatinine are at increased risk of adverse outcomes and suggests these patients have a condition termed ‘subclinical AKI’ where there may be tubular damage without glomerular impairment [Fig. 2][4].

The majority of studies assessing NGAL testing in AKI have focused on specific patient populations at high risk of AKI: namely post-cardiac surgery, post contrast infusion, intensive care and emergency admissions.
The advantage of using NGAL in post-surgery or post-contrast patients is that the time of insult is known and therefore NGAL can be measured at set time points for the early detection of AKI and timely intervention. It is more difficult to determine the best application of NGAL in ICU patients in regard to the timing and frequency of tests and it is less clear whether earlier detection can improve outcomes in these patients frequently complicated by multi-organ failure. In the emergency admissions setting NGAL has fewer advantages over serum creatinine since early detection (within hours) is less likely to be applicable. Also NGAL, like creatinine, can be raised in CKD so may require multiple measurements to detect AKI but more patients are likely to have had a previous creatinine result than an NGAL result.

Although there is an abundance of observational studies showing that AKI can be detected earlier using NGAL compared to serum creatinine there is an absence of randomized clinical trials to demonstrate that using NGAL instead of current practice will improve patient outcomes or provide cost benefits. This is probably the biggest barrier to the adoption of NGAL testing in routine practice and better treatments and interventions may be required to overcome it. This would suggest that one of the most important roles for NGAL and earlier biomarkers of AKI is in the discovery and development of effective interventions and therapeutics.
Another consideration regarding interventions for AKI is that NGAL only detects renal tubular damage, it does not distinguish between different causes. However, effective treatments may require the underlying cause to be determined and therefore further biomarkers may be needed to differentiate between causative factors and indicate the most appropriate intervention.

Conclusion
A large number of clinical studies suggest that NGAL may provide an early diagnostic and prognostic biomarker for AKI. However, further randomized clinical trials comparing the use of NGAL to standard practice are required to show cost benefits or improvements in patient outcomes. It seems that even if biomarkers like NGAL enable us to detect AKI earlier, this alone may not be sufficient to improve patient care but hopefully they will facilitate the development of better interventions that will eventually lead to improved outcomes for patients with AKI.

References
1. Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney Int. Suppl. 2012; 2: 1–138.
2. ADQI Consensus on AKI Biomarkers and Cardiorenal Syndromes. Contrib Nephrol. Basel: Karger, 2013; 182: 13–29.
3. Schmidt-Ott KM, Mori K, Li JY, Kalandadze A, Cohen DJ, Devarajan P, Barasch J. Dual action of neutrophil gelatinase-associated lipocalin. J Am Soc Nephrol. 2007; 18: 407–413.
4.  Haase M, Devarajan P, Haase-Fielitz A, Bellomo R, Cruz DN, Wagener G, Krawczeski CD, Koyner JL, Murray P, Zappitelli M, Goldstein SL, Makris K, Ronco C, Martensson J, Martling CR, Venge P, Siew E, Ware LB, Ikizler TA, Mertens PR. The outcome of neutrophil gelatinase-associated lipocalin-positive subclinical acute kidney injury: a multicenter pooled analysis of prospective studies. J Am Coll Cardiol. 2011; 57(17): 1752–1761.

The author

Ashley Garner PhD
Department of Blood Sciences,
Leeds Teaching Hospitals Trust, Leeds, UK

E-mail: Ashley.Garner@leedsth.nhs.uk

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, 26 August 2020/in Featured Articles /by 3wmedia
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, 26 August 2020/in Featured Articles /by 3wmedia
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, 26 August 2020/in Featured Articles /by 3wmedia
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C119 GA Generic Assays Figure 1

CytoBead Assays – A state of the art combination of cell-based immunofluorescence and microparticle technology for simultaneous screening and differentiation in autoimmune diagnostics

, 26 August 2020/in Featured Articles /by 3wmedia

Autoimmune diseases affect approximately 5 % of the population of developed countries with an increasing incidence. Analysis of disease-associated autoantibodies (AAb) plays a significant role in the differential diagnosis thereof. Indirect immunofluorescence (IIF) has been established as the gold standard for AAb screening in particular for systemic rheumatic diseases. In the recommended two-tier approach for antibody serology, confirmatory testing by molecular assay techniques such as ELISA is required to confirm positive findings by screening using IIF. To cope with the constantly increasing demand for AAb testing, new efficient diagnostic approaches are required. Thus, a new generation of IIF assays have been developed to combine screening and confirmatory testing on one platform for the simultaneous detection of AAb by cell-based and bead-based assays in one reaction environment.  The multiplex analysis of antineutrophil cytoplasmic antibodies (ANCA) for the differential diagnosis of vasculitides will be discussed as a first application of this novel approach.

by Dr. Christina Fritz, Mandy Sowa and Dirk Roggenbuck

ANCA-associated vasculitis
Vasculitis is an inflammation affecting blood vessel walls and resulting in their damage, fibrinoid necrosis, tissue ischemia and necrosis, and finally vessel rupture with bleeding into the surrounding tissue [1, 2]. Due to etiological factors, systemic vasculitis is differentiated into primary and secondary vasculitis. Primary systemic vasculitis of particularly small vessels often has an autoimmune pathogenesis accompanied by the occurrence of ANCA [3,5-8]. Those so called ANCA-associated systemic vasculitides (AASV) comprise microscopic polyangiitis (MPA), eosinophilic granulomatosis with polyangiitis (EGPA or Churg-Strauss syndrome) or granulomatosis with polyangiitis (GPA or Wegener’s granulomatosis)[1, 2, 4]. In contrast, secondary vasculitis occurs in 5 – 10 % of patients with rheumatoid arthritis or with other autoimmune diseases (e.g., systemic lupus erythematosus [SLE], Sjögren’s syndrome). In addition, vasculitis can occur in patients suffering from infections such as HIV or hepatitis C.
In general, an acute AASV generally requires immunosuppressive treatment with high doses of cortisone. In severe cases, cyclophosphamide is recommended. Once remission is achieved, methotrexate, azathioprin, cotrimoxazol, leflunomid or mucophenolate mofetil are used as maintenance therapy.

Diagnosis of ANCA-associated vasculitis
According to the international consensus statement for the assessment of ANCA, IIF on ethanol-fixed human neutrophils (ethN) is followed by confirmation with antigen-specific molecular immunoassays [6-8]. IIF reveals two ANCA patterns sub-classifying ANCAs into cytoplasmic ANCA (cANCA) and perinuclear ANCA (pANCA). Regarding the autoantigenic target of ANCA, c and pANCA are directed against proteinase 3 (PR3) and myeloperoxidase (MPO), respectively. A positive cANCA pattern confirmed by the presence of PR3-ANCA is pathognomonic for GPA[5], whereas a positive pANCA pattern confirmed by MPO-ANCA is decisive for MPA and EGPA. Furthermore, the corresponding ANCA titres are strongly associated with activity of disease in patients suffering from GPA and MPA.
As a matter of fact, IIF is currently the only technique to provide a single reaction environment for the combined screening and confirmation of ANCA.  Simultaneous detection of c and pANCA along with PR3- and MPO-ANCA would overcome time-consuming single parameter detection by different techniques [10].

The use of multiplexing bead-based IIF assays for the simultaneous detection of single ANCA reactivities provides the ideal reaction environment to be combined with ethN-based ANCA testing. The corresponding principle is based on a covalent surface immobilization of MPO and PR3 on microbeads coded by size and fluorescence. The differentiation in size and/or intensity of a red fluorescence dye filling entirely each microbead population generates a novel reaction environment for parallel analyte analysis [11] (figure 1).

Combination of cell-based and microbead based ANCA assessment by CytoBead assay
The CytoBead assay is a unique combination of a conventional cell-based immunofluorescence assay with multiplexing microbead technology in one reaction environment. A newly designed microscopic glass slide with triple parted wells is employed to fix ethN in the middle compartment and PR3- as well as MPO-coated microbeads in the right-hand compartment of the slide (figure 2). Thus, anti-PR3 antibody positive sera show a positive cytoplasmic fluorescence on ethN and a green fluorescence halo on the surface of PR3-coated microbeads (9 µm). In contrast, anti-MPO antibody positive sera demonstrate a perinuclear fluorescence pattern on the immobilized ethN and a fluorescence halo on the surface of MPO-coated microbeads (15 µm) (figure 2). A reference microbead population (12 µm) is integrated for particle differentiation. This assay set offers the possibility of classical evaluation by a simple fluorescence microscope as well as automated analysis by interpretation systems like the AKLIDES®.

A recent clinical study with classical ANCA testing revealed a relative sensitivity and specificity of 98 % and 99.2 % for the novel CytoBead ANCA assay, respectively. Remarkably, the CytoBead ANCA assay showed a better discrimination of GPA and MPA patients in contrast to the classical anti-MPO and anti-PR3 ELISA. The detected cut-off values were determined on the basis of fluorescence intensity given in arbitrary units [AU] (personal communication).

Conclusion and future perspectives
The increasing demand for cost-effective autoimmune diagnostics requires new multiplexing technologies combining screening and confirmatory testing in one reaction environment. Thus, the novel CytoBead technology is a promising opportunity to accomplish this goal as demonstrated for the comprehensive assessment of ANCA. Automated digital immunofluorescence employed by recently established novel diagnostic interpretation system solutions such as Aklides even offers quantification and standardization of ANCA detection. The CytoBead technology provides an ideal reaction environment for the multiplexing of antinuclear antibody assessment and the simultaneous detection of celiac disease-specific antibodies. 

References
1. Watt RA, Scott DG. Recent advances in classification and assessment of vasculitis. Best Pract Res Clin Rheumatol. 2009; 23: 429-443
2. Jeanette JC, Falk RJ. Small-vessel vasculitis. N Eng J Med. 1997; 337: 1512-23
3. Gross WL, Trabant A, Reinhold-Keller E. Diagnosis and evaluation of vasculitis. Rheumatology (Oxford). 2000; 39: 245-52
4. Waller R, Ahmed A, Patel I, Luqami R. Update on the classification of vasculitis. Best Pract Res Clin Rheumatol. 2013; 27: 3-17
5. Bosch X, Guilabert A, Font J: Antineutrophil cytoplasmic antibodies. Lancet 2006, 368:404-18
6. Jennette JC, Falk RJ, Bacon PA, Basu N, Ferrario F, Flores-Suarez LF, Gross WL, Guillevin L, Hagen EC, Hoffman GS, Jayne DR,  Kallenberg CG, Lamprecht P, Langford CA, Lugmani RA, Mahr AD, Matteson EL, Merkel PA, Ozen S, Pusey CD, Rasmussen N, Rees AJ, Scott DG, Specks U, Stone JH, Takahashi K, Watts RA: 2012 revised International Chapel Hill Consensus Conference Nomenclature of Vasculitis. Arthritis Rheum. 2013, 65:1-11
7. Jennette JC, Falk RJ, Andrassy K, Bacon PA, Churg J, Gross WL, Hagen EC, Hoffman GS, Hunder GG, Kallenberg CG: Nomenclature of systemic vasculitides. Proposal of an international consensus conference. Arthritis Rheum 1994, 37:187-92
8. Savige JF, Gillis DF, Benson E, Davies DF, Esnault VF, Falk RJ, Hagen EC, Jayne D, Jennette JC, Paspaliaris B, Pollock W, Pusey C, Savage CO, Silvestrini R, van der Woude F, Wieslander J, Wiik A: International Consensus Statement on Testing and Reporting of Antineutrophil Cytoplasmic Antibodies (ANCA). Am J Clin Pathol 1999, 111:507-13
9. Merkel PA, Polisson RP, Chang Y, Skates SJ, Niles JL: Prevalence of antineutrophil cytoplasmic antibodies in a large inception cohort of patients with connective tissue disease. Ann. Intern. Med. 1997, 126;866
10. Choi HK, Liu S, Merkel, PA, Colditz GA, Niles Jl: Diagnostic performance of antineutrophil cytoplasmic antibody tests for idiopathic vasculitides: metaanalysis with a focus on antimyeloperoxidase antibodies. J. Rheumatol. 2001, 28:1584
11. Grossmann K, Roggenbuck D, Schröder C, Conrad K, Schierack P, Sack U: Multiplex Assessment of Non-Organ-Specific Autoantibodies with a Novel Microbead-Based Immunoassay. 2011, Cytometry Part A! 79A: 118”125

Author
Dr. Christina Fritz*, Mandy Sowa and Dirk Roggenbuck
Medipan GmbH, Ludwig-Erhard-Ring 3,
15827 Dahlewitz,
Germany

*Corresponding author
E-mail: c.fritz@medipan.de

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Brand new FilmArray Blood Culture Identification (BCID) Panel

, 26 August 2020/in Featured Articles /by 3wmedia
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Neurocysticercosis: can we trust serology?

, 26 August 2020/in Featured Articles /by 3wmedia

Which is the most common parasitic disease of the nervous system, which affection is the leading cause of seizures and acquired epilepsy in the developing world but still preventable? The answer: neurocysticercosis. An orphan disease suffering from the absence of a real ‘gold standard’ diagnosis. Meanwhile, many laboratories perform immunodiagnosis but what is its real value and what can it tell us?

by Dr Jean-François Carod

What is neurocysticercosis?
Cysticercosis of the central nervous system (neurocysticercosis) is caused by the larval stage (cysticerci) of the pork tapeworm Taenia solium. When people eat undercooked pork containing viable cysticerci, they develop an intestinal tapeworm infection (Fig. 1). Humans can also become intermediate hosts, however, by directly ingesting T. solium eggs shed in the feces of human carriers of the parasite. These eggs then develop into cysticerci, which migrate mostly into muscle (causing cysticercosis) and into the central nervous system where the cysticerci can cause seizures and many other neurological symptoms, neurocysticercosis (NCC). NCC is a major cause of epilepsy in endemic countries. It is the most important neurological disease of parasitic origin in humans. The pathogenesis is unclear but symptoms seem to correlate with the stage of the cyst. Starting as a viable entity, the cyst then gradually degenerates and become calcified. Seizures seem to appear at the degenerating and calcified stage but treatment is effective on the living cysts. Human cysticercosis is endemic in the Andean area of South America, Brazil, Central America and Mexico; China, the Indian subcontinent, South-East Asia; and Sub-Saharan Africa including Madagascar.

Why do we need to diagnose it?
Diagnosing NCC is required in the event of unexplained encephalitic disorders such as first onset of seizures in countries where NCC is endemic or in patients travelling in countries where NCC is endemic and who may have been at risk of infection (e.g. exposed to NCC risk factors, such as inadequate hand and food hygiene).

How can it be diagnosed?
The diagnosis of cysticercosis of the central nervous system involves the interpretation of non-specific clinical manifestations, such as seizures, often with characteristic findings on computed tomography (CT) or magnetic resonance imaging (MRI) of the brain, and the use of specific serological tests (Fig. 2). Diagnostic criteria based on objective clinical, imaging, immunological and epidemiological data have been proposed but are not generally used in areas endemic for the disease [1].

Serology is indicated for the diagnosis of T. solium seropositivity. But from a positive serology to the assessment of NCC diagnosis, there is a huge gap. A positive T. solium serology is not predictive for a neurological localization and serology may remain positive years after the end of the infection.
No single test can lead to a definitive diagnosis of NCC. CT-scan or MRI may be performed on the presentation of clinical symptoms that could be attributed to NCC (first onset of seizure, unexplained headache…) for people who were exposed to NCC risk factors. Imaging may show typical ring lesions with or without inflammation and calcification. However, the image is not pathognomonic of NCC unless hooks (scolex) are visible inside the ring. Thus, serology may give the clue if positive. A positive serology (antibody) may be confirmed by Western-blot or electro-immuno transfer blot (EITB), which show the typical bands specific of T. solium glycoproteins. Antigen detection in the blood can also be performed. This test is specific for T. solium and does not require laboratory confirmation. Both antigen and antibody assays can be performed in the cerebrospinal fluid (CSF). The presence of antibody or antigen in the CSF may contribute towards the assessment of the neurological localization of the disease. In developing countries, the regions most affected by T. solium infection, CT-scan and, of course, MRI are unaffordable, if ever available.

What are the current laboratory tools?
The laboratory diagnosis of cysticercosis is basically the immunodiagnostic based firstly on antibody detection with ELISA (enzyme-linked immunosorbent assay) or immunoblot.
The detection of antibodies against T. solium is a common method of infection diagnosis, but presents many limitations as a single cyst carrier may not be easily detected. Commercially available tests include essentially ELISA and Western-blots. Western-blots are the ‘gold standard’ assays for the detection of specific antibodies against T. solium. The reference Western-blot assay remains the one developed at the Centers for Disease Control (CDC), Georgia, USA, by Tsang et al. [2]. It employs a specific fraction of T. solium cysts. Many of the components have been identified and cloned. The test is very specific for exposure and/or disease and to confirm the diagnosis. Both ELISA tests and Western-blot relay on antigens that have varied significantly throughout the years (Fig. 3) [3]. Historically, the first assays used crude soluble extracts, then purified proteins such as lentil lectin glycoproteins (LLGPs) Recent trends, though not yet commercialized, tend to emphasize the use of recombinant proteins. Designing recombinant antigens requires a proteinomic approach (Fig. 4) that is now frequently used in development units. Current studies propose the use of nanobodies for diagnostic purposes. These evolutions increased both the sensitivity and the specificity of the tests.

Another available technique is based on the detection of circulating parasitic antigens using monoclonal antibodies [4]. This test is capable of detecting single cyst carriers and is more specific than available antibody ELISA tests. Its main advantage is its ability to monitor the response to cysticidal therapy.

Understanding the performance assessment of T. solium detection tests
Most commercially available ELISA tests have been evaluated by poor methodology. Assessing that a performance evaluation used the proper method means ensuring that the study used a serum bank of parasitologically-defined sera to assess test sensitivity. Defined cysticercosis sera should ideally include the following sera: two or more viable cysts, single viable cysts, degenerating cysts, calcified cysts.
Each series should be initially tested separately. A parasitologically-defined sera should correspond to the Del Brutto criteria [1]. In the absence of a true ‘gold standard’ for the diagnosis of neurocysticercosis, positive sera (cases) should be taken from patients with (1) absolute diagnosis of NCC, or (2) probable NCC diagnosis.       
     
The test specificity should be carefully evaluated using defined negative and potentially cross-reactive sera. Negative sera (control) should be taken from the same area and if possible from people exposed to the same risk factors as the positive cases, with age and sex correlation. Negative cases are usually taken from blood donors of developed countries. Those people have not been in contact with many parasitic infections and the sensitivity of the test will not be accurate/reliable for use in developing countries. This is why specificity should not only be assessed on negative samples from Western countries but also on other parasitic infections from cysticercosis-free developing countries.

What are the new trends in laboratory tests?
If only immunodiagnostic tools based on antibody or antigen detection are currently commercialized, new approaches have been developed including molecular biology (gene amplification in CSF mostly) (Fig. 5). However, so far none constitutes a ‘gold standard’. Table 1 summarizes the pros and cons of NCC diagnosis tools.

Conclusions and future
A test is reliable and useful if it contributes to a care improvement; that is to say to an appropriate therapy for all the patients. As for NCC; the decision to treat is still subject to controversy. Furthermore, even basic serologies are unaffordable or unavailable in endemic countries, not to mention imaging. The key will be in developing a reliable rapid test able to screen infected patients and correlated to neurological lesions of cysticerci.

References
1. Del Brutto OH. Diagnostic criteria for neurocysticercosis, revisited. Pathog Glob Health 2012; 106(5): 299–304.
2. Tsang VC, Brand JA,  Boyer AE. An enzyme-linked immunoelectrotransfer blot assay and glycoprotein antigens for diagnosing human cysticercosis (Taenia solium). J Infec Dis. 1989; 159(1): 50–59.
3. Esquivel-Velázquez M, Ostoa-Saloma P, Morales-Montor J, Hernández-Bello R, Larralde C. Immunodiagnosis of neurocysticercosis: ways to focus on the challenge. J Biomed Biotechnol. 2011; 2011: 516042. Doi:10.1155/2011/516042.
4. Garcia HH, Harrison LJ, Parkhouse RM, Montenegro T, Martinez SM, Tsang VC, Gilman RH. A specific antigen-detection ELISA for the diagnosis of human neurocysticercosis. The Cysticercosis Working Group in Peru. Trans R Soc Trop Med Hyg. 1998; 92(4): 411–414.

The author
Jean-François Carod Pharm D, MSc
Laboratoire de Biologie Médicale, GCS de l’ARC Jurassien, Centre Hospitalier Louis Jaillon, 2 Montée de l’hôpital, 39200 Saint-Claude, France.
E-mail: jean-francois.carod@ch-stclaude.fr

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c106 fig

Lipocalin 2 and brain-derived neurotrophic growth factor: biomarkers that link colorectal cancer and obesity?

, 26 August 2020/in Featured Articles /by 3wmedia

Colorectal cancer is one of the most prevalent types of cancer and is the fourth most common cause of cancer mortality. Identification of non-invasive biomarkers representative of disease heterogeneity is critical for diagnosis of early stage disease when the chance for cure is greatest. This article discusses two such biomarkers, brain-derived neurotrophic growth factor and lipocalin 2, which also reflect key independent risk factors for the disease obesity.

by Dr K. Y. C. Fung, Dr B. Tabor, Prof. P. Gibbs, Dr J. Tie, Dr P. McMurrick, Mr J. Moore, Prof. A. Ruszkiewicz, Prof. A. Burgess, Dr L. Cosgrove

Biomarkers for colorectal cancer: current status
Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide where epidemiological studies have drawn strong correlations between its incidence and lifestyle factors [1, 2]. The incidence of CRC varies considerably with geographic region, where it is highest in affluent countries (e.g. in the USA, UK, Europe, Australia and New Zealand the incidence is approximately 20–45 per 100 000) and lowest in African and Asian countries (incidence of approximately 5–20 per 100 000) [2]. In countries with increasing industrialization such as Japan, Korea and Singapore, the incidence of CRC is rapidly approaching that of high risk countries with a longer history of affluence [2]. For most sporadic CRC, the transformation from normal colonic mucosa to carcinoma is believed to occur over 10–15 yrs [3]. This relatively long time frame for disease development enables implementation of population screening programmes for disease detection as early stage diagnosis and removal of premalignant (adenoma or polyp) or early stage malignant disease (stage I) can either prevent the occurrence of CRC or significantly increase the chance of a complete cure.

Ideally, diagnostic tests are robust and cost effective and biomarkers should have high sensitivity and specificity for the disease they are proposed to detect. Currently, colonoscopy is regarded as the ‘gold standard’ for CRC diagnosis (sensitivity and specificity greater than 95%) but it is expensive and invasive. Accordingly, low cost alternatives such as the fecal occult blood test (FOBT) and the fecal immune test (FIT) are currently in use in population screening programmes in a number of countries [4]. These tests detect the presence of blood in stool samples and have low specificity for CRC. Their low sensitivity also leads to high rates of false positive results and they do not reliably detect early stage disease [5, 6]. As a result, identification of suitable biomarker(s) with high sensitivity and specificity for CRC that can be included in a non-invasive test suitable for population screening is urgently required. Despite extensive research efforts, no single biomarker has been identified and it is becoming apparent that a panel of biomarkers panel reflecting the heterogeneity of the disease will be more effective.

Sporadic CRC is linked to multiple environmental risk factors, with obesity consistently demonstrated to be a significant and independent risk factor [1]. Brain-derived neurotrophic growth factor (BDNF) and lipocalin 2 (LCN2) are two protein biomarkers that have been implicated in both obesity and CRC. BDNF has been shown to have a key role in neural regulation of appetite and food intake control [7], where low BDNF levels in the hypothalamic region of the brain have been associated with decreased satiety and weight gain. There is also evidence indicating that serum BDNF levels are lower in patients with type 2 diabetes in comparison to controls [8]. Similarly, elevated levels of circulating LCN2 have been documented in obese men and women and in patients with metabolic syndrome [9]. With the aim of identifying a panel of biomarkers to identify individuals potentially at risk of developing CRC, we investigated the utility of BDNF and LCN2 as individual biomarkers and as a biomarker panel to determine if this combination provided higher sensitivity for CRC diagnosis.

BDNF and LCN2 as CRC biomarkers
We have previously reported on the utility of circulating BDNF and lipocalin as biomarkers for CRC [10, 11]. In these studies, enzyme-linked immunosorbent assays (ELISAs) were used to measure the concentrations of each biomarker in the sera of a cohort of CRC patients (n=97) and age/gender matched controls (n=99). In this cohort, the median BDNF concentration was found to be significantly lower (P<0.0001) in the control population (18.8 ng/mL, range 4.0–56.5 ng/mL) when compared to the CRC group (23.4 ng/mL, range 3.0–43.1 ng/mL). Conversely, in the same cohort, the median concentration of LCN2 was significantly higher (P<0.0001) in the CRC group (121.5 ng/mL, range 31.65–432.6 ng/mL) when compared to the control group (86.36 ng/mL, range 17.11–189.9 ng/mL). At 95% specificity, the sensitivity of BDNF was 18% [area under curve (AUC) 0.69, P<0.0001)] and the sensitivity of LCN2 was 31% (AUC 0.71, P<0.0001). Although both biomarkers performed equally well at separating CRC patients from the normal cohort (demonstrated by the AUC), neither biomarker when considered alone reached the desired sensitivity for clinical use as a diagnostic approach for CRC. Figure 1 shows the receiver operating characteristic (ROC) curve for BDNF, LCN2 and for BDNF and LCN2 in combination. Table 1 summarizes the sensitivity at 95% specificity for BDNF and LCN2 individually and as a biomarker combination for each disease stage. LCN2 had consistently higher sensitivity than BDNF for diagnosing CRC overall and at each Dukes’ stage, and the LCN2 and BDNF combination does not appear to improve diagnostic efficacy. For example, at 95% specificity, the sensitivity was 33% for the LCN2 and BDNF combination (compared with 32% for LCN2). Strategies for biomarker identification
Current strategies for CRC biomarker identification include identification of tumour specific biomarkers and biomarkers indicative of the disease process, such as inflammation, the immune response, angiogenesis, and metastasis. Investigators have also reported on the utility of biomarker combinations that include established tumour markers such as CEA and CA19-9 [12, 13]. These strategies have yielded many promising individual candidate markers and marker panels that have been tested in small cohort studies, but none has resulted in the sensitivity and specificity required for population based screening. This lack of success has been attributed to factors such as small sample size, over-representation of late stage disease in test cohorts leading to overestimation of biomarker sensitivity, and disease heterogeneity where CRC subsets with different genetic backgrounds have been characterized [14].

As part of our strategy, we have also considered biomarkers indicative of established risk factors such as obesity and type 2 diabetes. Inclusion of these biomarkers, or biomarkers that are indicative of other risk factors, should enable us to identify those individuals who may be at greater risk of developing the disease and hence improve our ability for earlier diagnosis. This is critical for reducing mortality and morbidity associated with CRC where the 5-year survival rate for patients with stage I disease is >90% in comparison to 5% at stage D. Currently, more than 50% of malignancies are detected at an advanced stage despite the implementation of screening programmes. Although the BDNF and LCN2 combination does not provide adequate sensitivity and specificity for use in a clinical setting, it is possible that a combination of (one of) these markers with a CRC tumour specific marker may yield the desired analytical performance.

Future directions
The lack of FDA approval for any biomarkers as a diagnostic for CRC highlights the challenges associated with discovery, verification and validation of biomarkers. While –omics technologies (e.g. genomics, transcriptomics and proteomics) have been, and continues to be, the primary tool for discovery of novel biomarkers, these efforts have largely focused on identification of tumour specific markers. Incorporation of biomarkers representative of other disease factors will likely improve our chances of identifying a panel of markers to successfully diagnose CRC. Furthermore, stratification of risk based on genotype or environmental/lifestyle factors together with a panel of molecular biomarkers may prove to be more successful than any one of these factors alone for early diagnosis.

Acknowledgements
We thank the Victorian Cancer Biobank (Melbourne, Victoria) for their assistance with sample collection and Ms Ilka Priebe for technical assistance with the ELISAs. This work was funded by the CSIRO Preventative Health National Research Flagship and the National Health and Medical Research Council (grant number 1017078).

References
1. World Cancer Research Fund / American Institute for Cancer Research. Food, nutrition, physical activity, and the prevention of cancer: a global perspective.  Washington, DC: AICR 2007.
2. Jemal A, Bray F, et al. Global cancer statistics. CA Cancer J Clin. 2011; 61(2): 69–90.
3. Fearon ER, Vogelstein B. A genetic model for colorectal tumorigenesis. Cell 1990; 61(5): 759–767.
4. Hewitson P, Glasziou P, Watson E, Towler B, Irwig L. Cochrane systematic review of colorectal cancer screening using the fecal occult blood test (hemoccult): an update. Am J Gastroenterol. 2008; 103(6): 1541–1549.
5. Morikawa T, Kato J, Yamaji Y, Wada R, Mitsushima T, Shiratori Y. A comparison of the immunochemical fecal occult blood test and total colonoscopy in the asymptomatic population. Gastroenterology 2005; 129(2): 422–428.
6. Parra-Blanco A, Gimeno-García AZ, Quintero E, Nicolás D, et al. Diagnostic accuracy of immunochemical versus guaiac faecal occult blood tests for colorectal cancer screening. J Gastroenterol. 2010; 45(7): 703–712.
7. Vanevski F, Xu B. Molecular and neural bases underlying roles of BDNF in the control of body weight. Front Neurosci. 2013; 7: 37.
8. Fujinami A, Ohta K, Obayashi H, Fukui M, et al. Serum brain-derived neurotrophic factor in patients with type 2 diabetes mellitus: Relationship to glucose metabolism and biomarkers of insulin resistance. Clin Biochem. 2008; 41(10–11): 812–817.
9. Wang Y, Lam KS, Kraegen EW, Sweeney G, et al. Lipocalin-2 is an inflammatory marker closely associated with obesity, insulin resistance, and hyperglycemia in humans. Clin Chem. 2007; 53(1): 34–41.
10. Brierley GV, Priebe IK, Purins L, Fung KY, et al. Serum concentrations of brain-derived neurotrophic factor (BDNF) are decreased in colorectal cancer patients. Cancer Biomark. 2013; 13(2): 67–73.
11. Fung KY, Priebe I, Purins L, Tabor B, et al. Performance of serum lipocalin 2 as a diagnostic marker for colorectal cancer. Cancer Biomark. 2013; 13(2): 75–79.
12. Herszényi L, Farinati F, Cardin R, István G, et al. Tumor marker utility and prognostic relevance of cathepsin B, cathepsin L, urokinase-type plasminogen activator, plasminogen activator inhibitor type-1, CEA and CA 19-9 in colorectal cancer. BMC Cancer 2008; 8: 194.
13. Shimwell NJ, Wei W, Wilson S, Wakelam MJ, et al. Assessment of novel combinations of biomarkers for the detection of colorectal cancer. Cancer Biomark. 2010; 7(3): 123–132.
14. Tao S, Hundt S, Haug U, Brenner H. Sensitivity estimates of blood-based tests for colorectal cancer detection: impact of overrepresentation of advanced stage disease. Am J Gastroenterol. 2011; 106(2): 242–253.

The authors
Kim Y. C. Fung1* PhD; Bruce Tabor1 PhD; Peter Gibbs2 MBBS, MD, FRACP; Jeanne Tie2 MD; Paul McMurrick3 MBBS, FRACS; James Moore4 MBBS, MD, FRACS; Andrew Ruszkiewicz5 MD, FRCPA; Antony Burgess6 PhD; and Leah Cosgrove1 PhD

1CSIRO, Preventative Health National Research Flagship, Australia
2Royal Melbourne Hospital, Melbourne, Australia
3Cabrini Hospital, Melbourne, Australia
4Royal Adelaide Hospital, Adelaide, Australia
5SA Pathology, Adelaide, Australia
6Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia

*Corresponding author
E-mail: Kim.fung@csiro.au

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CLINITEST hCG pregnancy test

, 26 August 2020/in Featured Articles /by 3wmedia
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