Recently several clinical laboratories have reported antibody cocktails to perform leukocyte differentiation for routine screening. Distinct advantages over microscopic leukocyte differentiation are the large number of counted cells (tens of thousands) and objective immunological definition of the cell types. Here we review the published protocols and their usefulness for a routine setting.
by Dr G-J van de Geijn, Dr M. Beunis, Dr H. Janssen and Dr T. Njo
Differential white blood cell counting
Differential white blood cell count (dWBC) is an important and widely applied diagnostic test. The current generation of routine cell counters automatically produce a fast and reliable dWBC for most non-pathological samples. If dWBC results are aberrant or there are technical issues, the routine haematological analyser typically ‘flags’ a sample, and microscopic differentiation is mandatory. This dogma has been challenged by recent publications from independent groups. Although technically different, the approaches these groups have in common is that they each use a single flow cytometric tube for dWBC. This makes an implementation, which may be technically complicated and expensive, potentially feasible for clinical practice. Here we review the relative merits of the different flow cytometric approaches and attempt to position flow cytometric dWBC in clinical practice.
To appreciate the merits and disadvantages of the new flow cytometric approaches against the current microscopic practice, one must realise that leukocyte identification by flow cytometry is fundamentally different from microscopy. For example, microscopy can not differentiate lymphocyte subsets (B, T and NK cells), which are essentially defined immunologically. Flow cytometry can not replicate the microscopic classification of myeloid precursors because antigen expression in myeloid differentiation follows a different path from the microscopic phases. Although some of the dogmas for the interpretation of the microscopic leukocyte differentiation are more ‘practice-based’ than ‘evidence-based’, microscopy has the distinct advantage of a long history in clinical practice. A significant amount of training is required to ensure and maintain sufficient expertise among technicians to offer reliable round-the-clock service for microscopic dWBC. Due to the low number of cells counted (100-200) and the unequal distribution of cells on the slide, statistical variation and inter-observer differences are significant, well known disadvantages of microscopy [1,2].
Advantages of flow cytometry over microscopy are the large number of cells that are analysed (tens of thousands and more) and the objective immunological definitions of the different leukocyte types, using monoclonal antibodies defined by the international Human Leukocyte Differentiation Antigens (HLDA) classification system. This facilitates a more robust and evidence-based approach. In addition, different and more classes of leukocytes can be defined using flow cytometry compared to microscopy, providing growth potential for defining new cell populations for diagnosing and following up clinical diagnoses. Disadvantages of flow cytometry are increased costs of equipment, and that it is currently not used in many first-line haematology labs.
A new position for flow cytometry in routine clinical practice?
In the current clinical diagnostic setting, flow cytometry is almost exclusively performed in specialised laboratories during office hours, mainly as an established technique in leukaemia and lymphoma diagnostics. In routine haematological practice flow cytometry is not widely adopted. It is sometimes used as a reference method for quantifying leukocytes, erythroblasts and platelets during validation of a routine cell counter. Besides quantifying platelets and CD4 cell counts in the Celldyn-4000 and Sapphire routine cell counters, there is currently no widely adopted application in the routine laboratory. For leukocyte differentiation flow cytometry is mentioned in the CLSI guidelines as a candidate reference method for leukocyte differentiation. However the current reference method is still microscopic differentiation [3].
Flow cytometry
Flow cytometry uses specific monoclonal antibodies to detect cellular characteristics. These antibodies are labelled with fluorescent dyes emitting light at different specific wavelengths. Cell suspensions stained with a cocktail of antibodies can be analysed rapidly by flow cytometry which runs the cells past a laser. Light scatter and fluorescent signal are detected in different channels to give information on cell type, granularity and maturity of cells. Using combinations of these parameters the different cell types are detected in two-parameter dot-plots by so-called gates.
Flow cytometric differential white blood cell counting
In recent years several labs have reported antibody cocktails combined with acquisition protocols to perform flow cytometric dWBC [4-7]. The goal of these publications is to test if flow cytometric dWBC can be performed in a single tube as a screening tool for samples flagged for review by the haematology analyser [Figure 1]. Flagged samples are tested first by flow cytometry, which may reduce the number of microscopic differentiations required. These protocols have in common that they use a single tube approach requiring a small amount of blood and a cocktail of antibodies to determine an extended dWBC by using flow cytometry. Which leukocyte populations are defined, the number of leukocyte populations and the strategy used to define them differs [Table 1]. The main features of these protocols are discussed below.
Faucher and colleagues were the first to report their antibody cocktail, discriminating 12 different cell populations using a 6-marker/5-colours protocol [4]. This is the only cocktail using CD2, which enables identification of mature T-cells as well as T-blasts. This can be an advantage in detecting T-ALL with CD34- CD3- blasts. Another difference with the other cocktails is the use of CD294 to positively identify basophils, eosinophils and T-cells. The description of the lymphocyte subsets is incomplete as NK and T-cells cannot be discriminated. Although there is no general blast-marker to aid blast detection, blasts are detected and classified as T-lineage, B-lineage, monocytic or other blasts. NRBCs and plasma cells are not detected.
Using this antibody cocktail with a slightly adapted gating strategy, the first routine application, with flow cytometric dWBC integrated in the workflow of a haematology laboratory was published [8]. Samples flagged by the haematology analyser were analysed by flow cytometry before microscopy. Flow cytometer acquisition software that automatically adapts the gates to fit the different leukocyte populations and an automated pipetting station were used as technical aids. The authors show that this approach reduces the number of microscopic differentiations, manual hands-on time and turn-around-time. A group from Korea tested this cocktail with automatic gating software on a set of leukopenic samples, known to give problems with a reliable microscopic dWBC [9]. Both groups report that the gates were set correctly by the automatic software in >75% of the samples.
The cocktail reported by Bjornsson et al differentiates all nucleated cells in 11 categories using 6 markers and DRAQ5 staining with a 5-colour flow cytometer [5]. This protocol cannot discriminate between T and B-lymphocytes and uses CD203 to facilitate basophil detection. In contrast to the other cocktails, when the sample is diluted and re-measured using a low acquisition rate, CD36 can also be used to detect platelets.
Cherian and colleagues describe a 10 markers/8-colour cocktail including Hoechst staining to detect 12 leukocyte categories and NRBCs [6]. Strong points of their approach are the inclusion of CD34/117 for more robust blast detection, resulting in good correlations with microscopy. Furthermore CD33/64 is used for positive definition of monocytes and eosinophils, CD123 for basophils, CD38 for plasma cells and Hoechst to quantify NRBCs. No positive defining marker for T-cells is included.
Recently we reported our 10 marker/5-colour flow cytometric dWBC cocktail called Leukoflow [7]. Compared to the other cocktails, this cocktail uses the largest number of antibodies on a 5 colour machine. Although behind the scenes this requires a complex gating strategy to define the populations, the manual gating is not too difficult. Compared with the other methods, this assay is the most complete in defining lymphocyte subsets. Using CD3, CD19, CD16, CD56 and CD4 all lymphocyte subsets can be defined, including CD4-positive T-cells, except for the double positive CD3 and CD8 cells. CD138 is used to detect plasma cells. CD34 aids detection of blasts which can be further subdivided into blasts of the B-lymphoid, T-lymphoid or myeloid lineage. There is no positive marker for basophils. NRBCs can be quantified using a separate staining with DRAQ5 and antibodies.
Correlations between flow cytometry and cell counter/microscopy
The results of each of these reported flow cytometric protocols were compared with the results from haematology analysers and microscopy for sets of normal and abnormal blood samples. For normal, implicit, blood samples there are no real differences in the correlations between flow cytometry and microscopy for the different cocktails. In general, the correlations for neutrophils, lymphocytes and eosinophils are very good (>0.9) whereas the correlation for monocytes is lower (0.63-0.86) and the correlation for basophils is the poorest (0.29-0.70). To assess how these protocols compare when differentiating leukocytes in abnormal blood samples (e.g. containing plasma cells, blasts or immature granulocytes), these protocols should be compared on the same samples. This has not yet been reported in literature.
Additional clinical value of flow cytometric dWBC
Given the fact that different and more leukocyte populations can be identified with flow cytometric dWBC the question arises as to whether this additional information also has additional diagnostic value. Several examples of this have already been demonstrated. Roussel et al report efficient use of the ratio of T and B lymphocytes to discriminate B lymphoproliferative disorders in a random selected group of 349 with WBC >4×109/L [8]. This indicates that other flow cytometric dWBC methods that measure B- and T-lymphocytes, such as the ones reported by Cherian et al and our group can also use this [6,7]. Faucher et al demonstrated that in patients without known haematological disease flow cytometric dWBC can help to detect those with inflammatory syndrome (acute bacterial infection, heart failure, cancer, systemic disease) by their enhanced count of CD16-positive monocytes [4]. CD16-positive monocytes are found in nearly all inflammatory diseases [10]. CD16 positive monocytes are modulated during conditions such as atopic eczema, malaria infection and sepsis [11,12]. Information on CD16-positive monocytes can also be obtained with the other antibody cocktails using CD14, CD36 or CD33+CD64 to define monocytes.
The cocktail by Cherian et al contains CD64, which is reportedly upregulated on granulocytes during infection or sepsis [6,13]. Proper validation of the added clinical diagnostic value of all these parameters requires further investigations comparing patient cohorts homogeneous for the conditions mentioned above with the appropriate control patients.
Conclusion
All studies reported so far demonstrate that flow cytometric dWBC is technically feasible, and its results in general correlate well with the other known dWBC techniques. In order to compare the performance of these cocktails with each other it is crucial that they are compared on the same sample set. To our knowledge, such a comparison has not been published yet. Since all publications report good correlations between their flow cytometric dWBC and other methods for dWBC, we expect no big differences between the different cocktails for normal samples. For abnormal samples there will be differences due to the different composition of the cocktails. For implementation in a routine setting as a screening technique in between the haematology analyser and microscopic smear review, an automatic gating protocol is a significant advantage. This is only available for one of the reported methods so far. However, in order to make it a robust system suitable for use by a large group of technicians with 24/7 service, development of a flagging system that detects abnormalities/errors in the automated gating, as is present on haematology analysers, is a must. Unfortunately this is not available for any of the reported flow cytometric protocols yet, but it deserves significant attention to make this promising technique attractive for routine laboratories.
References
1. Pierre RV. Peripheral blood film review. The demise of the eyecount leukocyte differential. Clin Lab Med 2002;22(1):279-97.
2. Ruemke CL. The statistically expected variability in differential leukocytes counting In: Koepke JA, editor. Differential Leucocytes Counting. CAP Conference Aspen College of American Pathologist 1977; p 39-46.
3. Koepke JA, Van Assendelft OW, Brindza LJ, Davis BH, Fernandes BJ, Gewirtz AS, Rabinovitch A. Reference Leukocyte (WBC) Differential Count (Proportional) and Evaluation of Instrumental Methods; Approved Standard-Second Edition. Wayne, Pennsylvania: Clinical and Laboratory Standards Institute 2007; 1-35 p.
4. Faucher JL, Lacronique-Gazaille C, Frebet E, Trimoreau F, Donnard M, Bordessoule D, Lacombe F, Feuillard J. ‘6 markers/5 colors’ extended white blood cell differential by flow cytometry. Cytometry A 2007;71(11):934-44.
5. Bjornsson S, Wahlstrom S, Norstrom E, Bernevi I, O’Neill U, Johansson E, Runstrom H, Simonsson P. Total nucleated cell differential for blood and bone marrow using a single tube in a five-color flow cytometer. Cytometry B Clin Cytom 2008;74(2):91-103.
6. Cherian S, Levin G, Lo WY, Mauck M, Kuhn D, Lee C, Wood BL. Evaluation of an 8-color flow cytometric reference method for white blood cell differential enumeration. Cytometry B Clin Cytom 2010;78(5):319-328.
7. van de Geijn GJ, van Rees V, van Pul-Bom N, Birnie E, Janssen H, Pegels H, Beunis M, Njo T. Leukoflow: multiparameter extended white blood cell differentiation for routine analysis by flow cytometry. Cytometry A 2011;79(9):694-706.
8. Roussel M, Benard C, Ly-Sunnaram B, Fest T. Refining the white blood cell differential: the first flow cytometry routine application. Cytometry A 2010;77(6):552-63.
9. Jo Y, Kim SH, Koh K, Park J, Shim YB, Lim J, Kim Y, Park YJ, Han K. Reliable, accurate determination of the leukocyte differential of leukopenic samples by using Hematoflow method. Korean J Lab Med 2011;31(3):131-7.
10. Ziegler-Heitbrock L. The CD14+ CD16+ blood monocytes: their role in infection and inflammation. J Leukoc Biol 2007;81(3):584-92.
11. Novak N, Allam P, Geiger E, Bieber T. Characterization of monocyte subtypes in the allergic form of atopic eczema/dermatitis syndrome. Allergy 2002;57(10):931-5.
12. Skrzeczynska J, Kobylarz K, Hartwich Z, Zembala M, Pryjma J. CD14+CD16+ monocytes in the course of sepsis in neonates and small children: monitoring and functional studies. Scand J Immunol 2002;55(6):629-38.
13. Davis BH, Olsen SH, Ahmad E, Bigelow NC. Neutrophil CD64 is an improved indicator of infection or sepsis in emergency department patients. Arch Pathol Lab Med 2006;130(5):654-61.
The authors
Dr Gert-Jan van de Geijn, Dr Marlène Beunis, Dr Hans Janssen and drs Tjin Njo, MD.
Department of Clinical Chemistry (KCHL),
Sint Franciscus Gasthuis,
Kleiweg 500,
3045 PM Rotterdam,
The Netherlands.
e-mail: g.vandegeijn@sfg.nl
Glycomat 3000
, /in Featured Articles /by 3wmediaKimes 2012
, /in Featured Articles /by 3wmediaMulti-Constituent Controls
, /in Featured Articles /by 3wmedia‘Getting to zero’: first the good news
, /in Featured Articles /by 3wmediaIt is thirty years since the first diagnoses of AIDS were reported, since when, according to the most recent UNAids report, 25 million people have died from HIV-related causes and around 34 million people are currently living with the virus. However, as we enter the fourth decade of this devastating pandemic, there is certainly some light at the end of the tunnel, reflected in the theme that was adopted for this year’s World AIDS Day and until 2015: ‘Getting to Zero’. Although more aspirational than achievable, very real progress has been made.
The good news is that the number of AIDS-related deaths last year was the lowest (1.8 million deaths) since the peak of 2.2 million deaths in 2005, predominantly because of increasing access to antiretroviral treatment (ART) in low- and middle-income countries where the disease burden is heaviest, and where nearly seven million people are now receiving appropriate therapy. The UN-backed Global Fund against AIDS, TB and Malaria has played a significant role in this achievement. The incidence of HIV has also fallen in 33 countries, two thirds of which are in sub-Saharan Africa. Not only has ART reduced transmission, including vertical transmission, of the virus, but education and condom provision, more widespread HIV testing even in low-resource settings and counselling if necessary have all had a large impact. While efforts to introduce an effective HIV vaccine continue to be disappointing, results from trials on the pre-exposure use of antiretrovirals for prophylaxis are encouraging, and more easily tolerated drugs, such as rilpivirine, will improve life for some patient groups.
So what is the bad news? Firstly in some Western countries, where infected people can be diagnosed and treated early and have a near-normal lifespan, the incidence of HIV is actually increasing. And more important globally, there are still around ten million people waiting for treatment, the number of people with new infections remains higher than the number of people starting ART, and the staunch efforts of the Global Fund may now be affected by the financial fraud which was exposed in four recipient countries earlier this year as well as by the global economic crisis. Last month it was revealed that whilst international donors (the principal donors are the US, Germany, France and Japan) have been asked for donations totalling around fifteen billion Euros, the Global Fund has received only eight and a half billion Euros, which is lower than the amount needed to maintain its current programmes for the next three years. It is indeed a tragedy if millions of people continue to suffer from HIV because of the greed and mismanagement of a powerful few.
Recent progress in laboratory diagnosis of hereditary spherocytosis
, /in Featured Articles /by 3wmediaHereditary spherocytosis is an inherited haemolytic anaemia due to fragile red cells. This article gives a brief overview of the pathophysiology of this red cell disorder, and presents the key points on the different screening tests.
by Dr May-Jean King
Membrane structure of human red blood cell and associated defects
The human red blood cell (RBC) is discoid or biconcave in shape. It deforms when navigating through blood vessels and capillaries. The integrity and elasticity of RBC are maintained and regulated by a series of interactions between two layers of proteins localised to the outer lipid bilayer and the cytoskeleton on the cytoplasmic side [Figure 1]. The resulting RBC membrane is a 3D structure composed of specific transmembrane proteins (the band 3 macro-complex, and the glycophoein C-protein 4.1R) and a 2D network of skeleton proteins spectrin, actin, protein 4.1R and other minor components [1]. A qualitative or quantitative abnormality in one of these membrane proteins will lead to fragile red cells and haemolytic anaemia. Hereditary spherocytosis is associated with defects in the vertical interaction of the band 3 macrocomplex (i.e., band 3, CD47, and Rh complex) with protein 4.2, and ankyrin to which β-spectrin binds directly [Figure 1]. Hereditary elliptocytosis has abnormalities in protein 4.1R or defective spectrin self-association [2]. A partial deficiency of protein 4.1R can affect its interaction with glycophorin C and P55 in a junctional complex, which is stabilised by a band 3-adducin-spectrin bridge [3]. The mutations located in the self-association site for spectrin αβ heterodimers can affect the formation of tetramers or higher oligomers that enable the extension of the spectrin-based cytoskeleton to cover the cytoplasmic side of the red cell membrane. HS and hereditary elliptocytosis are not single-gene diseases.
Hereditary spherocytosis
Hereditary spherocytosis (HS) is more prevalent among the Northern European populations (about 1 in 2000 to 5000 births) than in other ethnic groups. Where the cytoskeleton fails to attach to band 3 in the membrane via protein 4.2 and ankyrin, that area of membrane becomes detached and is pinched off from the intact RBC. This continuous loss of membrane lipid and integral membrane proteins reduces the RBC volume and transforms it into a spherocyte. Splenic sequestration of spherocytes reduces their lifespan in circulation to <120 days. Therefore a patient with HS presents a haemolytic anaemia with reticulocytosis, jaundice and possibly gallstones and/or splenomegaly [4]. The clinical phenotype of HS is heterogeneous, ranging from asymptomatic, mild, moderate to severe haemolysis requiring blood transfusion. HS is diagnosed in newborn or as late as in the fifth to seventh decade of life. A mild HS condition can be exacerbated by an infection (e.g., Parvovirus B19, CMV, Herpes 6, gastroenteritis), resulting in a severe haemolytic anaemia. Laboratory testing for HS
Membranopathy is suspected when the cause of haemolytic anaemia remains unknown after the exclusion of enzymopathy, haemoglobinopathy and other extrinsic factors. Finding spherocytes in a blood smear indicates HS, but is not necessarily definitive. Exclusion of immune haemolytic anaemia (AIHA) is important because this condition also presents with spherocytosis [5]. Typical HS is expected to present almost all of the following features: evidence of a haemolytic process (e.g., raised bilirubin and LDH, low or no haptoglobin), low Hb, reduced mean cell volume, elevated mean cell haemoglobin concentration, and raised reticulocyte count [Figure 2]. The raised MCHC and increased % hyperdense RBCs are useful markers [6]. The diagnosis of dominant HS (75% of cases) is straightforward when family history of HS and the results for the red cell indices and blood chemistry are available. In the case of recessive HS, the proband may present a severe haemolytic anaemia with the blood smear showing anisocytosis and occasional cell fragments whereas the parents are apparently asymptomatic.
The majority of subjects with HS can be diagnosed by using a screening test without resorting to further investigation [Figure 2]. Two traditional screening tests for HS are still in use: the osmotic fragility test [7] and the acid glycerol lysis time test [8] [Table 1]. The cryohaemolysis test uses a change in temperature to effect red cell lysis [9]. The ektacytometer gives specific deformability profiles for a range of red cell disorders [Table 1]. However, this technique can give similar profiles for both HS and AIHA. SDS-polyacrylamide gel electrophoresis of erythrocyte membrane proteins is the confirmatory test because it detects all the membrane proteins known to be associated with HS [Figure 3, panel I]. Molecular analysis of membrane protein genes is usually performed by research laboratories. However, knowing the membrane protein defects and the associated protein gene mutation(s) does not influence the management of HS patients [12]. Unlike the aforementioned HS screening tests, the unusual feature of the EMA (eosin-5’-maleimide) Binding test [13] is the use of a flow cytometer, which analyses individual intact RBC in a sample. Confocal microscopy of EMA-labelled RBCs showed emission of both green and red fluorescence. RBCs of different sizes and shapes are labelled [Figure 3, panels II and III], [14]. The test is robust, only a low volume of patient specimen (5 µL packed RBC) and test reagent is required, and the test gives consistently reproducible results.
Conclusion
There is no screening test that has 100% sensitivity and 100% specificity for the diagnosis of HS. The adoption of the EMA Binding test is because it is easy to use and an abnormal result often indicates a membrane-associated red cell disorder. When this flow method is used in conjunction with the Osmotic Fragility test, differential diagnosis of HS and hereditary stomatocytosis can be made [described in 12].
References
1. Mohandas N & Gallagher PG. Red cell membrane: past, present, and future. Blood 2008; 112: 3939-3948.
2. Gallagher PG. Update on the clinical spectrum and genetics of red blood cell membrane disorders. Current Hematol Reports 2004; 3: 85-91.
3. Anong W et al. Adducin forms a bridge between the erythrocyte membrane and its cytoskeleton, and regulates membrane cohesion. Blood 2009; 114: 1904-1912.
4. Perrotta et al. Hereditary spherocytosis. Lancet 2008; 372:1411-1426.
5. Packman CH. The spherocytic haemolytic anaemias (historical review). Br J Haematol 2001;112: 888-899.
6. Cynober T et al. Red cell abnormalities in hereditary spherocytosis: relevance to diagnosis and understanding of the variable expression of clinical severity. J Lab Clin Med 1996;128:259-269.
7. Parpart AK et al. The osmotic resistance (fragility) of human red cells. J Clin Invest 1947; 26: 636-640.
8. Zanella A et al. Acidified glyceraol lysis test: a screening test for spherocytosis. Br J Haematol 1980; 45:481-486.
9. Streichman S & Gescheidt Y. Cryohemolysis for the detection of hereditary spherocytosis: correlation studies with osmotic fragility and authemolysis. A J Hematol 1998; 58:206-212.
10. Clark MR et al. Osmotic gradient ektacytometry: comprehensive characterization of red cell volume and surface maintenance. Blood 1983; 61: 899-910.
11. Johnson RM & Ravindranath Y. Osmotic scan ektacytometry in clinical diagnosis. J Ped Hematol Oncol 1996; 18: 122-129.
12. Bolton-Maggs et al. Guidelines for the diagnosis and management of hereditary spherocytosis – 2011 update. Br J Haematol 2011; doi:10.1111/j.1365-2141.2011.08921.x
13. King M-J et al. Rapid flow cytometric test for the diagnosis of membrane cytoskeleton-associated haemolytic anaemia. Br J of Haematol 2000; 111: 924-933.
14. King M-J et al. Using the eosin-5-maleimide binding test in the differential diagnosis of hereditary spherocytosis and hereditary pyropoikilocytosis. Cytometry Part B 2008; 74B: 244-250.
15. wKing M-J et al. Eosin-5-maleimide binding to band 3 and Rh-related proteins forms the basis of a screening test for hereditary spherocytosis. Br J Haematol 2004; 124:106-113.
The author
May-Jean King
Membrane Biochemistry
NHS Blood and Transplant
North Bristol Park
Filton
Bristol BS34 7QH
UK
e-mail: may-jean.king@nhsbt.nhs.uk
Go with the flow? Use of flow cytometry for routine leukocyte differential
, /in Featured Articles /by 3wmediaRecently several clinical laboratories have reported antibody cocktails to perform leukocyte differentiation for routine screening. Distinct advantages over microscopic leukocyte differentiation are the large number of counted cells (tens of thousands) and objective immunological definition of the cell types. Here we review the published protocols and their usefulness for a routine setting.
by Dr G-J van de Geijn, Dr M. Beunis, Dr H. Janssen and Dr T. Njo
Differential white blood cell counting
Differential white blood cell count (dWBC) is an important and widely applied diagnostic test. The current generation of routine cell counters automatically produce a fast and reliable dWBC for most non-pathological samples. If dWBC results are aberrant or there are technical issues, the routine haematological analyser typically ‘flags’ a sample, and microscopic differentiation is mandatory. This dogma has been challenged by recent publications from independent groups. Although technically different, the approaches these groups have in common is that they each use a single flow cytometric tube for dWBC. This makes an implementation, which may be technically complicated and expensive, potentially feasible for clinical practice. Here we review the relative merits of the different flow cytometric approaches and attempt to position flow cytometric dWBC in clinical practice.
To appreciate the merits and disadvantages of the new flow cytometric approaches against the current microscopic practice, one must realise that leukocyte identification by flow cytometry is fundamentally different from microscopy. For example, microscopy can not differentiate lymphocyte subsets (B, T and NK cells), which are essentially defined immunologically. Flow cytometry can not replicate the microscopic classification of myeloid precursors because antigen expression in myeloid differentiation follows a different path from the microscopic phases. Although some of the dogmas for the interpretation of the microscopic leukocyte differentiation are more ‘practice-based’ than ‘evidence-based’, microscopy has the distinct advantage of a long history in clinical practice. A significant amount of training is required to ensure and maintain sufficient expertise among technicians to offer reliable round-the-clock service for microscopic dWBC. Due to the low number of cells counted (100-200) and the unequal distribution of cells on the slide, statistical variation and inter-observer differences are significant, well known disadvantages of microscopy [1,2].
Advantages of flow cytometry over microscopy are the large number of cells that are analysed (tens of thousands and more) and the objective immunological definitions of the different leukocyte types, using monoclonal antibodies defined by the international Human Leukocyte Differentiation Antigens (HLDA) classification system. This facilitates a more robust and evidence-based approach. In addition, different and more classes of leukocytes can be defined using flow cytometry compared to microscopy, providing growth potential for defining new cell populations for diagnosing and following up clinical diagnoses. Disadvantages of flow cytometry are increased costs of equipment, and that it is currently not used in many first-line haematology labs.
A new position for flow cytometry in routine clinical practice?
In the current clinical diagnostic setting, flow cytometry is almost exclusively performed in specialised laboratories during office hours, mainly as an established technique in leukaemia and lymphoma diagnostics. In routine haematological practice flow cytometry is not widely adopted. It is sometimes used as a reference method for quantifying leukocytes, erythroblasts and platelets during validation of a routine cell counter. Besides quantifying platelets and CD4 cell counts in the Celldyn-4000 and Sapphire routine cell counters, there is currently no widely adopted application in the routine laboratory. For leukocyte differentiation flow cytometry is mentioned in the CLSI guidelines as a candidate reference method for leukocyte differentiation. However the current reference method is still microscopic differentiation [3].
Flow cytometry
Flow cytometry uses specific monoclonal antibodies to detect cellular characteristics. These antibodies are labelled with fluorescent dyes emitting light at different specific wavelengths. Cell suspensions stained with a cocktail of antibodies can be analysed rapidly by flow cytometry which runs the cells past a laser. Light scatter and fluorescent signal are detected in different channels to give information on cell type, granularity and maturity of cells. Using combinations of these parameters the different cell types are detected in two-parameter dot-plots by so-called gates.
Flow cytometric differential white blood cell counting
In recent years several labs have reported antibody cocktails combined with acquisition protocols to perform flow cytometric dWBC [4-7]. The goal of these publications is to test if flow cytometric dWBC can be performed in a single tube as a screening tool for samples flagged for review by the haematology analyser [Figure 1]. Flagged samples are tested first by flow cytometry, which may reduce the number of microscopic differentiations required. These protocols have in common that they use a single tube approach requiring a small amount of blood and a cocktail of antibodies to determine an extended dWBC by using flow cytometry. Which leukocyte populations are defined, the number of leukocyte populations and the strategy used to define them differs [Table 1]. The main features of these protocols are discussed below.
Faucher and colleagues were the first to report their antibody cocktail, discriminating 12 different cell populations using a 6-marker/5-colours protocol [4]. This is the only cocktail using CD2, which enables identification of mature T-cells as well as T-blasts. This can be an advantage in detecting T-ALL with CD34- CD3- blasts. Another difference with the other cocktails is the use of CD294 to positively identify basophils, eosinophils and T-cells. The description of the lymphocyte subsets is incomplete as NK and T-cells cannot be discriminated. Although there is no general blast-marker to aid blast detection, blasts are detected and classified as T-lineage, B-lineage, monocytic or other blasts. NRBCs and plasma cells are not detected.
Using this antibody cocktail with a slightly adapted gating strategy, the first routine application, with flow cytometric dWBC integrated in the workflow of a haematology laboratory was published [8]. Samples flagged by the haematology analyser were analysed by flow cytometry before microscopy. Flow cytometer acquisition software that automatically adapts the gates to fit the different leukocyte populations and an automated pipetting station were used as technical aids. The authors show that this approach reduces the number of microscopic differentiations, manual hands-on time and turn-around-time. A group from Korea tested this cocktail with automatic gating software on a set of leukopenic samples, known to give problems with a reliable microscopic dWBC [9]. Both groups report that the gates were set correctly by the automatic software in >75% of the samples.
The cocktail reported by Bjornsson et al differentiates all nucleated cells in 11 categories using 6 markers and DRAQ5 staining with a 5-colour flow cytometer [5]. This protocol cannot discriminate between T and B-lymphocytes and uses CD203 to facilitate basophil detection. In contrast to the other cocktails, when the sample is diluted and re-measured using a low acquisition rate, CD36 can also be used to detect platelets.
Cherian and colleagues describe a 10 markers/8-colour cocktail including Hoechst staining to detect 12 leukocyte categories and NRBCs [6]. Strong points of their approach are the inclusion of CD34/117 for more robust blast detection, resulting in good correlations with microscopy. Furthermore CD33/64 is used for positive definition of monocytes and eosinophils, CD123 for basophils, CD38 for plasma cells and Hoechst to quantify NRBCs. No positive defining marker for T-cells is included.
Recently we reported our 10 marker/5-colour flow cytometric dWBC cocktail called Leukoflow [7]. Compared to the other cocktails, this cocktail uses the largest number of antibodies on a 5 colour machine. Although behind the scenes this requires a complex gating strategy to define the populations, the manual gating is not too difficult. Compared with the other methods, this assay is the most complete in defining lymphocyte subsets. Using CD3, CD19, CD16, CD56 and CD4 all lymphocyte subsets can be defined, including CD4-positive T-cells, except for the double positive CD3 and CD8 cells. CD138 is used to detect plasma cells. CD34 aids detection of blasts which can be further subdivided into blasts of the B-lymphoid, T-lymphoid or myeloid lineage. There is no positive marker for basophils. NRBCs can be quantified using a separate staining with DRAQ5 and antibodies.
Correlations between flow cytometry and cell counter/microscopy
The results of each of these reported flow cytometric protocols were compared with the results from haematology analysers and microscopy for sets of normal and abnormal blood samples. For normal, implicit, blood samples there are no real differences in the correlations between flow cytometry and microscopy for the different cocktails. In general, the correlations for neutrophils, lymphocytes and eosinophils are very good (>0.9) whereas the correlation for monocytes is lower (0.63-0.86) and the correlation for basophils is the poorest (0.29-0.70). To assess how these protocols compare when differentiating leukocytes in abnormal blood samples (e.g. containing plasma cells, blasts or immature granulocytes), these protocols should be compared on the same samples. This has not yet been reported in literature.
Additional clinical value of flow cytometric dWBC
Given the fact that different and more leukocyte populations can be identified with flow cytometric dWBC the question arises as to whether this additional information also has additional diagnostic value. Several examples of this have already been demonstrated. Roussel et al report efficient use of the ratio of T and B lymphocytes to discriminate B lymphoproliferative disorders in a random selected group of 349 with WBC >4×109/L [8]. This indicates that other flow cytometric dWBC methods that measure B- and T-lymphocytes, such as the ones reported by Cherian et al and our group can also use this [6,7]. Faucher et al demonstrated that in patients without known haematological disease flow cytometric dWBC can help to detect those with inflammatory syndrome (acute bacterial infection, heart failure, cancer, systemic disease) by their enhanced count of CD16-positive monocytes [4]. CD16-positive monocytes are found in nearly all inflammatory diseases [10]. CD16 positive monocytes are modulated during conditions such as atopic eczema, malaria infection and sepsis [11,12]. Information on CD16-positive monocytes can also be obtained with the other antibody cocktails using CD14, CD36 or CD33+CD64 to define monocytes.
The cocktail by Cherian et al contains CD64, which is reportedly upregulated on granulocytes during infection or sepsis [6,13]. Proper validation of the added clinical diagnostic value of all these parameters requires further investigations comparing patient cohorts homogeneous for the conditions mentioned above with the appropriate control patients.
Conclusion
All studies reported so far demonstrate that flow cytometric dWBC is technically feasible, and its results in general correlate well with the other known dWBC techniques. In order to compare the performance of these cocktails with each other it is crucial that they are compared on the same sample set. To our knowledge, such a comparison has not been published yet. Since all publications report good correlations between their flow cytometric dWBC and other methods for dWBC, we expect no big differences between the different cocktails for normal samples. For abnormal samples there will be differences due to the different composition of the cocktails. For implementation in a routine setting as a screening technique in between the haematology analyser and microscopic smear review, an automatic gating protocol is a significant advantage. This is only available for one of the reported methods so far. However, in order to make it a robust system suitable for use by a large group of technicians with 24/7 service, development of a flagging system that detects abnormalities/errors in the automated gating, as is present on haematology analysers, is a must. Unfortunately this is not available for any of the reported flow cytometric protocols yet, but it deserves significant attention to make this promising technique attractive for routine laboratories.
References
1. Pierre RV. Peripheral blood film review. The demise of the eyecount leukocyte differential. Clin Lab Med 2002;22(1):279-97.
2. Ruemke CL. The statistically expected variability in differential leukocytes counting In: Koepke JA, editor. Differential Leucocytes Counting. CAP Conference Aspen College of American Pathologist 1977; p 39-46.
3. Koepke JA, Van Assendelft OW, Brindza LJ, Davis BH, Fernandes BJ, Gewirtz AS, Rabinovitch A. Reference Leukocyte (WBC) Differential Count (Proportional) and Evaluation of Instrumental Methods; Approved Standard-Second Edition. Wayne, Pennsylvania: Clinical and Laboratory Standards Institute 2007; 1-35 p.
4. Faucher JL, Lacronique-Gazaille C, Frebet E, Trimoreau F, Donnard M, Bordessoule D, Lacombe F, Feuillard J. ‘6 markers/5 colors’ extended white blood cell differential by flow cytometry. Cytometry A 2007;71(11):934-44.
5. Bjornsson S, Wahlstrom S, Norstrom E, Bernevi I, O’Neill U, Johansson E, Runstrom H, Simonsson P. Total nucleated cell differential for blood and bone marrow using a single tube in a five-color flow cytometer. Cytometry B Clin Cytom 2008;74(2):91-103.
6. Cherian S, Levin G, Lo WY, Mauck M, Kuhn D, Lee C, Wood BL. Evaluation of an 8-color flow cytometric reference method for white blood cell differential enumeration. Cytometry B Clin Cytom 2010;78(5):319-328.
7. van de Geijn GJ, van Rees V, van Pul-Bom N, Birnie E, Janssen H, Pegels H, Beunis M, Njo T. Leukoflow: multiparameter extended white blood cell differentiation for routine analysis by flow cytometry. Cytometry A 2011;79(9):694-706.
8. Roussel M, Benard C, Ly-Sunnaram B, Fest T. Refining the white blood cell differential: the first flow cytometry routine application. Cytometry A 2010;77(6):552-63.
9. Jo Y, Kim SH, Koh K, Park J, Shim YB, Lim J, Kim Y, Park YJ, Han K. Reliable, accurate determination of the leukocyte differential of leukopenic samples by using Hematoflow method. Korean J Lab Med 2011;31(3):131-7.
10. Ziegler-Heitbrock L. The CD14+ CD16+ blood monocytes: their role in infection and inflammation. J Leukoc Biol 2007;81(3):584-92.
11. Novak N, Allam P, Geiger E, Bieber T. Characterization of monocyte subtypes in the allergic form of atopic eczema/dermatitis syndrome. Allergy 2002;57(10):931-5.
12. Skrzeczynska J, Kobylarz K, Hartwich Z, Zembala M, Pryjma J. CD14+CD16+ monocytes in the course of sepsis in neonates and small children: monitoring and functional studies. Scand J Immunol 2002;55(6):629-38.
13. Davis BH, Olsen SH, Ahmad E, Bigelow NC. Neutrophil CD64 is an improved indicator of infection or sepsis in emergency department patients. Arch Pathol Lab Med 2006;130(5):654-61.
The authors
Dr Gert-Jan van de Geijn, Dr Marlène Beunis, Dr Hans Janssen and drs Tjin Njo, MD.
Department of Clinical Chemistry (KCHL),
Sint Franciscus Gasthuis,
Kleiweg 500,
3045 PM Rotterdam,
The Netherlands.
e-mail: g.vandegeijn@sfg.nl
Coagulation testing in a haematology lab: improving quality and efficiency
, /in Featured Articles /by 3wmediaOver the last three years, the haematology laboratory at Sheikh Khalifa Medical City (SKMC) in Abu Dhabi has introduced two STA-R Evolution analysers to fully automate coagulation testing. CLI spoke to Dima Yassin, Senior Supervisor in the haematology lab at SKMC, to discover how the new system has improved quality and efficiency in her lab and benefited both patients and healthcare personnel.
Q. Could you first tell us a little about the Sheikh Khalifa Medical City. What is its structure, how is it managed and what patient population does it serve?
Sheikh Khalifa Medical City (SKMC), managed by Cleveland Clinic, serves as the flagship institution for SEHA, Abu Dhabi’s healthcare organisation. SKMC was formed in 2005 as a result of merged healthcare entities in the Island of
Abu Dhabi.
SKMC comprises a 568 bed acute care hospital, 14 outpatient speciality clinics and a blood bank, all accredited by Joint Commission International (JCI). In addition, SKMC manages a 125 bed behavioral sciences pavilion, six family medicine clinics, two urgent Care Centres and two dental Centres.
Q. How is the diagnostic laboratory structured and roughly how many tests are carried out per day?
The diagnostic laboratory in SKMC is a CAP (College of American Pathology) accredited laboratory. The laboratory offers a full range of clinical laboratory services for the detection and diagnosis of disease. These services include phlebotomy, anatomical pathology, cytology, clinical chemistry, haematology/coagulation, microbiology, blood transfusion, a donor blood bank unit, immunology, serology, molecular pathology, histocompatibility testing and point-of-care testing. We run around 160,000 procedures per month.
Q. How many of these tests involve the haematology lab, and which tests are most frequently carried out in this lab? Are coagulation tests a major part of your workload and is this increasing? Do you carry out coagulation tests on pre-surgical patients as well as on patients who have coagulation abnormalities, or are on anticoagulation therapy?
In the haematology department at SKMC, we process around 1000 specimens per day, which include routine haematology and coagulation testing, special haematology and coagulation testing, bone marrow processing and flow cytometry. Coagulation is a vital part of our testing activities, which include monitoring patients on anticoagulant therapy, pre-surgical screening and investigation of coagulopathies.
Q.When did you invest in STA-R Evolution automated coagulation analysers for these tests and what were your reasons for choosing these instruments?
We installed the first STA-R Evolution analyser in our lab in 2008, and then followed this by the second STA-R Evolution analyser in 2010. Because the work load was increasing, we had decided we needed a fully automated stand-alone work station with high throughput and rapid processing of STAT samples
without the need to interrupt the current testing.
Q.What effect did the introduction of these analysers have on the organisation and productivity of the lab, and particularly on TATs?
The STA-R Evolution analysers are fully automated coagulation analysers designed to integrate comprehensive testing with minimal hands-on specimen handling. The analysers are fully integrated with the Laboratory Information System, which reduces turnaround times, increases quality and improves efficiency in the pre-analytical processing of specimens.
Q.Were you satisfied with the training and technical support you received?
The efficiency during the implementation, and in the planning and training provided by Diagnostica Stago played a vital role in the success of this project. This support continues to be available, with technical support provided as well as further updates and training workshops.
Q. Will you still be able to cope should your workload increase substantially?
Recently, we implemented a fully automated coagulation line integrated with two STA-R evolution analysers. This new technology is designed to accommodate a larger volume of work that can be completed in an efficient and timely manner.
Q.Finally how would you say that medical and technical staff, and most importantly the patients, have benefited from the introduction of these coagulation analysers?
The automated system eliminates almost all hands-on specimen handling for routine tests. It improves turnaround times and ensures that specimens are processed in an efficient and consistent manner. This allows us to provide high quality patient care.
Diagnostica Stago
Asnières sur Seine, France
Plague and its laboratory diagnosis
, /in Featured Articles /by 3wmediaPlague is an acute bacterial infection in man caused by Yersinia pestis. Historically, it has resulted in devastating pandemics (Black Death) throughout the world with high mortality rates in which pneumonic man-to-man transmission followed the usual flea-to-man transmission [1]. Plague may have retreated over the past decades due to availability of effective antibiotics and intensive vector control, but it has not been completely eradicated [2], and the third pandemic can be regarded as still ongoing, since Y. pestis sporadically re-emerges from its reservoir of wild rodents and spreads to the human population [3]. During the last 15 years more than 20 countries have reported plague cases to the WHO [3].
Outbreaks of plague in India emphasise the need to maintain the necessary skills and public health infrastructure to detect, monitor and combat a wide range of in infectious disease agents. Y. pestis is spread by aerosol and is usually fatal if treatment is not started within 24 hours of onset of symptoms [3,4]. A precise and quick diagnosis of plague allows prompt intervention, especially necessary during plague outbreaks. When rapidly diagnosed and promptly treated, plague may be successfully managed with antibiotics, reducing the mortality from 60% to less than 15% [5,6].
Clinical features
The diagnosis of plague still relies on clinical symptoms and exposure history in most endemic areas [1,3]. The three main clinical presentations of plague are bubonic, septicaemic and pneumonic plague. Bubonic plague is the classical form of the disease, characterised by fever, headache, chills and swollen, extremely tender lymph nodes or buboes within 2-6 days after contact with the pathogen. Buboes typically involve lymph nodes that drain the site of initial infection and are usually located in the inguinal, axillary or cervical region. In septicaemic plague, patients have positive blood cultures without palpable lymphadenopathy. Clinical symptoms, such as chills, headache, malaise and gastrointestinal disturbances resemble septicaemia caused by other gram negative bacteria. Pneumonic plague is the rarest form of plague with the highest mortality rate. Signs of pneumonic plague include severe pneumonia accompanied by high fever, dyspnea and often haemoptysis.
Laboratory diagnosis
Laboratory diagnosis of plague is mainly based on bacteriological and/or serological evidence. However molecular biological techniques based on PCR and DNA hybridisation have also been developed in recent years. Plague should be suspected if: clinical symptoms are compatible with plague i. e., fever and lymphadenopathy in a person who resides in or has recently travelled to a plague-endemic area; and small gram-negative and/or bipolar-staining coccobacilli are seen on a smear taken from affected tissues, e.g. bubo (bubonic plague), blood (septicaemic plague) and tracheal/lung aspirate (pneumonic plague).
The presumptive diagnosis of plague can be made if: an immunofluorescence stain of a relevant sample is positive for the presence of Y. pestis Fraction 1 capsular (F1) antigen; and a single serum specimen is tested and the anti-F1 antigen titre by agglutination is >1:10.* Confirmed plague is diagnosed if: an isolated culture is lysed by specific bacteriophage; two serum specimens demonstrate a four fold anti-F1 antigen titre rise by agglutination testing;* and a single serum specimen tested by agglutination has a titre of >1:128 and the patient has no known previous plague exposure or vaccination history.*
*Agglutination testing must be shown to be specific to Y. pestis F1 antigen by
haemagglutination inhibition.
Bacteriological work-up
This includes microscopy, isolation by cultivation, identification and confirmation by NAT tests and animal pathogenicity tests for Y. pestis. Specimens should be obtained from relevant sites at the appropriate time to enhance the reliability of the results. The preferred specimen for microscopic examination and isolation from a bubonic case is pus from an accessible bubo, which contains numerous organisms. Blood cultures should be taken whenever possible, particularly in septicaemic plague. Bronchial/tracheal washing should be taken from patients suspected of pneumonic plague. Throat swabs are not ideal for isolation of plague bacilli since they often contain many other bacteria that can mask the
presence of plague organisms [9].
Staining techniques such as Gram, Giemsa, Wright or Wayson stains can provide supportive but not confirmatory evidence of plague [2]. Blood smears taken from suspected bubonic plague patients are frequently negative as the bacteria are intermittently released from lymph nodes; periodic specimen collection at 10-30 minutes intervals gives more reliable results [9]. Sputum or throat smears taken from pneumonic plague patients may contain too many other organisms which can mask plague if only the staining techniques mentioned above are used. In addition smears should be stained using the more specific fluorescent antibody test (FA), which utilises fluorescent dye and targets capsular F1 antigen expressed predominantly at 37° C [2,9]. A positive fluorescent antibody test can be used as presumptive evidence of Y. pestis infection however it necessitates a specialised instrument along with costly reagents. Samples that have been refrigerated for more than 30 hours or collected from cultures that were incubated at temperatures lower than 35°C (from fleas, for instance) may be negative [2].
Specimens intended for culture should be taken before antibiotic therapy is started [2]. Y. pestis takes two days to form visible, hammered metal-like colonies. If patients have been treated with a bacteriostatic antibiotic for more than four days, bacterial cultures should be incubated for more than five days to allow the remaining organisms to build up a population. A single colony from the culture is then tested for Y. pestis using biochemical tests, inoculation into laboratory animals and use of specific bacteriophage. All automated microbiological test systems are not programmed to identify Y. pestis and its low growth rate restricts the use of biochemical identification [2]. Lysis by specific bacteriophage is used by the CDC to conclusively identify Y. pestis [2], but all these procedures are too complex and time-consuming, and also expensive. Furthermore, incorrect handling while shipping the specimens from the collection centre to the diagnostic centres may lead to desiccation, contamination of the samples and consequent death of the bacteria [6].
Serological analysis
Serological tests are useful especially when cultures yield negative results [9] and/or only serum samples are available as clinical specimens. Such tests are often used retrospectively to confirm the diagnosis of plague; paired serum samples are collected during either the acute and convalescent phases or the convalescent and post-convalescent phases. Serological tests are primarily based on Passive Haemagglutination (PHA) tests and ELISA [10]. PHA has been routinely performed for the last 30 years for the serodiagnosis of plague according to the procedure described by the WHO (1970), which advocates the use of formaldehyde-fixed and F1 sensitised sheep RBC. Being a simple, cheap, rapid and sensitive method, it is regularly practiced at CDC to analyse samples for the presence of anti-F1 antibodies. A four-fold rise in the titre is considered confirmatory for plague. A single serum sample with a titre greater than 1:10 in a person not previously infected or vaccinated against plague is presumptive evidence of recent infection [2]. However, PHA has proved to be an invaluable tool in surveillance programmes for large scale screening [11].
Using monoclonal antibody as a capture antibody and purified rabbit immunoglobulin as an indicator, Williams et al described an ELISA that detects up to 8 ng of F1 antigen per mL serum [12]. ELISA has been used to measure the level of F1 antigen as well as IgG and IgM antibodies to F1 antigen. Detection of IgM antibodies by ELISA in convalescent phase sera is indicative of recent infection. However because of the low concentration of IgM antibody relative to IgG, it is conceivable that some early convalescent phase sera may be IgG positive but IgM negative [12]. Even though it is efficient for serodiagnosis, plague ELISA is not widely accepted because it is less sensitive than FA [12], difficult to perform in the field, and requires specific equipment and expensive reagents.
As well as the two tests described above, tests such as complement fixation and immunodiffusion tests have also been used for plague diagnosis, but have not been widely accepted due to their long turn around time and greater complexity [12]. Furthermore the rarely encountered cases with weak F1 antigen expression also limit the sensitivity of serodiagnostic tests for plague. The latest developments in immunological test design have resulted in availability of rapid diagnostic tests (RDT for plague diagnosis, discussed later in this article.
Nucleic acid tests
When live organisms are not available, e.g., in specimens taken postmortem from lymphoid tissues, lung and bone marrow, DNA of Y. pestis can still be detected [2, 9, 10]. Such methods include PCR and DNA hybridisation techniques. PCR, utilising primers derived from the pla and caf 1 genes that are contained in two different Y. pestis virulence plasmids, can detect levels as low as 10-50 bacteria and thereby help in presumptive diagnosis of plague [10]. However the sensitivity of the method was found to be low when it was used in a field study [13]. This may have been due to suboptimal field conditions and the small volumes of samples used for DNA extraction [13]. Several methods for amplification of Y. pestis DNA have been developed, but none of them has been evaluated with clinical specimens. In spite of its probable usefulness in field studies, DNA hybridisation techniques are of minimal value due to their low limit of detection (minimum of 105 bacteria) and the longer time required to perform the tests [2].
Rapid tests
Even though a number of presumptive and confirmative techniques are available, none are sufficiently simple, economical and non-instrumental to be used routinely by clinical laboratories and in field studies, surveillance or point-of-care testing [2]. The RDT for plague based on F1 antigen has been tested in laboratories and has provided promising results. It is as specific as and at least as sensitive as the available standard methods for plague diagnosis. The excellent specificity of RDT coupled with its lower detection threshold makes it a very useful screening test, in addition to bacteriological tests and ELISA [4].
Span’s Crystal Ypes is a simple and cost-effective RDT based on the principle of immunochromatography. As in the company’s other immunochromatography tests, monoclonal antibodies labelled with a visually detectable marker viz. colloid gold bind to the target antigen. The complex is arrested at the test area (band) coated with another monoclonal antibody and forms a visible band. To the best of our knowledge, it is the only commercially available RDT to diagnose plague at present. The test detects the F1 antigen specific for Y. pestis, which is present in large amount in sputum and bubo samples of infected people. The F1 antigen is stable in tropical climates and can be still be detected in patients after several days of treatment [4]. F1 antigen is detected at a wider range of concentration than other tests, within 10-15 minutes, without the prozone phenomenon, thus avoiding false negative results especially in post mortem specimens or sputum specimens which can contain a very high concentration of F1 antigen [4]. The striking feature of Crystal Ypes is the innovative design of its sample processing device, which minimises the laboratory operator’s contact with highly contagious clinical specimens such as bubo aspirates and tracheal wash without compromising the ease and simplicity of carrying out the test. Because the F1 antigen is highly stable, and there is a reasonably good detection threshold, a short time to result and the test is cost-effective, it is the most suitable test for the immunodetection of plague even in anthropological applications such as burial site studies, especially when archeological and historical data are incomplete or non-existent [14,15].
References
1. Butler T et al. Journal of infectious disease 1977; 136(2): 317-320.
2. Perry RD and. Fetherston JD. Clinical Microbiology reviews 1997; 10(1): 35-66.
3. Thullier P et al. Am J Med Hyg 2003; 69(4): 450-451.
4. Chanteau S et al. The lancet 2003; 361: 211-216.
5. WHO programmes and projects global alert and response, disease covered by EPR, Plague, 2009.
6. Leal NC, de Almedia MP. Rev Med trop S Paulo 1999; 41(6):339-342.
7. Infectious disease epidemiology section office of Public health, Louisiana Dept of Health and hospitals, plague, 2004.
8. CDC report, Division of vector born disease, Plague, Laboratory test criteria for diagnosis of plague, 2005.
9. CDC, Plague diagnosis CDC Division of vector born infectious diseases, 2005.
10. Murry PR et al. Manual of Clinical Microbiology, 8th Ed. ASM press, 2003, 673-683.
11. de Almeida AMP and de Souza FLC. Mem Inst Inst Oswaldo Cru [online]. 1992; 87 n.1 ISSN 0074-0276. [Online]. 1992; 87 no.1 ISSN 0074-0276
12. Shepherd AJ et al. Journal of Clinical Microbiology 1986; 24(6):1075-1078.
13. Rahalison L et al. Institut Pasteur de Madagascar, Antananarivo, Madagascar 1999.
14. Bianucci R et al. American Journal of Physical Anthropology 2008; 136(3):361-7
15. Bianucci R et al. C R biologies 2007; 33: 0747-754.
Span Diagnostics Ltd
Udhna, Surat, India
Diagnosing diabetes mellitus in Asia using HbA1c
, /in Featured Articles /by 3wmediaThe prevalence of diabetes mellitus in Asia is rapidly increasing. Diabetes in Asia develops in a shorter time, at a younger age and in individuals with a lower body mass index than in the West. This review summarises the epidemiology and pathophysiology of diabetes in Asia as well as the difficulties and challenges in using HbA1c as a diagnostic test in the region.
by Dr R. C. Hawkins
The worldwide rates of diabetes mellitus have more than doubled in the last 30 years, driven by diet, obesity and lifestyle factors [1]. The International Diabetes Federation predicts that the number of individuals affected by diabetes will increase from 240 million in 2007 to 380 million by 2025 [2]. Diabetes is an important health priority in Asia involving huge individual, societal and national costs. Agreement as to appropriate criteria for diagnosis is essential for patient management as well as healthcare planning and epidemiological discussion.
Epidemiology of diabetes in Asia
Asia is a heterogeneous region in terms of ethnicity, culture and socioeconomic development and great differences are seen in the prevalence of diabetes both between and within Asian countries. As the world’s most populous region, Asia is projected to comprise more than 60% of the global diabetic population by 2025. The effects of high population growth, ageing and increasing urbanisation suggest that India and China will remain the two countries with the highest numbers of people with diabetes (79 million and 42 million, respectively) by 2030 [3]. Other Asian countries (Indonesia, Pakistan, Bangladesh, and the Philippines) are in the top ten countries for diabetes prevalence. The prevalence of impaired glucose tolerance in Southeast Asia was estimated as 6.0% in 2007, suggesting that there is a substantial population pool at risk of developing overt diabetes. Differences between ethnic groups may be seen in a single country. In Singapore, a nationwide study in 1998 showed the prevalence of diabetes to be highest in the Indian population (12.8%) followed by Malays (11.3%) and Chinese (8.4%). Age-specific prevalence also varies between Asian populations, with a peak in Indians at 60-69 years compared to 70-89 years in Chinese. South Indians have a higher age-specific prevalence and prevalence of impaired glucose tolerance at a younger age than Chinese. A particular characteristic of diabetes in Asia is the high prevalence of young-onset diabetes. The prevalence of diabetes in China in the 35-44 year age group rose by 88% between 1994 and 2000 while the fraction of diabetics under 44 years of age rose from 25% to 35.7% in South India between 2000 and 2006. Rates of diabetes in children across the region also show alarming rises.
Pathophysiology of diabetes in Asia
The prevalence of insulin resistance and metabolic syndrome is high in Asian people. Although Asian populations have lower rates of obesity than Western populations as defined by the conventional body mass index cut-offs, the prevalence of diabetes in Asians often matches or exceeds that in the West.
Compared to Europeans, Asians have lower muscle mass and increased abdominal obesity and visceral fat. Obesity is associated with many of the metabolic mechanisms that worsen insulin tolerance. Excess lipolysis leads to elevation of blood non-esterified fatty acids and triglycerides, suppressing glucose uptake by muscle. Obesity can also diminish insulin action through leptin and adiponectin secretion. This difference in body fat varies between Asian ethnicities and explains in part the differences in diabetes prevalence seen between ethnic groups. For example, for the same age and BMI, Singaporean Indians have the greatest percentage of body fat, followed by Malays and then Chinese; an order reflecting the different prevalence of diabetes in each group. All three ethnicities have higher body fat percentages than Europeans. The World Health Organisation convened an expert consultation to review the BMI cut offs to define risks in Asian populations and recommended that for Asians, BMI of 23 kg/m2 or higher marks a moderate increase in risk while a BMI of 27.5 kg/m2 or more represents high risk. Several Asian countries have subsequently adopted lower BMI cut-offs than those used in the West. India and Japan use BMI cut-offs of 23 and 25 to define overweight and obese categories while Singapore uses 23 and 27.5 kg/m2.
Genetic differences in risk allele frequencies and location for diabetes genes between Asian and European populations may contribute to some of the physiological differences observed. Asians, especially from Southeast Asia, show higher postprandial glucose concentrations and lower insulin sensitivity than Europeans following a glucose challenge despite controlling for age, BMI, waist circumference, birth weight and diet. Frequency differences between Asian and European populations include transcription factor 7-like 2 gene TCF7L2 (rs7901349) with a minor allele frequency of 0.03 in Asians and 0.27 in Europeans and the potassium voltage-gated channel, subfamily Q, member 1 gene KCNQ1 (rs2237892) with allele frequency of 0.28-0.41 in East Asians and 0.05-0.07 in Europeans. The effect of the same genetic variant may also vary between populations. For example, the effect of the FTO variant is linked to changes in fat mass and obesity in Europeans but its link to body size is weaker in Indian populations.
Nutritional factors may also play a role in the increased rates of diabetes seen in Asia. Increasing urbanisation across Asia has seen an increase in consumption of animal products and fat. Some traditional food sources such as ghee (clarified butter), which is high in trans fatty acids, and polished rice and refined wheat (which have high glycaemic indices) may contribute to obesity and glucose intolerance. Such dietary factors, coupled with an increasingly sedentary lifestyle (e.g. replacement of bicycles with automobiles across Asia) and high cigarette smoking rates (which increases insulin resistance), are helping fuel diabetes rates across the region.
Diagnosis of diabetes mellitus in Asia
Diabetes mellitus has traditionally been defined as a state of chronic hyperglycaemia and measurement of blood glucose concentrations has been the gold standard criterion for diagnosis. The International Expert Committee recently recommended that diabetes should be diagnosed when HbA1c is ≥6.5% and this approach has been adopted by the American Diabetes Association [4].
HbA1c results from the reaction of glucose with the N-terminal valine of the β chain of haemoglobin to form the aldimide (Schiff base or labile HbA1c), which then undergoes an Amadori rearrangement to the stable ketoamine (HbA1c) [5]. To compensate for variation in the total haemoglobin concentration, HbA1c is expressed as a ratio (HbA1c/total haemoglobin). There are a variety of analytical methods for HbA1c determination, including those based on charge differences (e.g. ion-exchange chromatography, electrophoresis, capillary electrophoresis and isoelectric focusing) and structural differences (e.g. affinity chromatography, immunochemical and enzymatic assays). Methods based on charge differences face potential interferences from other haemoglobin moieties (e.g., Schiff base, carbamylated haemoglobin, and haemoglobin variants). Affinity chromatography measures all glycohaemoglobin bound to the resin, not just HbA1c, and thus results are not specific for HbA1c. However as the ratio of HbA1c to all glycohaemoglobin is fixed, it is possible to standardise the reporting to HbA1c equivalent units. Immunoassays are generally less affected by the structural changes of haemoglobin variants than other methods.
There are more than 700 known haemoglobin variants and about half of these variants are clinically silent. The prevalence and type of haemoglobinopathy in Asia differs from that seen in Western populations. Both α and β haemoglobin chain variants can interfere with HbA1c measurement [6]. Common haemoglobin variants seen in Asia affecting HbA1c measurement include HbE, HbC and HbS. Thalassaemia is also endemic in the region and may be accompanied by an increase in HbF concentration. High proportions of HbF compared to HbA can cause falsely low values for HbA1c when the ratio of HbA1c to total haemoglobin is calculated. Red cell lifespan can also be reduced in thalassaemia, causing falsely low HbA1c values. Since many commercial HbA1c methods have been optimised for Western settings, ensuring accurate measurement in Asian populations can be an analytical challenge for the laboratory.
The suggestion that diabetes should be diagnosed when HbA1c is ≥6.5% has led to increasing study in differences in HbA1c between ethnic groups. HbA1c has been shown to be higher in non-Caucasian populations, including Hispanics, Asians and Africans. In a study of Caucasian, Chinese, Malay, Eurasian and Indian outpatients in Singapore, we have shown that HbA1c in all Asian groups was higher than the Caucasian group when corrected for age, sex and fasting glycaemic concentration [7]. Compared to the Caucasian group, Malays and Indians had the highest HbA1c (both 0.6 %HbA1c units higher), followed by Eurasians and Chinese (both 0.3%). The reasons for these ethnic differences in HbA1c are unclear, with potential mechanisms including biological (e.g. glycation and erythrocyte survival) and social (cultural/economic) factors.
We recently examined the performance of HbA1c compared to oral glucose tolerance testing (OGTT) for the diagnosis of diabetes in our outpatient population. Details of OGTT with paired HbA1c samples from 2005-11 were extracted from the laboratory database for statistical analysis. OGTT (75 glucose) was performed and interpreted according to WHO recommendations with 0 and 120 min sampling. All HbA1c (turbidometric immunoinhibition method) and glucose measurements were performed on Beckman Coulter LX20 PRO analysers. Diabetes mellitus was diagnosed using three different methods: (1) fasting plasma glucose ≥ 7.0 mmol/L, (2) 120 minute post prandial plasma glucose ≥ 11.1 mmol/L and (3) fasting plasma glucose ≥ 7.0 mmol/L or 120 minute post prandial plasma glucose ≥ 11.1 mmol/L.
There were 212 records available with average age 57y (29-95); 134 men, 168 Chinese, 28 Indian, 16 Malay. The prevalence of diabetes by (1) was 25%, by (2) was 43%, by (3) was 48% and using a HbA1c cut-off of 6.5% was 38%. The AUC for HbA1c to predict diabetes [see Figure 1] by (1) was 0.89 (95% CI: 0.83-0.94), by (2) was 0.74 (0.67-0.81) and by (3) was 0.78 (0.72-0.85). At the suggested cut-off of HbA1c 6.5% [see Table 1], concordance, kappa and phi values between diabetes diagnosis by HbA1c and (1) was 78%, 0.54, 0.64; (2) 72%, 0.43, 0.44; and (3) 74%, 0.48, 0.50. Maximum efficiency for HbA1c in detecting diabetes as defined by (3) was 0.75 at a cut-off of 6.2% (sensitivity 0.804 (0.714-0.876), specificity 0.691 (0.596-0.776)). There was no significant difference in the age, sex or ethnic makeup of the diabetic groups identified by HbA1c testing or by the other three criteria. Thus there was significant discordance of diabetic classification between use of HbA1c and the OGTT results with a 10% absolute reduction in diabetes prevalence with use of a HbA1c cut-off of 6.5% alone. Thirty-seven percent of OGTT-positive individuals would not be identified by a HbA1c cut-off of 6.5% while 15% of OGTT-negative individuals would be identified as diabetic. These results suggest that the two approaches are not interchangeable and appear to identify different patient groups.
This small study supports reports from large epidemiological studies of lack of agreement between HbA1c- and glucose-based diagnosis and lower prevalence rates with the HbA1c-based criterion [8-10]. Moving to HbA1c-based diagnosis of diabetes can be anticipated to have a substantial effect on prevalence rates and will identify different individuals from the traditional glucose-based criteria. Given that the epidemiology and pathophysiology of diabetes in Asia differs from Western populations, it is perhaps not surprising if diagnostic criteria may need to be customised to local conditions. The need or desirability for different ethnic-based HbA1c cut-offs is unclear and further work is required to examine HbA1c in different ethnic groups within Asia. As HbA1c and glucose-based criteria appear to identify different groups, a clear algorithm outlining the order of testing is required to clarify the role of HbA1c and glucose-based criteria. Unstandardised use of HbA1c and glucose diagnostic testing will complicate epidemiological study of diabetes, both within and between countries. Although a routine combined approach using both HbA1c and glucose measurements may allow the greatest detection of diabetics, it may not be practical or economically feasible for many in Asia. These problems illustrate the difficulty in global standardisation of disease definitions using biological markers and the need to validate approaches in local ethnic populations before introduction.
References
1. Danaei G et al. National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2•7 million participants. Lancet 2011;378:40
2. Chan JC et al. Diabetes in Asia: epidemiology, risk factors, and pathophysiology. JAMA 2009;301:2129-40
3. Ramachandran A et al. Diabetes in Asia. Lancet 2010;375:408-18
4. International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 2009;32:1327-34
5. Weykamp C et al. A review of the challenge in measuring hemoglobin A1c. J Diabetes Sci Technol 2009;3:439-45
6. Schnedl WJ et al. Hemoglobin variants and determination of glycated hemoglobin (HbA1c). Diabetes Metab Res Rev 2001;17:94-8
7. Hawkins R. Differences in HbA1c between Caucasians, Chinese, Indians, Malays and Eurasians. Clin Chim Acta 2011;412:1167
8. Malkani S et al. Implications of using hemoglobin A1C for diagnosing diabetes mellitus. Am J Med 2011;124:395-401
9. Kim CH et al. Discordance between fasting glucose-based and hemoglobin A1c-based diagnosis of diabetes mellitus in Koreans. Diabetes Res Clin Pract 2011;91:e8-e10
10. Christensen DL et al. Moving to an A1C-based diagnosis of diabetes has a different impact on prevalence in different ethnic groups. Diabetes Care 2010;33:580-2
The author
Dr Robert C Hawkins
Department of Laboratory Medicine
Tan Tock Seng Hospital
Singapore
e-mail: Robert_Hawkins@ttsh.com.sg
Oxidised low-density lipoprotein and oxLDL auto-antibodies: immunity modulates atherosclerosis
, /in Featured Articles /by 3wmediaOxidised LDL and antibodies to oxLDL are pathogenetically significant contributors in animal models of atherosclerosis, but the pathophysiological role of anti-oxLDL in humans, discussed in this article, remains to be clarified.
by Prof. Dr Thomas Dschietzig
Oxidised LDL
It is currently generally accepted that oxidised low-density lipoprotein (oxLDL) plays a major pathogenetic role in initiating and fueling the process of atherosclerosis [1], [Figure 1]. In the sub-endothelial space, it is taken up via different scavenger receptors (SR-A1, SR-A2, and LOX-1) on the surface of macrophages, which induces foam cell formation and the appearance of fatty streaks, the first histological signs of atherosclerosis. Moreover, oxLDL leads to endothelial dysfunction, chronic vascular inflammation and transformation of vascular smooth muscle cells into the so-called synthetic phenotype typical of vascular remodeling.
OxLDL is measured in plasma using ELISA techniques [2]. As oxidation of lipoproteins is a complex process generating hundreds of unique epitopes, the different antibodies used may vary significantly in their readings. This currently poses a major limitation since these ELISAs are not necessarily comparable, either in terms of absolute values or, more importantly, in terms of pathophysiological meaning [2]. On the other hand, the largest database, which was hitherto collected with the antibody E06 detecting the amount of oxidised phospholipid epitopes on apolipoprotein B-100 (oxPL/apoB), clearly reveals the potential clinical utility of measuring oxLDL: in several studies [2] including the Bruneck [3] and the EPIC-Norfolk study [4], oxPL/apoB was demonstrated to correlate strongly with atherosclerosis and to predict future death, myocardial infarction, stroke and need for revascularisation. In those analyses, the parameter was independent of all traditional and non-traditional risk factors, including inflammatory and thrombotic risk factors, with occasional exceptions for Lp(a). Even more importantly, in the EPIC-Norfolk study, there was evidence of increasing c-statistic values (a measure of added value of new parameters in logistic regression models) when a panel of oxidative biomarkers was added to oxPL/apoB, including Lp(a), CRP, myeloperoxidase, Lp-PLA2 (phospholipase A2) activity and soluble PLA2 mass and activity.
Auto-antibodies against oxLDL
The rate of LDL oxidation is increased when cardiovascular risk factors such as smoking, diabetes mellitus, dyslipidaemia and hypertension induce oxidative stress in the vessel wall [5]. OxLDL, in turn, represents a variety of differently modified lipid and protein components of LDL, the most abundant of which are malonyldialdehyde-LDL (MDA-LDL) and copper-oxidised LDL (Cu-LDL) [5]. This modification renders oxLDL highly immunogenic; correspondingly, auto-antibodies of the IgM and IgG classes are commonly found. Natural IgM auto-antibodies form immune complexes with oxLDL that cannot bind to Fcγ receptors on macrophages and, therefore, do not activate these key players in atherosclerosis. Hence, IgM auto-antibodies may serve to clear oxLDL particles from circulation in a non-inflammatory, protective manner. In contrast, IgG auto-antibodies obviously promote atherosclerosis because they bind and activate macrophages via Fcγ receptors [6] [Figure 2].
In animal studies, the circulating levels of free oxLDL auto-antibodies reflected the general activity of the atherosclerotic process [6]. Natural IgM antibodies – i. e. antibodies pertaining to innate immunity – recognising oxLDL were shown to be protective in different mouse models of atherosclerosis [7,8].
In clinical studies, an inverse relationship between circulating IgM anti-oxLDL and the occurrence of cardiovascular atherosclerosis (carotid artery disease, coronary artery disease) was observed while the opposite, a positive correlation, held true for IgG antibodies [9-11]. Additionally, an unstable phenotype of coronary plaque has been linked to high levels of IgG anti-oxLDL; in contrast, high levels of IgM anti-oxLDL are associated with stable plaques [6]. In these epidemiological studies, however, all described associations were not independent: after correction for other known risk factors in multivariate analyses, anti-oxLDL levels were no longer predictive of atherosclerotic burden. It remains therefore a matter of debate whether oxLDL antibodies in humans represent mere markers of disease or causal players, albeit that the above-mentioned animal studies provided remarkable evidence in favour of the latter hypothesis.
For anti-oxLDL detection by ELISA, oxidation-specific epitopes (‘model oxLDL’), mostly MDA-LDL or Cu-LDL epitopes, are generated in vitro and coupled onto micro-titre plates. Free oxLDL antibodies in diluted plasma samples bind to these epitopes and are then detected with secondary antibodies specific to IgG or IgM [see Figure 1].
Summary
Oxidised LDL and antibodies to oxLDL are pathogenetically significant contributors in animal models of atherosclerosis. As opposed to oxLDL itself, the pathophysiological role of anti-oxLDL in humans (marker or player?) remains to be clarified. Both parameters can be measured using ELISA techniques. For clinical risk assessment in patients with metabolic syndrome and atherosclerosis, circulating oxLDL appears to offer added value to traditional risk factors. It allows significant readjustment of the Framingham Risk Score [3;4] which will help determine how aggressively other risk factors should be treated. Also, combining oxLDL measurement with other parameters of oxidative damage may be useful, with the general caveat that new oxLDL tests be validated thoroughly with regard to their pathophysiological meaning.
References
1. Mitra S, Goyal T, Mehta JL. Oxidized LDL, LOX-1 and Atherosclerosis. Cardiovasc Drugs Ther 2011;25:419-429.
2. Tsimikas S, Miller YI. Oxidative modification of lipoproteins: mechanisms, role in inflammation and potential clinical applications in cardiovascular disease. Curr Pharm Des 2011;17:27-37.
3. Kiechl S, Willeit J, Mayr M, Viehweider B, Oberhollenzer M, Kronenberg F, Wiedermann CJ, Oberthaler S, Xu Q, Witztum JL, Tsimikas S. Oxidized phospholipids, lipoprotein(a), lipoprotein-associated phospholipase A2 activity, and 10-year cardiovascular outcomes: prospective results from the Bruneck study. Arterioscler Thromb Vasc Biol 2007;27:1788-1795.
4. Tsimikas S, Mallat Z, Talmud PJ, Kastelein JJ, Wareham NJ, Sandhu MS, Miller ER, Benessiano J, Tedgui A, Witztum JL, Khaw KT, Boekholdt SM. Oxidation-specific biomarkers, lipoprotein(a), and risk of fatal and nonfatal coronary events. J Am Coll Cardiol 2010;56:946-955.
5. Gounopoulos P, Merki E, Hansen LF, Choi SH, Tsimikas S. Antibodies to oxidized low density lipoprotein: epidemiological studies and potential clinical applications in cardiovascular disease. Minerva Cardioangiol 2007;55:821-837.
6. van Leeuwen M, Damoiseaux J, Duijvestijn A, Tervaert JW. The therapeutic potential of targeting B cells and anti-oxLDL antibodies in atherosclerosis. Autoimmun Rev 2009;9:53-57.
7. Lewis MJ, Malik TH, Ehrenstein MR, Boyle JJ, Botto M, Haskard DO. Immunoglobulin M is required for protection against atherosclerosis in low-density lipoprotein receptor-deficient mice. Circulation 2009;120:417-426.
8. Shaw PX, Horkko S, Chang MK, Curtiss LK, Palinski W, Silverman GJ, Witztum JL. Natural antibodies with the T15 idiotype may act in atherosclerosis, apoptotic clearance, and protective immunity. J Clin Invest 2000;105:1731-1740.
9. Hulthe J, Bokemark L, Fagerberg B. Antibodies to oxidized LDL in relation to intima-media thickness in carotid and femoral arteries in 58-year-old subjectively clinically healthy men. Arterioscler Thromb Vasc Biol 2001;21:101-107.
10. Karvonen J, Paivansalo M, Kesaniemi YA, Horkko S. Immunoglobulin M type of autoantibodies to oxidized low-density lipoprotein has an inverse relation to carotid artery atherosclerosis. Circulation 2003;108:2107-2112.
11. Tsimikas S, Brilakis ES, Lennon RJ, Miller ER, Witztum JL, McConnell JP, Kornman KS, Berger PB. Relationship of IgG and IgM autoantibodies to oxidized low density lipoprotein with coronary artery disease and cardiovascular events. J Lipid Res 2007;48:425-433.
The author
Prof. Dr med. Thomas Dschietzig
Charité Berlin, Germany