Parkinson’s disease (PD) is a chronic neurological disorder affecting one in 100 people over the age of 60, with estimates suggesting that approximately 5 million people are suffering from the condition worldwide. PD develops when the dopamine-producing neurons of the substantia nigra part of the brain are lost over time. Dopamine is needed for the coordination of movement, the loss of which is therefore responsible for the appearance of the main PD symptoms of stiffness, tremor and slowness. There is no cure for PD and treatment is aimed at managing symptoms, with medication being effective only in the short term. Currently there is no clinical test for PD, but diagnosis is based on medical history and assessment of simple physical tasks. Additionally, most instances of PD are idiopathic, with the risks from genetic and/or environmental causes being very low, except in certain rare cases. Hence, diagnosis, particularly in the early stages of symptoms, can be difficult and inconclusive. Additionally, as with many of the neurodegenerative conditions, physical symptoms only become apparent late in the development of the condition – after the loss of 80% of dopamine. However, the help of a woman with a remarkable sense of smell is bringing the creation of a definitive clinical test for PD closer. Joy Milne is a retired nurse from Perth, Scotland, whose husband Les, a consultant anesthetist, was diagnosed with PD at the age of 45 and died at 65. Approximately 10 years before the diagnosis, Joy realized that Les had developed a different, slightly muskier smell. After meeting other people with PD, Joy found that they all had the same unusual aroma. Joy’s ability to detect PD by smell was confirmed in tests conducted by scientists at the University of Edinburgh and she is now working with Dr Perdita Barran at the University of Manchester to isolate the specific compounds that create the distinctive PD aroma. So far, a handful of compounds have been identified. Currently, a definitive clinical test would allow a conclusive diagnosis for patients suffering from the varied and vague early symptoms of PD. In the future, however, given the lack of identifiable risk factors and the fact that the changes responsible for PD as well as the development of the unusual PD aroma happen up to a decade before external physical symptoms appear, for any medication that will cure or at least prevent disease progression to have any real chance of success, screening of the apparently healthy, asymptomatic population will have to be carried out.

Monoclonal gammopathy (MG) refers to the presence of monoclonal immunoglobulin produced by clonally expanded plasma cells or immunoglobulin-expressing lymphocytes. MG is a key feature of a wide spectrum of diseases ranging from the indolent MG of undetermined significance to the overt multiple myeloma. In this article, we discuss the utility and pitfalls of common biochemical techniques used to detect MG.

by Dr Michelle L. Parker and Dr Pak Cheung Chan

Introduction
The monoclonal immunoglobulins or ‘M-proteins’ detected in monoclonal gammopathy (MG) are produced by clonally expanded plasma cells, or less frequently by immunoglobulin-expressing lymphocytes at different stages of maturation. The prevalence of MG in the general population over 50 years of age is approximately 3 % and increases with age. M-proteins secreted by plasma cells (Fig. 1a) can be partial or intact immunoglobulins, with the latter consisting of two heavy chains and two light chains that together form a Y-shaped structure with constant and highly variable antigen-binding domains (Fig. 1b). M-proteins that are immunologically functional may cause disease by directly binding to self-antigens, e.g. in some peripheral neuropathy. Other unique chemical properties may cause the M-protein to transform into insoluble amyloids, to increase plasma viscosity, or even to block capillary blood flow by precipitating out at the low temperatures in the extremities. As the production of M-protein increases, the mass effect can be exerted through the expanded clonal plasma cells compressing neighbouring cell lineages in the bone marrow, resulting in reduced red blood cell production (anemia), pan-leukopenia (recurrent infections), thrombocytopenia (bleeding diathesis), suppressed non-involved plasma cells (immune paresis) and bone resorption (hypercalcemia and bone lesions). Large amounts of circulating M-protein could promote plasma hyperviscosity, thrombosis, and tissue and organ damage. For example, excess filtered free light chains in multiple myeloma can directly damage the kidney proximal tubules, form amyloids rupturing glomeruli and form obstructive casts in the distal tubules leading to cell death and nephritis. In general, measured M-protein concentration is taken to reflect the tumour burden and is prognostic for disease progression or survival, e.g. in monoclonal gammopathy of undetermined significance (MGUS), smouldering myeloma and multiple myeloma.

Conditions associated with MG cover a wide range of clinical presentations and severity, including MGUS, multiple myeloma, P.O.E.M.S., light chain deposition disease, plasmacytoma, Waldenstrom’s macroglobulinemia, non-Hodgkin’s lymphoma and chronic lymphocytic leukemia. In some of these diseases, the severity of tissue or organ damage may not be related to the M-protein concentration. For example, in some amyloid light chain (AL)-amyloidosis, extensive kidney damage is reflected by massive proteinuria, yet the circulating monoclonal free light chain can be barely, or not at all, demonstrable by serum and/or urine testing [1]. Nevertheless, the presence of an M-protein can be a defining hallmark of many of these conditions and its detection provides a critical link to their final diagnosis.

Biochemical detection of monoclonal immunoglobulins
Five common biochemistry tests form the core of first-line MG investigations and will be discussed below: serum protein electrophoresis (SPE), serum immunofixation electrophoresis (IFE), urine protein electrophoresis (UPE), urine immunofixation electrophoresis (uIFE), and serum free light chain (sFLC) assays. Other techniques such as mass spectrometry-based assays and HevyliteTM analysis are increasingly available for specific circumstances but will not be discussed here.

SPE and UPE
SPE and UPE resolve serum and urine proteins respectively into five or six major fractions, viz. albumin, alpha-1, alpha-2, beta (total beta, or beta-1 and beta-2 depending on resolution), and gamma (Fig. 2). If a monoclonal antibody is present, an additional peak may be observed, most frequently in the gamma (hence the term gammopathy) (Fig. 2) but other regions such as beta and alpha-2 are also possible. Estimating the size of this extra peak gives the amount of M-protein present and is one of the recommended methods for monitoring disease activity. However, the detection of M-protein this way requires that it is readily distinguished from background polyclonal immunoglobulins or other co-migrating proteins, which not only limits the analytical sensitivity to around 0.5–2.0 g/L [2] and prevents its use to rule-out low abundance M-proteins [3, 11], but also limits the accuracy of quantification especially at low M-protein concentrations and/or high background in any electrophoretic regions.

Importantly, an ‘abnormal’ peak identified by SPE does not prove that it is an endogenous monoclonal immunoglobulin, as the peak may be due to a haptoglobin variant, iodinated contrast material, aminoglycoside, administered biologics, or increases in other proteins such as tumour markers, transferrin in severe iron deficiency, C-reactive protein in acute inflammation, and fibrinogen in plasma or incompletely clotted serum [4]. Similarly, a positive finding in UPE can only be regarded as presumptive and should be confirmed by techniques such as IFE.

Historically, qualitative deviations from the expected SPE pattern have been taken to imply clinical conditions such as bisalbuminemia, acute-phase inflammatory response, alpha-1-antitrypsin deficiency, nephrotic syndrome, cirrhosis, hypogammaglobulinemia, etc. However, not all of these conditions as predicted by SPE patterns have been validated, nor have their clinical utility in terms of MG investigation been established [5].

IFE and uIFE
For IFE, a combination of antisera against the heavy chains (IgG, IgA, IgM, IgD, IgE), the two light chains (total kappa and total lambda) and/or the free light chains (free kappa and free lambda) is selected and separately overlaid on the electrophoresed sample. Immuno-precipitation results in a blush of staining in the presence of polyclonal immunoglobulins, while a discrete band indicates the presence of an M-protein and its isotype is determined when discrete bands in the heavy and light chain lanes are aligned (Fig. 2 inset). This immunological detection not only characterizes the M-protein whose isotype provides prognostic information, but also improves the analytical sensitivity (typically 0.2 to 0.5 g/L) enabling detection of M-proteins even when the SPE pattern is visibly normal [2]. However, a notable short fall is that the interpretation is unavoidably subjective especially when bands are faint or not well defined.

In uIFE, the focus is to detect monoclonal free light chains or Bence Jones proteins that passed through the kidneys unabsorbed. In normal individuals, immunoglobulin light chains are produced in slight excess of the heavy chains and are secreted into the circulation. Because of their small sizes, free light chains are readily filtered through the glomeruli but are efficiently absorbed in the proximal tubules. Thus, in patients with MG, the detection of monoclonal free light chains in urine usually indicates an increased production exceeding renal reabsorbing capacity, compromised reabsorption, or both. Since the secretion of free light chains into the circulation is sporadic throughout the day, a ‘pooled’ sample such as a 24-h urine collection usually improves the sensitivity as well as the reliability of urine testing, although a first-morning urine has also been accepted for initial investigations.

sFLC assays
The fully automated sFLC measures polyclonal immunoglobulin free light chains individually with high analytical sensitivity (down to mg/L) and targets the light chain epitopes that are otherwise hidden when bound to heavy chains (Fig. 3)[2]. Patients with MG often have increased concentrations of the involved free light chains, resulting in a skewed free kappa/lambda ratio as the uninvolved free light chains remains normal or suppressed. A skewed ratio not only supports the diagnosis of MG but also provides prognostication information on malignant progression for MGUS, smouldering myeloma and multiple myeloma. A free kappa/lambda ratio >100 has even been taken as a defining feature for multiple myeloma [6].

Similar to many other immunoassays, the sFLC assay is subject to antigen excess and displays dilutional non-linearity, raising concern over the accuracy of results at both high concentrations (variation due to different dilution response) and low concentrations (high dose hook effect). Additionally, falsely abnormal free kappa/lambda ratios have been reported in individuals with polyclonal gammopathy, hospitalized patients and patients with renal dysfunction. In one study, the reported positive predictive value of an abnormal ratio amongst primary care patients was only 39 % [7], underscoring the high false-positive rate in unselected patients. Although there are sFLC assays reportedly less susceptible to these limitations [8], a general lack of standardization renders the results non-commutable and values cannot be interchanged between methods.

Diagnostic testing algorithms
Although the biochemical tests discussed above play an important role in the detection of M-proteins, the information that each test provides does overlap substantially, and different test combinations may be required for different monoclonal gammopathies. Moreover, these tests tend to be costly, labour intensive, and/or require expertise for result interpretation. There is ongoing debate on the optimal testing algorithm due to competing priorities such as maximizing clinical sensitivity or diagnostic efficiency, streamlining workflows, improving economic feasibility, and reducing unnecessary or redundant testing.

With a primary goal of maximizing clinical sensitivity, the International Myeloma Working Group (IMWG) recommends SPE, IFE and sFLC as first-line tests for confirming multiple myeloma and other plasma cell disorders, with the addition of 24-hour urine studies only if AL-amyloidosis is suspected [2, 8]. Although the recommendation falls short of indicating that these tests may be performed in tandem depending on findings, it does represent a welcomed change to previous versions as 24-h urine samples are inconvenient to collect and UPE and uIFE are expensive to perform. Although sFLC testing has largely obviated the need for first-line urine studies, no single serum test has adequate clinical sensitivity for screening all plasma cell disorders [8, 9]; in one large study, SPE, IFE and sFLC had clinical sensitivities of just 79, 87 and 74 % respectively [3].

The optimal combination of first-line and reflexed tests remains difficult to determine owing to the wide spectrum of MG diseases. There is substantial redundancy if SPE and IFE are performed simultaneously. IFE contains a protein lane that provides the same qualitative detection of M-proteins as SPE. A separate SPE only provides additional information regarding quantity of the M-protein, as there are no true positives that would be missed by IFE but identified by SPE. For economic and other reasons, SPE is often performed initially and is reflexed to IFE for confirmation if SPE presents with features suggestive of an M-protein, including the observation of restricted staining or a clearly discrete band, increased beta fraction [10], or decreased gamma fraction [11]. However, this approach has been shown to miss up to 20 % of cases [3, 10–12] as some M-proteins, especially free light chains and those existing in small concentrations, may not present with any abnormal features in SPE. Recently, it was argued that the increased sensitivity of IFE over SPE warrants its use as the first-line screening test, despite being more expensive and labour intensive. The use of modified IFE protocols such as combined light chain immunofixation (a mixture of anti kappa and anti-lambda antisera), or the penta-IFE using a mixture of five antisera (anti IgG,  IgA,  IgM,  kappa, and  lambda) seems to make this approach more feasible. The counterpoint to this approach, though, is that the detection of very low concentration M proteins by IFE may lead to unnecessary investigation of transient or low risk conditions [13]. On the other hand, without full characterization of the M-protein (both isotype and concentration), it may be premature to judge the significance of an M-protein based only on its low concentration.

Concluding Remarks
Clearly, further studies are needed to balance the competing priorities of various testing algorithms and provide evidence-based approaches to MG investigations suited to the diverse clinical environments, ranging from family practice to speciality hematology clinics. Irrespective of the algorithm used, it is good practice to interpret laboratory findings within the specific clinical context to mitigate the risk of false-positive or false-negative test results.

References
1. Truong D, Blasutig IM, Kulasingam V, Chan PC. A patient with monoclonal gammopathy-related nephrotic syndrome revealed no electrophoretic “nephrotic pattern” or skewed free light chain ratio. Clin Biochem 2018; 51: 110–111.
2. Dispenzieri A, Kyle R, Merlini G, Miguel JS, Ludwig H, Hajek R, et al. International Myeloma Working Group guidelines for serum-free light chain analysis in multiple myeloma and related disorders. Leukemia 2009; 23(2): 215–224.
3. Katzmann JA, Kyle RA, Benson J, Larson DR, Snyder MR, Lust JA, et al. Screening panels for detection of monoclonal gammopathies. Clin Chem 2009; 55(8): 1517–1522.
4. McCudden CR, Jacobs JFM, Keren D, Caillon H, Dejoie T, Andersen K. Recognition and management of common, rare, and novel serum protein electrophoresis and immunofixation interferences. Clin Biochem 2018; 51: 72–79.
5. Chan PC, Chen Y, Randell EW. On the path to evidence-based reporting of serum protein electrophoresis patterns in the absence of a discernible monoclonal protein – A critical review of literature and practice suggestions. Clin Biochem 2018; 51: 29–37.
6. Rajkumar SV, Dimopoulos MA, Palumbo A, Blade J, Merlini G, Mateos MV, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol 2014; 15(12): e538–548.
7. Hill PG, Forsyth JM, Rai B, Mayne S. Serum free light chains: An alternative to the urine Bence Jones proteins screening test for monoclonal gammopathies. Clin Chem 2006; 52(9): 1743–1748.
8. Tate JR, Graziani MS, Mollee P, Merlini G. Protein electrophoresis and serum free light chains in the diagnosis and monitoring of plasma cell disorders: laboratory testing and current controversies. Clin Chem Lab Med 2016; 54(6): 899–905.
9. Willrich MAV, Murray DL, Kyle RA. Laboratory testing for monoclonal gammopathies: focus on monoclonal gammopathy of undetermined significance and smoldering multiple myeloma. Clin Biochem 2018; 51: 38–47.
10. Chan PC, Lem-Ragosnig B, Chen J. Diagnostic implications of enumerating and reporting beta fraction(s) for the detection of beta-migrating monoclonal immunoglobulins in serum protein electrophoresis. Clin Biochem 2018; 53: 77–80.
11. Chan PC, Chen J. Value of reflex testing based on hypogammaglobulinemia as demonstrated in serum protein electrophoresis. Clin Biochem 2015; 48: 674–678.
12. Pretorius CJ. Screening immunofixation should replace protein electrophoresis as the initial investigation of monoclonal gammopathy: Point. Clin Chem Lab Med 2016; 54(6): 963–966.
13. Smith JD, Raines G, Schneider HG. Should routine laboratories stop doing screening serum protein electrophoresis and replace it with screening immune-fixation electrophoresis? No quick fixes: Counterpoint. Clin Chem Lab Med 2016; 54(6): 967–971.

The authors
Michelle L. Parker¹ PhD, Pak Cheung Chan*^1,2 PhD, DABCC, FCACB
¹Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
²Department of Laboratory Medicine & Molecular Diagnostics, Sunnybrook Health Sciences Centre, Toronto, ON, Canada

*Corresponding author
E-mail: pc.chan@sunnybrook.ca

Age-related macular degeneration is a late-onset disease of the eye macula that can result in blindness and in a significant deterioration of quality of life. Genetics and oxidative stress from light exposure and smoking are major risk factors. In this brief report, we discuss genetic and plasma epigenetic biomarkers that are examined for their association with the disease.

by Prof. Christos Kroupis, Prof. George Kitsos, Prof. Marilita M. Moschos and Prof. Michael B. Petersen

Introduction
Age-related macular degeneration (AMD) is a slow and progressive disease of the macula, i.e. the central part of the retina, and the leading cause of irreversible visual loss in the Western world. Globally, AMD accounts for 8.7% of all blindness and is predicted to affect 196 million people by 2020; it is more prevalent in populations of European descent than those of Asian and African descent [1]. With the loss of central vision frequently involving both eyes, AMD is a debilitating condition affecting daily tasks such as reading and driving, and ultimately having severe consequences on independence and quality of life. AMD is a late-onset disease with a complex etiology. Major risk factors contributing to susceptibility include age, family history (genetics), light exposure and smoking [2–4].

AMD can be considered a multifactorial dysfunction of the retinal photoreceptor cells and their support system, which includes the retinal pigment epithelium (RPE), Bruch’s membrane (BrM), and the choroidal vasculature. The fundamental cause of vision loss in AMD is the progressive damage to photoreceptors, which can be triggered by RPE dysfunction and atrophy, impaired transport of oxygen, nutrients and metabolites between vessels and outer retinal cells and leakage from choroidal capillaries that invade the retina through the RPE [5].

Light entering the eye is focused on the retina, where delicately specialized rod and cone photoreceptors allow its transduction into chemical signals to visual centers in the brain. Photoreceptors are metabolically active neurons with oxygen requirements that are among the highest in the human body. In humans, rods and cones exhibit a distinct topography; the macula (6-mm diameter) contains a cone-dominated fovea (0.8-mm diameter) that is associated with high-acuity vision [5] (Fig. 1a). Just posterior to the photoreceptors, the RPE consists of polarized epithelial cells located at the base of the retina as a single layer of hexagonal cells that are densely packed with pigment granules (melanosomes). The RPE is firmly attached to the underlying basement membrane (BrM). The RPE provides the nutrients needed to maintain visual function by light-sensitive outer segments of the photoreceptors. RPE melanosomes absorb excess incoming light, which protects the retina from light damage. Other critical roles for the RPE involve phagocytosing shed outer retinal segments and scavenging photoreceptor debris, thus, serving as part of the waste-disposal system for the retina. The RPE is known to produce and to secrete a variety of growth factors to help build and sustain the choroid and photoreceptors [6]. The choroid is an extensive vascular meshwork of capillaries lining the posterior part of the eye that supplies nutrients utilized by the retina and acts as a conduit for the by-products of photoreceptor and RPE metabolism [5]. The inner aspect of the choroid, next to the RPE, is the BrM, a laminar extracellular matrix composed mainly of collagen and elastin. Accumulating evidence suggests that the molecular, structural and functional properties of the BrM are dependent on age, genetics, environmental factors, retinal location and disease state. As a result, some properties of the BrM are unique to each human individual at a given age and, therefore, affect uniquely the progression of AMD [6].

AMD pathology
There are two AMD forms: dry (in 90% of patients) and wet (in 10%). In the dry form of AMD, apoptosis of the RPE, neuroretina and choriocapillaris progresses slowly and causes permanent central vision loss. Initially, the BrM exhibits increased deposition of cholesterol and calcium with age. Drusen genesis is a sign of AMD progression (Fig. 1b). Drusen are amorphic extracellular deposits of lipids, proteins, inflammatory molecules in the space between RPE and BrM. The alternative complement path is activated by lipofuscin constituents (which are mostly by-products of the retinal vision cycle) as a response to the inflammatory process connected with drusen genesis. Unfortunately, as we age, mitochondrial function decreases (and mtDNA mutations accumulate) and, therefore, oxidative damage increases. In parallel, antioxidant capacity decreases and the efficiency of repair systems and cytoprotective ubiquitin proteolytic system become impaired [4]. Environmental factors associated with increased production of reactive oxygen species (ROS), such as increased light exposure and cigarette smoking, are additive and have been linked with AMD risk. Collectively, these factors create an environment in which proteins, DNA and lipids become oxidatively damaged. The combination of inadequately neutralized oxidized proteins in the drusen and inflammation associated with OSEs (oxidative specific epitopes) induce focal loss of RPE cells, degeneration of the overlying photoreceptors and vision loss as described in Figure 2 [4].

In the advanced dry form of AMD, geographic atrophy (GA) develops from large, confluent drusen proceeds to hyperpigmentation and then, to cell apoptosis. At present, there is no effective treatment of the dry form. In the wet form, the cause of potential central vision loss is choroidal neovascularization (CNV). An inflammatory reaction initiates pathological angiogenesis that penetrates through defects in the BrM and the RPE layers to the subretinal space, where exudation and bleeding destroy photoreceptors. Commonly used anti-VEGF factors given in repeated intravitreal injections inhibit neovascularization and can stabilize vision acuity in most wet AMD patients.

Genetic biomarkers in AMD
Identification of associated genetic variants can help uncover disease mechanisms and provide entry points for therapy. Linkage of AMD families to 1q32 and the complement factor H (CFH) gene by many groups in 2005, led to the identification of the first common genome-wide significant risk variant, Y402H (rs1061170, g.43097C>T) with variable frequencies across various populations. This SNP (single nucleotide polymorphism) results in an impaired alternative complement pathway inactivation. This discovery propagated numerous genetic and genomic studies that have contributed to our understanding of the pathological mechanisms contributing to AMD. Notably, the subsequent association of common and rare alleles at or near several additional complement genes (CFH, C2/CFB, C3, CFI and C9) has led to the ‘inflammation hypotheses’, with cumulative evidence from genetics and histopathological studies [3]. Another major non-complement pathway AMD-associated locus lies on chromosome 10q26 (LOC387715) and many studies have demonstrated a strong association between AMD and the ARMS2 gene that encodes for a small 107-amino acid protein. ARMS2 A69S SNP (rs10490924, g.5270G>T) is a mutation associated with subsequent mitochondrial dysfunction, ROS generation and accumulation of somatic mitochondrial DNA mutations. These initial promising findings prompted world-wide efforts and culminated in the AMD Gene consortium 2013 study where 19 common variants were associated with the disease in a large number of patients with the use of SNP microarrays; still the two aforementioned SNPs possessed the highest odds ratios (OR) for AMD development (between 2.4 and 2.7) with some differences in their effect according to their different allele frequencies in various populations. It was estimated that these 19 variants can explain ~45% of the genetic heterogeneity in AMD patients above 85 years old; the two main AMD associations with CFH and ARMS2 genes account for a significant 25% of the total cases [5]. Therefore, we and other groups have developed fast, high-throughput robust and accurate genotyping assays for their accurate detection (Fig. 3) [7–9]. Early identification of individuals at risk provides an opportunity to prevent or attenuate the AMD disease. Homozygosity for both CFH and ARMS2 risk alleles increases the progression to advanced AMD stages (GA or CNV) to 48% compared to 5% for those carrying wild-type alleles in both genes [10]. Models incorporating these alleles and/or an expanded variant panel along with smoking and body mass index have been the basis for various commercial tests estimating AMD risk, such as RetnaGene (Nicox), Macula/Vita Risk (ArcticDx), Asper Ophthalmics, etc. Potential nutrigenetic antioxidant interventions have been proposed based on CFH and ARMS2 genotypes [11, 12]. In dry AMD where no therapy exists, anti-complement antibodies are in clinical trials right now (eculizumab, lampalizumab) and genetic tests providing information for complement polymorphisms could select appropriate patients that could benefit from such therapy.

The largest and latest 2016 AMD Gene Consortium study identified additional loci by using an Illumina human core exome array for >12 million variants in 16,144 advanced AMD patients versus 17,832 controls; 52 independently associated common and rare variants were distributed across 34 loci [13]. Now that technological advances permit – with the advent of next-generation sequencing platforms – it would be extremely useful to validate AMD-specific gene-panels for these patients.
Plasma epigenetic biomarkers in AMD
A small, non-coding micro(mi)RNA (18–24 nt) binds to specific mRNAs – depending on its sequence – and results in their degradation by cleavage, translational repression and/or polyA-deadenylation. One miRNA can target many mRNAs but also one mRNA can be targeted by many miRNAs. Emerging evidence arising from tissue studies suggest that beside environmental and genetic factors, epigenetic mechanisms (such as miRNA regulation of gene expression) are relevant to AMD and are providing an exciting new avenue for research and therapy. Sera and plasma (which are easily collected non-invasively) contain cell free DNA, RNA and circulating nucleic acids that can serve as potential biomarkers. The miRNAs identified in human plasma are known to be relatively stable, as they have been found to be resistant to RNase degradation. A recent study has identified a plasma miRNA expression profile specific for AMD patients [14]. Plasma miRNA expression was first screened for multiple miRNAs and then, those showing differences between patients and healthy controls were further explored with individual, specific RT-qPCR assays in a larger number of samples. In another study exploring wet and dry AMD differences in plasma, the miRNA expression analysis revealed increased expression of miR661 and miR3121 in dry AMD patients and miR4258, miR889 and let7 in wet AMD patients compared to controls [15].

References
1. Wong WL, Su X, Li X, Cheung CM, Klein R, Cheng CY, Wong TY. Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis. Lancet Glob Health 2014; 2: e106–e116.
2. Kokotas H, Grigoriadou M, Petersen MB. Age-related macular degeneration: genetic and clinical findings. Clin Chem Lab Med 2011; 49: 601–616.
3. Tan PL, Bowes RC, Katsanis N. AMD and the alternative complement pathway: genetics and functional implications. Hum Genomics 2016; 10: 23.
4. Chiras D, Kitsos G, Petersen MB, Skalidakis I, Kroupis C. Oxidative stress in dry age-related macular degeneration and exfoliation syndrome. Crit Rev Clin Lab Sci 2015; 52: 12–27.
5. Fritsche LG, Fariss RN, Stambolian D, Abecasis GR, Curcio CA, Swaroop A. Age-related macular degeneration: genetics and biology coming together. Annu Rev Genomics Hum Genet 2014; 15: 151–171.
6. Bhutto I, Lutty G. Understanding age-related macular degeneration (AMD): relationships between the photoreceptor/retinal pigment epithelium/Bruch’s membrane/choriocapillaris complex. Mol Aspects Med 2012; 33: 295–317.
7. Velissari A, Skalidakis I, Oliveira SC, Koutsandrea C, Kitsos G, Petersen MB, Kroupis C. Novel association of FCGR2A polymorphism with age-related macular degeneration (AMD) and development of a novel CFH real-time genotyping method. Clin Chem Lab Med 2015; 53: 1521–15219.
8. Sarli A, Skalidakis I, Velissari A, Koutsandrea C, Stefaniotou M, Petersen MB, Kroupis C, Kitsos G, Moschos MM. Investigation of associations of ARMS2, CD14, and TLR4 gene polymorphisms with wet age-related macular degeneration in a Greek population. Clin Ophthalmol 2017; 11: 1347–1358.
9. Xu Y, Guan N, Xu J, Yang X, Ma K, Zhou H, Zhang F, Snellingen T, Jiao Y, et al. Association of CFH, LOC387715, and HTRA1 polymorphisms with exudative age-related macular degeneration in a northern Chinese population. Mol Vis 2008; 14: 1373–1381.
10. Seddon JM, Francis PJ, George S, Schultz DW, Rosner B, Klein ML. Association of CFH Y402H and LOC387715 A69S with progression of age-related macular degeneration. JAMA 2007; 297: 1793–1800.
11. Awh CC, Hawken S, Zanke BW. Treatment response to antioxidants and zinc based on CFH and ARMS2 genetic risk allele number in the Age-Related Eye Disease Study. Ophthalmology 2015; 122: 162–169.
12. Vavvas DG, Small KW, Awh CC, Zanke BW, Tibshirani RJ, Kustra R. CFH and ARMS2 genetic risk determines progression to neovascular age-related macular degeneration after antioxidant and zinc supplementation. Proc Natl Acad Sci U S A 2018; 115: E696–E704.
13. Fritsche LG, Igl W, Bailey JN, Grassmann F, Sengupta S, Bragg-Gresham JL, Burdon KP, Hebbring SJ, Wen C, et al. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants. Nat Genet 2016; 48: 134–143.
14. Ertekin S, Yıldırım O, Dinç E, Ayaz L, Fidancı SB, Tamer L. Evaluation of circulating miRNAs in wet age-related macular degeneration. Mol Vis 2014; 20: 1057–1066.
15. Szemraj M, Bielecka-Kowalska A, Oszajca K, Krajewska M, Goś R, Jurowski P, Kowalski M, Szemraj J. Serum microRNAs as potential biomarkers of AMD. Med Sci Monit 2015; 21: 2734–2742.

The authors
Christos Kroupis*¹ MSc, PhD; George Kitsos² MD, PhD; Marilita M. Moschos³ MD, PhD; Michael B. Petersen⁴ MD, PhD

*Corresponding author
E-mail: ckroupis@med.uoa.gr

Flow cytometry has traditionally been used to identify hemato-lymphoid neoplasms. However, the flow cytometry laboratories that deal with tissues would often receive samples that have an epithelial neoplasm. In our laboratory, we use flow cytometry to identify cells with epithelial differentiation using Ber-EP4 antibody that targets CD326 (EpCAM). We have formulated an algorithm-based approach for the application of this marker. This approach has been elaborated in this article.

by Dr Pranav Dorwal and Dr Helen Moore

Introduction
The use of flow cytometry in the laboratory has traditionally been applied for diagnosing lymphomas and leukemias. The biggest advantage that flow cytometry has over histopathology is a much quicker turn-around-time, as most of the samples are fresh and can be processed right away, unlike a histopathology sample which needs to undergo fixation and processing before it is ready to be examined. Any additional testing on flow cytometry samples can be performed instantly, whereas the same usually requires another day in the histopathology lab. Many of the lymph node malignancies (primary lymphomas versus metastatic involvement) can appear undifferentiated. In these cases, the histopathologist needs the help of a plethora of immunohistochemical markers to reach a diagnosis. The ability to identify samples where non-hematological malignancies are present can be helpful for the treating physician as well as the reporting histopathologist, who can then test with a more dedicated panel. The ultimate aim of this testing is to get an early diagnosis so that patient’s treatment is not delayed.

A large number of markers have been used to identify epithelial differentiation in tumours by immunohistochemistry (IHC), including cytokeratin (CK), carcinoembryonic antigen (CEA), cancer antigen 125 (CA-125) as well as epitopes recognized by the antibodies LeuM1 (anti-CD15 antibody), and MOC-31 and Ber-EP4 antibodies, both of which recognize epitopes on EpCAM (the epithelial cell adhesion molecule). However, most of these are not available for use by flow cytometry. EpCAM (also known as CD326) was first discovered in 1979 and at that time thought to be specific for colonic carcinoma [1]. Ber-EP4 is, therefore, an anti-CD326 antibody which binds to a cell membrane glycoprotein on human epithelia. There is a comprehensive list of tumours that are Ber-EP4 positive, as described by Went et al. and Spizzo et al. [2, 3]. The traditional use of Ber-EP4 in histopathology has been limited essentially for differentiation between adenocarcinoma and malignant mesothelioma [4]. This could be due to the fact that other epithelial markers (such as CK) are expressed more often than the CD326 (EpCAM) in epithelial malignancies and thus are more helpful in lineage determination.

We use an algorithmic approach to decide the flow cytometry panel to be applied (Fig. 1). When the clinical details or radiological findings are indicative of a non-hematopoietic malignancy, we apply the CD326 panel. This panel is composed of CD326, CD56 and CD45. CD56 was included in the panel to identify myeloma cells (which may be present in the CD45-negative region) and cells with neuroendocrine differentiation. If, on analysis, there is no CD45-negative population and the sample is composed of predominantly lymphoid cells, a lymphoid screening panel is then used. Samples that are received with diagnosis of suspected lymphoma are initially processed with a routine lymphoid screening panel. In these cases, Ber-EP4 antibody is tested only if large numbers of CD45-negative events are identified.

Method for Ber-EP4 testing
The tissue and fine-needle aspirate (FNA) samples are received fresh in RPMI medium. The tissues are placed on the metal sieve and ground using a glass pestle to form a cell suspension using 2 % PBS-FCS. This suspension is subsequently filtered, which is then washed and lysed. The cell count is ascertained by the cell counter only in cases of larger tissues, where we may have to dilute the sample to adjust the cell count to approximately 10×10⁹/L. FNA and core biopsies are usually paucicellular and do not need a cell count.

The sample is stained with 5 µl of CD45-PC5 [Immunotech SAS (Beckman Coulter)], 20 µl of CD56-PE (Immunotech SAS) and 10 µl of monoclonal mouse anti-human epithelial antigen-FITC conjugated antibody (Clone: Ber-EP4) (Dako Denmark A/S). The sample is then incubated at 4 °C for 30 minutes, followed by a washing step and is ready to be run on the flow cytometer (Beckman Coulter Life Sciences). A total of 10 000 events are acquired with the time threshold set at 300 seconds for the acquisition.

Flow cytometric analysis
The flow cytometric analysis is performed using Navios and Kaluza softwares (Beckman Coulter Life Sciences). The various populations of interest are gated with the focus on identifying the expression of CD326 (with or without CD56) in the CD45-negative population.

Discussion
In our experience of testing for CD326 by flow cytometry, we have been able to comment on the presence or absence of CD326 expression in CD45-negative populations (Figs 2(a, b) and 3). The various carcinomas where we have identified CD326 positivity are: adenocarcinoma, small cell carcinoma, Merkel cell carcinoma, renal cell carcinoma, squamous cell carcinoma, prostate carcinoma, germ cell tumour of testis, and myxoma. We have observed that the expression of CD326 in melanomas can be variable, but they more frequently express CD56. The co-expression of CD326 and CD56 usually indicates a neuroendocrine tumour. Our concordance rate with histopathology using CD326 testing was found to be 97.6 %, which we have published previously [5].

CD326 expression has also been reported to be a prognostic marker with poor outcomes in epithelial ovarian and gall bladder carcinomas [6, 7]. Another important role of this testing could be application in decision making for use of monoclonal antibodies for targeted therapy. The first EpCAM targeting antibody, Catumaxomab (trade name Removab, Fresenius Biotech GmbH) received European market approval in EpCAM-positive carcinomas for the treatment of malignant ascites. Another modification that could be useful in diagnosing epithelial malignancies is to apply Ki67 testing using flow cytometry. This could be done in the same tube as CD326, and thus more information could be obtained with the same amount of sample [8].

There has been considerable data describing the use of the Ber-EP4 antibody in malignant effusions [9–11]. The literature mentions that the presence of epithelial cells in the body fluid should raise the suspicion of metastatic epithelial malignancy, as the reactive body fluids may be composed of lymphocytes and reactive mesothelial cells in varying proportions. There have been multiple studies in the past where flow cytometric CD326 testing has been applied for identifying epithelial cells in body fluid effusions. We have found that our results have a very good concordance with histopathology results. This is in keeping with the findings of Davidson et al., although their study looked at the detection of malignant cells in effusions [12].

The disadvantage of using Ber-EP4 for identifying epithelial differentiation is that there are many epithelial malignancies that do not express CD326 (EpCAM). As mentioned earlier, the use of a broader antibody like cytokeratin (pan-CK) may solve this problem. But unfortunately, such an antibody is not currently available for clinical use by flow cytometry, to the best of our knowledge. Meanwhile, Ber-EP4 should give us the answer in most of the cases. Another disadvantage is that CD326 will be negative in cases of neoplasms of mesenchymal origin, such as sarcomas.
Most flow cytometry laboratories across the world will liaise with histopathology departments for the diagnosis of non-Hodgkin lymphomas. The use of Ber-EP4-testing flow cytometry may play an important role even in epithelial malignancies. The antibody used by us is a CE-marked antibody for in vitro diagnostics and, thus, requires a limited verification process. We followed the method recommended by the manufacturer. The rapid turn-around-time of flow cytometry results makes it a useful screening tool. Our experience shows that flow cytometric testing for CD326 (EpCAM) can be a useful method for diagnosing non-lymphoid malignancies that are poorly differentiated. We suggest that this method would be more useful if the protocol for its application is set up in consultation with the histopathology department, along with setting up a channel of bilateral communication. The histopathologist, based on the flow cytometry information provided, can then set up a more directed immunohistochemical panel. We would like to emphasize at this stage that the aim of the flow cytometric CD326 testing is not to formally diagnose carcinomas, but to highlight the presence of epithelial cells which may lead to the diagnosis of carcinoma. Final classification obviously remains the role of the histopathologist.

References
1. Patriarca C, Macchi RM, Marschner AK, Mellstedt H. Epithelial cell adhesion molecule expression (CD326) in cancer: a short review. Cancer Treat Rev 2012; 38(1): 68–75.
2. Went PT, Lugli A, Meier S, Bundi M, Mirlacher M, Sauter G, Dirnhofer S. Frequent EpCam protein expression in human carcinomas. Hum Pathol 2004; 35(1): 122–128.
3. Spizzo G, Fong D, Wurm M, Ensinger C, Obrist P, Hofer C, Mazzoleni G, Gastl G, Went P. EpCAM expression in primary tumour tissues and metastases: an immunohistochemical analysis. J Clin Pathol 2011; 64(5): 415–420.
4. Sheibani K, Shin SS, Kezirian J, Weiss LM. Ber-EP4 antibody as a discriminant in the differential diagnosis of malignant mesothelioma versus adenocarcinoma. Am J Surg Pathol 1991; 15(8): 779–784.
5. Dorwal P, Moore H, Stewart P, Harrison B, Monaghan J. CD326 (EpCAM) testing by flow cytometric BerEP4 antibody is a useful and rapid adjunct to histopathology. Cytometry B Clin Cytom 2017; doi: 10.1002/cyto.b.21543.
6. Spizzo G, Went P, Dirnhofer S, Obrist P, Moch H, Baeuerle PA, Mueller-Holzner E, Marth C, Gastl G, Zeimet AG. Overexpression of epithelial cell adhesion molecule (Ep-CAM) is an independent prognostic marker for reduced survival of patients with epithelial ovarian cancer. Gynecol Oncol 2006; 103(2): 483–488.
7. Varga M, Obrist P, Schneeberger S, Mühlmann G, Felgel-Farnholz C, Fong D, Zitt M, Brunhuber T, Schäfer G, et al. Overexpression of epithelial cell adhesion molecule antigen in gallbladder carcinoma is an independent marker for poor survival. Clin Cancer Res 2004; 10(9): 3131–3136.
8. Sikora J, Dworacki G, Zeromski J. DNA ploidy, S-phase, and Ki-67 antigen expression in the evaluation of cell content of pleural effusions. Lung 1996; 174: 303-313.
9. Pillai V, Cibas ES, Dorfman DM. A simplified flow cytometric immunophenotyping procedure for the diagnosis of effusions caused by epithelial malignancies. A J Clin Pathol 2013; 139(5): 672–681.
10. Krishan A, Ganjei‐Azar P, Hamelik R, Sharma D, Reis I, Nadji M. Flow immunocytochemistry of marker expression in cells from body cavity fluids. Cytometry A 2010; 77(2): 132–143.
11. Risberg B, Davidson B, Dong HP, Nesland JM, Berner A. Flow cytometric immunophenotyping of serous effusions and peritoneal washings: comparison with immunocytochemistry and morphological findings. J Clin Pathol 2000; 53(7): 513–517.
12. Davidson B, Dong HP, Berner A, Christensen J, Nielsen S, Johansen P, Bryne M, Asschenfeldt P, Risberg B. Detection of malignant epithelial cells in effusions using flow cytometric immunophenotyping. Am J Clin Pathol 2002; 118(1): 85–92.

The authors
Pranav Dorwal* MBBS, DCP, DNB; Helen Moore MBChB, FRACP, FRCPA
Waikato Hospital, Pembroke St, Hamilton 3204, New Zealand

*Corresponding author
E-mail: Pranav.dorwal@waikatodhb.health.nz