by Dr Petraki Munujos The antinuclear antibodies (ANA) determination is one of the most commonly used techniques in the autoimmunity clinical laboratory. Far from being outdated, indirect immunofluorescence (IF) is a powerful laboratory tool not only for clinical diagnostics, but for disease follow-up and prognosis estimation as well. Unlike other more precise quantitative techniques, IF […]
Introduction
Methodologies to detect pathogenic viruses in clinical specimens have transitioned from classic cell culture and antibody–antigen techniques to more sensitive molecular methods such as polymerase chain reaction (PCR). The targeted nature of these methodologies inhibits their ability to accommodate the true diversity of human pathogens in a clinical specimen, especially viruses [1]. Next-generation sequencing (NGS) technologies are quickly demonstrating their ability to provide broad detection of infectious agents in a target-independent manner [2–7]. NGS has many advantages beyond the improved detection of all suspected, unsuspected, or even novel pathogens in a clinical specimen [8]. Familiarization with pathogen genomic sequences within clinical specimens enhances our understanding of infectious disease through further discovery of pathogen variability and genotyping [9–11], drug resistance or response to therapy [12], vaccine development and efficacy monitoring [13], and further characterization of the metagenome [14]. The use of NGS for routine use in clinical diagnostics is emerging with its own set of limitations and challenges [13, 15]. Focusing on viruses of public health importance, we compared the performance of NGS alongside other more common viral detection methodologies.
Conventional methods versus NGS
We investigated applications of NGS in a clinical laboratory to detect pathogenic viruses in common specimen types and compared NGS data to that which could be obtained by more conventional methods for detecting and characterizing the following viruses of public health importance: adenovirus, herpesvirus, hepatitis C virus, and influenza [16]. We compared results obtained by NGS to viral culture, immunofluorescence staining, serum neutralization, and PCR in terms of turnaround time as well as the clinical relevance of the information obtained.
Table 1 describes the turnaround time of conventional methods to NGS for detecting adenoviruses and herpesviruses, both DNA viruses. The amount of time it takes to grow a virus in culture is variable, ranging from 1 day for herpes simplex viruses to 18 days for adenoviruses. All NGS data could be obtained in 4 days, which includes nucleic acid extraction, sequencing library preparation, sequencing and data analysis. Although most laboratories are not currently equipped with in-house bioinformaticians, much of the analysis can be done simply using common sequencing analysing software and the quickly growing number of applications online. For data analysis, we used PathSeq™Virome which enabled us to feed large read files into the application which would generate a report describing the viruses present, including a ‘detection score’ to distinguish strong and weak presence. NGS data provided much more information regarding the exact isolate which may aid health professionals in tracking and relating individual cases with others. Group C adenoviruses are treatable with cidofovir and NGS data was able to identify the amino acid motif that most affects antiviral resistance.
Hepatitis C virus (HCV) is a growing concern for public health and tends to be difficult to design targeted methodologies around owing to the high variability of viral genomes known, even within the same patient. NGS is a powerful tool for characterizing HCV infections and, in our experience, more informational than targeted genotyping assays (Table 2). As we were able to sequence nearly the entire HCV genome (coverage ranged from 92.4–95.6%), data could be generated describing the mutations at key locations across the genomes that are known to cause drug resistance. Antiviral resistance is also critical when characterizing current circulating influenza virus strains and NGS was able to identify viruses that would be considered susceptible to neuraminidase inhibitors (Table 3). In two cases, the viral load of the specimen was too low to achieve good genome coverage across the neuraminidase gene, but this issue could be resolved by screening specimens for high titre (i.e. qPCR) or using enrichment techniques such as ultracentrifugation or filtration of other background nucleic acid.
In most cases, with the exception of one specimen where no cytomegalovirus was definitively identified (HSV5, Table 1), information retrieved by NGS met or exceeded that of conventional methodologies. NGS proves to be a laboratory tool capable of not only detecting pathogenic viruses in clinical specimens, but also predicting the effects of drug treatment as well.
Summary
Through increased use of NGS technologies, reference databases of whole genome sequences can grow and enhance our ability to more definitively identify sequencing reads. Although this review describes conventional methods versus NGS for detecting specific viruses, there was also evidence of the presence of co-infecting viruses such as hepatitis G and Torque Teno virus that weren’t originally targeted. The standard 4-day turnaround time needed to complete NGS could be improved with extraction and library preparation automation, as well as advances in sequencing technology (each run ~40 hours). Based on our laboratory’s experience and the growing body of literature, NGS will change our approach as clinical laboratorians and improve our ability to detect and more fully characterize agents of infectious disease in clinical specimens in a non-targeted manner.
References
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2. Bzhalava D, Johansson H, Ekström J, Faust H, Möller B, Eklund C, Nordin P, Stenquist B, Paoli J, Persson B, Forslund O, Dillner J. Unbiased approach for virus detection in skin lesions. PLoS One 2013; 8(6): e65953.
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9. Arroyo LS, Smelov V, Bzhalava D, Eklund C, Hultin E, Dillner J. Next generation sequencing for human papillomavirus genotyping. J Clin Virol 2013: 58(2): 437–442.
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12. Sijmons S, Van Ranst M, Maes P. Genomic and functional characteristics of human cytomegalovirus revealed by next-generation sequencing. Viruses 2014; 6(3): 1049–1072.
13. Watson SJ, Welkers MRA, DePledge DP, Coulter E, Breuer JM, de Jong MD, Kellam P. Viral population analysis and minority-variant detection using short read next-generation sequencing. Philos Trans R Soc Lond B Biol Sci 2013; 368(1614): 20120205.
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15. Messiaen P, Verhofstede C, Vandenbroucke I, Dinakis S, Van Eygen V, Thys K, Winters B, Aerssens J, Vogelaers D, Stuyver LJ, Vandekerckhove L. Ultra-deep sequencing of HIV-1 reverse transcriptase before start of an NNRTI-based regimen in treatment-naive patients. Virology 2012; 426(1): 7–11.
16. Parker J, Chen J. Application of next generation sequencing for the detection of human viral pathogens in clinical specimens. J Clin Virol 2017; 86: 20–26.
The authors
Jayme Parker1,2 PhD and Jack Chen*1,2 PhD
1Department of Biology and Wildlife, Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
2Alaska State Public Health Virology Laboratory, Fairbanks, AK 99775, USA
*Corresponding author
E-mail: j.chen@alaska.edu
Early detection of disease-associated mutations in patients with familial hypercholesterolemia (FH) is crucial for early interventions that can reduce the risk of cardiovascular disease. Here, we describe real-time PCR-based approaches for the rapid detection of single nucleotide substitutions or insertions of the low density lipoprotein receptor gene for cascade screening of relatives.
by Sarojini Pandey and Dimitris K. Grammatopoulos
Introduction
Familial hypercholesterolemia (FH) 5 (OMIM#606945) is an autosomal-dominant disorder associated with abnormally high serum concentrations of low density lipoprotein (LDL) cholesterol (LDL-C) [1]. FH is one of the most common inherited disorders, with a worldwide prevalence estimated at 1 in 200–500 [2]. Affected individuals have increased risk of premature coronary heart disease and death [3]; however, most remain undiagnosed, untreated or inadequately treated. It has been proven that early detection of the disease and treatment reduces morbidity and mortality [4]. The majority of FH cases are caused by genetic defects in the LDL receptor (LDLR) as well as apolipoprotein B, or proprotein convertase subtilisin/kexin type 9. More than 80% of FH patients have mutations in the LDLR gene [5]. Over 1400 different mutations are listed in the LDLR gene database of University College London to date.
To address the screening deficit, the National Institute for Health and Clinical Excellence (NICE) in the United Kingdom developed guidelines on FH management strongly recommending identification of causal mutations in suspected cases of FH phenotype and cascade screening of relatives using a combination of genetic testing and LDL-C concentration measurement to identify affected relatives of those index individuals with a clinical diagnosis of FH [6]. This approach of genetic testing of affected individuals and screening of relatives is considered the most cost-effective strategy for detecting cases of FH across the population [7]. However, the most appropriate and cost-effective diagnostic testing protocol for use across the FH clinical diagnostic services remains to be established. Here, we describe an experimental approach suitable for the rapid detection of known single nucleotide substitutions or insertions of the LDLR gene in suspected individuals using real-time based PCR.
Real-time PCR-based method for identifying LDLR gene mutations
Genomic DNA was extracted from saliva or EDTA-containing blood samples using a QIAamp DNA Blood Mini Kit (Qiagen), and DNA concentration was quantified by ND-1000 spectrophotometer (NanoDrop, Thermo Scientific).
Genomic DNA was amplified with specific oligonucleotide primers and fluorescently labelled probes to identify the PCR product (LC FastStart DNA Master Hybridization Probe kit, Roche). The specific genotype was determined by performing a melting-curve analysis based on fluorescence resonance energy transfer (FRET) technique. Each 10-μL reaction contained 1× LightCycler FastStart DNA Master HybProbe, 3 mmol/L MgCl2, 500 nmol/L of forward and reverse primers, and 200 nmol/L of each hybridization probe. The amplification conditions consisted of one denaturation/activation cycle of 10 min at 95 °C and 45 cycles of three-temperature amplification. Each cycle consisted of 95 °C for 10 seconds, 60 °C for 10 seconds, and 72 °C for 15 seconds with a single fluorescence acquisition step at the 60 °C hold. This was followed by a melting-curve analysis of 95 °C for 20 seconds, 40 °C for 20 seconds, and a slow ramp (0.2 °C/second) to 85 °C with continuous fluorescence acquisition [8].
For LDLR 2054C>T genotyping the LightSNP® Kit rs28942084 LDLR [P685L] from TIB MOLBIOL (Berlin, Germany) whereas LDLR c.1474G>A; c.1567G>C; c.487dupC and c.647G>C mutations were identified by custom-made assays as previously described [8].
Results
Repeatability/reproducibility studies using five replicates of the same DNA sample or different batches of DNAs of heterogeneous genotypes were analysed five times and showed no intra-patient or between-batch variation. All LightCycler assays consistently identified the genotype correctly, confirming their analytical reliability and suitability for routine use.
All PCR methods demonstrated excellent robustness and analytical performance characteristics even when processing genomic DNA of less than optimal DNA purity (absorbance ratio 260/280 <1.6) and quantity (2.5–50 ng/μL). The genotype of all patients tested was correctly identified.
Figure 1 shows examples of wild-type and heterozygous for the LDLR c.1474G>A mutation. Heterozygote patients showed two distinct melting peaks and the G>A nucleotide substitution was detected by a melting temperature (Tm) shift of 7 °C.
In addition to ease of use and cost-effectiveness, a major advantage of this methodology is the rapid turn-around time of 90 min from genomic DNA extraction to PCR genotyping. This identifies potential uses outside large specialist centres in local one-stop clinics.
Discussion
The UK National Institute for Health and Care Excellence (NICE) recommends genetic testing of candidate patients presenting with FH phenotype and, once a disease-causing mutation is identified, screening of relatives; this is considered as the most cost-effective strategy for early detection of unsuspected cases of FH [9], and for distinguishing monogenic FH from sporadic or polygenic hypercholesterolaemia [10]. Detection of unknown mutations in the LDLR gene, where the majority of disease-causing mutations are found, requires complex and specialized molecular methods suitable for comprehensive scanning of the nucleotide sequence [11]. In contrast, once the disease-causing mutation has been identified, screening of relatives for the presence of the mutation does not pose a significant analytical challenge and a number of methodologies are available to the diagnostic services. Selection of these methods ultimately depends on local clinical service configuration, available laboratory expertise and resources and budget constraints. Some of these test requirements can be addressed by real-time PCR methods, which provide a cost-effective (the cost of each PCR method is estimated below £20) and rapid method for screening mutations associated with FH in family studies. Thus, these methods have the potential to deliver the second line of investigations of the FH cascade testing NICE pathway. The fast turn-around time of the method offers a significant advantage allowing the provision of a faster service as well as supporting delivery models such as a one-stop lipid clinic. This would allow the fast-tracking of clinical decision-making and choice of treatment as well as patient convenience, thus offering additional financial savings to the healthcare provider.
References
1. Marks D, Thorogood M, Neil HA, Humphries SE. A review on the diagnosis, natural history, and treatment of familial hypercholesterolaemia. Atherosclerosis 2003; 168: 1–14.
2. Benn M, Watts GF, Tybjaerg-Hansen A, Nordestgaard BG. Familial hypercholesterolemia in the Danish general population: prevalence, coronary artery disease, and cholesterol-lowering medication. J Clin Endocrinol Metab 2012; 97: 3956–3964.
3. Austin MA, Hutter CM, Zimmern RL, Humphries SE. Familial hypercholesterolemia and coronary heart disease: a HuGE association review. Am J Epidemiol 2004; 160: 421–429.
4. Neil A, Cooper J, Betteridge J, Capps N, McDowell I, Durrington P, Seed M, Humphries SE. Reductions in all-cause, cancer, and coronary mortality in statin-treated patients with heterozygous familial hypercholesterolaemia: a prospective registry study. Eur Heart J 2008; 29: 2625–2633.
5. Usifo E, Leigh SE, Whittall RA, Lench N, Taylor A, Yeats C, Orengo CA, Martin AC, Celli J, Humphries SE. Low-density lipoprotein receptor gene familial hypercholesterolemia variant database: update and pathological assessment. Ann Hum Genet 2012; 76: 387–401.
6. Chiou KR, Charng MJ, Chang HM. Array-based resequencing for mutations causing familial hypercholesterolemia. Atherosclerosis 2011; 216: 383–389.
7. Hinchcliffe M, Le H, Fimmel A, Molloy L, Freeman L, Sullivan D, Trent RJ. Diagnostic validation of a familial hypercholesterolaemia cohort provides a model for using targeted next generation DNA sequencing in the clinical setting. Pathology 2014; 46: 60–68.
8. Pandey S, Leider M , Khan M , Grammatopoulos DK. Cascade screening for familiar hypercholesterolaemia: PCR methods with melting-curve genotyping for the targeted molecular detection of apolipoprotein B and low density lipoprotein receptor gene mutations to identify affected relatives. JALM 2016; 02: 109–118.
9. Nherera L, Marks D, Minhas R, Thorogood M, Humphries SE. Probabilistic cost-effectiveness analysis of cascade screening for familial hypercholesterolaemia using alternative diagnostic and identification strategies. Heart 2011; 97: 1175–1181.
10. Talmud PJ, Shah S, Whittall R, Futema M, Howard P, Cooper JA, Harrison SC, Li K, Drenos F, et al. Use of low-density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case-control study. Lancet 2013; 381: 1293–1301.
11. Hollants S1, Redeker EJ, Matthijs G. Microfluidic amplification as a tool for massive parallel sequencing of the familial hypercholesterolemia genes. Clin Chem 2012; 58: 717–724.
The authors
Sarojini Pandey1 MSc and Dimitris K. Grammatopoulos*1,2 PhD, FRCPath
1Department of Clinical Biochemistry,
University Hospital Coventry and Warwickshire, Coventry CV2 2DX, UK
2Division of Translational and Systems Medicine, Warwick Medical School,
Coventry CV4 7AL,
UK
*Corresponding author
E-mail: Sarojini.Pandey@uhcw.nhs.uk
Indirect immunofluorescence (IIF) is an indispensable method for autoantibody diagnostics, providing high sensitivity and specificity together with a broad antigenic spectrum. However, the microscopic evaluation of the fluorescence patterns is both time-consuming and challenging for laboratory staff, and is, moreover, based on subjective interpretation. Laboratories are increasingly turning to automated systems to facilitate and standardize the IIF readout and interpretation. In recent years various automation systems have been developed, which provide automated digital acquisition of IIF images, discrimination of positive and negative samples, as well as pattern classification for key applications. This article focuses on the EUROPattern system, which provides computer-aided immunofluorescence microscopy for anti-nuclear antibodies (ANA), anti-neutrophil granulocyte cytoplasm antibodies (ANCA), antibodies against double-stranded DNA (anti-dsDNA) on Crithidia luciliae, monospecific antigen microdots (EUROPLUS) and transfected cell-based assays e.g. for anti-neuronal antibodies. The accuracy of automated evaluation compared to visual assessment has been investigated in various published studies.
by Dr Jacqueline Gosink
ANA
ANA represent a key diagnostic criterion for many autoimmune diseases, including systemic lupus erythematosus (SLE), mixed connective tissue disease, Sjögren’s syndrome, systemic sclerosis, polymyositis, dermatomyositis and primary biliary cirrhosis. The gold standard for ANA determination is IIF on human epithelial (HEp-2) cells. This substrate provides the complete antigen spectrum and allows investigation of over 100 different autoantibodies. Observation of the fluorescence pattern enables classification of the antibody or antibodies present in the patient sample. Positive results are confirmed by monospecific tests such as ELISA, immunoblot or IIF microdot assays.
The automated evaluation of HEp-2 cells includes reliable discrimination of positive and negative ANA results, as well as classification of all ANA patterns [1] (Figure 1), encompassing homogeneous, speckled, nuclear dots, nucleolar, centromeres, nuclear envelope and cytoplasmic. The ANA patterns identified by EUROPattern correspond to the competent level reporting defined by the International Consensus on ANA Patterns (ICAP; www.anapatterns.org). Mixed patterns, which occur when more than one antibody is present, are also recognized and reported as such. The pattern is assigned by analysing its features and comparing it to a reference database of over 5000 images, corresponding to 115,000 cells. Unspecific signals originating from outside of the cells are identified by means of a DNA counterstain and subsequently rejected. The evaluation also includes titre designations with confidence values for the detected antibodies. Results from the HEp-2 screening can be monospecifically confirmed using microdot substrates of purified antigens, which are incubated and evaluated in parallel.
To assess the diagnostic accuracy, the automated evaluation was compared to conventional visual interpretation by experts in the field using 351 patient sera [2]. The concordance for positive/negative discrimination was 99%, with an analytical sensitivity of 100% and a specificity of 98%. In 60% of samples, the pattern, including variable mixed patterns, was recognized completely by the software. In 94% of samples, the main pattern was correctly designated. A further study showed 79% correct pattern assignment.
Anti-dsDNA antibodies
Anti-dsDNA antibodies are a hallmark of SLE and represent an important criterion for diagnosis. Their prevalence in SLE ranges from 30% to 98% in different studies, depending among other things on the test method used. Like the gold standard Farr assay, IIF using Crithidia luciliae as the substrate (CLIFT) is considered to have a very high disease specificity. The method takes advantage of the kinetoplast of C. luciliae, which is rich in DNA but contains hardly any other antigens, thus enabling highly selective detection of anti-dsDNA antibodies. However, manual reading of the fluorescence signals is subjective and leads to high intra- and inter-laboratory variation, making standardized automated evaluation a desirable goal.
Automated interpretation of CLIFT has recently been incorporated into the EUROPattern system [3] (Figure 2). The software is able to recognize the organelles of the protozoan and evaluates the specific kinetoplast fluorescence rather than just dark-light classification, increasing the reliability of the evaluation. Results are classified as positive or negative, and include a titre designation based on the fluorescence intensity.
In a clinical study, automated and visual evaluation of C. luciliae IIF was compared using 569 consecutive sera submitted for routine anti-dsDNA screening and 100 sera from healthy blood donors. The automated system recognized all 73 of the anti-dsDNA positive samples identified by the visual evaluation. Moreover, 93% of the titre designations were concordant. The overall sensitivity of the system amounted to 100% with a high specificity of 97%. Compared to visual microscopy the overall accuracy was 97%.
ANCA
ANCA are important serological markers for diagnosis and differentiation of autoimmune vasculitides, especially granulomatosis with polyangiitis (GPA, formally known as Wegener’s granulomatosis), which is characterized by autoantibodies against proteinase 3 (PR3), and microscopic polyangiitis, which is typified by autoantibodies against myeloperoxidase (MPO). In addition, ANCA can be found in chronic inflammatory bowel diseases. ANCA are detected by IIF with monospecific confirmation using ELISA, immunoblot or IIF microdot assays.
The IIF substrates ethanol-fixed and formalin-fixed granulocytes are used to identify the typical ANCA staining patterns of anti-PR3 (cytoplasmic, cANCA) and anti-MPO (perinuclear, pANCA) antibodies. An additional substrate consisting of HEp-2 cells coated with granulocytes allows immediate differentiation between ANCA and ANA, while purified antigen microdots of PR3, MPO or glomerular basement membrane (GBM) antigen provide simultaneous monospecific antibody characterization. The different substrates are incubated and automatically evaluated in parallel as BIOCHIP mosaics, thus providing ANCA screening and confirmation in one step.
Evaluation software such as EUROPattern provides automated positive/negative discrimination of samples, as well as recognition of pANCA and cANCA patterns [1] (Figure 3). Further pattern constellations such as DNA-ANCA (atypical pANCA, xANCA), which can arise from antibodies against lactoferrin or other antigens, are also taken into account by the software. The automated system proposes a result based on the recognized cellular patterns and the results on the antigen microdots. An estimated titre with a confidence value is given.
Anti-neuronal antibodies
Neuronal cell-surface autoantibodies occur in autoimmune encephalitis and their detection can secure an early diagnosis, enabling immediate treatment which is critical for patient outcome. In recent years a considerable number of novel target antigens has been discovered, for example, glutamate receptors of type NMDA and AMPA, GABAB receptors, voltage-gated potassium channel-associated proteins LGI1 and CASPR2, DPPX and IgLON5.
Diagnostic tests for the new parameters are based on recombinant-cell (RC) IIF, in which transfected cells expressing the relevant antigen are used for monospecific antibody detection. This test method enables authentic presentation of the fragile membrane-associated surface antigens. Since many of the autoantibody markers are rare and do not always overlap, a multiparametric screening using BIOCHIP mosaics made up of different substrates is recommended. Results for RC-IIF assays can be evaluated automatically using a newly developed function of EUROPattern. The system automatically takes digital images of the substrates and provides a positive/negative classification.
The quality of the acquired images was assessed by comparing on-screen appraisal with visual microscopy using 753 incubations of numerous serum samples sent to a clinical immunology laboratory [4]. Ambiguous fluorescence signals detected at the microscope were excluded to avoid inter-reader deviations. The two evaluation strategies revealed a concordance of 100% with respect to positive/negative discrimination, confirming the high quality of the images.
Arbovirus antibodies
Immunofluorescence microscopy is also useful for infectious disease diagnostics. For example, infections with Zika virus, dengue virus and chikungunya virus are difficult to tell apart clinically as they manifest with similar symptoms and are endemic in much the same regions. Serological tests are an important diagnostic method, especially beyond the short viremic phase when direct detection is no longer effective. Viral antibodies can be detected by IIF using virus-infected cells. However, cross reactions between flavivirus antibodies can occur.
A BIOCHIP mosaic comprising substrates for Zika, dengue and chikungunya viruses enables parallel antibody determination, aiding clarification of cross reactivities and supporting differential diagnosis. The substrates can be evaluated semi-automatically using the digital image acquisition function of EUROPattern. In particular, inspection of the images side-by-side on the computer screen considerably facilitates the interpretation.
Fully automated immunofluorescence microscopy
Computer-aided fluorescence microscopy can be further standardized and facilitated through use of complementary hardware. The EUROPattern microscope (Figure 4) has been tailored to the requirements of immunofluorescence. Next to the high-precision optical system, it has a controlled LED, which maintains a constant light flux, ensuring highly reproducible results. The cLED has an extremely long life span without maintenance (over 50,000 hours) and low power consumption, ensuring cost-effectiveness for laboratories. The microscope is equipped with a slide magazine which can process up to 500 analyses in succession within 2.5 hours (18 seconds per field), correctly identifying the slides by means of matrix codes.
Results from the automated IIF evaluation can be viewed and validated directly at the computer screen, enabling a diagnosis to be established quickly and efficiently. The high-resolution images are sharply focused with the aid of a counterstain. The counterstain also serves to verify correct performance of the incubation. Negative results can be verified in batches, while positive samples can be individually checked and confirmed by the medical technologist. Results from different serum dilutions and substrates are consolidated into one report per patient, and new findings are compared with previous records. Final results can be signed electronically and forwarded at a click.
Perspectives
The need for standardization and automation in IIF is tremendous in all fields of autoimmune diagnostics. In particular, manual evaluation of results is time consuming and subjective. Automation platforms with harmonized software and hardware components have in recent years contributed enormously to the standardization and simplification of the evaluation process, especially for ANA, ANCA and CLIFT. Advanced software provides positive/negative classification, pattern recognition and titre designation at a quality equivalent to visual microscopy. The recording of tissue substrates, such as liver, kidney, stomach, esophagus, small intestine, heart and neuronal tissue, is also feasible. Future development will focus on the recognition of organ- and non-organ-specific autoantibodies on tissues, for example antibodies against mitochondria, epithelial membrane, epidermal basement membrane, desmosomes, heart muscle and neuronal antigens. The continued development of automated evaluation systems is anticipated to lead to even greater standardization of IIF and further reductions in workflow for diagnostic laboratories.
References
1. Krause et al. Lupus 2015: 24: 516-29
2. Voigt et al. Clin. Devel. Immunol. 2012: vol 2012, article ID 651058
3. Gerlach et al. J. Immunol. Res. 2015: vol 2015, article ID 742402
4. Fraune et al. Autoimmunity Reviews 15 (2016) 937-942
The author
Jacqueline Gosink, PhD
EUROIMMUN AG, Seekamp 31, 23560 Luebeck, Germany
E-mail: j.gosink@euroimmun.de
March 2026
Prins Hendrikstraat 1
5611HH Eindhoven
The Netherlands
info@clinlabint.com
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