Mitochondrial DNA mutations (mtDNA) have been described that are associated with leukemia. To identify somatic mutations it is necessary to have a control tissue from the same individual for comparison. In this review we describe a new next-generation sequencing approach to identify leukemia-associated mtDNA mutations by using remission samples as control.
by Dr Ilaria Stefania Pagani
Introduction The identification of acquired somatic mutations in leukemic samples is of considerable importance for diagnosis and prognostication. In order to identify somatic mutations it is necessary to have a control tissue from the same individual for comparison. Non-hematopoietic tissues, such as mesenchymal stromal cells (MSCs) or hair follicles are preferred, but not always available. When patients with leukemia achieve remission, the remission peripheral blood (PB) may be a suitable and easily available control tissue. This article will provide recommendations for the identification of tumour-associated mtDNA somatic mutations, highlighting advantages and disadvantages of the method.
mtDNA characteristics Human mitochondrial (mt) DNA is a 16 569 bp double-stranded, circular DNA molecule that encodes 13 polypeptides of the oxidative phosphorylation system (OXPHOS), 22 transfer RNAs and 2 ribosomal RNAs. Several important differences between the mt genome and the nuclear genome complicate the study of mtDNA mutations. Ninety-three percent of the sequence consists of coding DNA, introns are absent, the only non-coding region is at the level of the D-loop containing the promoters of the genes and it is maternally inherited. Each cell has a variable number of mitochondria (typically several hundred) and each mitochondrion contains a variable number of genomes (typically 2–10). Consequently, mtDNA mutations do not follow the pattern of a diploid genome: rather, a cell may have a single mt genotype (homoplasmy) or multiple mt genotypes (heteroplasmy). Heteroplasmy may be at any frequency, could vary between cells and many variants will be below the limit of detection of Sanger sequencing, and therefore technically difficult to validate [1]. To date, more than 400 mtDNA mutations have been associated with human diseases, most of them being heteroplasmic. Therefore, an accurate determination of the level of heteroplasmy is important for disease association studies [2].
mtDNA mutations and cancer MtDNA mutations may potentially contribute to a cell to becoming cancerous, leading to invasion and metastasis [3]. Heteroplasmic somatic mtDNA mutations have been reported in hematological neoplasms, including myelodysplastic syndromes, chronic lymphocytic leukemia, chronic myeloid leukemia (CML), acute myeloid leukemia, and acute lymphoblastic leukemia (ALL) [1]. Many cancer types, including leukemia, have a tendency to be highly glycolytic, increasing the production of the reactive oxygen species (ROS), that lead to genomic instability. The mtDNA genome is susceptible to ROS-induced mutations owing to the high oxidative stress in the mitochondrion and limited DNA-repair mechanisms [3]. The identification of acquired somatic mutations in leukemic samples is of considerable importance for diagnosis and prognostication. In a study in acute myeloid leukemia, for example, patients with mutated NADH dehydrogenase subunit 4 (ND4) showed greater overall survival than patients with wild-type ND4 [4].
mtDNA somatic mutations: the problem of control tissue MtDNA acquires somatic mutations at a rate 10-fold higher than nuclear DNA, so mtDNA single nucleotide variants (SNVs) accumulate with age, and may be tissue-specific [5]. This means that there is no absolutely reliable source of ‘germline’ mtDNA, especially in older individuals [1]. Somatic mutations must be distinguished from non-pathogenic germline variants by comparison with a control tissue sample. Non-hematopoietic tissues, such as buccal cells, hair follicles or MSCs are preferred, but not always available. PB cells from a post-treatment remission sample may be used as alternative. This method is widely used for nuclear mutations, but less commonly for mt mutations [1]. Blood samples are readily accessible from leukemia patients who achieve morphological remission after treatment. Therefore, a method for the detection of leukemia-associated mtDNA mutations based on comparison with a remission sample may be useful. A new approach to identify mtDNA somatic mutations at diagnosis by using remission samples as control tissue Pagani IS and colleagues developed a next-generation sequencing (NGS) approach for the identification of leukemia-associated mtDNA mutations using samples from CML patients at diagnosis and in remission following treatment with tyrosine kinase inhibitors (TKIs) [1]. This approach could also be applied to both hematopoietic and non-hematopoietic cancers, such as epithelial tumours, in which a tumour biopsy specimen can be compared with the normal mucosa.
Twenty-six chronic phase CML patients enrolled in the Australasian Leukaemia and Lymphoma Group CML9 trial (TIDEL-II; ID: ACTRN12607000325404) [6] took part in the study [6]. PB samples from leucocytes at diagnosis before commencing TKI treatment, and remission after 12 months of therapy were compared. Hair follicles (n=4), bone marrow MSCs (n=18), or both (n=4) were used as non-hematopoietic control samples. The comparison of a diagnostic sample with a non-hematopoietic control tissue is the standard method to identify somatic mutations in leukemia [1]. The concordance between this classic method and the diagnosis versus remission approach has been investigated. NGS assay for the mt genome The workflow chart is represented in Figure 1. Briefly the genomic DNA (comprising a mixture of nuclear and mtDNA) was extracted by a phenol/chloroform method from PB leukocytes and non-hematopoietic tissues. The mtDNA was amplified by long-range PCR, generating two or three overlapping fragments covering the entire mt genome. The PCR amplicons were then pooled at equimolar concentrations and sequencing libraries were prepared using the Nextera XT kit (Illumina). Indexed libraries were multiplexed and run on an Illumina MiSeq instrument using the 600 cycle MiSeq Reagent kit (v3) generating 300-bp paired-end reads [1]. Somatic mutation calling from high-throughput sequencing datasets and validation The majority of the variant-calling methods in use are based on low-coverage human re-sequencing data and diploid calls with discrete frequencies of interest (0%, 50% or 100%) [7, 8]; however, these assumptions do not apply to mtDNA. The LoFreq software (loFreq-star version 2.11, genome Institute of Singapore; http://csb5.github.io/lofreq/) was chosen because it was developed for viral and bacterial genomes as well as diploid data, and because of its ability to automate comparison with a matched control tissue for the detection of somatic mutations [8]. The revised Cambridge Reference Sequence (rCRS) for the human mt genome (NC_012920) was used as reference sequence to identify SNVs. Tumour tissue (test) and control were then compared to identify somatic mutations specific only for the tumour tissue. Variants in common between the test and the control sample were considered to represent germline polymorphisms or mutations and were filtered out by the software. A binomial test was applied to the remaining variants to determine whether an apparent difference between samples could be due to inadequate read coverage in the control. Variants passing the binomial test were retained in the final list of putative somatic mutations (Fig. 2a) [8]. The identified mutations should be considered putative and, in common with most other NGS strategies for the discovery of novel mutations, any specific mutation of clinical interest would need to be confirmed using an independent method, as Sanger sequencing (limit of detection 20%), Sequenom MassArray, digital array (Fluidigm) or another NGS platform.
NGS: error rate, false positives and threshold Before the application of NGS technologies, no evidence of heteroplasmy was detected, probably because of the lower sensitivity of earlier techniques [9]. NGS technologies enable the inquiry of mt heteroplasmy at the genome-wide scale with much higher resolution because many independent reads are generated for each position [2]. However, the higher error rate associated with the more sensitive NGS methodology must be taken into consideration to avoid false detection of heteroplasmy. Short-read sequencing technologies (like in Illumina systems) have a high intrinsic error rate (approximately 1 in 102–103 bases) when applied at the very high depth required to detect and measure low-level heteroplasmy. Thus, appropriate criteria for avoiding false positives due to sequencing errors are required. The most obvious way to distinguish between sequencing errors and heteroplasmy is to invoke a threshold. Two duplicate sequencing run, of which one was ultra-deep (validation run), were compared to determine sensitivity (proportion of true positives that are correctly identified as such) and specificity (proportion of true negatives that are correctly identified as such). An empirical threshold of 2% was therefore applied to distinguish true variants from sequencing errors. Variants with a variant allele fraction (VAF, the variant allele’s read depth divided by total read depth at each nucleotide position) between 2 and 98% where then considered as heteroplasmic, and variants with a VAF >2% were called homoplasmic [1]. This threshold could be refined by an iterative process in which a different threshold is identified for each nucleotide position [10], as some variation in error rate was observed. The incorporation of molecular barcodes in the initial long-range PCR would also reduce the risk of false-positive mutations due to PCR artefact [1].
Remission samples as control tissue in the identification of the mtDNA somatic mutations at diagnosis In the four patients who had both MSC and hair follicle DNA available as control tissue, the same mutations at diagnosis have been identified, therefore the results using the non-hematopoietic tissues as control were combined. Remission samples were then used as control tissue to determine mtDNA somatic mutations at diagnosis, and the concordance between this method and the conventional diagnosis versus the MSC/hair follicle approach was examined. Seventy-three somatic mutations (81%) were identified in common, 11 mutations (12%) were identified only in comparison with the non-hematopoietic control, and six (6.7%) only by comparison with remission samples (Fig. 2b) [1]. Divergent results occurred as the result of differences in read quality or depth at a specific nucleotide not reaching statistical significance in the algorithm. False-negative results could be encountered using remission samples as the control tissue, because of low-level heteroplasmic mutations in the control sample that would lead to the same mutation at diagnosis being removed through filtering.
Concluding remarks Remission samples can be used as control tissues to detect candidate mtDNA somatic mutations in leukemic samples when non-hematopoietic tissues are not available. The presence of mutations at low VAF in the remission samples in common with the diagnosis tissue, could be filtered out by the LoFreq software leading to false-negative results. Therefore visual inspection of the unfiltered variants is recommended.
References 1. Pagani IS, Kok CH, Saunders VA, van der Hoek MB, Heatley SL, Schwarer AP, Hahn CN, Hughes TP, White DL, Ross DM. A method for next-generation sequencing of paired diagnostic and remission samples to detect mitochondrial DNA mutations associated with leukemia. J Mol Diagn 2017; 19(5): 711–721. 2. Li M, Schonberg A, Schaefer M, Schroeder R, Nasidze I, Stoneking M. Detecting heteroplasmy from high-throughput sequencing of complete human mitochondrial DNA genomes. Am J Hum Genet 2010; 87(2): 237–249. 3. van Gisbergen MW, Voets AM, Starmans MH, de Coo IF, Yadak R, Hoffmann RF, Boutros PC, Smeets HJ, Dubois L, Lambin P. How do changes in the mtDNA and mitochondrial dysfunction influence cancer and cancer therapy? Challenges, opportunities and models. Mutat Res Rev Mutat Res 2015; 764: 16–30. 4. Damm F, Bunke T, Thol F, Markus B, Wagner K, Gohring G, Schlegelberger B, Heil G, Reuter CW, et al. Prognostic implications and molecular associations of NADH dehydrogenase subunit 4 (ND4) mutations in acute myeloid leukemia. Leukemia 2012; 26(2): 289–295. 5. Gattermann N. Mitochondrial DNA mutations in the hematopoietic system. Leukemia 2004; 18(1): 18–22. 6. Yeung DT, Osborn MP, White DL, Branford S, Braley J, Herschtal A, Kornhauser M, Issa S, Hiwase DK, et al. TIDEL-II: first-line use of imatinib in CML with early switch to nilotinib for failure to achieve time-dependent molecular targets. Blood 2015; 125(6): 915–923. 7. Meldrum C, Doyle MA, Tothill RW. Next-generation sequencing for cancer diagnostics: a practical perspective. Clin Biochem Rev 2011; 32(4): 177–195. 8. Wilm A, Aw PP, Bertrand D, Yeo GH, Ong SH, Wong CH, Chiea CK, Rosemary P, Martin LH, Niranjan N. LoFreq: a sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets. Nucleic Acids Res 2012; 40(22): 11189–11201. 9. Chatterjee A, Dasgupta S, Sidransky D. Mitochondrial subversion in cancer. Cancer Prev Res 2011; 4(5): 638–654. 10. Kerpedjiev P, Frellsen J, Lindgreen S, Krogh A. Adaptable probabilistic mapping of short reads using position specific scoring matrices. BMC Bioinformatics 2014; 15: 100.
The author Ilaria Stefania Pagani1,2 PhD 1Cancer Theme, South Australian Health & Medical Research Institute, Adelaide, Australia 2School of Medicine, Faculty of Health Sciences, University of Adelaide, Adelaide, Australia
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Dermatomycoses are extremely widespread, and are characteristically long-lasting, recurring and very difficult to cure. Early and accurate identification of the causative agent is essential for targeted therapy. A new DNA microarray provides direct detection and differentiation of the most important dermatomycosis pathogens in one reaction. The assay simultaneously detects up to 50 dermatophyte species, and provides species identification for 23 of these, as well as 6 yeasts and moulds. The microarray analysis aids differential diagnosis of dermatomycoses from other dermatoses (e.g. psoriasis), and specifically identifies mixed infections with yeasts and moulds. The dermatomycosis microarray is part of the established EUROArray platform, which also includes microarrays for multiplex identification of sexually transmitted infections (STI) and complete detection and typing of human papillomaviruses (HPV).
by Dr Jacqueline Gosink
Dermatomycosis Dermatomycoses are infections of the skin, hair and nails which are typically caused by dermatophytes and in rarer cases by yeasts and moulds. Fungal infections of the skin are the most frequently occurring infectious diseases globally with high and growing relapse rates. Elderly people and immunocompromised patients are especially at risk. Worldwide, around 20 to 25% of the population is affected by fungal skin diseases.
Infections which are caused exclusively by dermatophytes are referred to as dermatophytoses or tinea. Tinea pedis, which occurs on the soles of the feet and between the toes, is one of the most frequent forms worldwide, followed by tinea unguium, which affects the nails, and tinea corporis, which affects the neck, back or trunk. Further forms, for example, on the face, legs, beard area, arms and hands, are rarer. Nail infections caused by dermatophytes and/or yeasts/moulds are called onychomycoses. They are typically accompanied by deformation of the nail.
Pathogens of dermatomycosis Dermatophytes encompass fungi of the genera Trichophyton, Epidermophyton, Nannizzia, Paraphyton, Lophophyton, Microsporum and Arthroderma. Individual species are classified as anthropophilic, zoophilic or geophilic according to their main occurrence. Human pathogenic yeasts and moulds include Candida spp., Scopulariopsis brevicaulis, Fusarium spp. and Aspergillus fumigatus.
Around 70% of human dermatophyte infections are caused by anthropophilic species. Trichophyton rubrum, in particular, is the most frequent cause of fungal skin infections worldwide. Infections can spread easily to other areas of the body or to other persons, for example, via showers, bathtubs or floors. Zoophilic dermatophytes are transmitted to humans by close contact with animals, especially pets, which are often asymptomatic. They can cause severe inflammatory reactions in humans. Geophilic dermatophytes cause disease less frequently in humans. Infections typically occur in gardeners and farm workers or children who play outside. Moulds and yeasts often cause opportunistic infections, benefitting from damage to the skin or nail caused by an existing dermatophyte infection. In immunocompromised individuals, local fungal infections may develop into systemic mycosis.
Clinical picture Dermatomycoses are clinically heterogeneous and cannot always be differentiated from other dermatoses, such as eczema, psoriasis, erysipelas, or autoimmune diseases such as Lichen ruber planus. Furthermore, 5 to 15% of onychomycosis cases comprise mixed infections of dermatophytes with yeasts and moulds. Simultaneous bacterial infection of the damaged skin, pretreatment with corticosteroid-containing preparations, or secondary contact allergy can also hinder diagnosis.
Dermatomycoses must always be treated. This is generally undertaken using various topical antifungal drugs, with severe cases sometimes requiring oral medication. Each drug has a limited activity spectrum. Positive pathogen identification prior to treatment enables targeted selection of the most suitable drug and optimal planning of the oftentimes lengthy therapy. In multiple infections, a change of the primary pathogenic agent may occur during the therapy and it may seem like the therapy is failing. This must be taken into account in the treatment of fungal infections of the nails, which may only yield first success after months. Identification of the causative pathogen also helps to determine the source of the infection. In the case of zoophilic pathogens, for example, this is usually a pet.
Laboratory diagnostics Laboratory diagnostic methods for identifying dermatomycosis pathogens include microscopic detection and an attempt at culturing from clinical material. Successful culture in most cases enables species assignment based on micro- and macromorphological presentation of the fungus. Culturing is, however, time-consuming and is not possible for all dermatophytes. In mixed infections, false diagnoses may occur since slowly growing species may be overgrown or overlooked. Furthermore, antifungal therapy started before the sampling can hinder the culture.
Direct detection of pathogen genomic material by DNA microarray enables secure and accurate identification of the causative agent. Microarray analysis offers a significant time advantage over detection by culturing, and is especially useful for detecting dermatophytes that are difficult to cultivate. It provides higher sensitivity and specificity, even in patients already undergoing treatment. The EUROArray Dermatomycosis analysis includes a universal dermatophyte detection encompassing 50 species of the genera Trichophyton, Epidermophyton, Microsporum, Nannizzia, Arthoderma, Lophophyton, as well as species identification for the 23 dermatophyte and 6 yeast and mould species listed in Table 1.
EUROArray procedure The EUROArray procedure (Figure 1) is performed on DNA samples isolated from skin scales, nail shavings or hair stubs. Defined gene sections of the pathogens are first amplified by multiplex polymerase chain reaction (PCR). The fluorescently labelled PCR products are then incubated with biochip microarray slides containing immobilized complementary probes. Specific binding (hybridization) of the PCR products to their corresponding oligonucleotide probes is detected using a special microarray scanner. The signals are evaluated and interpreted automatically by the EUROArrayScan software (Figure 2). A detailed result report is produced for each patient and all data are documented and archived. Meticulously designed primers and probes, ready-to-use PCR components and integrated controls all contribute to the reliability of the analysis. The entire EUROArray procedure from sample arrival to report release is IVD-validated and CE-registered, supporting quality management in diagnostic laboratories.
Specifications and evaluation The lower detection limit of the test system depends on the pathogen and lies between 50 and 600 DNA copies per reaction, in individual cases also higher. Evaluation studies verified that template DNA in concentrations ranging from the lower detection limit to 50 ng can be used in the PCR without generating any false positive results. Furthermore, potential cross reactivity with 37 microorganisms of the resident and transient skin flora was excluded experimentally.
In an evaluation study with 409 clinical samples, the EUROArray Dermatomycosis yielded a good agreement with the precharacterization. In many cases additional pathogens that were not included in the precharacterization were detected. The additional findings were confirmed by further independent tests or sequencing. Thus, the microarray provides reliable results and broad detection capabilities.
STI detection The EUROArray STI is based on the same technology and provides parallel direct detection of the pathogenic agents of eleven sexually transmitted infections (STIs) in one reaction, namely Chlamydia trachomatis, Neisseria gonorrhoea, Mycoplasma genitalium, Mycoplasma hominis, Ureaplasma urealyticum, Ureaplasma parvum, Haemophilus ducreyi, Treponema pallidum, Trichomonas vaginalis and herpes simplex viruses 1 and 2.
STIs are often asymptomatic, but can nevertheless lead to serious sequelae, for example infertility, fetal damage during pregnancy, and severe postnatal infections in newborns. The PCR-based detection allows identification of both manifest and silent infections, and is thus suitable for diagnosis of symptomatic patients as well as for general screening. It offers a huge time advantage over cultivation and is especially useful for detecting sexually transmitted pathogens that are difficult or impossible to cultivate, e.g. C. trachomatis, Mycoplasma, Ureaplasma, T. pallidum. Due to amplification of the pathogen DNA, infections with a reduced pathogen number can also be reliably detected. A broad screening for STI pathogens is particularly important in asymptomatic or clinically ambiguous cases and for detecting multiple infections, which are often missed during single-parameter testing.
HPV detection and typing The EUROArray HPV provides detection and typing of all 30 genitally relevant HPV subtypes in one test. HPV are involved in the development of cervical carcinoma, and HPV testing plays a central role in risk assessment and early diagnosis of this cancer. In contrast to Pap examinations, HPV detection is not dependent on subjective evaluation and it offers very high sensitivity even in the early stages of infection. The EUROArray HPV is based on detection of the viral oncogenes E6 and E7, which provides the highest possible sensitivity. Using an extensive panel of specific primers and probes, the EUROArray detects and distinguishes between 18 high-risk subtypes that may trigger cancer (16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 73, 82) and 12 low-risk subtypes that cause benign genital warts (6, 11, 40, 42, 43, 44, 54, 61, 70, 72, 81, 89). Multiple infections are reliably identified, and primary and persistent infections can be differentiated. A positive result for a high-risk subtype indicates an increased risk for cervical carcinoma, which can then be minimised by more frequent follow-up examinations to detect morphological cell changes at an early stage. Based on the recommendations of the respective professional societies, HPV-negative women can forgo subsequent HPV tests and Pap smears for a longer time interval.
Conclusions Molecular diagnostic tests such as the EUROArray are an important tool for identifying the precise pathogenic agent in various infectious diseases, supporting decision-making on specific treatment. The new EUROArray Dermatomycosis provides the most comprehensive direct detection of dermatomycosis pathogens currently available commercially, and complements existing assays for STI and HPV. The EUROArray procedure is easy to perform and does not require extensive expertise in molecular biology. Moreover, the fully automated evaluation ensures objective, accurate and reproducible results. Further infectious disease microarrays based on the same technology are in development.
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The global prevalence of diabetes mellitus is increasing rapidly; affecting 8.8% of the population. The Randox automated immunoturbidimetric HbA1c test offers an improved method for the rapid direct measurement of HbA1c in human blood; which is available for use on the RX modena, RX imola and the RX daytona+.
Introduction to the RX series The RX series combines robust hardware and intuitive software with a world leading test menu comprising of routine chemistries, specific proteins, lipids, therapeutic drugs, drugs of abuse, antioxidants and diabetes testing and a range of niche tests including the HbA1c assay. The RX series removes the need for a separate HbA1c analyser and allows laboratories to expand their testing capabilities onto one single platform, providing cost savings through consolidation. Built on three core values- reliability, accuracy and precision, the RX series reduces costly test re-runs and misdiagnosis, offering complete confidence in results. The RX series range of clinical chemistry analysers includes the RX misano, (semi-automated) RX monaco, RX daytona+, RX imola and RX modena.
Background Diabetes is a global epidemic that affects approximately 271 million people around the world and according to the International Diabetes Federation; it is a figure that is on the rise. Their calculations forecast that diabetes will affect roughly 552 million by the year 2030, highlighting the fundamental need to manage patients with diabetes. The USA is one of the most prominent countries affected by diabetes when analysing its prevalence worldwide. It affects roughly 24 million Americans which is a stark contrast to the UK where around 3.5 million people have been diagnosed. It is also important to note that serious health complications can result from diabetes over time which reinforces the need to test HbA1c levels to evaluate how well diabetes is being controlled. The longer you have diabetes, the higher the risk of complications. These can include cardiovascular disease, nerve damage and kidney damage; including end-stage kidney disease which can require dialysis or a kidney transplant. With the rising figures and growing list of complications associated with the disease, diabetes remains one of the leading causes of death in the world and the seventh leading cause of death in the US.
HbA1c explained further HbA1c, also known as hemoglobin A1c or glycated hemoglobin, is an important blood test that is able to determine how well diabetes is being controlled. It develops when hemoglobin, a protein within red blood cells that carries oxygen throughout the body, joins with glucose in the blood, becoming ‘glycated’. As glycation is irreversible, HbA1c remains in the same state in the red blood cell for 8-12 weeks; giving an overall picture of what the average blood sugar level is. This is particularly important as it allows clinicians to monitor the ‘glycemic’ control in individuals with diabetes.
What is the HbA1c assay used for? The concentration of HbA1c in the blood of diabetic patients increases with rising blood glucose levels and is representative of the mean blood glucose level over the preceding six to eight weeks. HbA1c can therefore be described as a long term indicator of diabetic control unlike blood glucose which is only a short term indicator of diabetic control. It is recommended that HbA1c levels are monitored every three to four months. In patients who have recently changed their therapy or in those who have gestational diabetes it may be beneficial to measure HbA1c levels more frequently, at two to four week intervals. The onset of diabetes, particularly type two diabetes, tends to be gradual and thus proves difficult to diagnose early. With HbA1c clinicians are able to monitor blood glucose levels periodically to deliver accurate and quick results that can improve patient care.
The clinical significance of HbA1c The measurement of HbA1c is used in the long term monitoring of diabetes mellitus. This assay should not be used in the diagnosis of diabetes mellitus or for day to day glucose monitoring. Diabetes mellitus is a disease associated with poor glycemic control. Numerous clinical studies, including the Diabetes Control and Complications Trial, have shown that diabetes-related complications may be reduced by the long term monitoring and tight control of blood glucose levels. In the diabetic patient where blood glucose levels are abnormally elevated the level of HbA1c also increases, the reason for this is that HbA1c is formed by the non-enzymatic glycation of the N-terminus of the ß-chain of hemoglobin A0.
Randox HbA1c assay features:
Sample type – suitable for use with whole blood samples
Latex enhanced immunoassay method – the Randox assay utilizes an immunoassay method making it simple and quick to perform.
Liquid ready to use reagents – for ease of use and convenience
Excellent stability – all reagents are stable to expiry date when stored at +2-8ºC or 28 days on board the analyser at approximately 10°C.
Advantages of the RX series clinical chemistry analysers for direct HbA1c testing:
Fully automated on-board haemolysis function for HbA1c testing
Continuous loading & STAT sample functionality to enhance productivity in the laboratory- analyser dependant
Low sample volumes required
1200 tests per hour including ISE (RX modena)
User friendly software
Low water consumption
Dual 5 speed stirrers optimized for reach chemistry reaction
Reagent micropipette with liquid level sensor and crash detection
Liquid level sensor, crash, bubble and clot detection
Key benefits of using the RX series clinical chemistry analysers and Randox HbA1c assay Direct HbA1c testing eliminates the need for the sample incubation step which is required on alternative methods; allowing samples to be to run immediately on the RX series and providing faster and more accurate results when they are needed. The removal of the offline preparation stage increases the recovery times, allowing laboratories to enhance their workflow and also consolidate testing onto one single clinical chemistry platform. Additional benefits of using the RX series in conjunction with the Randox HbA1c assay include having one assay instead of two, which enables quicker calibration; saving the user time and making the overall method simple and quick to perform, setting a new standard in HbA1c determination and patient care.
For further information or for a quotation for the HbA1c test or to enquire about any analyser in the RX series range, please contact marketing@randox.com.
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by Nicolas Heureux (DIASource Immunoassays, Louvain-La-Neuve, Belgium)
Vitamin D testing is part of laboratory practice since more than 30 years but has become a routine parameter only recently, due to a highly increasing amount of research in the field resulting in new clinical applications. Vitamin D actually represents a family of molecules of which 25OH Vitamin D and 1,25(OH)2 Vitamin D, under their D3 and D2 forms, are the most important to date. Physical detection methods and immunoassays exist for both molecules and are being reviewed and discussed. New developments in the measurement of C3-epi-25OH Vitamin D, 24,25(OH)2 Vitamin D, and free/bioavailable 25OH Vitamin D are also presented. The future of Vitamin D testing is considered based on the evolution of laboratories and based on the scientific research that is currently performed.
This chapter was originally published in the book Advances in Clinical Chemistry, Vol. 78 edited by Gregory S. Makowski and published by Elsevier.www.sciencedirect.com/science/article/pii/S0065242316300531
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New NGS sequencing approach of paired diagnostic and remission samples to detect somatic mitochondrial DNA mutations in leukemia
, /in Featured Articles /by 3wmediaMitochondrial DNA mutations (mtDNA) have been described that are associated with leukemia. To identify somatic mutations it is necessary to have a control tissue from the same individual for comparison. In this review we describe a new next-generation sequencing approach to identify leukemia-associated mtDNA mutations by using remission samples as control.
by Dr Ilaria Stefania Pagani
Introduction
The identification of acquired somatic mutations in leukemic samples is of considerable importance for diagnosis and prognostication. In order to identify somatic mutations it is necessary to have a control tissue from the same individual for comparison. Non-hematopoietic tissues, such as mesenchymal stromal cells (MSCs) or hair follicles are preferred, but not always available. When patients with leukemia achieve remission, the remission peripheral blood (PB) may be a suitable and easily available control tissue. This article will provide recommendations for the identification of tumour-associated mtDNA somatic mutations, highlighting advantages and disadvantages of the method.
mtDNA characteristics
Human mitochondrial (mt) DNA is a 16 569 bp double-stranded, circular DNA molecule that encodes 13 polypeptides of the oxidative phosphorylation system (OXPHOS), 22 transfer RNAs and 2 ribosomal RNAs. Several important differences between the mt genome and the nuclear genome complicate the study of mtDNA mutations. Ninety-three percent of the sequence consists of coding DNA, introns are absent, the only non-coding region is at the level of the D-loop containing the promoters of the genes and it is maternally inherited. Each cell has a variable number of mitochondria (typically several hundred) and each mitochondrion contains a variable number of genomes (typically 2–10). Consequently, mtDNA mutations do not follow the pattern of a diploid genome: rather, a cell may have a single mt genotype (homoplasmy) or multiple mt genotypes (heteroplasmy). Heteroplasmy may be at any frequency, could vary between cells and many variants will be below the limit of detection of Sanger sequencing, and therefore technically difficult to validate [1]. To date, more than 400 mtDNA mutations have been associated with human diseases, most of them being heteroplasmic. Therefore, an accurate determination of the level of heteroplasmy is important for disease association studies [2].
mtDNA mutations and cancer
MtDNA mutations may potentially contribute to a cell to becoming cancerous, leading to invasion and metastasis [3]. Heteroplasmic somatic mtDNA mutations have been reported in hematological neoplasms, including myelodysplastic syndromes, chronic lymphocytic leukemia, chronic myeloid leukemia (CML), acute myeloid leukemia, and acute lymphoblastic leukemia (ALL) [1]. Many cancer types, including leukemia, have a tendency to be highly glycolytic, increasing the production of the reactive oxygen species (ROS), that lead to genomic instability. The mtDNA genome is susceptible to ROS-induced mutations owing to the high oxidative stress in the mitochondrion and limited DNA-repair mechanisms [3]. The identification of acquired somatic mutations in leukemic samples is of considerable importance for diagnosis and prognostication. In a study in acute myeloid leukemia, for example, patients with mutated NADH dehydrogenase subunit 4 (ND4) showed greater overall survival than patients with wild-type ND4 [4].
mtDNA somatic mutations: the problem of control tissue
MtDNA acquires somatic mutations at a rate 10-fold higher than nuclear DNA, so mtDNA single nucleotide variants (SNVs) accumulate with age, and may be tissue-specific [5]. This means that there is no absolutely reliable source of ‘germline’ mtDNA, especially in older individuals [1]. Somatic mutations must be distinguished from non-pathogenic germline variants by comparison with a control tissue sample. Non-hematopoietic tissues, such as buccal cells, hair follicles or MSCs are preferred, but not always available. PB cells from a post-treatment remission sample may be used as alternative. This method is widely used for nuclear mutations, but less commonly for mt mutations [1]. Blood samples are readily accessible from leukemia patients who achieve morphological remission after treatment. Therefore, a method for the detection of leukemia-associated mtDNA mutations based on comparison with a remission sample may be useful.
A new approach to identify mtDNA somatic mutations at diagnosis by using remission samples as control tissue
Pagani IS and colleagues developed a next-generation sequencing (NGS) approach for the identification of leukemia-associated mtDNA mutations using samples from CML patients at diagnosis and in remission following treatment with tyrosine kinase inhibitors (TKIs) [1]. This approach could also be applied to both hematopoietic and non-hematopoietic cancers, such as epithelial tumours, in which a tumour biopsy specimen can be compared with the normal mucosa.
Twenty-six chronic phase CML patients enrolled in the Australasian Leukaemia and Lymphoma Group CML9 trial (TIDEL-II; ID: ACTRN12607000325404) [6] took part in the study [6]. PB samples from leucocytes at diagnosis before commencing TKI treatment, and remission after 12 months of therapy were compared. Hair follicles (n=4), bone marrow MSCs (n=18), or both (n=4) were used as non-hematopoietic control samples. The comparison of a diagnostic sample with a non-hematopoietic control tissue is the standard method to identify somatic mutations in leukemia [1]. The concordance between this classic method and the diagnosis versus remission approach has been investigated.
NGS assay for the mt genome
The workflow chart is represented in Figure 1. Briefly the genomic DNA (comprising a mixture of nuclear and mtDNA) was extracted by a phenol/chloroform method from PB leukocytes and non-hematopoietic tissues. The mtDNA was amplified by long-range PCR, generating two or three overlapping fragments covering the entire mt genome. The PCR amplicons were then pooled at equimolar concentrations and sequencing libraries were prepared using the Nextera XT kit (Illumina). Indexed libraries were multiplexed and run on an Illumina MiSeq instrument using the 600 cycle MiSeq Reagent kit (v3) generating 300-bp paired-end reads [1].
Somatic mutation calling from high-throughput sequencing datasets and validation
The majority of the variant-calling methods in use are based on low-coverage human re-sequencing data and diploid calls with discrete frequencies of interest (0%, 50% or 100%) [7, 8]; however, these assumptions do not apply to mtDNA. The LoFreq software (loFreq-star version 2.11, genome Institute of Singapore; http://csb5.github.io/lofreq/) was chosen because it was developed for viral and bacterial genomes as well as diploid data, and because of its ability to automate comparison with a matched control tissue for the detection of somatic mutations [8]. The revised Cambridge Reference Sequence (rCRS) for the human mt genome (NC_012920) was used as reference sequence to identify SNVs. Tumour tissue (test) and control were then compared to identify somatic mutations specific only for the tumour tissue. Variants in common between the test and the control sample were considered to represent germline polymorphisms or mutations and were filtered out by the software. A binomial test was applied to the remaining variants to determine whether an apparent difference between samples could be due to inadequate read coverage in the control. Variants passing the binomial test were retained in the final list of putative somatic mutations (Fig. 2a) [8]. The identified mutations should be considered putative and, in common with most other NGS strategies for the discovery of novel mutations, any specific mutation of clinical interest would need to be confirmed using an independent method, as Sanger sequencing (limit of detection 20%), Sequenom MassArray, digital array (Fluidigm) or another NGS platform.
NGS: error rate, false positives and threshold
Before the application of NGS technologies, no evidence of heteroplasmy was detected, probably because of the lower sensitivity of earlier techniques [9]. NGS technologies enable the inquiry of mt heteroplasmy at the genome-wide scale with much higher resolution because many independent reads are generated for each position [2]. However, the higher error rate associated with the more sensitive NGS methodology must be taken into consideration to avoid false detection of heteroplasmy. Short-read sequencing technologies (like in Illumina systems) have a high intrinsic error rate (approximately 1 in 102–103 bases) when applied at the very high depth required to detect and measure low-level heteroplasmy. Thus, appropriate criteria for avoiding false positives due to sequencing errors are required. The most obvious way to distinguish between sequencing errors and heteroplasmy is to invoke a threshold. Two duplicate sequencing run, of which one was ultra-deep (validation run), were compared to determine sensitivity (proportion of true positives that are correctly identified as such) and specificity (proportion of true negatives that are correctly identified as such). An empirical threshold of 2% was therefore applied to distinguish true variants from sequencing errors. Variants with a variant allele fraction (VAF, the variant allele’s read depth divided by total read depth at each nucleotide position) between 2 and 98% where then considered as heteroplasmic, and variants with a VAF >2% were called homoplasmic [1]. This threshold could be refined by an iterative process in which a different threshold is identified for each nucleotide position [10], as some variation in error rate was observed. The incorporation of molecular barcodes in the initial long-range PCR would also reduce the risk of false-positive mutations due to PCR artefact [1].
Remission samples as control tissue in the identification of the mtDNA somatic mutations at diagnosis
In the four patients who had both MSC and hair follicle DNA available as control tissue, the same mutations at diagnosis have been identified, therefore the results using the non-hematopoietic tissues as control were combined. Remission samples were then used as control tissue to determine mtDNA somatic mutations at diagnosis, and the concordance between this method and the conventional diagnosis versus the MSC/hair follicle approach was examined. Seventy-three somatic mutations (81%) were identified in common, 11 mutations (12%) were identified only in comparison with the non-hematopoietic control, and six (6.7%) only by comparison with remission samples (Fig. 2b) [1]. Divergent results occurred as the result of differences in read quality or depth at a specific nucleotide not reaching statistical significance in the algorithm. False-negative results could be encountered using remission samples as the control tissue, because of low-level heteroplasmic mutations in the control sample that would lead to the same mutation at diagnosis being removed through filtering.
Concluding remarks
Remission samples can be used as control tissues to detect candidate mtDNA somatic mutations in leukemic samples when non-hematopoietic tissues are not available. The presence of mutations at low VAF in the remission samples in common with the diagnosis tissue, could be filtered out by the LoFreq software leading to false-negative results. Therefore visual inspection of the unfiltered variants is recommended.
References
1. Pagani IS, Kok CH, Saunders VA, van der Hoek MB, Heatley SL, Schwarer AP, Hahn CN, Hughes TP, White DL, Ross DM. A method for next-generation sequencing of paired diagnostic and remission samples to detect mitochondrial DNA mutations associated with leukemia. J Mol Diagn 2017; 19(5): 711–721.
2. Li M, Schonberg A, Schaefer M, Schroeder R, Nasidze I, Stoneking M. Detecting heteroplasmy from high-throughput sequencing of complete human mitochondrial DNA genomes. Am J Hum Genet 2010; 87(2): 237–249.
3. van Gisbergen MW, Voets AM, Starmans MH, de Coo IF, Yadak R, Hoffmann RF, Boutros PC, Smeets HJ, Dubois L, Lambin P. How do changes in the mtDNA and mitochondrial dysfunction influence cancer and cancer therapy? Challenges, opportunities and models. Mutat Res Rev Mutat Res 2015; 764: 16–30.
4. Damm F, Bunke T, Thol F, Markus B, Wagner K, Gohring G, Schlegelberger B, Heil G, Reuter CW, et al. Prognostic implications and molecular associations of NADH dehydrogenase subunit 4 (ND4) mutations in acute myeloid leukemia. Leukemia 2012; 26(2): 289–295.
5. Gattermann N. Mitochondrial DNA mutations in the hematopoietic system. Leukemia 2004; 18(1): 18–22.
6. Yeung DT, Osborn MP, White DL, Branford S, Braley J, Herschtal A, Kornhauser M, Issa S, Hiwase DK, et al. TIDEL-II: first-line use of imatinib in CML with early switch to nilotinib for failure to achieve time-dependent molecular targets. Blood 2015; 125(6): 915–923.
7. Meldrum C, Doyle MA, Tothill RW. Next-generation sequencing for cancer diagnostics: a practical perspective. Clin Biochem Rev 2011; 32(4): 177–195.
8. Wilm A, Aw PP, Bertrand D, Yeo GH, Ong SH, Wong CH, Chiea CK, Rosemary P, Martin LH, Niranjan N. LoFreq: a sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets. Nucleic Acids Res 2012; 40(22): 11189–11201.
9. Chatterjee A, Dasgupta S, Sidransky D. Mitochondrial subversion in cancer. Cancer Prev Res 2011; 4(5): 638–654.
10. Kerpedjiev P, Frellsen J, Lindgreen S, Krogh A. Adaptable probabilistic mapping of short reads using position specific scoring matrices. BMC Bioinformatics 2014; 15: 100.
The author
Ilaria Stefania Pagani1,2 PhD
1Cancer Theme, South Australian Health & Medical Research Institute, Adelaide, Australia
2School of Medicine, Faculty of Health Sciences, University of Adelaide, Adelaide, Australia
*Corresponding author
E-mail: Ilaria.pagani@sahmri.com
Direct detection and differentiation of dermatomycosis pathogens by DNA microarray
, /in Featured Articles /by 3wmediaDermatomycoses are extremely widespread, and are characteristically long-lasting, recurring and very difficult to cure. Early and accurate identification of the causative agent is essential for targeted therapy. A new DNA microarray provides direct detection and differentiation of the most important dermatomycosis pathogens in one reaction. The assay simultaneously detects up to 50 dermatophyte species, and provides species identification for 23 of these, as well as 6 yeasts and moulds. The microarray analysis aids differential diagnosis of dermatomycoses from other dermatoses (e.g. psoriasis), and specifically identifies mixed infections with yeasts and moulds. The dermatomycosis microarray is part of the established EUROArray platform, which also includes microarrays for multiplex identification of sexually transmitted infections (STI) and complete detection and typing of human papillomaviruses (HPV).
by Dr Jacqueline Gosink
Dermatomycosis
Dermatomycoses are infections of the skin, hair and nails which are typically caused by dermatophytes and in rarer cases by yeasts and moulds. Fungal infections of the skin are the most frequently occurring infectious diseases globally with high and growing relapse rates. Elderly people and immunocompromised patients are especially at risk. Worldwide, around 20 to 25% of the population is affected by fungal skin diseases.
Infections which are caused exclusively by dermatophytes are referred to as dermatophytoses or tinea. Tinea pedis, which occurs on the soles of the feet and between the toes, is one of the most frequent forms worldwide, followed by tinea unguium, which affects the nails, and tinea corporis, which affects the neck, back or trunk. Further forms, for example, on the face, legs, beard area, arms and hands, are rarer. Nail infections caused by dermatophytes and/or yeasts/moulds are called onychomycoses. They are typically accompanied by deformation of the nail.
Pathogens of dermatomycosis
Dermatophytes encompass fungi of the genera Trichophyton, Epidermophyton, Nannizzia, Paraphyton, Lophophyton, Microsporum and Arthroderma. Individual species are classified as anthropophilic, zoophilic or geophilic according to their main occurrence. Human pathogenic yeasts and moulds include Candida spp., Scopulariopsis brevicaulis, Fusarium spp. and Aspergillus fumigatus.
Around 70% of human dermatophyte infections are caused by anthropophilic species. Trichophyton rubrum, in particular, is the most frequent cause of fungal skin infections worldwide. Infections can spread easily to other areas of the body or to other persons, for example, via showers, bathtubs or floors. Zoophilic dermatophytes are transmitted to humans by close contact with animals, especially pets, which are often asymptomatic. They can cause severe inflammatory reactions in humans. Geophilic dermatophytes cause disease less frequently in humans. Infections typically occur in gardeners and farm workers or children who play outside. Moulds and yeasts often cause opportunistic infections, benefitting from damage to the skin or nail caused by an existing dermatophyte infection. In immunocompromised individuals, local fungal infections may develop into systemic mycosis.
Clinical picture
Dermatomycoses are clinically heterogeneous and cannot always be differentiated from other dermatoses, such as eczema, psoriasis, erysipelas, or autoimmune diseases such as Lichen ruber planus. Furthermore, 5 to 15% of onychomycosis cases comprise mixed infections of dermatophytes with yeasts and moulds. Simultaneous bacterial infection of the damaged skin, pretreatment with corticosteroid-containing preparations, or secondary contact allergy can also hinder diagnosis.
Dermatomycoses must always be treated. This is generally undertaken using various topical antifungal drugs, with severe cases sometimes requiring oral medication. Each drug has a limited activity spectrum. Positive pathogen identification prior to treatment enables targeted selection of the most suitable drug and optimal planning of the oftentimes lengthy therapy. In multiple infections, a change of the primary pathogenic agent may occur during the therapy and it may seem like the therapy is failing. This must be taken into account in the treatment of fungal infections of the nails, which may only yield first success after months. Identification of the causative pathogen also helps to determine the source of the infection. In the case of zoophilic pathogens, for example, this is usually a pet.
Laboratory diagnostics
Laboratory diagnostic methods for identifying dermatomycosis pathogens include microscopic detection and an attempt at culturing from clinical material. Successful culture in most cases enables species assignment based on micro- and macromorphological presentation of the fungus. Culturing is, however, time-consuming and is not possible for all dermatophytes. In mixed infections, false diagnoses may occur since slowly growing species may be overgrown or overlooked. Furthermore, antifungal therapy started before the sampling can hinder the culture.
Direct detection of pathogen genomic material by DNA microarray enables secure and accurate identification of the causative agent. Microarray analysis offers a significant time advantage over detection by culturing, and is especially useful for detecting dermatophytes that are difficult to cultivate. It provides higher sensitivity and specificity, even in patients already undergoing treatment. The EUROArray Dermatomycosis analysis includes a universal dermatophyte detection encompassing 50 species of the genera Trichophyton, Epidermophyton, Microsporum, Nannizzia, Arthoderma, Lophophyton, as well as species identification for the 23 dermatophyte and 6 yeast and mould species listed in Table 1.
EUROArray procedure
The EUROArray procedure (Figure 1) is performed on DNA samples isolated from skin scales, nail shavings or hair stubs. Defined gene sections of the pathogens are first amplified by multiplex polymerase chain reaction (PCR). The fluorescently labelled PCR products are then incubated with biochip microarray slides containing immobilized complementary probes. Specific binding (hybridization) of the PCR products to their corresponding oligonucleotide probes is detected using a special microarray scanner. The signals are evaluated and interpreted automatically by the EUROArrayScan software (Figure 2). A detailed result report is produced for each patient and all data are documented and archived. Meticulously designed primers and probes, ready-to-use PCR components and integrated controls all contribute to the reliability of the analysis. The entire EUROArray procedure from sample arrival to report release is IVD-validated and CE-registered, supporting quality management in diagnostic laboratories.
Specifications and evaluation
The lower detection limit of the test system depends on the pathogen and lies between 50 and 600 DNA copies per reaction, in individual cases also higher. Evaluation studies verified that template DNA in concentrations ranging from the lower detection limit to 50 ng can be used in the PCR without generating any false positive results. Furthermore, potential cross reactivity with 37 microorganisms of the resident and transient skin flora was excluded experimentally.
In an evaluation study with 409 clinical samples, the EUROArray Dermatomycosis yielded a good agreement with the precharacterization. In many cases additional pathogens that were not included in the precharacterization were detected. The additional findings were confirmed by further independent tests or sequencing. Thus, the microarray provides reliable results and broad detection capabilities.
STI detection
The EUROArray STI is based on the same technology and provides parallel direct detection of the pathogenic agents of eleven sexually transmitted infections (STIs) in one reaction, namely Chlamydia trachomatis, Neisseria gonorrhoea, Mycoplasma genitalium, Mycoplasma hominis, Ureaplasma urealyticum, Ureaplasma parvum, Haemophilus ducreyi, Treponema pallidum, Trichomonas vaginalis and herpes simplex viruses 1 and 2.
STIs are often asymptomatic, but can nevertheless lead to serious sequelae, for example infertility, fetal damage during pregnancy, and severe postnatal infections in newborns. The PCR-based detection allows identification of both manifest and silent infections, and is thus suitable for diagnosis of symptomatic patients as well as for general screening. It offers a huge time advantage over cultivation and is especially useful for detecting sexually transmitted pathogens that are difficult or impossible to cultivate, e.g. C. trachomatis, Mycoplasma, Ureaplasma, T. pallidum. Due to amplification of the pathogen DNA, infections with a reduced pathogen number can also be reliably detected. A broad screening for STI pathogens is particularly important in asymptomatic or clinically ambiguous cases and for detecting multiple infections, which are often missed during single-parameter testing.
HPV detection and typing
The EUROArray HPV provides detection and typing of all 30 genitally relevant HPV subtypes in one test. HPV are involved in the development of cervical carcinoma, and HPV testing plays a central role in risk assessment and early diagnosis of this cancer. In contrast to Pap examinations, HPV detection is not dependent on subjective evaluation and it offers very high sensitivity even in the early stages of infection.
The EUROArray HPV is based on detection of the viral oncogenes E6 and E7, which provides the highest possible sensitivity. Using an extensive panel of specific primers and probes, the EUROArray detects and distinguishes between 18 high-risk subtypes that may trigger cancer (16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 73, 82) and 12 low-risk subtypes that cause benign genital warts (6, 11, 40, 42, 43, 44, 54, 61, 70, 72, 81, 89). Multiple infections are reliably identified, and primary and persistent infections can be differentiated. A positive result for a high-risk subtype indicates an increased risk for cervical carcinoma, which can then be minimised by more frequent follow-up examinations to detect morphological cell changes at an early stage. Based on the recommendations of the respective professional societies, HPV-negative women can forgo subsequent HPV tests and Pap smears for a longer time interval.
Conclusions
Molecular diagnostic tests such as the EUROArray are an important tool for identifying the precise pathogenic agent in various infectious diseases, supporting decision-making on specific treatment. The new EUROArray Dermatomycosis provides the most comprehensive direct detection of dermatomycosis pathogens currently available commercially, and complements existing assays for STI and HPV. The EUROArray procedure is easy to perform and does not require extensive expertise in molecular biology. Moreover, the fully automated evaluation ensures objective, accurate and reproducible results. Further infectious disease microarrays based on the same technology are in development.
The author
Jacqueline Gosink, PhD
EUROIMMUN AG, Seekamp 31,
23560 Luebeck, Germany
www.euroimmun.com
Direct HbA1c testing capabilities on the RX series range of clinical chemistry analysers
, /in Featured Articles /by 3wmediaThe global prevalence of diabetes mellitus is increasing rapidly; affecting 8.8% of the population. The Randox automated immunoturbidimetric HbA1c test offers an improved method for the rapid direct measurement of HbA1c in human blood; which is available for use on the RX modena, RX imola and the RX daytona+.
Introduction to the RX series
The RX series combines robust hardware and intuitive software with a world leading test menu comprising of routine chemistries, specific proteins, lipids, therapeutic drugs, drugs of abuse, antioxidants and diabetes testing and a range of niche tests including the HbA1c assay. The RX series removes the need for a separate HbA1c analyser and allows laboratories to expand their testing capabilities onto one single platform, providing cost savings through consolidation. Built on three core values- reliability, accuracy and precision, the RX series reduces costly test re-runs and misdiagnosis, offering complete confidence in results. The RX series range of clinical chemistry analysers includes the RX misano, (semi-automated) RX monaco, RX daytona+, RX imola and RX modena.
Background
Diabetes is a global epidemic that affects approximately 271 million people around the world and according to the International Diabetes Federation; it is a figure that is on the rise. Their calculations forecast that diabetes will affect roughly 552 million by the year 2030, highlighting the fundamental need to manage patients with diabetes. The USA is one of the most prominent countries affected by diabetes when analysing its prevalence worldwide. It affects roughly 24 million Americans which is a stark contrast to the UK where around 3.5 million people have been diagnosed. It is also important to note that serious health complications can result from diabetes over time which reinforces the need to test HbA1c levels to evaluate how well diabetes is being controlled. The longer you have diabetes, the higher the risk of complications. These can include cardiovascular disease, nerve damage and kidney damage; including end-stage kidney disease which can require dialysis or a kidney transplant. With the rising figures and growing list of complications associated with the disease, diabetes remains one of the leading causes of death in the world and the seventh leading cause of death in the US.
HbA1c explained further
HbA1c, also known as hemoglobin A1c or glycated hemoglobin, is an important blood test that is able to determine how well diabetes is being controlled. It develops when hemoglobin, a protein within red blood cells that carries oxygen throughout the body, joins with glucose in the blood, becoming ‘glycated’. As glycation is irreversible, HbA1c remains in the same state in the red blood cell for 8-12 weeks; giving an overall picture of what the average blood sugar level is. This is particularly important as it allows clinicians to monitor the ‘glycemic’ control in individuals with diabetes.
What is the HbA1c assay used for?
The concentration of HbA1c in the blood of diabetic patients increases with rising blood glucose levels and is representative of the mean blood glucose level over the preceding six to eight weeks. HbA1c can therefore be described as a long term indicator of diabetic control unlike blood glucose which is only a short term indicator of diabetic control. It is recommended that HbA1c levels are monitored every three to four months. In patients who have recently changed their therapy or in those who have gestational diabetes it may be beneficial to measure HbA1c levels more frequently, at two to four week intervals. The onset of diabetes, particularly type two diabetes, tends to be gradual and thus proves difficult to diagnose early. With HbA1c clinicians are able to monitor blood glucose levels periodically to deliver accurate and quick results that can improve patient care.
The clinical significance of HbA1c
The measurement of HbA1c is used in the long term monitoring of diabetes mellitus. This assay should not be used in the diagnosis of diabetes mellitus or for day to day glucose monitoring. Diabetes mellitus is a disease associated with poor glycemic control. Numerous clinical studies, including the Diabetes Control and Complications Trial, have shown that diabetes-related complications may be reduced by the long term monitoring and tight control of blood glucose levels. In the diabetic patient where blood glucose levels are abnormally elevated the level of HbA1c also increases, the reason for this is that HbA1c is formed by the non-enzymatic glycation of the N-terminus of the ß-chain of hemoglobin A0.
Randox HbA1c assay features:
Advantages of the RX series clinical chemistry analysers for direct HbA1c testing:
Key benefits of using the RX series clinical chemistry analysers and Randox HbA1c assay
Direct HbA1c testing eliminates the need for the sample incubation step which is required on alternative methods; allowing samples to be to run immediately on the RX series and providing faster and more accurate results when they are needed. The removal of the offline preparation stage increases the recovery times, allowing laboratories to enhance their workflow and also consolidate testing onto one single clinical chemistry platform. Additional benefits of using the RX series in conjunction with the Randox HbA1c assay include having one assay instead of two, which enables quicker calibration; saving the user time and making the overall method simple and quick to perform, setting a new standard in HbA1c determination and patient care.
For further information or for a quotation for the HbA1c test or to enquire about any analyser in the RX series range, please contact marketing@randox.com.
Randox Laboratories Ltd
55 Diamond Rd
Crumlin, Co. Antrim BT29 4QY
UK
www.randox.com
Chapter Two – Vitamin D Testing—Where Are We and What Is on the Horizon?
, /in Featured Articles /by 3wmediaby Nicolas Heureux (DIASource Immunoassays, Louvain-La-Neuve, Belgium)
Vitamin D testing is part of laboratory practice since more than 30 years but has become a routine parameter only recently, due to a highly increasing amount of research in the field resulting in new clinical applications. Vitamin D actually represents a family of molecules of which 25OH Vitamin D and 1,25(OH)2 Vitamin D, under their D3 and D2 forms, are the most important to date. Physical detection methods and immunoassays exist for both molecules and are being reviewed and discussed. New developments in the measurement of C3-epi-25OH Vitamin D, 24,25(OH)2 Vitamin D, and free/bioavailable 25OH Vitamin D are also presented. The future of Vitamin D testing is considered based on the evolution of laboratories and based on the scientific research that is currently performed.
This chapter was originally published in the book Advances in Clinical Chemistry, Vol. 78 edited by Gregory S. Makowski and published by Elsevier.www.sciencedirect.com/science/article/pii/S0065242316300531
Nova StatStrip® Reduces Glucose Meter Related Patient Deaths and Adverse Events by 98%
, /in Featured Articles /by 3wmediaSuspicion of Venous Thromboembolism
, /in Featured Articles /by 3wmediaLiquid, ready-to-use assays
, /in Featured Articles /by 3wmediaThe accuracy of LC-MS/MS technology with the convenience of automation
, /in Featured Articles /by 3wmediaThe new nSMOL Antibody Bioanalysis Kit
, /in Featured Articles /by 3wmediarx series – Excellence In Clinical Chemistry Testing
, /in Featured Articles /by 3wmedia