Niguarda Hospital in Milan is one of Italy’s leading general hospitals, and provides an extensive range of medical disciplines for adults and children throughout the Lombardy region and beyond.
Our hospital’s Department of Laboratory Medicine aim is to offer a complete, continuous and prompt diagnostic laboratory testing service, in order to guarantee effective support for this widespread clinical demand, and is committed to research into automation and analysis to ensure this is maintained. Our busy Molecular Biology Laboratory performed an estimated 40,000 tests in 2015, which is approximately 10% increase on the previous year.
The growing annual molecular workload is attributed, in part, to the development of new therapeutic strategies. Our staff, consisting of 8 laboratory technicians, one director and one manager, work 5 days per week and are expected to cope with increased workloads and demands for reduced turnaround times without any increase in resources, in terms of the number of staff and costs.
A large proportion of the molecular biology workload consists of viral load measurements for human immunodeficiency virus type 1 (HIV-1), hepatitis C virus (HCV), hepatitis B virus (HBV) and cytomegalovirus (CMV) (figure 1).
With a very important Italian transplant centre located at Niguarda Hospital, CMV analyses are vital and results are needed quickly, without delay. In addition, the laboratory performs viral load measurements for HIV-1, HCV, and HBV in order to evaluate and monitor therapeutic response. In these instances, rapid results are extremely important for patient management decisions, for example to maintain or change treatment.
Since 2005, these measurements have been performed using our laboratory’s current method, which has separate sample preparation and amplification/detection platforms. These are situated on separate benches within the same room, with one sample preparation system in another room. The accuracy and precision of this method is good, however, in order to be cost effective, it is necessary to optimize the size of the batches. Since they can’t be processed in the same day, sample test tubes often need to be collected and stored for several days, which increases the turnaround time considerably. In addition, this method involves many manual steps, which demand time, space and coordination of work between different members of staff.
A new automated molecular diagnostics method
As part of our Department of Laboratory Medicine’s investigations into increased automation in the laboratory, Niguarda Hospital became a beta trial site for the new DxN VERIS Molecular Diagnostics System (Beckman Coulter), which consolidates DNA extraction, nucleic acid amplification, quantification and detection onto a single automated instrument for a number of molecular targets, including HIV-1, HCV, HBV and CMV.
The first step in assessing the DxN VERIS was to validate the assays in order to determine whether their performance is comparable with our laboratory’s existing method. Daily quality control measurements demonstrated good performance of the VERIS HBV assay for high level, low level and negative HBV samples (table 1). This assay was also shown to have excellent linearity within the range of 1.68 – 8.82 Log IU/mL, a limit of detection of 6.82 IU/mL, and good precision, achieving within run and between run mean standard deviations of less than 0.16 (table 2).
A series of performance evaluation studies, conducted in several laboratories around the world, have demonstrated that the VERIS HBV, HCV, HIV-1 and CMV assays have comparable precision, sensitivity and linearity to a range of alternative, commercially available viral load methods [1-13]. In accordance with these findings, the VERIS HBV assay correlated well with the existing method at Niguarda Hospital (Abbott m2000) and, indeed, detected HBV DNA in 23 samples that were negative using the current method, 22 of which were found to be positive by one or more serology assay (table 3). Regarding the 55 specimens that were quantified both with DxN VERIS and Abbott m2000, 7 of them had an HBV DNA concentration discordant for more than 1 Log.
Comparable performance, including sensitivity and specificity, was achieved for each of the DxN VERIS assays: HIV-1, HCV, HBV and CMV.
Workflow improvements
In addition to validating the performance of the VERIS assays, a time/workflow analysis study was performed at Niguarda Hospital by Nexus Global Solutions (Plano, Texas, USA). The study compared workflows and time to results between the current viral load method for HIV-1, HCV, HBV and CMV (Abbott m2000sp and m2000rt systems) and the new DxN VERIS Molecular Diagnostic System.
By reducing manual intervention and automating processes from sample loading to reporting of results, the DxN VERIS offers the potential to transform clinical laboratory workflows. Each assay is supplied in a unique, single cartridge system, and all consumables and reagents are stored on board the system, which cuts preparation time compared to alternative methods. In addition, unlike traditional plate-based systems, there is no need to batch assays. The DxN VERIS allows true, single sample random access, which means that viral load assays can be performed as soon as they arrive in the laboratory. This, combined with short assay runtimes, ensures rapid turnaround of results and, since there are no empty plate wells, wastage and consumable costs are reduced.
The comparative time/workflow analysis in our study revealed that DxN VERIS involved only 10 steps and required just five reagents, compared to 26 steps and over 20 consumables for the current method, and required much less hands-on time for each of the viral load assays (figure 2). Notably, by consolidating the assay menu, time savings of up to 2 hours could be achieved.
In addition to an increase in productivity (achieving more results in an 8-hour working day), the time to the first result for the DxN VERIS was greatly reduced compared to the current method, with subsequent results available every 2.5 minutes. This is in contrast to the current method, where results are not available until the end of the assay run (table 4).
With these time savings, and by eliminating the need to batch samples, the DxN VERIS allowed much faster turnaround of results in a normal working week, with all results being reported within 8 hours of receipt, unlike the current method, which often required several days (figure 3).
The true single sample random access capability of the DxN VERIS has the potential to simplify sample management in the laboratory and to make the organization of viral load assays more fluid. It increases productivity by allowing the continuous loading of samples for different assays, eliminating the need for batching and reducing turnaround times. This is the most important advantage of random access testing for us because it increases the availability of medical reports to the different departments and is a great benefit to patient management and care by allowing more timely clinical decisions.
The DxN VERIS is easy to use with its few consumables, reduced maintenance requirements, complete automation and intuitive computer interface. By improving laboratory organization and workflows and reducing manual intervention, viral loads (which account for about 50% of the molecular workload) could be completed in a single day using the DxN VERIS. Requiring fewer people to be dedicated to this purpose, this makes it possible to accomplish more work with the same number of staff.
For further information about the DxN VERIS Molecular Diagnostic System and the VERIS assays currently available, please contact: Tiffany Page, Senior Pan European Marketing Manager Molecular Diagnostics, Email: info@beckmanmolecular.com or visit www.beckmancoulter.com/moleculardiagnostics
References
1. Williams, JA, Rodriguez, J, Wang, Z et al (2014) Poster presentation, ESCV, Prague.
2. Drago, M, Franchetti, E, Fanti, D and Gesu, GP (2015) Poster presentation, EuroMedLab, Paris.
3. Zurita, S, Gutiérrez, F, Folgueira, MD et al (2015) Poster presentation, EuroMedLab, Paris.
4. Christenson, R, Maggert, K, Ruiz, RM et al (2015) Poster presentation, ECCMID, Copenhagen.
5. Trimoulet, P, Tauzin, B, Belloc, E et al (2015) Poster presentation, EuroMedLab, Paris.
6. Gilfillan, R, Wang, Z, Xu, Y et al (2014) Poster presentation, ECCMID, Barcelona.
7. Xu, Y, Gilfillan, R, Wang, Z et al (2014) Poster presentation, ESCV, Prague.
8. Mengelle, C, Sauné, K, Haslé, C et al (2014) Poster presentation, RICAI.
9. Mengelle, C, Sauné, K, Haslé, C et al (2015) Poster presentation, ECCMID, Copenhagen.
10. Silvestro, A, Duan, H, Lim, S et al (2014) Poster presentation, ECCMID, Barcelona.
11. Li, Q, Williams, J, Maggert, K et al (2014) Poster presentation, ECCMID, Barcelona.
12. Xu, Y, Dineen, S, Annese, V et al (2014) Poster presentation, ESCV, Prague.
13. Williams, JA, Rodriguez, J, Wang, Z et al (2014) Poster presentation, ECCMID, Barcelona.
The author
Diana Fanti, Molecular Biology Laboratory Manager
Department of Laboratory Medicine, Niguarda Hospital,
Milan, Italy
Biochemical markers of alcohol intake can be separated into two categories: direct markers of ethanol metabolism and indirect markers. The different alcohol markers have varying time windows of detection and are a useful additional tool to detect alcohol intake in alcohol-dependent clients.
by Jane Armer and Rebecca Allcock
Introduction
Alcohol dependence is characterized by craving, tolerance, a preoccupation with alcohol and continued drinking in spite of harmful consequences. The World Health Organization Alcohol Use Disorders Identification Test (AUDIT) is recommended for the identification of individuals that are dependent on alcohol [1]. The prevalence of alcohol use disorders (including dependence and harmful use of alcohol) is 11.1% in the UK compared to 7.5% across Europe [2]. In England, 250 000 people are believed to be moderately or severely dependent and require intensive treatment [3].
Alcohol use is the third leading risk factor contributing to the global burden of disease after high blood pressure and tobacco smoking [4]. In 2012, 3.3 million deaths (5.9% of all global deaths) were attributable to alcohol consumption [2]. It is estimated that the UK National Health Service (NHS) spends £3.5 billion/year in costs related to alcohol and the number of alcohol-related admissions has doubled over the last 15 years [3].
In the UK, one unit equals 10 mL or 8 g of pure alcohol, which is around the amount of alcohol the average adult can process in an hour. The latest UK recommendations are to not regularly drink more than 14 units per week (men and women) and to limit the total amount of alcohol consumed on a single occasion [5].
The most common entry into alcohol treatment services in England is either self-referral or referral by the GP [3]. Services have a limited number of options to determine if an individual in treatment for alcohol dependence is continuing to drink alcohol. They rely on self-report by the individuals in the form of alcohol diaries and breathalyser tests. There is no regular schedule for biochemical markers. If a client is found to be drinking alcohol during the treatment programme, an assessment is done of the amount of alcohol consumed, the pattern of alcohol consumption and how it will impact on their treatment. This is factored into the recovery plan and there is a re-assessment of the support and interventions needed for that client. Possible interventions include cognitive behavioural therapies, pharmacological therapies or in-patient assisted withdrawal. In 2013/14, only 38% of clients in alcohol treatment in England successfully completed their treatment [3].
Monitoring clients in alcohol treatment
Diaries that record alcohol intake are commonly used to monitor the progress of clients. However, this relies on accurate self-reporting of alcohol intake by the client and under reporting is a common problem. Biochemical markers of alcohol intake can provide a more comprehensive assessment of a client’s progress.
Direct markers of alcohol intake
Direct markers of alcohol intake include ethanol, ethyl glucuronide (EtG), ethyl sulphate (EtS), fatty acid ethyl esters (FAEE) and phosphatidylethanol (PEth).
Following the ingestion of ethanol, >95% is metabolized in the liver by alcohol dehydrogenase to acetaldehyde then by aldehyde dehydrogenase to acetic acid [14]. Less than 5% is excreted unchanged in the urine, breath and sweat. A small amount of ethanol is conjugated to form EtG and EtS (Fig. 1). Ethanol is usually only detectable in breath and urine after very recent alcohol consumption and the detection time window depends on the amount of alcohol consumed. In comparison, urine EtG and EtS remain detectable for around 24 hours after moderate alcohol intake and for up to 130 hours in subjects admitted for alcohol detoxification [6, 7]. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods have been developed for EtG and EtS. An immunoassay is also available for EtG [8, 9].
Many studies have demonstrated the benefit of measuring EtG and EtS in clients in alcohol treatment. Continued alcohol consumption can be detected by the measurement of urine EtG and EtS in clients who do not admit to consuming alcohol and provide a negative breathalyser test. This is due to the increased time window of detection for urine EtG and EtS compared to breath ethanol. This demonstrates the unreliability of self-reporting of alcohol intake and the benefit of biochemical markers to detect clients that are continuing to drink alcohol [10].
As with urine testing for drugs of abuse, it is possible for a client to consume a large volume of water to dilute the sample and produce negative EtG and EtS results. Creatinine should always be measured to check for adulteration and it may be beneficial to report EtG and EtS as creatinine ratios to overcome this problem. Further work is required to define cut-offs for EtG and EtS as creatinine ratios.
False negative EtG results can be caused by the presence of Escherichia coli in urine as glucuronidase is present with high activity in most strains. False positive EtG and EtS results have also been reported following use of ethanol based mouthwash or hand gels and after the consumption of non-alcoholic beers (up to 0.5% alcohol). Due to the risk of positive results due to unintentional alcohol exposure, particularly for urine EtG, it is important that clinical cut-offs used are clearly defined and LC-MS/MS methods that measure both EtG and EtS are preferred [11]. In the USA, the Substance Abuse and Mental Health Administration (SAMHSA) have suggested that EtG results >1.0 mg/L are consistent with alcohol intake and that results between 0.1 and 1.0 mg/L should be interpreted with caution. It is accepted that further work is required to clearly define cut-offs for EtG and EtS and that other biomarkers may be useful when interpreting borderline positive results in the range 0.10–0.50 mg/L [12].
Methods for the measurement of EtG and FAEEs in hair have been developed allowing a longer term assessment of alcohol intake. Hair analysis is most suitable for subjects where longer term abstinence needs to be demonstrated such as in patients awaiting liver transplantation. EtG cut-offs have been suggested by the Society of Hair Testing for chronic excessive alcohol consumption (30 pg/mg) and abstinence assessment (7 pg/mg). However, results may be influenced by hair products and this needs to be taken into account when interpreting results.
PEth is formed from ethanol and phosphatidylcholine in cell membranes. The reaction is catalysed by phospholipase D and occurs in the cell membranes of erythrocytes; therefore, PEth is found in the red blood cell fraction of blood rather than in serum or plasma. PEth is a group of phospholipids with varying carbon lengths and LC-MS/MS methods to detect the major forms of PEth in whole blood have been developed. A single dose of ethanol does not produce a measurable amount of PEth and it has been demonstrated that approximately 50 g of ethanol/day (6.25 UK units) is required to provide a positive PEth result. In comparison to serum carbohydrate deficient transferrin (CDT; see ‘Indirect markers of alcohol intake’ below), urine EtG and urine EtS, PEth demonstrated the highest sensitivity for regular alcohol consumption in clients in alcohol treatment and was found to be positive twice as often as CDT [13]. Further work is required to understand how PEth can be used optimally in combination with other alcohol markers in clients in treatment for alcohol dependence [14].
Indirect markers of alcohol intake
The indirect markers include mean corpuscular volume (MCV), gamma glutamyl transferase (GGT) and CDT. These markers increase following significant alcohol intake over a prolonged time period and are not useful for detecting a single alcohol ‘binge’. MCV and GGT are not specific markers of alcohol intake.
CDT refers to altered glycoforms of transferrin as a result of alcohol-induced changes in the carbohydrate composition of transferrin. The main component of serum transferrin is tetrasialotransferrin, which makes up approximately 80% of the total. Normal samples usually contain approximately 15%, 4–5%, 1–1.5% and 1% of pentasialotransferrin, trisialotransferrin, disialotransferrin and hexasialotransferrin, respectively. An alcohol consumption of at least 60 g/day (7.5 UK units) for 2 weeks is required to increase the disialotransferrin [15]. CDT may also be increased if genetic variants are present and in advanced liver disease. The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) has recently proposed a reference measurement procedure for CDT and more studies assessing the diagnostic performance of CDT to detect alcohol dependence are now needed using methods harmonized to the international reference measurement procedure.
Table 1 summarizes the time window of detection and limitations of the alcohol markers discussed.
Conclusions
Currently, the assessment of clients in alcohol treatment relies largely on self-reporting and limited biochemical testing, which makes assessment of a client’s progress challenging. There are a number of available biochemical markers that could improve the detection of alcohol use in clients with alcohol dependence and ultimately lead to initiation of early intervention and altered treatment strategies. This in turn could improve the numbers successfully completing treatment. A combination of short-term and longer term biochemical markers is likely to be the most useful approach depending on the treatment setting. The advantage of the breathalyser test over biochemical markers that require laboratory analysis is the immediate availability of the result which allows an immediate intervention for a client with a positive result. Laboratory tests need to be available in a timely manner and with appropriate and well-defined cut-offs. The clinical benefit of alcohol markers in improving the number of clients that successfully complete their treatment for alcohol dependency has not yet been demonstrated. Randomized controlled trials comparing outcomes with or without the use of biochemical markers are required.
References
1. Babor TF, Higgins-Biddle JC, Saunders JB, Monteiro MG. Alcohol use disorders identification test (AUDIT). World Health Organization, 2001. (http://www.alcohollearningcentre.org.uk/Topics/Browse/BriefAdvice/?parent=4444&child=4896)
2. Global status report on alcohol and health. World Health Organization, 2014. (http://www.who.int/substance_abuse/publications/global_alcohol_report/msb_gsr_2014_2.pdf?ua=1)
3. Alcohol Treatment England 2013–14. Public Health England, 2014. (http://www.nta.nhs.uk/uploads/adult-alcohol-statistics-2013-14-commentary.pdf )
4. Lim S, Vos T, Flaxman A, Danaei G, Shibuya K, Adair-Rohani H, Amann M, Anderson HR, Andrews KG, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380: 2224–2260.
5. UK Chief Medical Officers’ Alcohol Guidelines Review. Department of Health, 2016. (https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/489795/summary.pdf)
6. Dahl H, Stephanson N, Beck O, Helander A. Comparison of urinary excretion characteristics of ethanol and ethyl glucuronide. J Anal Toxicol. 2002; 26: 201–204.
7. Helander A, Bottcher M, Fehr C, Dahmen N, Beck A. Detection times for urinary ethyl glucuronide and ethyl sulphate in heavy drinkers during alcohol detoxification. J Anal Toxicol. 2009; 44: 55–61.
8. Politi L, Morini L, Groppi A, Poloni V, Pozzi F, Polettini A. Direct determination of the ethanol metabolites ethyl glucuronide and ethyl sulphate in urine by liquid chromatography/electrospray tandem mass spectrometry. Rapid Commun Mass Spectrom. 2005; 19: 1321–1331.
9. Bottcher M, Beck O, Helander A. Evaluation of a new immunoassay for urinary ethyl glucuronide testing. Alcohol Alcohol. 2008; 43: 46–48.
10. Junghanns K, Graf I, Pfluger J, Wetterling G, Ziems C, Ehrenthal D, Zöllner M, Dibbelt L, Backhaus J, Weinmann W, Wurst FM. Urinary ethyl glucuronide (EtG) and ethyl sulphate (EtS) assessment: valuable tools to improve verification of abstention in alcohol-dependent patients during in-patient treatment and at follow ups. Addiction 2009; 104: 921–926.
11. Wurst F, Thon N, Yegles M, Schruck A, Preuss UW, Weinmann W. Ethanol metabolites: their role in the assessment of alcohol intake. Alcohol Clin Exp Res. 2015; 39: 2060–2072.
12. The role of biomarkers in the treatment of alcohol use disorders. SAMHSA, 2012. (http://store.samhsa.gov/product/The-Role-of-Biomarkers-in-the-Treatment-of-Alcohol-Use-Disorders-2012-Revision/SMA12-4686)
13. Helander A, Peter O, Zheng Y. Monitoring of the alcohol biomarkers PEth, CDT and EtG/EtS in an outpatient treatment setting. Alcohol Alcohol. 2012; 47: 552–557.
14. Viel G, Boscalo-Berto R, Cecchetto G, Fais P, Nalesso A, Ferrara SD. Phosphatidylethanol in blood as a marker of chromic alcohol use: a systematic review and emta-analysis. Int J Mol Sci. 2012; 13: 14788–14812.
15. Stibler H. Carbohydrate Deficient Transferrin in serum: a new marker of potentially harmful alcohol consumption reviewed. Clin Chem. 1991; 37: 2029–2037.
The authors
Jane Armer*1 BA MSc FRCPath and
Rebecca Allcock2 BSc MSc FRCPath
1Department of Blood Sciences,
East Lancashire Hospitals NHS Trust,
Blackburn, UK
2Department of Clinical Biochemistry,
Lancashire Teaching Hospitals NHS
Foundation Trust, Preston, UK
*Corresponding author
E-mail: jane.armer@elht.nhs.uk
November 2025
Prins Hendrikstraat 1
5611HH Eindhoven
The Netherlands
info@clinlabint.com
PanGlobal Media is not responsible for any error or omission that might occur in the electronic display of product or company data.