Advances in circulating biomarker research have led to the use of blood samples to characterize cancer patients’ tumour DNA where a lack of tumour tissue prevents molecular testing. This is critical for non-small cell lung cancer (NSCLC) patients who require tumour molecular characterization in order to access life-extending treatments that would be denied without biopsy. Here we describe a new liquid biopsy diagnostic service for NSCLC patients at the All Wales Medical Genetics Service, Cardiff, UK.
by Dr Angharad Williams, Dr Daniel Nelmes, Helen Roberts and Dr Rachel Butler

Liquid biopsies and cell-free circulating tumour DNA (ctDNA) in clinical practice
The term ‘liquid biopsy’ comes from the sampling of a cancer patient’s tumour DNA from a simple, non-invasive blood test rather than an invasive surgical biopsy. This circulating tumour DNA (ctDNA) is a small fraction of the total cell-free circulating DNA (cfDNA) and consists of short strands of DNA shed by degrading tumour cells directly into a patient’s bloodstream. The levels of ctDNA present will vary greatly based on clinical factors such as proximity of sampling to chemotherapy or radiotherapy, as well as the burden and activity of the tumour [1].

Genetic mutations within the patient’s tumour are detectable at extremely low levels in the ctDNA in the blood [2]. The detection of such mutations provides many potential uses for ctDNA as a biomarker in disease diagnosis and screening, monitoring of therapy response and resistance and detection of minimal residual disease and relapse [3–6].

The many advantages for using ctDNA as a biomarker rest on the fact that ctDNA can be simply extracted from blood; therefore, invasive biopsy procedures can be avoided. Such simple blood sampling is beneficial if the patient is too ill for invasive surgery and is also useful if biopsy-based tumour analysis has failed; thus, unnecessary re-biopsies can be averted. Another benefit of the use of ctDNA over biopsies is that serial blood samples can be taken to replace the need for a re-biopsy to monitor a patient’s response to therapy in ‘real-time’ in the clinic. Practically, blood samples can be arranged, taken and sent for processing at a much faster pace than surgery, gaining valuable time for patients who are in need of urgent cancer-related treatments.

There are, however, potential pitfalls in using ctDNA as a diagnostic biomarker that should be considered prior to setting up a ctDNA-based diagnostic service as well as when interpreting genetic results from ctDNA (summarized in Figure 1). The greatest concern is the fragile nature of cfDNA molecules [7], which means that cfDNA will degrade in a blood sample to undetectable levels the longer that the blood is left unprocessed. Efficient centrifugation and separation of the blood to plasma and storage at −80 °C can be used to halt degradation of cfDNA. In cases where analysis of the cfDNA sample identifies no genetic mutations, this raises the important question of whether the patient was actually shedding ctDNA at the time of the blood sampling or did the ctDNA degrade prior to sample processing? This indicates the unfortunate possibility of false negative results when using ctDNA in the diagnostic setting. Another important factor to consider is that the level of a mutation in the ctDNA, which can quite often be as low as ≤1% mutated ctDNA to wild-type patient cfDNA [8]. Thus, only highly sensitive molecular analysis options should be considered for diagnostic testing strategies using ctDNA.

Molecular analysis of the epidermal growth factor receptor gene in non-small cell lung cancer patients
The epidermal growth factor receptor gene (EGFR) encodes the EGRF protein, a signalling protein that is part of the cellular pathways that control normal cell growth, differentiation and angiogenesis [9]. Approximately 10–20% of ethnically Caucasian non-small cell lung cancer (NSCLC) patients with the adenocarcinoma histological subtype will have a DNA mutation in the EGFR gene, which will activate abnormal constitutive signalling and tumorigenesis [10].

The most common sensitizing EGFR mutations, which represent 85% of known activating EGFR mutations in NSCLC, are the exon 21 point mutation c.2573T>G (p.Leu858Arg) and in-frame deletions in exon 19 [9]. These activating mutations provide a convenient target for first and second generation tyrosine kinase inhibitor (TKI) treatments such as gefitinib (Iressa®, AstraZeneca) [11–13] and act as positive predictive biomarkers for response to these drugs. Traditionally, for patients to access these TKI treatments, tumour biopsy in the form of a formalin-fixed sample is tested for evidence of these activating EGFR mutations at clinical genetic testing centres, such as the All Wales Medical Genetics Service (AWMGS) in Cardiff. However, preservation of the tumour biopsy as formalin-fixed paraffin-embedded (FFPE) tissue leads to a number of issues with genetic analysis including poor quality and yields of DNA (noted in Figure 1). Additionally, a large proportion of NSCLC patients are not well enough to have a biopsy taken and so genetic analysis of tumour DNA and subsequent access to TKI treatments is not possible. This inequity in service provision indicated a clinical need to expand current testing options for NSCLC patients to reach those patients who cannot access TKI-based stratified medicine treatment options. To address this clinical need, a ctDNA-based diagnostic NHS service was developed within AWMGS to detect activating EGFR mutations from patient blood samples in order to alleviate the need for biopsy.

In addition to the availability of first and second generation TKIs, a new third generation TKI, osimertinib (Tagrisso®, AstraZeneca), has recently been made available to a specific group of NSCLC patients. Approximately 50% of patients on first and second generation TKIs will develop an EGFR resistance mutation, c.2369C>T (p.Thr790Met) (commonly known as T790M), leading to disease progression [6]. Since October 2016, osimertinib (Tagrisso®, AstraZeneca), has been available to UK patients shown to harbour the T790M mutant in their tumour via either biopsy or ctDNA analysis through the NHS Cancer Drugs Fund [14]. CtDNA testing has become a popular method of testing for resistance mutations as it mitigates the need for a second invasive biopsy for the patient and, also, serial blood samples can be used to track the patient’s response over a period of time [15].

Establishing the ctDNA-based NSCLC stratified medicine service in the All Wales Medical Genetics Service
Since 2009, the AWMGS has been providing stratified medicine services for NSCLC patients, as well as metastatic colorectal cancer patients, melanoma and gastrointestinal stromal tumour patients in Wales. Though all of these services are based on FFPE tumour analysis, we have developed a wealth of experience in using ctDNA from blood in the field of clinical trials. By 2015, following a number of successful ctDNA-based feasibility studies by laboratory staff and research students, we were confident that we had the knowledge and expertise to bring ctDNA into service, and were one of the first laboratories in the UK to do so.

Owing to the inherent shortcomings of using ctDNA as a biomarker, discussed previously, the following questions were deliberated during validation to find the most appropriate testing methods for the diagnostic service:

• How do we best protect ctDNA in blood during sampling and shipping to the lab, to ensure that the sample that reaches us is faithful to the patient’s real mutation status?
• As important mutations in ctDNA can be at very low levels, how do we ensure we can detect a low enough range of mutations to be clinically relevant to interpretation?

To guarantee sample quality and maintain sufficient levels of ctDNA, we have imposed stringent quality measures on the blood collection and dispatch. The main requirement is that blood samples should be taken in a specialist preservative tube such as CellSave Preservative Tubes (Janssen Diagnostics) or Cell-Free DNA BCT® (Streck) and must reach the laboratory for processing within a strict 96-hour window. This was decided on after discussion with other research groups and internal investigations on the stability of ctDNA in blood and the use of preservative tubes [7].

The sensitivity of the molecular ctDNA assay was paramount in our decision to use the recently developed technology droplet digital polymerase chain reaction (ddPCR) by Bio-Rad (Bio-Rad Laboratories, Inc, California, USA). ddPCR is a highly sensitive fluorescence-based PCR method with an extreme lower limit of detection of 0.0001% of mutant DNA in a wild-type background, which makes it the superior choice over other technologies such as next-generation sequencing and quantitative PCR (qPCR). Practically, in the service, we have detected EGFR mutations in patient ctDNA at an abundance as low as 0.7%.

The AWMGS now provides ctDNA-based testing of the EGFR gene in NSCLC patients at both first-line testing for sensitizing mutations and for resistance mutation testing on patient progression on TKIs (Figure 2). The service launched across Wales in April 2016 and has since been expanded to provide testing for certain centres in the South West of England with funding from AstraZeneca. A year on, over 100 patients have been tested, the majority (approximately 60%) of patient referrals have been for T790M progression testing to avoid repeat biopsies for patients. Six patients, for whom TKIs were previously inaccessible due to failed FFPE-based testing or inability to biopsy, were successfully tested through the ctDNA service and are now receiving first-line EGFR TKI therapy following the detection of activating EGFR mutations in ctDNA.

Ongoing and future developments
The field of liquid biopsies is steadily gaining pace in the UK and abroad with a number of centres now providing EGFR ctDNA testing. New circulating biomarkers, such as exosomes and circulating tumour cells, are coming through from translation research and have vast potential in the field of stratified medicine. At the AWMGS, we aim to expand our current liquid biopsy testing in the near future with targets for both metastatic colorectal cancer and metastatic melanoma.

References
1. Schwarzenbach H, Hoon DS, Pantel K. Cell-free nucleic acids as biomarkers in cancer patients. Nat Rev Cancer 2011; 11: 426–437.
2. Bettegowda C, Sausen M, Leary RJ, Kinde I, Wang Y, Agrawal N, Bartlett BR, Wang H, Luber B, et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med 2014; 6: 224ra24.
3. Chen KZ, Lou F, Yang F, Zhang JB, Ye H, Chen W, Guan T, Zhao MY, Su XX, et al. Circulating tumor DNA detection in early-stage non-small cell lung cancer patients by targeted sequencing. Sci Rep 2016; 6: 31985.
4. Dawson S-J, Tsui DWY, Murtaza M, Biggs H, Rueda OM, Chin SF, Dunning MJ, Gale D, Forshew T, et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med 2013; 368: 1199–1209.
5. Forshew T, Murtaza M, Parkinson C, Gale D, Tsui DW, Kaper F, Dawson SJ, Piskorz AM, Jimenez-Linan M, et al. Noninvasive identification and monitoring of cancer mutations by targeted deep sequencing of plasma DNA. Sci Transl Med 2012; 4: 136ra68.
6. Murtaza M, Dawson SJ, Tsui DW, Gale D, Forshew T, Piskorz AM, Parkinson C, Chin SF, Kingsbury Z, et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 2013; 497: 108–112.
7. Rothwell DG, Smith N, Morris D, Leong HS, Li Y, Hollebecque A, Ayub M, Carter L, Antonello J, et al. Genetic profiling of tumours using both circulating free DNA and circulating tumour cells isolated from the same preserved whole blood sample. Mol Oncol 2016; 10: 566–574.
8. Heitzer E, Ulz P, Geigl JB. Circulating tumor DNA as a liquid biopsy for cancer. Clin Chem 2015; 61: 112–123.
9. Jänne PA, Engelman JA, and Johnson BE. Epidermal growth factor receptor mutations in non–small-cell lung cancer: implications for treatment and tumor biology. J Clin Onc 2005; 23: 3227–3234.
10. Li T, Kung H-J, Mack PC, Gandara DR. Genotyping and genomic profiling of non-small-cell lung cancer: implications for current and future therapies. J Clin Onc 2013; 31: 1039–1049.
11. Douillard JY, Ostoros G, Cobo M, Ciuleanu T, Cole R, McWalter G, Walker J, Dearden S, Webster A, et al. Gefitinib treatment in EGFR mutated Caucasian NSCLC: circulating-free tumor DNA as a surrogate for determination of EGFR status. J Thorac Oncol 2014; 9: 1345–1353.
12. Goto K, Ichinose Y, Ohe Y, Yamamoto N, Negoro S, Nishio K, Itoh Y, Jiang H, Duffield E, et al. Epidermal growth factor receptor mutation status in circulating free DNA in serum: from IPASS, a phase III study of gefitinib or carboplatin/paclitaxel in non-small cell lung cancer. J Thorac Oncol 2012; 7: 115–121.
13. National Institute for Health and Care Excellence (NICE). Gefitinib for the first-line treatment of locally advanced or metastatic non-small-cell lung cancer. Technology appraisal guidance [TA192] 2010. [https: //www.nice.org.uk/guidance/ta192]
14. NICE. Osimertinib for treating locally advanced or metastatic EGFR T790M mutation-positive non-small-cell lung cancer. Final appraisal determination [TA10022] 2016. [https: //www.nice.org.uk/guidance/GID-TA10022/documents/final-appraisal-determination-document]
15. Sundaresan TK, Sequist LV, Heymach JV, Riely GJ, Jänne PA, Koch WH, Sullivan JP, Fox DB, Maher R, et al. Detection of T790M, the acquired resistance EGFR mutation, by tumor biopsy versus noninvasive blood-based analyses. Clin Cancer Res 2016; 22: 1103–1110.

The authors
Angharad Williams¹ PhD, Daniel Nelmes^2,3 PhD, Helen Roberts¹ BSc and Rachel Butler*¹ FRCPath
¹All Wales Medical Genetics Service,
NHS Wales, The Institute of Medical
Genetics, Cardiff and Vale University LHB,
University Hospital of Wales, Cardiff
CF14 4XW, Wales, UK
²School of Medicine, Cardiff University, Cardiff CF14 4XN, Wales, UK
³Velindre Cancer Centre, Cardiff
CF14 2TL, Wales, UK

*Corresponding author
E-mail: Rachel.Butler@wales.nhs.uk

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

Appropriate reference intervals are critical for interpretation of laboratory test results and accurate assessment of health and disease. However, pediatric reference intervals are severely lacking, leading to significant risk of misdiagnosis. CALIPER has addressed these gaps by establishing a robust reference interval database based on thousands of healthy children and adolescents.

by Victoria Higgins and Dr Khosrow Adeli

Introduction
The clinical laboratory provides objective data through laboratory testing of bodily fluids (e.g. serum, plasma) to aid in several aspects of medical decision making, including identifying risk factors and symptoms, diagnosing disease, and monitoring treatment. To correctly interpret laboratory test results, they are often compared to reference intervals (RIs), sometimes referred to as ‘normative’ or ‘expected’ values. RIs are commonly defined as the central 95% of the distribution of laboratory test results expected in a healthy, reference population [1]. Laboratory values that fall outside the appropriate RI may be interpreted as abnormal, possibly indicating the need for additional medical follow-up and/or treatment [2]. Given their critical importance to healthcare it would be expected that accurate RIs, appropriate for the patient population, are used in clinical practice. However, this is unfortunately far from the truth.

Importance of pediatric reference intervals
It can be challenging and costly for individual laboratories to develop RIs for their specific patient population, due to the necessity of recruiting a sufficiently large number of healthy individuals [i.e. The Clinical Laboratory Standards Institute (CLSI) recommends 120 individuals per partition] [1]. This is particularly true for pediatrics, a population in which unique RIs are of high importance. To interpret pediatric test results, laboratories often use RIs that were established on an adult reference population. The use of adult RIs to interpret pediatric test results can lead to erroneous and inaccurate interpretation. This is highlighted in Figure 1, which depicts the concentration of alkaline phosphatase (ALP) throughout pediatric, adult and geriatric age. It is evident that the pediatric population has vastly unique normative ALP values. Unique analyte concentrations in pediatrics is also true for sex hormones, growth hormones and several other analytes [3–5]. Therefore, children should not be viewed as small adults in the context of medical practice, but require separate RIs (i.e. partitions) for different age and/or sex groups, in addition to neonates and premature babies [5].

Closing the gaps in pediatric reference intervals
The current CLSI guidelines, which are mostly focused on adult RIs, acknowledge the special challenges of establishing age- and sex-specific pediatric RIs and recommend development of new initiatives to address the current gaps. The quality of a RI critically depends on the selected reference population. Therefore, the direct method of establishing RIs, which involves recruiting healthy individuals and applying exclusion criteria to select an appropriate reference population, is recommended over the indirect method, which involves using an already existing database (e.g. laboratory information system) to calculate RIs [1]. It is imperative for RI initiatives to focus on recruiting a sufficiently large and healthy reference population to accurately establish appropriate RIs for the pediatric population (i.e. using the direct method). Recognizing the critical need to establish pediatric RIs, several national initiatives have collected health information and blood samples from healthy pediatric populations. These initiatives include KiGGS in Germany [6], the Lifestyle of Our Kids (LOOK) study in Australia [7], CHILDx in the United States [8–10], The COPENHAGEN Puberty Study in the Nordic countries [11], and The Canadian Laboratory Initiative on Pediatric RIs (CALIPER) in Canada [5, 12].

The KiGGS initiative collected comprehensive, nationwide data on the health status of over 17 000 children and adolescents aged 0 to 17 years, across 167 locations in Germany [6]. This study has focused on laboratory parameters of general health indices, markers of nutritional status, immunization status, iron metabolism, thyroid, and indices of atopic sensitization. They have published age-dependent percentiles (3rd to 97th) in German, which may serve as a basis for RIs [13]. The LOOK study in Australia developed age-specific RIs for 37 chemistries, immunoassays, and derived parameters [7]. The CHILDx study was initiated in 2002 at ARUP (Associated Regional and University Pathologists) Laboratories and established RIs for 35 markers for children aged 6 months to 6 years and 58 markers for children aged 7–17 years [8–10]. The Nordic countries have also successfully established pediatric RIs for 21 biochemical properties using samples from healthy children and adolescents aged 5–19 years collected from schools from 2006–2008 in the Copenhagen area in Denmark as part of The COPENHAGEN Puberty Study [11]. However, arguably the most successful initiative has been the CALIPER project in Canada.

CALIPER project
The CALIPER project was initiated by The Paediatric Focus Group of the Canadian Society of Clinical Chemists (CSCC) and primarily based at The Hospital for Sick Children in Toronto (ON, Canada). CALIPER has recruited over 9 000 healthy children and adolescents from schools and community centres to participate at blood collection clinics by completing a health questionnaire, body measurements and donating a blood sample. Using this biobank of healthy pediatric samples, CALIPER has established age-, sex- and, for some biomarkers, Tanner Stage-specific pediatric RIs for over 100 biomarkers including, common biochemical markers, protein markers, lipids and enzymes [12], specialty endocrine markers [14], fertility hormones [15], cancer biomarkers [16], vitamins [17], metabolic disease biomarkers [18], testosterone indices [19] and specialized biochemical markers [20, 21]. All RIs were established in accordance with CLSI guidelines, including sample size requirements, outlier removal, statistical method for partitioning, as well as RI and confidence interval calculations [1].

The majority of RIs were established using Abbott ARCHITECT assays, initially limiting the direct applicability of the CALIPER database to all Canadian laboratories. CALIPER subsequently performed a series of transference and verification studies to expand the CALIPER database to additional assays commonly used in clinical laboratories, including Beckman, Ortho, Roche and Siemens [22–25]. Again, CALIPER performed these studies in accordance with CLSI guidelines and, in fact, often exceeded the sample size and statistical criteria requirements [1, 26]. The comprehensive CALIPER pediatric RI database is available online (www.caliperproject.ca), as well as through a mobile application (CALIPERApp) available on iTunes and Google Play. These tools allow the CALIPER database to be easily accessible to laboratory professionals, physicians, parents and patients.

Continued improvement in pediatric laboratory test interpretation
While significant improvements have been made in pediatric laboratory test interpretation over the past decade, several gaps remain. First, RI data for neonates (including premature babies) and infants (age 0 to <1 year) remains a challenge, owing to difficulties accessing a healthy neonate and infant population. However, the limited neonatal and infantile reference data CALIPER has collected highlights the profound differences in the newborn period, necessitating accurate RIs for this age group. For example, Figure 2 shows the dynamic concentration of creatinine throughout the pediatric age range, particularly the elevated and highly variable levels in the first two weeks of life. A large-scale, comprehensive study aimed at recruiting healthy neonates and infants is required to fill this gap. CALIPER is currently initiating a study with the aim of establishing a complete RI database for neonates and infants, which will greatly improve neonatal healthcare for premature babies, newborns, and infants from primary to complex, tertiary care pediatric centres.

Secondly, the effect of ethnicity on biomarker concentration remains to be comprehensively examined. The International Federation of Clinical Chemistry (IFCC) recommends that every country establishes RIs [27]; however, most nations adopt RIs from studies predominately performed in Western countries based on primarily Caucasian populations without considerations of ethnic differences. Although the majority of biomarkers do not differ between individuals of different ethnic backgrounds, a preliminary examination of the influence of ethnicity in pediatrics by CALIPER has shown that some biomarkers do significantly differ among ethnic groups, including immunoglobulin G (IgG), transferrin, ferritin, and follicle-stimulating hormone (FSH) [12, 14, 15]. Another study examined the influence of ethnicity in adults and found that serum creatine kinase (CK) activity is significantly higher for those of African ancestry. As elevated CK activity is an indicator of statin-induced myopathy, elevated CK activity in those of African ancestry could result in inappropriate discontinuation of statin therapy if ethnic-specific RIs are not used [28]. Another recent study used data from the National Health and Nutrition Examination Survey (NHANES) to develop racial/ethnic-specific RIs among Asians, Blacks, Hispanics, and Whites [29]. CALIPER has initiated a new study to robustly determine the effect of ethnicity on the concentration of routine serum biomarkers by examining and comparing reference values in the four major Canadian ethnic groups (i.e. Caucasian, South Asian, East Asian, and Black).

Lastly, as clinical laboratories adopt their RIs from numerous different sources, including textbooks, manufacturer product inserts, expert opinions, or published literature, RIs in clinical practice may vary substantially between laboratories. A national survey performed in Australia by the Australian Association of Clinical Biochemists (AACB) Harmonisation Group highlights the extensive variation in adult RIs used in clinical practice, which greatly compromises the consistency and reliability of laboratory test result interpretation and patient care [30]. A recent Canadian RI study (manuscript submitted; Adeli K, et al. 2017) by the CSCC Harmonized RI (hRI) Working Group, further highlights the considerable variation in RIs across laboratories with a greater variation observed in pediatric RIs in current clinical use, even between clinical laboratories using the same instrument. These surveys highlight the critical need for harmonized RIs in clinical practice. Initiatives in the Nordic countries [31], UK [32], Australia [33] and Japan [34] have already established harmonized RIs for a number of laboratory tests primarily for adults, but also for pediatrics. The CSCC hRI Working Group is now also working towards Canada-wide RI harmonization.

Conclusion
Children cannot be viewed as small adults and indeed require pediatric-specific RIs appropriately partitioned by age and sex for accurate laboratory test result interpretation. Several national initiatives have begun to address these critical gaps over the past decade by establishing age-, sex- and Tanner Stage-specific RIs for several major analytical platforms. The CALIPER initiative in Canada has arguably been the most comprehensive study to date, with clinical laboratories in several countries globally implementing the CALIPER database into clinical practice. Despite the significant strides recently achieved, further research is warranted in several areas including the establishment of RIs specific to the neonatal and infantile period, ethnic-specific RI for a subset of laboratory markers, and RI harmonization. Collectively, the comprehensive reference database published by CALIPER and the emerging data from ongoing studies directly address the evidence gap in pediatric RIs and contribute to evidence-based interpretation of laboratory test results and enhanced diagnostic accuracy of laboratory biomarkers in current clinical practice.

References
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3. Adeli K, Higgins V, Nieuwesteeg M, Raizman JE, Chen Y, Wong SL, Blais D. Biochemical marker reference values across pediatric, adult, and geriatric ages: establishment of robust pediatric and adult RIs on the basis of the Canadian Health Measures Survey. Clin Chem 2015; 61(8): 1049–1062.
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5. Shaw JLV, Binesh Marvasti T, Colantonio D, Adeli K. Pediatric RIs: challenges and recent initiatives. Crit Rev Clin Lab Sci 2013; 50(2): 37–50.
6. Kohse KP. KiGGS – the German survey on children’s health as data base for RIs and beyond. Clin Biochem 2014; 47(9): 742–743.
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10. Johnson-Davis KL, Moore SJ, Owen WE, Cutler JM, Frank EL. A rapid HPLC method used to establish pediatric RIs for vitamins A and E. Clin Chim Acta 2009; 405(1–2): 35–38.
11. Hilsted L, Rustad P, Aksglæde L, Sørensen K, Juul A. Recommended Nordic paediatric RIs for 21 common biochemical properties. Scand J Clin Lab Invest 2013; 73(1): 1–9.
12. Colantonio DA, Kyriakopoulou L, Chan MK, Daly CH, Brinc D, Venner AA, Pasic MD, Armbruster D, Adeli K. Closing the gaps in pediatric laboratory RIs: a CALIPER database of 40 biochemical markers in a healthy and multiethnic population of children. Clin Chem 2012; 58(5): 854–868.
13. Dortschy R, Schaffarth Rosario A, Scheidt-Nave C, Thierfelder W, Thamm M, Gutsche J. Bevölkerungsbezogene Verteilungswerte ausgewählter Laborparameter aus der Studie zur Gesundheit von Kindern und Jugendlichen in Deutschland (KiGGS). Beiträge zur Gesundheitsberichterstattung des Bundes. Berlin: Robert Koch-Institut; 2009.
14. Bailey D, Colantonio D, Kyriakopoulou L, Cohen AH, Chan MK, Armbruster D, Adeli K. Marked biological variance in endocrine and biochemical markers in childhood: establishment of pediatric RIs using healthy community children from the CALIPER cohort. Clin Chem 2013; 59(9): 1393–1405.
15. Konforte D, Shea JL, Kyriakopoulou L, Colantonio D, Cohen AH, Shaw J, Bailey D, Chan MK, Armbruster D, Adeli K. Complex biological pattern of fertility hormones in children and adolescents: a study of healthy children from the CALIPER cohort and establishment of pediatric RIs. Clin Chem 2013; 59(8): 1215–1227.
16. Bevilacqua V, Chan MK, Chen Y, Armbruster D, Schodin B, Adeli K. Pediatric population reference value distributions for cancer biomarkers and covariate-stratified RIs in the CALIPER cohort. Clin Chem 2014; 60(12): 1532–1542.
17. Raizman JE, Cohen AH, Teodoro-Morrison T, Wan B, Khun-Chen M, Wilkenson C, Bevilaqua V, Adeli K. Pediatric reference value distributions for vitamins A and E in the CALIPER cohort and establishment of age-stratified RIs. Clin Biochem 2014; 47(9): 812–815.
18. Teodoro-Morrison T, Kyriakopoulou L, Chen YK, Raizman JE, Bevilacqua V, Chan MK, Wan B, Yazdanpanah M, Schulze A, Adeli K. Dynamic biological changes in metabolic disease biomarkers in childhood and adolescence: a CALIPER study of healthy community children. Clin Biochem 2015; 48(13–14): 828–836.
19. Raizman JE, Quinn F, Armbruster DA, Adeli K. Pediatric RIs for calculated free testosterone, bioavailable testosterone and free androgen index in the CALIPER cohort. Clin Chem Lab Med 2015; 53(10): e239–243.
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The authors
Victoria Higgins PhD candidate; Khosrow Adeli* PhD, FCACB, DABCC, FACB
CALIPER program, Pediatric Laboratory Medicine, The Hospital for Sick Children, University of Toronto, Toronto, ON M5G 1X8, Canada

*Corresponding author
E-mail: khosrow.adeli@sickkids.ca

The use of suitably matched reference values derived from well-characterized individuals is critical to avoid misdiagnosis. Developing reference intervals in pediatric populations presents unique challenges. Recognizing these issues and bridging international biorepository efforts is essential to improving pediatric healthcare.

by Dr Carmen Gherasim, Sonia L. La’ulu, Sara P.Wyness and Dr Joely A. Straseski

Introduction
Children are unique individuals with dynamic developmental physiology which must be accounted for during clinical evaluation. In addition to a medical history and clinical examination, laboratory investigations constitute an integral part of diagnosis and therapeutic management. Understandably, children have limited ability to describe symptoms and medical providers must rely strongly on clinical and laboratory investigations. The availability of pediatric reference intervals (PRI) is, therefore, essential to avoid missed opportunities for treatment of preventable conditions and adverse consequences due to wrong diagnosis.

Depending on the analyte, PRI can differ substantially from RI in adult populations. Marked differences can even be observed within the pediatric population, with profound changes occurring during timeframes such as the first year of life or puberty. The dynamic process of growth, from the initial adaptation of infants living outside the womb to full sexual maturation associated with adulthood, is accompanied by changes in body composition and metabolic, immune, and hormonal fluctuations [1]. Furthermore, developmental stages in children, particularly during puberty, do not always correlate with age and can be affected by factors including nutritional status, body mass index (BMI), medications, or therapies (i.e. growth hormone therapy) [2]. It is therefore advantageous to develop PRI using clearly defined demographics such as age, sex, and race, along with stratifications accounting for physiological and sexual development to assist in clinical decision making.

From a clinical laboratory perspective, the dynamics of the sampled population along with regulatory and administrative requirements for determining PRI pose unique challenges for establishing high quality RI for pediatric populations [3]. Such challenges include: (1) defining ‘healthy’ in children; (2) obtaining research ethics board approval for sample collections; (3) obtaining informed parental and/or child consent for participation; (4) accommodating small sample volumes; and (5) partitioning of data. Collectively, these can hamper access to a sufficient number of specimens from healthy children, precluding many laboratories from performing PRI studies.

Origination of PRI
While RI studies may be performed by in vitro diagnostic manufacturers for commercially available assays, these often lack pediatric data or have minimal stratification reflecting children’s physiological variability. Although not unique to the pediatric population, recycling of RI determined using obsolete methods/instrumentation or adoption of RI from previously published sources without study traceability are often used to report and interpret laboratory data. Caveats in PRI adoption include the limited number of studies performed in pediatric populations, inclusion of data from hospitalized patients, data analysis techniques used, and lack of detailed information from existing studies including population tested and certain patient demographics. Therefore, careful examination of subjects and methods used in existing studies is critical.

Given the complexity of establishing new PRI, clinical laboratories should carefully consider the option to: (1) transfer, (2) verify or (3) establish PRI based on requirements addressed in guidelines (e.g. Clinical and Laboratory Standards Institute (CLSI) EP28-A3c) [4]. When a laboratory changes analytical methods for measuring an analyte for which they have previously established a RI, that RI may be ‘transferred’ following an acceptable method comparison study. This strategy may prove particularly useful when obtaining pediatric specimens is difficult. Other pre-determined RI must be ‘verified’ before their adoption by examining whether results from a minimum of 20 healthy individuals fall between the proposed limits. Finally, ‘establishing’ new RI requires examining a minimum of 120 samples for each statistically distinct group (partition) selected from qualified, healthy individuals chosen using well-defined inclusion/exclusion criteria (Fig. 1). This is an enormous effort, but particularly onerous in pediatric populations due to limited samples and numerous partitions. Due to this, routine clinical laboratories are often limited to verifying rather than establishing PRI.

Selection of reference populations for PRI
Ideally, reference studies should be conducted using ‘healthy’ volunteers but the identification and recruitment of a healthy representative pediatric population is complex. Health status of recruited children may be assessed by physical examination and health-related questionnaires; however, a definitive delineation of ‘healthy’ is challenging in pediatric populations, as subclinical problems may go unrecognized. Obtaining a sufficient number of pediatric specimens from truly healthy children remains a rate-limiting step of this process.

One strategy that circumvents this challenge is the use of residual blood samples from hospitalized children, deemed healthy due to unrelated or inconsequential medical conditions. This approach eliminates the undesirable blood collection procedure but can be affected by the lack of medical history that can influence test results and overall quality of the PRI established. Additionally, data mining methods exploiting laboratory results from hospitalized children can be used. First introduced by Robert Hoffmann, this approach assumes that the majority of specimens measured in the clinical laboratory represent ‘normal’ values, whereas the most extreme values account for the sickest populations [5].
The effect of common physiological variables such as age and sex on pediatric biomarkers is often evaluated using specific RI partitions. Complex factors such as BMI, Tanner staging, and race may also influence the concentration of select analytes. Despite the rising incidence of pediatric obesity in many developed countries, the effect of BMI on PRIs has been largely overlooked [6]. Challenges in designing studies to address this issue include susceptibility of analytes to BMI variability and delineation between BMI and changes in body composition throughout development. Also, physical and pubertal development in children is not always parallel. Surges in hormone concentrations trigger sexual development and their concentrations vary with the presence of secondary sexual characteristics (described by Tanner stages) rather than age. Finally, race-specific differences can also influence concentrations of pediatric analytes and covariates such as BMI, but their contribution could be underestimated due to their multifactorial etiology.

Statistical methods for PRI analysis
Laboratory data is interpreted in the context of RI, which typically describe the central 95% of results from a population of healthy volunteers. One particular concern with PRI is the availability of sufficient numbers of specimens to allow for statistical significance of each partition [7]. Selection of an appropriate statistical method to compute RI is dependent on the number of specimens in each partition and overall distribution of the data. A small number of pediatric specimens can result in sampling variability which decreases the confidence that a normal result will fall in the established RI. General statistical methods can be employed including parametric (smaller specimen numbers following Gaussian/normal distribution) and nonparametric methods (minimum 120 reference observations per partition). Current CLSI guidelines recommend the use of nonparametric approaches for estimation of RI as they do not make assumptions regarding the distribution of the data [4]. Despite the easy access to data, assumptions regarding data distribution and weak correlation studies often reveal that Hoffmann statistical approaches may be unreliable for establishing new RI in pediatric populations [8]. Increasing the statistical power of PRI determinations and understanding the effect of covariates remains challenging due to the large number of specimens required that can only be reasonably addressed in multicentre RI initiatives.

Current studies emphasizing the need for PRI
The importance of well-defined PRI is highlighted by our recent studies investigating a number of analytes with different concentrations in pediatric populations as compared to adults. A valuable component of our studies is the use of large numbers of well-characterized subjects selected using clearly defined inclusion/exclusion and partition criteria. Whereas some analytes show significant differences between age and sexes (bone markers osteocalcin, procollagen type 1N-terminal propeptide, bone-specific alkaline phosphatase, and C-telopeptide; thyroglobulin and free triiodothyronine), others do not (free thyroxine) [9–11]. PRI for 5α-dihydrotestosterone identified significant differences between sexes and Tanner stages [12]. These differences highlight the need for PRI for individual analytes and the large dataset for each partition in these studies was critical for appropriate data analysis and delineation of proper PRI. As the majority of clinical laboratories verify rather than establish PRI, reported studies should be carefully reviewed for study design, selection of reference individuals, methods used, analytical quality, and appropriate statistical analysis of the data before being considered for PRI adoption.

PRI initiatives
There are a number of initiatives around the world striving to improve the quality and accuracy of PRI (Table 1). Their major advantage is the recruitment of large cohorts of healthy children and adolescents using well-defined selection and partition criteria. Understandably, recruitment strategies vary between initiatives but generally include soliciting members of local communities, organizing clinics at schools and community centres, and/or enrolment prior to undergoing elective, non-invasive, outpatient surgeries. Although each initiative has focused on different biomarkers, most focus on common biochemical markers, blood analytes, vitamins, and/or hormones [13–16]. All studies included partitions for pediatric populations by age and sex and most reference values were analysed using nonparametric statistics to define central 95% PRI. Additional covariates such as Tanner staging, race, or BMI were addressed only by select initiatives including CHILDx, CALIPER and IDEFICS, respectively. A shortcoming of many of the studies was the relatively small representation of other races. Multicentre studies could address this problem, thereby promoting harmonization and diversity amongst PRI. In a recent position statement, the American Association for Clinical Chemistry expressed their support for the foundation of a national repository, enabling a comprehensive evaluation of all PRI covariates and provide and maintain up-to-date PRI databases [17].

Concluding remarks
Reference intervals for pediatric populations weigh heavily in the interpretation of laboratory results and can impact the outcome of clinical decisions. In recent years, we have witnessed an increased awareness of the ‘malpractices’ in PRI including adoption from suboptimal RI studies or from populations that do not mirror the healthy state in children. Recommendations to establish individual PRI that adequately represent the numerous variables in children’s development remain hard to meet by most laboratories, reinforcing a need for a collective effort in establishing PRI. Concentrating national and international efforts can support PRI initiatives and improve pediatric healthcare overall.

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The authors
Carmen Gherasim¹ PhD, Sonia L. La’ulu² BS, Sara P. Wyness² BA, and Joely A. Straseski*^1,2 PhD
¹Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA
²ARUP Institute for Clinical and Experimental Pathology, Salt Lake City, UT, USA

*Corresponding author
E-mail: joely.a.straseski@aruplab.com