The use of liquid chromatography-tandem mass spectrometry (LC-MS/MS) to measure serum folate has been recommended for population monitoring as it allows a more accurate and reproducible measurement than the commonly used protein binding assays. The ability to differentiate between endogenous folate vitamers and folic acid makes LC-MS/MS an extremely valuable tool, not least due to the uncertainty surrounding the potential adverse effects of high concentrations of circulating folic acid.

by Sarah Meadows

Role of folates
Folate is the general term for a water-soluble B vitamin naturally found in foods such as leafy vegetables, legumes, egg yolks, liver and some citrus fruits. Folic acid itself does not occur naturally but it can be found in individuals who take vitamin supplements or eat fortified foods [1, 2]. There are many critical cellular pathways that depend on folate, including DNA, RNA and protein methylation, as well as DNA synthesis and maintenance [2, 3], and because of this there are many health consequences of folate deficiencies among all age groups. These include megaloblastic anemia, depression, cognitive impairment, low birth weight, risk of placental abruption, neural tube defects and other birth defects including orofacial clefts and heart defects [4, 5]. The most widely publicized public health issue surrounding folate is that of low folate during pregnancy causing birth defects associated with the nervous system. Folate is an essential micronutrient during fetal development because of its roles in transmethylation reactions and in synthesis of DNA in growing cells [3]. A significant portion of the 300 000 neural tube defects (NTDs) that occur yearly worldwide are preventable by the periconceptual consumption of folic acid and continue to be a great public health burden globally [2]. The demonstration that periconceptional supplementation with folic acid dramatically reduces the incidence of NTDs has generated considerable clinical and public health interest and has led to fortification with folic acid of the food supply in the United States and some other countries [6]. The recent World Health Organization (WHO) guidelines for ‘Optimal serum and red blood cell folate in women of reproductive age for prevention of neural tube defects’ states that in 2012 an estimated 270 358 deaths globally were attributable to congenital abnormalities during the first 28 days of life. NTDs were one of the most serious and most common abnormalities and increasing awareness of the significance of insufficient folate intake has emphasized the need for identification of accurate biomarkers for large scale assessment of folate status [7].

As well as neural tube closure, B vitamins, including folate, are required for essential brain metabolic pathways and are fundamental in all aspects of brain development and maintenance of brain health throughout the lifecycle. Observational and animal evidence appears to be supportive for a role of maternal folate status in later cognitive performance of the child and there are also studies linking low maternal folate status with a higher incidence of behavioural and emotional problems, inattention and hyperactivity in their offspring [8]. Recent studies have also shown links between low plasma folate and poor cognitive performances in children and adolescents, and similarly a positive association between higher dietary folate intake and academic achievement [8].

Cognitive dysfunction in the elderly (ranging from cognitive impairment to dementia) is also a matter of concern. Brain changes progress long before the diagnosis of dementia is made, and given the increase in life expectancy, the numbers of individuals suffering is set to double by 2025. Therefore it is important to find early biomarkers that would enable timely interventions to delay the onset or slow the progression of the disease. There is emerging evidence suggesting that suboptimal status of folate and metabolically related B vitamins may be linked with cognitive dysfunction and dementia; if this can be slowed or prevented by improving the B vitamin status in healthy older people it could offer a cost effective preventative public health strategy in ageing populations [8].

Evidence showing that supplementation with folic acid protects against NTDs has led to government recommendations, which are in place worldwide, advising all women planning a pregnancy to consume 400 µg/day folic acid from preconception until the end of the first trimester of pregnancy [2, 8–11]. Even with this knowledge, public health campaigns remain largely unsuccessful and limited [2, 9]. Mandatory fortification programmes have been implemented in many countries to improve folate status and reduce high costs associated with prevention programmes such as education campaigns and other interventions that require behavioural change [2]. The Scientific Advisory Committee on Nutrition (SACN) has called for mandatory fortification in the United Kingdom to replace voluntary fortification in a bid to increase the UK population’s folate status [12].

Despite the unequivocal success of folic acid in reducing NTD rates, several studies have questioned whether unmetabolized folic acid in blood may have adverse effects [3, 11]. Concerns have been raised that due to fortification the subsequent increase in folic acid intakes across the population may have harmful effects on health, such as the masking of pernicious anemia, colorectal cancer promotion in people with pre-existing lesions or adverse cognitive effects in the elderly with low vitamin B₁₂ status [4, 9, 11, 13]. Measurement of unmetabolized folic acid has been suggested as a way of monitoring whether folic acid intake is in excess of body requirements [2, 5] and at a time when there are still questions regarding the effects of high levels of folic acid in the blood, the ability to differentiate between this and endogenous folates is valuable.
Serum folate is considered an indicator of recent folate intake whereas red blood cell folate concentrations indicate long term status [7, 10].

Measurement of folates
There are several methods currently in use to measure serum folates all with their own advantages and limitations (Table 1). Folate had traditionally been measured using a microbiological assay but, since the 1970s, commercial protein binding assays on automated clinical analysers have been widely used due to both the ease of use of these platforms and the increased throughput they offer. Microbiological assays have not been made obsolete by protein binding assays, as originally expected, due to these assays being well suited to low resource settings [6]. The microbiological assays are considered more accurate as they recover folate vitamers equally and are, therefore, considered the gold standard measurement [14], whereas the protein binding assays generally underestimate folate concentrations due to the different affinities of the folate vitamers for the binding protein used [1, 7].

In contrast to both the microbiological assay and protein binding assays, chromatography techniques are able to differentiate between individual folate species [7] and are now often coupled to mass spectrometers as this method has high sensitivity, specificity and selectivity compared to other detection methods such as fluorimetric or electrochemical detection [6, 7, 15].

The importance of measuring the different folate species is likely to become greater in the future as more information on genetic polymorphisms that affect nutritional status and folate distributions become available [1] and in order to determine the safety of free folic acid in the blood.

The differences seen in results produced by different assays have led the WHO to recommend the standardization of blood vitamin analysis [5, 7]. Initial steps to standardize folate methods began with the development of higher order reference methods that use isotope dilution/ liquid chromatography/tandem mass spectrometry and with recent advances in sample clean up procedures routine methods using LC/MS or LC-MS/MS are becoming more common [5].

Red cell folate is normally calculated using whole blood folate concentrations, serum folate concentrations and hematocrit. However, low concentrations of serum folate within an individual over the course of a month are also indicative of low folate or folate depletion [7, 16]. It has proven to be more technically challenging to measure whole blood folate by LC-MS/MS than it is to measure serum folate, in part because red blood cells first need to be hemolysed to release the polyglutamate folates, which then need to be deconjugated to monoglutamates without any folate loss before being analysed [6, 7]. This has led to whole blood assays only being carried out, commonly by microbiological assays, in specialist laboratories.

LC-MS/MS measurement of folates
The recommendation from an expert and stakeholder workshop for the use of an LC-MS/MS method to measure serum folate for UK population monitoring in 2009 [17] led to the establishment of a assay at the MRC Human Nutrition Unit, Cambridge for the measurement of serum folate in the UK National Diet and Nutrition Survey Rolling Programme (NDNS RP). This was developed from the published method used by the Centers for Disease Control and Prevention, Atlanta, GA for the US National Health and Nutrition Examination Survey (NHANES) [18]. The method described here is for a routine LC-MS/MS method allowing the determination and quantitation of six folate vitamers in serum: tetrahydrofolate (THF); 5-methyltetrahydrofolate (MTHF); 5-formyltetrahydrofolate (FTHF); free folic acid (polyglutamic acid/PGA); 5,10-methenyltetrahydrofolate (5,10 methenylTHF) and an oxidation product of MTHF, MeFox [19].

Samples undergo solid phase extraction, using phenyl columns, to isolate the folate forms in serum samples. Stable isotope-labelled internal standards are added during the extraction step and undergo processing identical to the analytes, thereby normalizing for sample preparation and instrument variability. Analytes are measured using isocratic reversed-phase UPLC prior to electrospray ionization tandem mass spectrometry with a run time of 3.5 minutes. The retention times for all the analytes are very similar and the internal standards are identical to their corresponding analytes, but due to their differing masses, there is clear distinction between them in the assay (Fig. 1). FTHF and MeFox have the same molecular weights and cannot be chromatographically separated, so transitions unique to each form have to be used. The ratio of analyte to internal standard signal is compared to that of a calibration curve to determine analyte concentration.
Recovery is 95.1% for MTHF and >78% for all the other analytes and within batch precision is <7% for all analytes. The calibration graphs are linear, R2 >0.99, for all analytes, from 1 to 100 nmol/L for MTHF and 0.5 to 20 nmol/L for all the other folate forms. Linearity extends above these ranges but these encompass the normal concentrations seen currently in the UK population. Total serum folate concentrations in the UK population lie mainly between 2 and 80 nmol/l. The main folate form in the serum is MTHF, free folic acid and THF are found at concentrations usually <2 nmol/L and MeFox is also found in the majority of samples at concentrations <10 nmol/L. FTHF and CH+THF are rarely found in the serum samples of the UK population. Tandem mass spectrometry may require operation by experienced personnel but it can provide high throughput measurements in a routine environment. The big disadvantage of this method of analysis to most laboratories is the large financial outlay required to purchase the equipment, but the recent advances in mass spectrometry has led to cheaper and smaller instruments being available and this has led to many more being implemented into routine clinical laboratories.
The use of immunoassays for clinical purposes may still be the preferred option for many routine clinical labs but LC-MS/MS is a more accurate, precise and reliable tool for population studies and research purposes than other available methods.

This work was funded by the Medical Research Council MRC_MC_U105960384.

References
1. Shane B. Folate status assessment history: implications for measurement of biomarkers in NHANES. Am J Clin Nutr. 2011; 94(1): 337S–342S.
2. Crider KS, Bailey LB, Berry RJ. Folic acid food fortification-its history, effect, concerns, and future directions. Nutrients, 2011; 3(3): 370–384.
3. Obeid R, Kasoha M, Kirsch SH, Munz W, Herrmann W. Concentrations of unmetabolized folic acid and primary folate forms in pregnant women at delivery and in umbilical cord blood. Am J Clin Nutr. 2010; 92(6): 1416–1422.
4. Smith AD. Folic acid fortification: the good, the bad, and the puzzle of vitamin B-12. Am J Clin Nutr. 2007; 85(1): 3–5.
5. de Benoist B. Conclusions of a WHO Technical Consultation on folate and vitamin B12 deficiencies. Food Nutr Bull. 2008; 29(2 Suppl): S238–244.
6. Bailey LB. Folate in health and disease, 2nd ed. Taylor & Francis 2010.
7. WHO. In: Guideline: Optimal serum and red blood cell folate concentrations in women of reproductive age for prevention of neural tube defects. WHO 2015. (http://apps.who.int/iris/bitstream/10665/161988/1/9789241549042_eng.pdf)
8. McGarel C, Pentieva K, Strain JJ, McNulty H. Emerging roles for folate and related B-vitamins in brain health across the lifecycle. Proc Nutr Soc. 2015; 74(1): 46–55.
9. Hopkins SM, Gibney MJ, Nugent AP, McNulty H, Molloy AM, Scott JM, Flynn A, Strain JJ, Ward M, Walton J, McNulty BA. Impact of voluntary fortification and supplement use on dietary intakes and biomarker status of folate and vitamin B-12 in Irish adults. Am J Clin Nutr. 2015; 101(6): 1163–1172.
10. Clarke R, Bennett D. Folate and prevention of neural tube defects. BMJ 2014; 349: g4810.
11. European Food Safety Authority (EFSA). Folic acid: an update on scientific developments. EFSA 2010. (https://www.efsa.europa.eu/en/supporting/pub/2e)
12. Scientific Advisory Committee on Nutrition (sacn). Folate and disease prevention. The Stationery Office 2006.
13. Bailey RL, Mills JL, Yetley EA, Gahche JJ, Pfeiffer CM, Dwyer JT, Dodd KW, Sempos CT, Betz JM, Picciano MF. Serum unmetabolized folic acid in a nationally representative sample of adults >/=60 years in the United States, 2001–2002. Food Nutr Res, 2012; 56: DOI: 10.3402/fnr.v56i0.5616.
14. Pfeiffer CM, Hughes JP, Lacher DA, Bailey RL, Berry RJ, Zhang M, Yetley EA, Rader JI, Sempos CT, Johnson CL. Estimation of trends in serum and RBC folate in the U.S. population from pre- to postfortification using assay-adjusted data from the NHANES 1988-2010. J Nutr. 2012; 142(5): 886–893.
15. Wang X, Zhang T, Zhao X, Guan Z, Wang Z, Zhu Z, Xie Q, Wang J, Niu B. Quantification of folate metabolites in serum using ultraperformance liquid chromatography tandem mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci. 2014; 962: 9–13.
16. McDowell MA, Lacher DA, Pfeiffer CM, Mulinare J, Picciano MF, Rader JI, Yetley EA, Kennedy-Stephenson J, Johnson CL. Blood folate levels: the latest NHANES results. NCHS Data Brief 2008; 6: 1–8.
17. Duthie SJ, Bird S, Mayer C, Macdonald H. FSA UK: Programme N08: Dietary surveys and nutrients in food: Informed systematic review and critical comparison of analytical methods for the quantification of blood folate status in the population. FSA Website April 2009.
18. Fazili Z, Whitehead RD Jr, Paladugula N, Pfeiffer CM. A high-throughput LC-MS/MS method suitable for population biomonitoring measures five serum folate vitamers and one oxidation product. Anal Bioanal Chem. 2013; 405(13): 4549–60.
19. Meadows S. Multiplex measurement of serum folate vitamers by UPLC-MS/MS. Methods in Molecular Biology 2016 (in press).

The author
Sarah Meadows MSc, CSci
MRC, Elsie Widdowson Laboratory, Cambridge, UK

E-mail: sarah.meadows@mrc-ewl.cam.ac.uk

Prednisolone is an attractive once-daily option to treat adrenal insufficiency. Its prior association to osteoporosis and diabetes is possibly due to widespread over-replacement. With the availability of an ultra-performance liquid-chromatography tandem mass spectrometry (UPLC-MS/MS) method to detect serum concentrations and guide treatment, we can assess the true effects of long-term low-dose prednisolone therapy.

by Dr Sirazum Choudhury and Dr Emma Williams

Introduction
Prednisolone is a pioneering synthetic corticosteroid synthesized by Arthur Nobile in 1950 as an anti-arthritic treatment [1, 2]. Sharing a similar structure to cortisol, prednisolone benefits from a longer half-life and increased potency compared to endogenous steroids, owing to a double bond found between C1 and C2 on the first carbocyclic ring (Fig. 1). Prednisolone has proven to be an indispensable anti-inflammatory drug and has long been used in the treatment of many conditions including asthma, inflammatory bowel disease and rheumatoid arthritis.

Use of prednisolone for adrenal insufficiency
More recently prednisolone is gaining traction as an option for glucocorticoid replacement therapy in adrenal insufficiency. There are an estimated 8400 individuals living with the condition in the UK, with an annual incidence of 4.4–6 cases per million in Europe [3]. The challenges of adrenal insufficiency are well characterized. In the era prior to the availability of effective treatment, the associated mortality was 85% in 2 years, and up to 100% in 5 years [4]. Over the last half-century, our increasing understanding of steroids has meant that patients are living longer, with a life expectancy approaching that of the normal population. However, a mortality gap does remain, which may in part be due to incorrect replacement of glucocorticoids, concurrently increasing the risk of diabetes, osteoporosis and cancer.

Oral hydrocortisone is the most commonly prescribed treatment for adrenal insufficiency, but is perhaps not the most ideal [5]. Due to the relatively short half-life, hydrocortisone must be administered three times daily, which can hinder compliance. For this reason it is our experience that some patients tend to omit the last dose of the day. Moreover, the price of hydrocortisone has been rising in the UK, costing £76 for a 1-month supply of 10 mg. This contrasts to a 1-month supply of 5 mg prednisolone tablets, which costs £0.88. With prednisolone offering a once-daily solution to adrenal insufficiency, it now features in the Endocrine Society clinical practice guidelines from earlier this year as an alternative to thrice-daily hydrocortisone therapy [6].

Prednisolone dose and adverse effects
The biggest obstacle to the widespread acceptance of prednisolone as a viable therapy has been its association with adverse metabolic effects such as osteoporosis. This is as a result of multiple studies purporting to show that ‘low dose’ prednisolone has a negative impact of the markers of bone turnover and bone absorptiometry [7]. Based on an assumed bioequivalence ratio of 4 : 1, 7.5 mg of prednisolone was judged to be equivalent to 30 mg of hydrocortisone and was considered ‘low dose’. The basis of this ratio is difficult to ascertain but was probably calculated from data on anti-inflammatory doses of prednisolone, which are significantly higher than the doses likely to be needed in steroid replacement therapy. More recently, a study comparing prednisolone to hydrocortisone in 44 children with congenital adrenal hyperplasia found that a lower dose of prednisolone than expected was required to control the condition [8]. Using objective biological markers, such as growth velocity, and hormonal markers such as androstenedione and 17-hyroxyprogesterone, the group discovered that prednisolone is 1.5 to 2 times more potent than previously thought, suggesting that a more appropriate prednisolone replacement dose is in fact 3 mg to 5 mg, and not as high as 7.5 mg.

To facilitate this shift towards the use of even lower doses of prednisolone, it is important to provide reassurance to both clinicians and patients that the lowest necessary dose of prednisolone is used to maintain an appropriate trough level towards the end of the day. This would be in keeping with the diurnal rhythm of cortisol. Our ability to more accurately and efficiently report serum prednisolone concentrations using an ultra-performance liquid-chromatography (UPLC) tandem mass spectrometry (MS/MS) technique provides this confidence.

Measurement of plasma prednisolone concentrations
Historically, the first assays to measure plasma prednisolone concentrations were competitive protein binding assays and radio-immunoassays [9]. The protein binding assays were designed to use cortisol binding globulin and were therefore non-specific to prednisolone. The early radio-immunoassays were prone to interference from other endogenous steroids and intermediaries, making them unreliable especially if patients continued to produce subclinical levels of cortisol. Specificity could be improved with the addition of a thin layer chromatography preparatory step; however, the lower limit of detection remained as high as 20 µg/L.

In the 1970s, high-performance liquid-chromatography (HPLC) methods gained popularity [10]. Offering greater specificity for prednisolone, the method involved a time-consuming liquid–liquid-extraction sample-preparation step. The extracted organic phase would be dried before being reconstituted with mobile phase and passed through a normal phase hydrophilic interaction chromatography HPLC column. Prednisolone concentrations were detected with ultraviolet absorbance spectrophotometry. Although this method could identify different corticosteroids, it proved to be cumbersome with retention times of up to 8 minutes for prednisolone, and 20 minutes for other steroids. With 76% recovery and a lower limit of detection of 25 µg/L, this technique is not suitable to assess trough levels of prednisolone, with a high likelihood of reporting undetectable results at the lower end, potentially facilitating over-replacement in patients.

Using a UPLC-MS/MS method, we are able to overcome the obstacles that have plagued prednisolone assays in the past (reference awaiting PubMed identifier). Serum samples are prepared using a protein precipitation method, involving zinc sulphate and the addition of deuterated (D6) prednisolone as internal standard. Following preparation, the extract is combined with both methanol and water based mobile phases before being passed through a C-18 chromatography column, which employs a reversed phase partition process. Prednisolone is eluted at approximately 1.0 minutes, before being detected by multiple reaction monitoring using electrospray ionization in positive ion mode. An example of the observed chromatograms can be found in Figure 2.

This method of measuring plasma prednisolone concentrations is linear to prednisolone concentrations of 1000 µg/L (Fig. 3), with an inter- and intra-assay co-efficient of variance at 50 µg/L of 4.1% and 2.5% respectively. The technique has proven more sensitive than HPLC with the lower limit of quantification at 10 µg/L without the HPLC recovery issues, and is equally as specific to prednisolone. By using a protein precipitation method, the preparation step is now significantly shorter. Additionally, with reduced prednisolone retention times, a prepared sample can now be analysed in 3.5 minutes before the next sample is immediately run. As a result, the UPLC-MS/MS technique is better suited to the modern clinical biochemistry laboratory being able to reliably cope with larger numbers of patient samples in shorter times than previously thought possible.

Measuring serum prednisolone concentrations has proven extremely valuable in monitoring glucocorticoid replacement therapy. There is observable variability in prednisolone metabolism between individuals, with terminal half-lives routinely varying between 1.75 and 3.75 hours. We currently measure a trough level at 8 hours post-prednisolone administration aiming for a concentration of 10–20 µg/L to ensure adequate replacement throughout the day and preserve an overnight corticosteroid nadir. The results are used clinically to inform the decision either to increase or decrease prednisolone doses as appropriate but also serve as objective proof to patients who are anxious about a reduction. The assay is also clinically useful in confirming patient compliance with their prescribed medication.

Future perspectives
Beyond the clinical utility in quantifying serum prednisolone levels, there is significant research potential for this assay. Addisonian crises are currently responsible for up to 15% of deaths in patients with adrenal insufficiency [11]. Our understanding of the disease process is limited by the urgency to provide treatment with either intravenous or intramuscular hydrocortisone, before a blood sample is taken. As this is detected by cortisol assays, it is difficult to interpret whether the pre-crisis hydrocortisone concentration was inadequate (suggesting non-compliance or reduced absorption) or appropriate (suggesting that the level was insufficient to match requirement). In patients treated with prednisolone who present with Addisonian crises, the assay will allow us to assess the pre-treatment serum prednisolone concentrations, even if the blood sample is taken after treatment with hydrocortisone.

More importantly in the immediate setting, it is anticipated that the previously accepted long-term effects of ‘low dose’ prednisolone can be explored. The availability of a reliable and specific assay will result in a greater number of patients on prednisolone who are appropriately treated and not over-replaced. In time, as more data becomes available, we will gain a clearer picture of the true effects of prednisolone.

References
1. Nobile A. The discovery of the delta 1,4-steroids, prednisone, and prednisolone at the Schering Corporation (USA). Steroids 1994; 59(3): 227–230.
2. Herzog HL, Nobile A, Tolksdorf S, Charney W, Hershberg EB, Perlman PL. New antiarthritic steroids. Science 1955; 121(3136): 176.
3. Charmandari E, Nicolaides NC, Chrousos GP. Adrenal insufficiency. Lancet 2014; 383(9935): 2152–2167.
4. Dunlop D. Eighty-six cases of Addison’s disease. Br Med J. 1963; 2(5362): 887–891.
5. Groves RW, Toms GC, Houghton BJ, Monson JP. Corticosteroid replacement therapy: twice or thrice daily? J R Soc Med. 1988; 81(9): 514–516.
6. Bornstein SR, Allolio B, Arlt W, Barthel A, Don-Wauchope A, Hammer GD, et al. Diagnosis and treatment of primary adrenal insufficiency: an Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab. 2016; 101(2): 364–389.
7. Jodar E, Valdepenas MP, Martinez G, Jara A, Hawkins F. Long-term follow-up of bone mineral density in Addison’s disease. Clin Endocrinol. (Oxf) 2003; 58(5): 617–620.
8. Caldato MC, Fernandes VT, Kater CE. One-year clinical evaluation of single morning dose prednisolone therapy for 21-hydroxylase deficiency. Arq Bras Endocrinol Metabol. 2004; 48(5): 705–712.
9. Wilson CG, Ssendagire R, May CS, Paterson JW. Measurement of plasma prednisolone in man. Br J Clin Pharmacol. 1975; 2(4): 321–325.
10. Loo JC, Butterfield AG, Moffatt J, Jordan N. Analysis of prednisolone in plasma by high-performance liquid chromatography. J Chromatogr 1977; 143(3): 275–280.
11. Erichsen MM, Lovas K, Fougner KJ, Svartberg J, Hauge ER, Bollerslev J, et al. Normal overall mortality rate in Addison’s disease, but young patients are at risk of premature death. Eur J Endocrinol. 2009; 160(2): 233–237.

The authors
Sirazum Choudhury BSc, MBBS, MRCP
and Emma Williams* BSc, PhD, FRCPath
Charing Cross Hospital, Fulham Palace Road, London W6 8RF, UK

*Corresponding author
E-mail: emma.walker@imperial.nhs.uk

Lp(a) is a complex macromolecule synthesized in the liver, it presents similarities with Low Density Lipoprotein (LDL) as it possesses a cholesterol-phospholipid core and a closely associated protein, apoB100. Lp(a) differs however from LDL in that each lipoprotein particle contains one copy of the glycoprotein apolipoprotein (a) [apo (a)] covalently bound to apoB100 by a single disufide bond [1]. Studies indicate the association of elevated levels of plasma Lp(a) and risk of coronary heart disease [2,3].  A study reported that elevated plasma Lp(a) and small apolipoprotein (a) increased the risk of recurrent arterial ischemic stroke in children [4]. Moreover, the structural similarities between apo(a) and plasminogen highlighted the importance of Lp(a) in both atherosclerosis and thrombogenesis [5-7]. The intra and inter-individual size heterogeneity of apo(a) is genetically determined, this size variation constitutes a challenge for the immunochemical measurement of Lp(a) in plasma. The use of a 5-point calibrator which take into account the heterogeneity of Lp(a) for each of the levels would reduce result discrepancies. This study reports the performance characteristics of an immunoturbidimetric assay for the determination of Lp(a) in serum or plasma with minimum apo(a) size related bias.

Methodology
In this immunoturbidimetric assay agglutination occurs due to an antigen-antibody reaction between Lp(a) in a sample and anti-Lp(a) antibody adsorbed to latex particles. The agglutination is detected as an absorbance change at 700 nm proportional to the concentration of Lp(a) in the sample. The reagents are stable and ready to use. Lp(a) Calibrator Series, Lp(a) Control and Lipid Controls were used (Randox Laboratories Limited, Crumlin, UK). The assay is applicable to a variety of clinical chemistry analysers, for the results of this study the RX Daytona Plus analyser was used (Randox Laboratories Limited, Crumlin, UK).

Results
Assay range
This immunoturbidimetric assay presented a reportable range of 3 to 106 mg/dL.

Sensitivity
The Limit of Quantitation (LOQ), the Limit of Detection (LOD) and the Limit of Blank were determined consistent with CLSI guidelines EP17-A (table 1).

Prozone
Antigen excess effects were not noted until Lp(a) levels approached 493 mg/dL.

Within run and total precision
Within run precision and total precision, expressed as CV(%), were <4.00 and <4.5 respectively (Table 2). Serum/plasma comparison
The assay was used to compare serum to plasma samples (n=56) collected into tubes containing Li heparin, Na heparin, Na EDTA, K EDTA or citrate. The data was subjected to linear regression analysis and in all cases the correlation coefficient (r) was > 0.996.

Conclusion   
The immunoturbidimetric assay reported here for the determination of Lp(a) in serum/plasma with minimum apo (a) size related bias showed optimal analytical performance. The assay utilises ready- to –use stable reagents which facilitates the application in test settings by simplifying the experimental procedure and reducing handling errors. Its applicability to different automated analysers ensures the reliability, the accuracy of the measurements and facilitates the testing procedure. This represents an excellent analytical tool to facilitate clinical investigation.

References
1. Utermann G, Weber W. Protein composition of Lp(a) lipoprotein from human plasma. FEBS Lett. 1983; 154: 357-361.
2. Bennet A, Di Angelantonio E, Erqou S, Eirikdottir G, Sigurdsson G, Woodward M, Rumley A, Lowe G.D, Danesh J, Gudnason V. Lipoprotein (a) levels and risk of future coronary heart disease: large-scale prospective data. Arch. Intern. Med. 2008; 168: 598-608.
3. Emerging Risk Factors Collaboration, Erqou S, Kaptoge S, Perry P.L, Di Angelantonio E, Thompson A, White I.R, Marcovina S.M, Collins R, Thompson S.G, Danesh J. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality. JAMA. 2009; 302: 412-423.
4. Goldenberg N.A, Bernard T.J, Hillhouse J, Armstrong-Wells J, Galinkin J, Knapp-Clevenger R, Jacobson, L, Marcovina S.M, Manco-Johnson M.J. Elevated lipoprotein(a), small apolipoprotein (a), and the risk of arterial ischemic stroke in North American children. Haematol. 2013; 98: 802-807.
5. McLean J.W, Tomlinson J.E, Kuang W.J, Eaton D.L, Chen E.Y, Fless G.M, Scanu A.M, Lawn R.M. cDNA sequence of human apolipoprotein(a) is homologous to plasminogen. Nature. 1987; 300: 132-137.
6. Tate J.R, Rifai N, Berg K, Couderc R, Dati F, Kostner G.M, Sakurabayashi I, Steinmetz A. International Federation of Clinical Chemistry standardization project for the measurement of lipoprotein(a). Phase I. Evaluation of the analytical performance of lipoprotein(a) assay systems and commercial calibrators. Clin Chem. 1998; 44: 1629-1640.
7. Hajjar K.A, Nachman R.L. The role of lipoprotein(a) in atherogenesis and thrombosis. Annu Rev Med. 1996; 47: 423-442.

Randox Laboratories Limited, Diamond Road, Crumlin, County Antrim, N. Ireland, BT29 4QY, UK
www.randox.com

Interactions of neoplastic cells with each other and the microenvironment are complex. The main factors contributing to intratumoral heterogeneity may be reflected in biomarker expression. The aim is to investigate the spatial intratumoral heterogeneity of Ki-67 immunostains in whole sections of pancreatic neuroendocrine neoplasms. The extent and range of heterogeneity has potential as a prognostic marker.

by Dr Nektarios A. Valous, Dr Frank Bergmann and Dr Niels Halama

Overview
Tumour heterogeneity means that a neoplasm comprises distinct cellular subpopulations that can vary in histology and growth rate. Phenotypic and functional heterogeneity arise among cancer cells within the neoplasm because of genetic change, environmental differences and reversible changes in cell properties [1, 2]. Genomic instability arises through various routes, leaving distinct genomic footprints and differentially affecting tumour evolution and patient outcome [3]. In addition, heterologous cell types within tumours can influence therapeutic response and shape resistance [4]. The interactions of neoplastic cells with each other and the microenvironment are complex. Clinicians assess complex cytological, histological, and morphological characteristics of tissues often in a semi-quantitative manner. In order to understand intratumoral heterogeneity, potentially subtle differences within neoplasms should be quantified.

The main factors contributing to intratumoral heterogeneity include the ischemic gradient within the neoplasm, the action of the microenvironment, mechanisms of intercellular transfer of genetic information, and differential mechanisms of modifications of genetic material/proteins [5]. This may be reflected in the expression of biomarkers and their clinical utility in the context of prognosis/stratification. A rigorous approach for assessing the spatial intratumoral heterogeneity of histological biomarker expression with accuracy and reproducibility is required, since patterns in immunohistochemical images exhibit scale-dependent changes in structure and can be challenging to identify and describe [6–8]. The aim is to determine the implications and prognostic value of observed variations, in a host of clinically relevant neoplastic properties [9].

Case study
It is recognized that proliferative heterogeneity is common in many tumours, including pancreatic neuroendocrine neoplasms [10]. These represent a rather heterogeneous group regarding histology, hormone secretion and functional activity, as well as biological behaviour. Pancreatic neuroendocrine neoplasms are classified as tumours (grade G1 and G2) and carcinomas (grade G3), based on proliferation activity. The latter is determined using a mitotic count in ten high-power fields or determination of fraction of Ki-67 positive cells within a highly proliferative area. In resected neoplasms, the proliferation-dependent tumour grade is shown to be a strong prognostic marker, whereas patient clinical management largely depends on proliferation activity. Key treatment decisions rely on the robust classification of these tumours.

Method
Earlier work has shown the advantages of using spatial statistics in histopathology [11]. A quantitative method from the fields of complex systems and image analysis that is particularly useful for characterizing complex irregular structures is lacunarity. The term lacunarity itself stems from the field of fractal geometry referring to a measure of how patterns fill space [12]. The approach has several theoretical and practical advantages for the assessment of spatial heterogeneity [13]. It is a multiscale technique, its computation is simple to implement, it exhaustively samples the image to quantify scaling changes, the analysis can be used for very sparse data, and the decay of the lacunarity index as a function of window size follows characteristic patterns for random, self-similar and structured spatial arrangements. Compared to previous approaches, the proposed methodology quantifies directly the distributional landscape of proliferative cells and not the textural content of the histological slide, thus providing a more realistic measure of heterogeneity within the sample space of the tumour region.

Workflow
Figure 1 provides an overview of the workflow for measuring the spatial intratumoral heterogeneity of proliferation in pancreatic neuroendocrine neoplasms. Immunohistochemical (IHC) staining for Ki-67 is performed on whole-slide sections taken from original tissue blocks using the avidin-biotin-peroxidase detection system on a fully automated staining facility. On IHC stains for Ki-67, the brown reaction product at the antigen site is in the cell nucleus. The slide is counterstained with hematoxylin to allow evaluation and assessment of staining localization. Glass slides are automatically imaged in bright-field mode. The resulting virtual slides are reviewed by a pathologist for determining the locality of the neoplastic region; areas are marked and large representative sections are cropped. The automated proliferative cell nuclei segmentation workflow is based on background removal, stain vector extraction/color deconvolution, and post-processing operations. Hence, for every virtual slide (large section of tumour region), a segmented image depicting proliferative nuclei is produced.

For measuring the spatial heterogeneity of proliferation using lacunarity, an automated sampling scheme is employed prior to analysis allowing better scrutiny and interpretation, thus keeping computation times manageable. The sampling method aims at capturing the spatial variability of Ki-67 positive cells in the images. Then, lacunarity is computed and subsequently visualized in a double log plot as a function of scale. These plots explicitly characterize the spatial organization of images and measure space filling capacity. From the plots, mean, median, and mode lacunarity curves are computed. These metrics capture the variability (or lack of) of the curves for the sampled sections. To ascertain that lacunarity describes the spatial organization of proliferation, the three metrics are used for partitioning the neoplasms into conceptually meaningful clusters. This is achieved by performing unsupervised learning using the k-means algorithm. First, their Mahalanobis distance is computed and then using principal component analysis vectors are decorrelated by projection into a subspace that minimizes reconstruction error in the mean squared sense. Finally, a phenomenological heterogeneity index is computed from the spatial distribution in order to provide direct numerical values.

Impact and outlook
Phenotypic heterogeneity that stems from genetic/non-genetic determinants constitutes a major source of therapeutic resistance, and is an important clinical obstacle [14]. Tissue architecture is generally not reflected in molecular assays, rendering this information underused. Heterogeneity in histological expression of biomarkers has been noted in earlier studies. However, experimental exploration has been limited by a lack of conceptual framework and tools. The critical bottleneck has become the development of computational methods to analyse, integrate, and connect data to prognostic and actionable clinical information [15].

The architectural complexity of immunohistological images has shown that single measurements are often insufficient for characterization. The selection of a region of interest as a surrogate for the complete complex structure is prey to selection bias and subsequent loss of reproducibility and precision. Especially for the neuroendocrine pancreatic tumours, the inhomogeneity of distribution depends not only on percentage content of proliferation phase but also on how the phase fills the space. An increased degree of spatial proliferative heterogeneity is observed in certain neoplasms comparing to others with similar histological grade. Whether this is a sign of different tumour biology and subsequently an association with a more benign or malignant clinical course needs to be investigated further. The approach provides an increased level of granularity for discerning different levels of spatial heterogeneity in biomarker expression, since manual inspection can be cumbersome and may not resolve finer differences. The extent and range of heterogeneity has the potential to be evaluated as a prognostic marker, e.g. for the evaluation of the clinical course utilizing the construction of survival curves. This heterogeneity is also most likely to play a role in different aspects of the clinical course. Clinical trials should incorporate such studies on heterogeneity so that the impact on therapeutic effectiveness can be understood. For practical reasons, the heterogeneity index outputted in the final step of the analysis is desirable when a single numerical value is required, e.g. in direct assessments or comparisons for the automated ranking of cases in order of increasing/decreasing heterogeneity.

In summary, the lacunarity morphometric provides information about the distribution of Ki-67 immunolabelling that corresponds to the degree of spatial organization of proliferation. This reflects a general approach with potential importance in clinical work, which is relevant to other solid tumours and a vast array of biomarkers. The additional level of understanding the distributional patterns of specific biomarkers holds promise for providing valuable information in a clinical setting. Drawing upon the richness of histopathological information and merits of computational biomedicine, the approach removes qualitative ambiguities and uncovers salient features for use in future studies of clinical relevance.

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The authors
Nektarios A. Valous*¹ PhD, Frank Bergmann² MD, Niels Halama³ MD, PhD
¹Applied Tumor Immunity Clinical
Cooperation Unit, National Center for Tumor Diseases, German Cancer Research Center, Heidelberg, Germany
²Institute of Pathology, Heidelberg
University Hospital, Heidelberg, Germany
³Department of Medical Oncology, National Center for Tumor Diseases,
Heidelberg University Hospital, Heidelberg, Germany

*Corresponding author
E-mail: nek.valous@nct-heidelberg.de