A framework for implementing best laboratory practices for non-integrated point of care tests in low resource settings.

The method we respond to pandemics is still inadequate for dealing with the point of care testing (POCT) requirements of the next large epidemic. The proposed framework highlights the importance of having defined policies and procedures in place for non-integrated POCT to protect patient safety. In the absence of a pathology laboratory, this paradigm may help in the supply of diagnostic services to low-resource centers. A review of the literature was used to construct this POCT framework for non-integrated and/or unconnected devices. It also sought professional advice from the Chemical Pathology faculty, quality assurance laboratory experts and international POCT experts from the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). Our concept presents a comprehensive integrated and networked approach to POCT with direct and indirect clinical laboratory supervision, particularly for outpatient and inpatient care in low-resource health care settings.

Calculated LDL-cholesterol: comparability of the extended Martin/Hopkins, Sampson/NIH, Friedewald and four other equations in South African patients.

AIMS: The reference method for low-density lipoprotein-cholesterol (LDL-C) is ultracentrifugation. However, this is unsuitable for routine use and therefore direct LDL-C assays and predictive equations are used. In this study, we compared the Friedewald, extended Martin/Hopkins, Sampson/NIH and four other equations to a direct assay. METHODS: We analysed 44 194 lipid profiles from a mixed South African population. The LDL-C predictive equations were compared with direct LDL-C assay and analysed using non-parametric statistics and error grid analysis. RESULTS: Both the extended Martin/Hopkins and Sampson/NIH equations displayed the best correlation with direct LDL-C in terms of desirable bias and total allowable error. The direct LDL-C assay classified 13.9% of patients in the low LDL-C (1.0-1.8 mmol/L) category, in comparison to the extended Martin/Hopkins equation (13.4%), the Sampson equation (14.6%) and the Friedewald equation (16.0%). The Sampson/NIH was least biased in the low LDL-C category (<1.8 mmol/L) and produced the least overall clinically relevant errors compared with the extended Martin/Hopkins and Friedewald equations in the low-LDL-C category. CONCLUSIONS: Our findings suggest only a marginal difference between the extended Martin/Hopkins equation and the Sampson/NIH equation with the use of the Beckman Coulter DxC800 analyser in this population. The results favour the implementation of the Sampson/NIH equation when the Beckman Coulter DxC analyser is used, but the extended Martin/Hopkins may also be safely implemented. Both of these equations performed significantly better than the Friedewald equation. We recommend that patients be monitored using one of these methods and that each laboratory perform its own validation of either equation to ensure continuation and accuracy, and to prevent between-method variation.

Neonatal presentation of a patient with Liddle syndrome, South Africa.

Introduction: Liddle syndrome is an autosomal dominantly inherited disorder usually arising from single mutations of the genes that encode for the alpha, beta and gamma epithelial sodium channel (ENaC) subunits. This leads to refractory hypertension, hypokalaemia, metabolic alkalosis, hyporeninaemia and hypoaldosteronism, through over-activation of the ENaC. Case presentation: We describe a 5-day old neonate who presented with severe hypernatraemic dehydration requiring admission to Steve Biko Academic Hospital in South Africa in 2012. Further evaluation revealed features in keeping with Liddle syndrome. Two compound heterozygous mutations located at different subunits encoding the ENaC were detected following genetic sequencing done in 2020. The severe clinical phenotype observed here could be attributed to the synergistic effect of these known pathological mutations, but may also indicate that one of the other variants detected has hitherto undocumented pathological effects. Management and outcome: This child's treatment course was complicated by poor adherence to therapy, requiring numerous admissions over the years. Adequate blood pressure control was achieved only after the addition of amiloride at the end of 2018, which raised the suspicion of an ENaC abnormality. Conclusion: To our knowledge, this is the first Liddle syndrome case where a combined effect from mutations resulted in severe disease. This highlights the importance of early recognition and management of this highly treatable genetic disease to prevent the grave sequelae associated with long-standing hypertension. Whole exome sequencing may assist in the detection of known mutations, but may also unveil new potentially pathological variants. What this study adds: This study highlights the importance of developing a high index of suspicion of tubulopathy such as Liddle syndrome for any child presenting with persistent hypertension associated with hypokalaemic metabolic alkalosis.

Performance of equations for calculated LDL-C in hypertriglyceridaemia: Which one correlates best with directly measured LDL-C?

BACKGROUND: The gold standard for measuring LDL-C is impractical and direct measurements have numerous shortcomings. Older predictive equations are used only with triglycerides (TG's) below 4.52 mmol/L. We evaluated the newer equations validated for use in hypertriglyceridaemia by comparison with direct LDL-C. MATERIALS AND METHODS: Datasets from two platforms (Abbott Architect and Roche Cobas) comprised of a large cohort of 64,765 individuals were used to compare the Sampson-National Institutes of Health 2 (S-NIH2) and Extended Martin-Hopkins (E-MH) equations for LDL-C with direct LDL-C (dLDL-C) assays. RESULTS: With TG's of 4.52-9.04 mmol/L the S-NIH2 equation tended to calculate lower values than measured by dLDL-C and the E-MH equation calculated higher values. Both equations correlated better with the dLDL-C measured on Abbott than Roche with the E-MH equation having more values falling within acceptable concordance levels on both platforms. CONCLUSION: The E-MH equation correlates better with dLDL-C than the S-NIH2 on both platforms with TG levels up to 9.04 mmol/L. With hypertriglyceridaemia, the E-MH equation is less likely than the S-NIH2 equation to underestimate LDL-C when compared to the dLDL-C and will be less likely to underdiagnose patients with LDL-C levels requiring treatment according to current guidelines.

25-Hydroxycholecalciferol Inhibits Cell Growth and Induces Apoptosis in SiHa Cervical Cells via Autocrine Vitamin D Metabolism.

Preclinical studies show that the anticancer actions of vitamin D metabolites are mediated by apoptosis, inhibition of cell proliferation and induction of cell cycle arrest. Cervical cancer cells express an autocrine vitamin D metabolising system (VDMS) comprised of a vitamin D receptor, vitamin D catabolic enzyme (CYP24A1), and the activating enzyme of 25-hydroxycholecalciferol (25(OH)D3), CYP27B1. We assessed the anticancer effects of 25(OH)D3 at clinically relevant concentrations on a cervical squamous cell cancer cell line, SiHa. We evaluated cell health parameters (cell count, viability, and cell cycle), cell death modes (apoptosis, autophagic-dependent death, and necrosis by flow cytometry and transmission electron microscopy), and autocrine VDMS gene and protein expression by qPCR and Western blot, respectively. Our study demonstrates that physiological and supraphysiological doses of 25(OH)D3 inhibit cell growth and viability and induce biochemical and morphological apoptosis in SiHa cells. These growth effects are mediated by alteration in the VDMS gene and protein expression, with prominent negative feedback at supraphysiological treatment dose. These data identify promising therapeutic potential of 25(OH)D3 in cervical cancer, which warrants further clinical translational investigations.

Best practice for LDL-cholesterol: when and how to calculate.

The lipid profile is important in the risk assessment for cardiovascular disease. The lipid profile includes total cholesterol, high-density lipoprotein (HDL)-cholesterol, triglycerides (TGs) and low-density lipoprotein (LDL)-cholesterol (LDL-C). LDL-C has traditionally been calculated using the Friedewald equation (invalid with TGs greater than 4.5 mmol/L and is based on the assumption that the ratio of TG to cholesterol in very- low-density lipoprotein (VLDL) is 5 when measured in mg /dL). LDL-C can be quantified with a reference method, beta-quantification involving ultracentrifugation and this is unsuitable for routine use. Direct measurement of LDL-C was expected to provide a solution with high TGs. However, this has some challenges because of a lack of standardisation between the reagents and assays from different manufacturers as well as the additional costs. Furthermore, mild hypertriglyceridaemia also distorts direct LDL-C measurements. With the limitations of the Friedewald equation, alternatives have been derived. Newer equations include the Sampson-National Institutes of Health (NIH) equation 2 and the Martin-Hopkins equation. The Sampson-NIH2 equation was derived using beta-quantification in a population with high TG and multiple least squares regression to calculate VLDL-C, using TGs and non-HDL-C as independent variables. These data were used in a second equation to calculate LDL-C. The Sampson-NIH2 equation can be used with TGs up to 9 mmol/L. The Martin-Hopkins equation uses a 180 cell stratification of TG/non-HDL-C to determine the TG:VLDL-C ratio and can be used with TGs up to 4.5 mmol/L. Recently, an extended Martin-Hopkins equation has become available for TGs up to 9.04 mmol/L.This article discusses the best practice approach to calculating LDL-C based on the available evidence.

Comparability of calculated LDL-C with directly measured LDL-C in selected paediatric and adult cohorts.

BACKGROUND AND AIMS: The gold standard for measuring LDL-C is impractical for routine use while direct measurements have numerous shortcomings. This study investigated the correlation of predictive equations with currently used enzymatic assays in populations where these have historically proven unreliable to determine whether equations may be used interchangeably. No reference measure was available for comparison in this study. MATERIALS AND METHODS: We examined two analytical datasets from different platforms to evaluate the correlation of predictive equations for LDL-C (Friedewald, Sampson-NIH2, Martin-Hopkins, Extended Martin-Hopkins, Hattori and Anandaraja) with direct LDL-C assays in a large paediatric (n = 7598) and an adult cohort with uncontrolled diabetes (n = 57165). Non-parametric statistics were used for comparison. RESULTS: In the paediatric cohort, the Sampson-NIH2 equation correlated best with the direct LDL-C assays with the most values falling within desirable bias (35.9-44%) and TEa (68.6-72.9%) and the lowest RMSE (0.5904-0.6138) across platforms, but tended to underestimate LDL-C levels. The Martin-Hopkins equation is less likely to underestimate these values. In diabetes, the Martin-Hopkins equation correlated the best with values falling within acceptable bias (40.2-50.5%) and TEa (75-80.6%). In hypertriglyceridaemia the Extended Martin-Hopkins equation correlates best with the direct LDL-C assays. CONCLUSION: Different measurement platforms influence the results of predictive equations and directly measured LDL-C. We propose utilising the Martin-Hopkins equation as an alternative to dLDL-C assays in adults with diabetes and for screening purposes in paediatric populations to avoid underestimating cardiovascular risk.

How should low-density lipoprotein cholesterol be calculated in 2022?

PURPOSE OF REVIEW: The reference method for low-density lipoprotein-cholesterol (LDL-C) quantitation is ß-quantification, a technically demanding method that is not convenient for routine use. Indirect calculation methods to estimate LDL-C, including the Friedewald equation, have been used since 1972. This calculation has several recognized limitations, especially inaccurate results for triglycerides (TG) >4.5 mmol/l (>400 mg/dl). In view of this, several other equations were developed across the world in different datasets.The purpose of this review was to analyze the best method to calculate LDL-C in clinical practice by reviewing studies that compared equations with measured LDL-C. RECENT FINDINGS: We identified 45 studies that compared these formulae. The Martin/Hopkins equation uses an adjustable factor for TG:very low-density lipoprotein-cholesterol ratios, validated in a large dataset and demonstrated to provide more accurate LDL-C calculation, especially when LDL <1.81 mmol/l (<70 mg/dl) and with elevated TG. However, it is not in widespread international use because of the need for further validation and the use of the adjustable factor. The Sampson equation was developed for patients with TG up to 9 mmol/l (800 mg/dl) and was based on ß-quantification and performs well on high TG, postprandial and low LDL-C samples similar to direct LDL-C. SUMMARY: The choice of equation should take into the level of triglycerides. Further validation of different equations is required in different populations.

Comparability of 11 different equations for estimating LDL cholesterol on different analysers.

OBJECTIVES: Low-density lipoprotein cholesterol (LDL-C) estimation is critical for risk classification, prevention and treatment of atherosclerotic cardiovascular disease (ASCVD). Predictive equations and direct LDL-C are used. We investigated the comparability between the Martin/Hopkins, Sampson, Friedewald and eight other predictive equations on two analysers, to determine whether the equation or analyser influences predicted LDL-C result. METHODS: In two unpaired datasets, 9,995 lipid profiles were analysed by the Abbott Architect and 4,782 by the Roche Cobas analysers. Non-parametric statistics and Bland Altman plots were used to compare LDL-C. RESULTS: On the Abbott analyser; the Martin/Hopkins, Sampson and Friedewald LDL-C were comparable (median bias ≤1.8%) over a range of 1-4.9 mmol/L. On the Roche platform, Martin/Hopkins LDL-C was comparable to Friedewald (median bias 0.3%) but not to Sampson LDL-C (median bias 25%). In patients with LDL-C <1.8 mmol/L and triglycerides (TG) ≤1.7 mmol/L, predicted LDL-C using Abbott reagents was similar between Martin/Hopkins, Sampson and Friedewald equations but not comparable using Roche reagents. Abbott reagents classified 10-20% of patients in the 1.0-1.8 mmol/L range (Martin/Hopkins 13.4%; Sampson 14.5%; Friedewald 16%; direct LDL-C 13.2%). Roche reagents classified 11-30% in the 1.0-1.8 mmol/L range (Martin/Hopkins 23%; Sampson 11%; Friedewald 25%; direct LDL-C 17%). CONCLUSIONS: Performance of predictive equations is influenced by the choice of analyser for total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and TG. Replacement of the Friedewald equation with Martin/Hopkins estimation to improve quality of LDL-C results can be safely implemented across analysers, whereas caution is advised regarding the Sampson equation.

Application of Single-Domain Antibodies ("Nanobodies") to Laboratory Diagnosis.

Antibodies have proven to be central in the development of diagnostic methods over decades, moving from polyclonal antibodies to the milestone development of monoclonal antibodies. Although monoclonal antibodies play a valuable role in diagnosis, their production is technically demanding and can be expensive. The large size of monoclonal antibodies (150 kDa) makes their re-engineering using recombinant methods a challenge. Single-domain antibodies, such as "nanobodies," are a relatively new class of diagnostic probes that originated serendipitously during the assay of camel serum. The immune system of the camelid family (camels, llamas, and alpacas) has evolved uniquely to produce heavy-chain antibodies that contain a single monomeric variable antibody domain in a smaller functional unit of 12-15 kDa. Interestingly, the same biological phenomenon is observed in sharks. Since a single-domain antibody molecule is smaller than a conventional mammalian antibody, recombinant engineering and protein expression in vitro using bacterial production systems are much simpler. The entire gene encoding such an antibody can be cloned and expressed in vitro. Single-domain antibodies are very stable and heat-resistant, and hence do not require cold storage, especially when incorporated into a diagnostic kit. Their simple genetic structure allows easy re-engineering of the protein to introduce new antigen-binding characteristics or attach labels. Here, we review the applications of single-domain antibodies in laboratory diagnosis and discuss the future potential in this area.

Molecules in pathogenesis: angiotensin converting enzyme 2 (ACE2).

The renin-angiotensin system is mainly associated with the regulation of blood pressure, but recently many other functions of this system have been described. ACE2, an 805-amino acid monocarboxypeptidase type I transmembrane glycoprotein, was discovered in 2000 and has sequence similarity to two other proteins, namely ACE and collectrin. The ACE2 gene is located on Xp22 and is highly polymorphic. ACE2 is expressed in numerous tissues especially the lung alveolar epithelial cells, heart, kidney and gastrointestinal tract. Animal studies have found that ACE2 is central in diseases affecting almost all organ systems, among other cardiac, respiratory, renal and endocrine functions. ACE2 was identified as the cellular contact point for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the global pandemic (COVID-19), and is a potential drug target. SARS-CoV-2 infection has several effects on the renin-angiotensin system and conversely, regulation of this receptor may affect the progress of infection. We describe the genetics and functions of ACE2, explore its various physiological functions in the renin-angiotensin system and discuss its role in the pathophysiology of disease. ACE2 opposes the vasopressor ACE pathway of the renin-angiotensin system by converting angiotensin (Ang) I to Ang (1-9) and Ang II to Ang (1-7) which initiates the vasodilatory pathway. ACE2 may have a protective effect in the lung and kidney as knockout mice display susceptibility to acute respiratory distress and hypertensive nephropathy. Binding of SARS-CoV-2 and the subsequent fusion and downregulation of this pathway during SARS-CoV-2 infection may explain some of the unusual sequelae seen in COVID-19.

Historical perspectives in clinical pathology: Bence Jones protein-early urine chemistry and the impact on modern day diagnostics.

This is the third in the series of historical articles dealing with developments in clinical pathology. Bence Jones proteins are immunoglobulin light chains found in excessive quantities in urine in multiple myeloma and are believed to be one of the first tumour markers ever discovered . Dr Henry Bence Jones is credited with the discovery of this protein in 1847 that bears his name and he can also be regarded as the first chemical pathologist/clinical chemist. Since then, numerous advances and refinements have been made in the measurement and detection of urine light chain proteins which have resulted in the current sensitive serum free light chain assays used today.

Hyperthyroidism in molar pregnancy: ß-HCG levels do not always reflect severity.

BACKGROUND: Molar pregnancy is a complication characterised by abnormal benign or malignant proliferation of trophoblastic cells resulting in markedly elevated ß-hCG (human chorionic gonadotrophin) levels, an established marker for the presence of the disease. Owing to the structural homology between ß-hCG and TSH, the raised ß-hCG can result in secondary hyperthyroidism. METHODS: Two patients aged 20 (Case 1) and 31 years (Case 2) presented to the emergency department within a few days of each other complaining of vaginal bleeding associated with abdominal pain. Ultrasound evaluation, ß-hCG and thyroid function tests were performed on both patients. RESULTS: Both had elevated ß-hCG levels and ultrasound evidence of molar pregnancy and were diagnosed with gestational trophoblastic disease (GTD) associated with hyperthyroidism based on thyroid function test results. Case 1 had lower ß-hCG levels and free T4 levels compared with Case 2 but clinical assessment of the former revealed severe illness and more complicated course with the development of a thyroid storm. Case 2 had ß-hCG levels almost double those of Case 1, yet was stable and her levels decreased much faster, reaching and maintaining undetectable levels. CONCLUSIONS: These cases demonstrate that the ß-hCG levels do not always correlate with disease severity and prognosis in patients with GTD.

Critical evaluation of equations for serum osmolality: Proposals for effective clinical utility.

BACKGROUND: Many studies have assessed the predictive accuracy of serum osmolality equations. Different approaches for selecting a usable equation were compared using thirty published equations and patient data from a regional hospital laboratory. METHODS: Laboratory records were extracted with same-sample results for measured serum osmolality, sodium, potassium, urea and glucose analysed in a regional hospital laboratory between 1/1/2017-31/12/2018. Differences were analysed using Passing-Bablok and difference (Bland-Altman) analysis. Three approaches were compared: the shotgun approach, adjusting for bias, and deriving a novel equation using multivariate analysis. The criteria for success included bias ≤0.7%, a 230 - 400 mOsm/kg range, and osmolal gap (OG) 95% reference limits within ±10 mOsm/kg. RESULTS: The majority of equations produced proportionally negative-biased results. The shotgun approach identified two equations (EQ19, EQ6) with bias ≤0.7% but unworkable OG reference limits. The bias adjustment approach produced several equations with bias ≤ 0.7% and OG reference limits within or equivalent to ±10 mOsm/kg. A novel equation generated by us (1.89Na+ + 1.71 K+ + 1.08 Urea + 1.08 Glucose + 13.7) improved with the adjustment of bias and was not superior to the adjusted published equations. CONCLUSION: Few published equations are immediately usable. Adjustment of bias derives several usable equations of which the best had OG ranges <20 mOsm/kg. We conclude that adjustment of bias can generate equations of equal or superior performance to that of novel equations.

Gene of the month: the 2019-nCoV/SARS-CoV-2 novel coronavirus spike protein.

The year 2020 has seen a major and sustained outbreak of a novel betacoronavirus (severe acute respiratory syndrome (SARS)-coronavirus (CoV)-2) infection that causes fever, severe respiratory illness and pneumonia, a disease called COVID-19. At the time of writing, the death toll was greater than 120 000 worldwide with more than 2 million documented infections. The genome of the CoV encodes a number of structural proteins that facilitate cellular entry and assembly of virions, of which the spike protein S appears to be critical for cellular entry. The spike protein guides the virus to attach to the host cell. The spike protein contains a receptor-binding domain (RBD), a fusion domain and a transmembrane domain. The RBD of spike protein S binds to Angiotensin Converting Enzyme 2 (ACE2) to initiate cellular entry. The spike protein of SARS-CoV-2 shows more than 90% amino acid similarity to the pangolin and bat CoVs and these also use ACE2 as a receptor. Binding of the spike protein to ACE2 exposes the cleavage sites to cellular proteases. Cleavage of the spike protein by transmembrane protease serine 2 and other cellular proteases initiates fusion and endocytosis. The spike protein contains an addition furin cleavage site that may allow it to be 'preactivated' and highly infectious after replication. The fundamental role of the spike protein in infectivity suggests that it is an important target for vaccine development, blocking therapy with antibodies and diagnostic antigen-based tests. This review briefly outlines the structure and function of the 2019 novel CoV/SARS-CoV-2 spike protein S.

Gene of the month: APOL1.

Apolipoprotein L1 (APOL1) is a protein encoded by the APOL1 gene, found only in humans and several primates. Two variants encoding two different isoforms exist for APOL1, namely G1 and G2. These variants confer increased protection against trypanosome infection, and subsequent African sleeping sickness, and also increase the likelihood of renal disease in individuals of African ancestry. APOL1 mutations are associated with increased risk of chronic kidney disease, inflammation, and exacerbation of systemic lupus erythematosus-associated renal dysfunction. This review serves to outline the structure and function of APOL1, as well as its role in several disease outcomes.