Bacterial vaginosis--a laboratory and clinical diagnostics enigma

Diagnosing bacterial vaginosis (BV) has long been based on the clinical criteria of Amsel et al., whereby three of four defined criteria must be satisfied. Though there are other criteria and scoring methods which function well in comparison (i.e. Nugent scoring), it is not certain that they will always identify the same category of patients. Point-of-care methods based on various combinations of microbial products, presence of RNA, or more complex laboratory instrumentations such as sensor arrays, have also been introduced for the diagnosis of BV. No method for diagnosing BV can at present be regarded as the best. It could be that--based partly on tacit knowledge on the part of the clinical investigators scoring in the clinic--various scoring systems have been chosen to fit a particular BV-related problem in a particular population. In this review we critically examine these pertinent issues influencing clinical scoring and laboratory diagnostics of BV.     

Commercial molecular diagnostics in the U.S.: The Human Genome Project to the clinical laboratory

Molecular diagnosis is the detection of pathogenic mutations in DNA and RNA samples to aid in detection, diagnosis, subclassification, prognosis, and monitoring response to therapy. Principles underlying nucleic-based diagnosis originate from localization, identification, and characterization of genes responsible for human disease. Clinical molecular genetics is now part of the mainstream of medical care in the United States. All commercial clinical reference laboratories now have a molecular genetic diagnostic unit, many of which are in contractual agreement with third party payers to provide services. Gene discovery provides valuable insight into the mechanisms of disease processes and gene-based markers will enable clinicians to study disease predisposition, as well as improved methods for diagnoses, prognosis, and monitoring of therapy. The broad range of mutation spectrum and type performed in the clinical laboratory requires the use of multiple technologies rather than a single typing platform. Platform choice depends on such diverse factors as local expertise, test volume, economies of scale, R&D budget, and royalties. Test validation is a major hurdle and positive control samples are often not readily available. Oversight and the regulatory environment for clinical molecular genetics laboratories in the United States are evolving rapidly. Several government agencies and private organizations are currently involved in revision of specific laboratory standards, including the Secretary's Advisory Committee on Genetic Testing (SACGT), Food and Drug Administration (FDA), Center for Disease Control (CDC), College of American Pathologists (CAP), American College of Medical Genetics (ACMG), and the individual states.     

eDiVA—Classification and prioritization of pathogenic variants for clinical diagnostics

Mendelian diseases have shown to be an and efficient model for connecting genotypes to phenotypes and for elucidating the function of genes. Whole‐exome sequencing (WES) accelerated the study of rare Mendelian diseases in families, allowing for directly pinpointing rare causal mutations in genic regions without the need for linkage analysis. However, the low diagnostic rates of 20–30% reported for multiple WES disease studies point to the need for improved variant pathogenicity classification and causal variant prioritization methods. Here, we present the exome Disease Variant Analysis (eDiVA; http://ediva.crg.eu ), an automated computational framework for identification of causal genetic variants (coding/splicing single‐nucleotide variants and small insertions and deletions) for rare diseases using WES of families or parent–child trios. eDiVA combines next‐generation sequencing data analysis, comprehensive functional annotation, and causal variant prioritization optimized for familial genetic disease studies. eDiVA features a machine learning‐based variant pathogenicity predictor combining various genomic and evolutionary signatures. Clinical information, such as disease phenotype or mode of inheritance, is incorporated to improve the precision of the prioritization algorithm. Benchmarking against state‐of‐the‐art competitors demonstrates that eDiVA consistently performed as a good or better than existing approach in terms of detection rate and precision. Moreover, we applied eDiVA to several familial disease cases to demonstrate its clinical applicability.     

A look to the future of animal clinical biochemistry: Implications for diagnostics and research

The changing environment in the medical biochemistry arena as a result of new and concerted pressures for cost containment will have and is having its inevitable effect on the field of animal clinical biochemistry. The animal clinical biochemist must be acutely aware of the changes engendered by these pressures and be prepared to respond in a meaningful way. First and foremost, the animal clinical biochemist must be positioned as a scientist with a unique capability to cross disciplinary lines as befits the needs to understand interspecies nuances. As a corollary, there is a need for the animal clinical biochemist to not only keep abreast of new developments but to be a generator of new knowledge in the field. This then implies that research and dissemination of new knowledge is an inherent responsibility of those in the field. In this way, the animal clinical biochemist is positioned as an independent scientist/principal investigator in a broad range of studies involving animals. This further implies that animal clinical biochemists must broaden their knowledge of clinical medicine to be able to converse freely in the language of medicine. Numerous new vistas are described and which can be exploited to advance the field and the scope of activities for animal clinical biochemists. Among these are the Point-of-Care systems, new approaches to diabetes management, thyroid disease, autoimmune disease and tumour markers. The list of additional areas is extensive; markers of inflammation, markers of nutritional disease or deficiency, DNA probes in inherited disease, DNA probes of infectious disease. All of these areas are ripe for new ideas and advances in knowledge needing only the imaginative efforts of the animal clinical biochemist.     

Blood culture diagnostics: a Nordic multicentre survey comparison of practices in clinical microbiology laboratories

ObjectivesAccurate and rapid microbiological diagnostics are crucial to tailor treatment and improve outcomes in patients with severe infections. This study aimed to assess blood culture diagnostics in the Nordic countries and to compare them with those of a previous survey conducted in Sweden in 2013.MethodsAn online questionnaire was designed and distributed to the Nordic clinical microbiology laboratories (CMLs) (n = 76) in January 2018.ResultsThe response rate was 64% (49/76). Around-the-clock incubation of blood cultures (BCs) was supported in 82% of the CMLs (40/49), although in six of these access to the incubators around the clock was not given to all of the cabinets in the catchment area, and 41% of the sites (20/49) did not assist with satellite incubators. Almost half (49%, 24/49) of the CMLs offered opening hours for ≥10 h during weekdays, more commonly in CMLs with an annual output ≥30 000 BCs. Still, positive BCs were left unprocessed for 60–70% of the day due to restrictive opening hours. Treatment advice was given by 23% of CMLs (11/48) in ≥75% of the phone contacts. Rapid analyses (species identification and susceptibility testing with short incubation), performed on aliquots from positive cultures, were implemented in 18% of CMLs (9/49). Compared to 2013, species identification from subcultured colonies (<6 h) had become more common.ConclusionsCMLs have taken action to improve aspects of BC diagnostics, implementing satellite incubators, rapid species identification and susceptibility testing. However, the limited opening hours and availability of clinical microbiologists are confining the advantages of these changes.     

panelcn.MOPS: Copy‐number detection in targeted NGS panel data for clinical diagnostics

Targeted next‐generation‐sequencing (NGS) panels have largely replaced Sanger sequencing in clinical diagnostics. They allow for the detection of copy‐number variations (CNVs) in addition to single‐nucleotide variants and small insertions/deletions. However, existing computational CNV detection methods have shortcomings regarding accuracy, quality control (QC), incidental findings, and user‐friendliness. We developed panelcn.MOPS, a novel pipeline for detecting CNVs in targeted NGS panel data. Using data from 180 samples, we compared panelcn.MOPS with five state‐of‐the‐art methods. With panelcn.MOPS leading the field, most methods achieved comparably high accuracy. panelcn.MOPS reliably detected CNVs ranging in size from part of a region of interest (ROI), to whole genes, which may comprise all ROIs investigated in a given sample. The latter is enabled by analyzing reads from all ROIs of the panel, but presenting results exclusively for user‐selected genes, thus avoiding incidental findings. Additionally, panelcn.MOPS offers QC criteria not only for samples, but also for individual ROIs within a sample, which increases the confidence in called CNVs. panelcn.MOPS is freely available both as R package and standalone software with graphical user interface that is easy to use for clinical geneticists without any programming experience. panelcn.MOPS combines high sensitivity and specificity with user‐friendliness rendering it highly suitable for routine clinical diagnostics.     

Diversity of virulence patterns among shiga toxin-producing Escherichia coli from human clinical cases-need for more detailed diagnostics

Intestinal infections due to shiga toxin-producing Escherichia coli bacteria (STEC) reveal a broad range of clinical symptoms and a large scale of virulence properties of the respective pathogens. The question whether all STEC variants or only a particular group of them need to be considered for clinical and epidemiological purposes was answered throughout this study. Using the PCR technique for the identification of 25 different virulence-associated genes, 266 E. coli strains belonging to 81 different E. coli serotypes from various clinical origins were investigated. A great genetic diversity of the virulence properties and a broad range of virulence marker combinations have been identified. However, distinct virulence marker combinations (e.g. Stx2/LEE/pO157 as well as Stx2dac/pO113) were found to be associated with the same notified clinical symptoms (e.g. HUS). Such an association speaks either for the "shiga toxin-only concept" or for several redundant, but clinically or epidemiologically important virulence properties.     

Change-point detection method for clinical decision support system rule monitoring

A clinical decision support system (CDSS) helps clinicians to manage patients, but malfunctions of its components or other systems on which it depends may affect its intended functions. Monitoring the system and detecting changes in its behavior that may indicate the malfunction can help to avoid any potential costs associated with its improper operation. In this paper, we investigate the problem of detecting changes in the CDSS operation, in particular its monitoring and alerting subsystem, by monitoring its rule firing counts. We aim to screen and detect changes in real-time, that is whenever a new datum (rule firing count) arrives, we want to have a score indicating how likely there is a change in the system. We develop a new method based on Seasonal-Trend decomposition with locally weighted regression (Loess) and likelihood ratio statistics to detect the changes. Experiments on daily rule-firing-count data collected from a real CDSS and known change-points show that our method improves the detection performance when compared with existing change-point detection methods.     

Sequencing‐based microsatellite instability testing using as few as six markers for high‐throughput clinical diagnostics

Microsatellite instability (MSI) testing of colorectal cancers (CRCs) is used to screen for Lynch syndrome (LS), a hereditary cancer‐predisposition, and can be used to predict response to immunotherapy. Here, we present a single‐molecule molecular inversion probe and sequencing‐based MSI assay and demonstrate its clinical validity according to existing guidelines. We amplified 24 microsatellites in multiplex and trained a classifier using 98 CRCs, which accommodates marker specific sensitivities to MSI. Sample classification achieved 100% concordance with the MSI Analysis System v1.2 (Promega) in three independent cohorts, totaling 220 CRCs. Backward–forward stepwise selection was used to identify a 6‐marker subset of equal accuracy to the 24‐marker panel. Assessment of assay detection limits showed that the 24‐marker panel is marginally more robust to sample variables than the 6‐marker subset, detecting as little as 3% high levels of MSI DNA in sample mixtures, and requiring a minimum of 10 template molecules to be sequenced per marker for >95% accuracy. BRAF c.1799 mutation analysis was also included to streamline LS testing, with all c.1799T>A variants being correctly identified. The assay, therefore, provides a cheap, robust, automatable, and scalable MSI test with internal quality controls, suitable for clinical cancer diagnostics.     

A clinical and genetic overview of 18 years neurofibromatosis type 1 molecular diagnostics in the Netherlands

NF1 mutations are the underlying cause of neurofibromatosis type 1 (NF1), a neuro‐cardio‐facio‐cutaneous syndrome (NCFC). Because of the clinical overlap between NCFCs, genetic analysis of NF1 is necessary to confirm a clinical diagnosis NF1. This report describes the clinical and genetic findings of 18 years of NF1 molecular diagnostics in the Netherlands. A pathogenic mutation was found in 59.3% (1178/1985) of the index patients, mostly de novo (73.8%). The majority of the index patients (64.3%) fulfilled the National Institute of Health NF1 criteria, a pathogenic mutation was found in 80.9% of these patients. Seventy‐four percent of the index patients with an NF1 pathogenic mutation and not fulfilling the NF1 criteria is <12 years, in agreement with the fact that some NF1 symptoms appear after puberty. Genotype–phenotype correlations were studied for 527 index patients. NF1 patients with a type 1 microdeletion have a sixfold higher risk of special education vs NF1 patients with an intragenic mutation. No evidently milder NF1 phenotype for patients with a missense mutation was observed. Forty‐six prenatal analyses were performed in 28 (2.4%) families, of which 29 (63%) showed heterozygosity for the familial pathogenic mutation. This indicates that there is a need for prenatal NF1 testing.     

Diagnosing infections—current and anticipated technologies for point-of-care diagnostics and home-based testing

In recent years, we have witnessed many transitions in healthcare systems around the globe. For example, population expansion and ageing, and the human immunodeficiency virus (HIV)-AIDS epidemics, have exerted pressure to decentralize the practice of healthcare outside of traditional settings to bring care to those in need. Upstream of patient management, diagnosis is aimed at adequately orienting medical decisions, and considerable efforts have been made to make this process faster and more efficient. However, there are several diseases and medical conditions that may/will benefit from technologies and tests that can be performed closer to the patient, at the point of care or even in the home. In this review, and in light of the paradox that technology and assay developers and healthcare officials must take into consideration for advancing human health in developed and developing countries, we present an overview of rapid diagnosis of infectious diseases at the point of care and of technologies that may contribute to enhancement of the worldwide point-of-care testing market.     

Clinical efficacy of a next‐generation sequencing gene panel for primary immunodeficiency diagnostics

Primary immunodeficiencies (PIDs) are rare monogenic inborn errors of immunity that result in impairment of functions of the human immune system. PIDs have a broad phenotype with increased morbidity and mortality, and treatment choices are often complex. With increased accessibility of next‐generation sequencing (NGS), the rate of discovery of genetic causes for PID has increased exponentially. Identification of an underlying monogenic diagnosis provides important clinical benefits for patients with the potential to alter treatments, facilitate genetic counselling, and pre‐implantation diagnostics. We investigated a NGS PID panel of 242 genes within clinical care across a range of PID phenotypes. We also evaluated Phenomizer to predict causal genes from human phenotype ontology (HPO) terms. Twenty‐seven participants were recruited, and a total of 15 reportable variants were identified in 48% (13/27) of the participants. The panel results had implications for treatment in 37% (10/27) of participants. Phenomizer identified the genes harbouring variants from HPO terms in 33% (9/27) of participants. This study shows the clinical efficacy that genetic testing has in the care of PID. However, it also highlights some of the disadvantages of gene panels in the rapidly moving field of PID genomics and current challenges in HPO term assignment for PID.     

Application of next generation sequencing for the detection of human viral pathogens in clinical specimens

BackgroundNext generation sequencing (NGS) is a new technology that can be used for broad detection of infectious pathogens and is rapidly becoming an essential platform in clinical laboratories. It is not known how NGS will displace or enhance gold standard methodologies in infectious disease diagnosis.ObjectivesTo investigate the feasibility and application of NGS technology in public health laboratories and compare NGS technology with conventional methods.Study designIllumina MiSeq system was used to detect viral pathogens alongside other conventional virology methods using typical clinical specimen matrices. Sixteen clinical specimens and two CDC proficiency panels containing seventeen specimens were analyzed.ResultsKnown pathogenic viral nucleic acid was positively identified in all clinical specimens, correlating and building upon results obtained by more conventional laboratory methods. Sequencing depths ranged from 0.008X to 319 and genome coverage ranged from 0.6% to 99.9%. To substantiate the described methods used to analyze data derived from clinical specimens, the results of a clinical proficiency panel are also presented.DiscussionOur results reveal true scarcity of known pathogenic viral nucleic acids in clinical specimens. NGS outperforms more conventional detection methods in this study by turnaround time as well as the improved depth of knowledge in regards to serotyping and drug resistance.     

CytoBas: Precision component-resolved diagnostics for allergy using flow cytometric staining of basophils with recombinant allergen tetramers

Background

Diagnostic tests for allergy rely on detecting allergen-specific IgE. Component-resolved diagnostics incorporate multiple defined allergen components to improve the quality of diagnosis and patient care.

Objective

To develop a new approach for determining sensitization to specific allergen components that utilizes fluorescent protein tetramers for direct staining of IgE on blood basophils by flow cytometry.

Methods

Recombinant forms of Lol p 1 and Lol p 5 proteins from ryegrass pollen (RGP) and Api m 1 from honeybee venom (BV) were produced, biotinylated, and tetramerized with streptavidin-fluorochrome conjugates. Blood samples from 50 RGP-allergic, 41 BV-allergic, and 26 controls were incubated with fluorescent protein tetramers for flow cytometric evaluation of basophil allergen binding and activation.

Results

Allergen tetramers bound to and activated basophils from relevant allergic patients but not controls. Direct fluorescence staining of Api m 1 and Lol p 1 tetramers had greater positive predictive values than basophil activation for BV and RGP allergy, respectively, as defined with receiver operator characteristics (ROC) curves. Staining intensities of allergen tetramers correlated with allergen-specific IgE levels in serum. Inclusion of multiple allergens coupled with distinct fluorochromes in a single-tube assay enabled rapid detection of sensitization to both Lol p 1 and Lol p 5 in RGP-allergic patients and discriminated between controls, BV-allergic, and RGP-allergic patients.

Conclusion

Our novel flow cytometric assay, termed CytoBas, enables rapid and reliable detection of clinically relevant allergic sensitization. The intensity of fluorescent allergen tetramer staining of basophils has a high positive predictive value for disease, and the assay can be multiplexed for a component-resolved and differential diagnostic test for allergy.

     

A modified artificial immune system based pattern recognition approach--an application to clinical diagnostics

Objective

This paper introduces a modified artificial immune system (AIS)-based pattern recognition method to enhance the recognition ability of the existing conventional AIS-based classification approach and demonstrates the superiority of the proposed new AIS-based method via two case studies of breast cancer diagnosis.

Methods and materials

Conventionally, the AIS approach is often coupled with the k nearest neighbor (k-NN) algorithm to form a classification method called AIS-kNN. In this paper we discuss the basic principle and possible problems of this conventional approach, and propose a new approach where AIS is integrated with the radial basis function - partial least square regression (AIS-RBFPLS). Additionally, both the two AIS-based approaches are compared with two classical and powerful machine learning methods, back-propagation neural network (BPNN) and orthogonal radial basis function network (Ortho-RBF network).

Results

The diagnosis results show that: (1) both the AIS-kNN and the AIS-RBFPLS proved to be a good machine leaning method for clinical diagnosis, but the proposed AIS-RBFPLS generated an even lower misclassification ratio, especially in the cases where the conventional AIS-kNN approach generated poor classification results because of possible improper AIS parameters. For example, based upon the AIS memory cells of “replacement threshold = 0.3”, the average misclassification ratios of two approaches for study 1 are 3.36% (AIS-RBFPLS) and 9.07% (AIS-kNN), and the misclassification ratios for study 2 are 19.18% (AIS-RBFPLS) and 28.36% (AIS-kNN); (2) the proposed AIS-RBFPLS presented its robustness in terms of the AIS-created memory cells, showing a smaller standard deviation of the results from the multiple trials than AIS-kNN. For example, using the result from the first set of AIS memory cells as an example, the standard deviations of the misclassification ratios for study 1 are 0.45% (AIS-RBFPLS) and 8.71% (AIS-kNN) and those for study 2 are 0.49% (AIS-RBFPLS) and 6.61% (AIS-kNN); and (3) the proposed AIS-RBFPLS classification approaches also yielded better diagnosis results than two classical neural network approaches of BPNN and Ortho-RBF network.

Conclusion

In summary, this paper proposed a new machine learning method for complex systems by integrating the AIS system with RBFPLS. This new method demonstrates its satisfactory effect on classification accuracy for clinical diagnosis, and also indicates its wide potential applications to other diagnosis and detection problems.     

Purified natural and recombinant Fel d 1 and cat albumin in in vitro diagnostics for cat allergy

BACKGROUND: Current diagnostics and therapeutics for cat allergy are based on cat epithelial extracts originating from highly variable source materials. This gives rise to several problems: variability of allergen composition, contamination with house dust mite allergens, and potential transfer of pathogenic agents. OBJECTIVE: The aim of this study was to investigate the feasibility of replacing cat epithelial extracts with purified natural or recombinant allergens. METHODS: Sera (n = 509) were selected on the basis of a positive cat RAST result and tested in a RAST for IgE reactivity to purified Fel d 1, cat albumin (CA), or both. The analysis was performed with both natural and recombinant allergens. In addition, some sera were further analyzed by means of immunoblotting. A serum pool was used for cat RAST inhibition with purified natural and recombinant allergens as inhibitors. RESULTS: Natural and recombinant Fel d 1 caused very similar results: 94.1% and 96.1% positive test results, respectively. In general, the negative sera were low responders to cat extract. The addition of CA (16.7% positive sera) resulted in a decrease in the number of discrepencies between purified allergens and whole extract to 2.8%. Only for 2% of all sera, sensitization to cat was largely explained by IgE reactivity to CA. IgE reactivity to Fel d 1 accounts for 88% of the total IgE response to cat allergens, as was demonstrated by RAST, with Fel d 1 concentrations nearing saturation. Recombinant Fel d 1 performed equally well in the RAST analysis. Recombinant CA was succesfully expressed in the yeast Pichia pastoris, and its immune reactivity closely resembled that of its natural counterpart. CONCLUSION: Natural and recombinant Fel d 1 and CA are good candidates for replacing ill-defined cat dander extracts in diagnostics for cat allergy. Although CA is not essential for the vast majority of cat-sensitized patients, some subjects are selectively sensitized to this serum protein.