The phenotype of 15 cases with rare 8q24.13-q24.3 deletions-A new syndrome or still an enigma?

Diagnosis of rare copy number variants (CNVs) with scarce literature evidence poses a major challenge for interpretation of the clinical significance of chromosomal microarray analysis (CMA) results, especially in the prenatal setting. Bioinformatic tools can be used to assist in this issue; however, this prediction can be imprecise. Our objective was to describe the phenotype of the rare copy number losses encompassing the 8q24.13-q24.3 locus, and to find common features in terms of genomic coordinates, gene content, and clinical phenotypic characteristics. Appropriate cases were retrieved using local databases of two largest Israeli centers performing CMA analysis. In addition, literature and public databases search was performed. Local database search yielded seven new patients with del (8)(q24.13q24.3) (one of these with an additional copy number variant). Literature and public databases search yielded eight additional patients. The cases showed high phenotypic variability, ranging from asymptomatic adults and fetuses with normal ultrasound to patients with autism/developmental delay (6/11 postnatal cases, 54.5%). No clear association was noted between the specific disease-causing/high-pLI gene content of the described del (8)(q24.13q24.3) to neurodevelopmental disorders, except for a possibly relevant locus encompassing the KCNQ3 gene. We present the challenges in classification of rare variants with limited clinical information. In such cases, genotype-phenotype correlation must be assessed with extra-caution and possibly using additional methods to assist the classification, especially in the prenatal setting.

Succinylated Jeffamine ED-2003 coated polycarbonate chips for low-cost analytical microarrays.

Analytical microarrays feature great capabilities for simultaneous detection and quantification of multiple analytes in a single measurement. In this work, we present a rapid and simple method for bulk preparation of microarrays on polycarbonate sheets. Succinylated Jeffamine® ED-2003 was screen printed on polycarbonate sheets to create a polyfunctional shielding layer by baking at 100 °C. After microdispension of capture probes (antibodies, oligonucleotides, or small molecules) in a microarray format, chips were assembled with a flow cell from double-sided tape. It was shown that the shielding layer was firmly coated and suppressed unspecific binding of proteins. Universal applicability was demonstrated by transferring established flow-based chemiluminescence microarray measurement principles from glass slides to polycarbonate chips without loss of analytical performance. Higher chemiluminescence signals could be generated by performing heterogeneous asymmetric recombinase polymerase amplification on polycarbonate chips. Similar results could be shown for sandwich microarray immunoassays. Beyond that, lower inter- and intra-assay variances could be measured for the analysis of Legionella pneumophila Serogroup 1, strain Bellingham-1. Even surface regeneration of indirect competitive immunoassays was possible, achieving a limit of detection of 0.35 ng L-1 for enrofloxacin with polycarbonate microarray chips. Succinylated Jeffamine ED-2003 coated polycarbonate chips have great potential to replace microtiter plates by flow-based chemiluminescence microarrays for rapid analysis. Therefore, it helps analytical microarrays to advance into routine analysis and diagnostics. Graphical abstract ᅟ.

Analytical validation of an ultra low-cost mobile phone microplate reader for infectious disease testing.

Most mobile health (mHealth) diagnostic devices for laboratory tests only analyze one sample at a time, which is not suitable for large volume serology testing, especially in low-resource settings with shortage of health professionals. In this study, we developed an ultra-low-cost clinically-accurate mobile phone microplate reader (mReader), and clinically validated this optical device for 12 infectious disease tests. The mReader optically reads 96 samples on a microplate at one time. 771 de-identified patient samples were tested for 12 serology assays for bacterial/viral infections. The mReader and the clinical instrument blindly read and analyzed all tests in parallel. The analytical accuracy and the diagnostic performance of the mReader were evaluated across the clinical reportable categories by comparison with clinical laboratorial testing results. The mReader exhibited 97.59-99.90% analytical accuracy and <5% coefficient of variation (CV). The positive percent agreement (PPA) in all 12 tests achieved 100%, negative percent agreement (NPA) was higher than 83% except for one test (42.86%), and overall percent agreement (OPA) ranged 89.33-100%. We envision the mReader can benefit underserved areas/populations and low-resource settings in rural clinics/hospitals at a low cost (~$50 USD) with clinical-level analytical quality. It has the potential to improve health access, speed up healthcare delivery, and reduce health disparities and education disparities by providing access to a low-cost spectrophotometer.

Cost Effectiveness of Karyotyping, Chromosomal Microarray Analysis, and Targeted Next-Generation Sequencing of Patients with Unexplained Global Developmental Delay or Intellectual Disability.

BACKGROUND: Genetic diagnosis of unexplained global developmental delay and intellectual disability (GDD/ID) often ends the diagnostic odyssey and can lead to changes in clinical management. OBJECTIVE: The objective of this study was to investigate the cost effectiveness of testing scenarios involving several methods used to diagnose GDD/ID: karyotyping, chromosomal microarray analysis (CMA), and targeted next-generation sequencing (NGS). METHODS: We used decision-tree models to estimate the number of genetic diagnoses, the cost from a payers' perspective in the USA, and the incremental cost per additional genetic diagnosis. Model parameters were taken from peer-reviewed literature and governmental fee schedules. RESULTS: CMA testing results in more genetic diagnoses at an incremental cost of US $2692 per additional diagnosis compared with karyotyping, which has an average cost per diagnosis of US $11,033. Performing both tests sequentially results in the same number of diagnoses, but the total cost is less when CMA testing is done first and karyotyping second. Furthermore, when CMA testing yields a variant of unknown significance, additional genetic diagnoses can be obtained at an incremental cost of US $4220 by CMA testing of both parents, and when parents are not available or the patient had a normal CMA result, targeted NGS of the patient can add diagnoses at a further incremental cost of US $12,295. CONCLUSION: These results provide a cost effectiveness rationale for the use of CMA as the first-tier test for the genetic diagnosis of unexplained GDD/ID and further indicate that testing of both parents may be cost effective when a variant of unknown significance is detected in the patient.

Rapid Isolation and Detection of Exosomes and Associated Biomarkers from Plasma.

Exosomes found in the circulation are a primary source of important cancer-related RNA and protein biomarkers that are expected to lead to early detection, liquid biopsy, and point-of-care diagnostic applications. Unfortunately, due to their small size (50-150 nm) and low density, exosomes are extremely difficult to isolate from plasma. Current isolation methods are time-consuming multistep procedures that are unlikely to translate into diagnostic applications. To address this issue, we demonstrate the ability of an alternating current electrokinetic (ACE) microarray chip device to rapidly isolate and recover glioblastoma exosomes from undiluted human plasma samples. The ACE device requires a small plasma sample (30-50 µL) and is able to concentrate the exosomes into high-field regions around the ACE microelectrodes within 15 min. A simple buffer wash removes bulk plasma materials, leaving the exosomes concentrated on the microelectrodes. The entire isolation process and on-chip fluorescence analysis is completed in less than 30 min which enables subsequent on-chip immunofluorescence detection of exosomal proteins, and provides viable mRNA for RT-PCR analysis. These results demonstrate the ability of the ACE device to streamline the process for isolation and recovery of exosomes, significantly reducing the number of processing steps and time required.

A microcosting and cost-consequence analysis of clinical genomic testing strategies in autism spectrum disorder.

PurposeWhole-exome (WES) and whole-genome sequencing (WGS) increase the diagnostic yield in autism spectrum disorder (ASD) compared to chromosomal microarray (CMA), but there have been no comprehensive cost analyses. The objective was to perform such an assessment of CMA, WES, and WGS and compare the incremental cost per additional positive finding in hypothetical testing scenarios.MethodsFive-year patient and program costs were estimated from an institutional perspective. WES and WGS estimates were based on HiSeq 2500 with an additional WGS estimate for HiSeq X platforms. Parameter uncertainty was assessed with probabilistic and deterministic sensitivity analysis.ResultsThe cost per ASD sample was CAD$1,655 (95% CI: 1,611; 1,699) for WES, CAD$2,851 (95% CI: 2,750; 2,956) for WGS on HiSeq X, and CAD$5,519 (95% CI: 5,244; 5,785) on HiSeq 2500, compared to CAD$744 (95% CI 714, 773) for CMA. The incremental cost was over CAD$25,000 per additional positive finding if CMA was replaced by newer technology.ConclusionWhile costs for WES and WGS remain high, future reductions in material and equipment costs, and increased understanding of newly discovered variants and variants of unknown significance will lead to improved value.

High-throughput and automated diagnosis of antimicrobial resistance using a cost-effective cellphone-based micro-plate reader.

Routine antimicrobial susceptibility testing (AST) can prevent deaths due to bacteria and reduce the spread of multi-drug-resistance, but cannot be regularly performed in resource-limited-settings due to technological challenges, high-costs, and lack of trained professionals. We demonstrate an automated and cost-effective cellphone-based 96-well microtiter-plate (MTP) reader, capable of performing AST without the need for trained diagnosticians. Our system includes a 3D-printed smartphone attachment that holds and illuminates the MTP using a light-emitting-diode array. An inexpensive optical fiber-array enables the capture of the transmitted light of each well through the smartphone camera. A custom-designed application sends the captured image to a server to automatically determine well-turbidity, with results returned to the smartphone in ~1 minute. We tested this mobile-reader using MTPs prepared with 17 antibiotics targeting Gram-negative bacteria on clinical isolates of Klebsiella pneumoniae, containing highly-resistant antimicrobial profiles. Using 78 patient isolate test-plates, we demonstrated that our mobile-reader meets the FDA-defined AST criteria, with a well-turbidity detection accuracy of 98.21%, minimum-inhibitory-concentration accuracy of 95.12%, and a drug-susceptibility interpretation accuracy of 99.23%, with no very major errors. This mobile-reader could eliminate the need for trained diagnosticians to perform AST, reduce the cost-barrier for routine testing, and assist in spatio-temporal tracking of bacterial resistance.

Establishment of a reborn MMV-microarray technology: realization of microbiome analysis and other hitherto inaccessible technologies.

BACKGROUND: With the accelerating development of bioscience, the problem of research cost has become important. We previously devised and developed a novel concept microarray with manageable volumes (MMV) using a soft gel. It demonstrated the great potential of the MMV technology with the examples of 1024-parallel-cell culture and PCR experiments. However, its full potential failed to be expressed, owing to the nature of the material used for the MMV chip. RESULTS: In the present study, by developing plastic-based MMVs and associated technologies, we introduced novel technologies such as C2D2P (in which the cells in each well are converted from DNA to protein in 1024-parallel), NGS-non-dependent microbiome analysis, and other powerful applications. CONCLUSIONS: The reborn MMV-microarray technology has proven to be highly efficient and cost-effective (with approximately 100-fold cost reduction) and enables us to realize hitherto unattainable technologies.

Graphene nano-ink biosensor arrays on a microfluidic paper for multiplexed detection of metabolites.

The development of a miniaturized and low-cost platform for the highly sensitive, selective and rapid detection of multiplexed metabolites is of great interest for healthcare, pharmaceuticals, food science, and environmental monitoring. Graphene is a delicate single-layer, two-dimensional network of carbon atoms with extraordinary electrical sensing capability. Microfluidic paper with printing technique is a low cost matrix. Here, we demonstrated the development of graphene-ink based biosensor arrays on a microfluidic paper for the multiplexed detection of different metabolites, such as glucose, lactate, xanthine and cholesterol. Our results show that the graphene biosensor arrays can detect multiple metabolites on a microfluidic paper sensitively, rapidly and simultaneously. The device exhibits a fast measuring time of less than 2 min, a low detection limit of 0.3 µM, and a dynamic detection range of 0.3-15 µM. The process is simple and inexpensive to operate and requires a low consumption of sample volume. We anticipate that these results could open exciting opportunities for a variety of applications.

Chromosomal microarray impacts clinical management.

Chromosomal microarray analysis (CMA) is standard of care, first-tier clinical testing for detection of genomic copy number variation among patients with developmental disabilities. Although diagnostic yield is higher than traditional cytogenetic testing, management impact has not been well studied. We surveyed genetic services providers regarding CMA ordering practices and perceptions about reimbursement. Lack of insurance coverage because of perceived lack of clinical utility was cited among the most frequent reasons why CMA was not ordered when warranted. We compiled a list of genomic regions where haploinsufficiency or triplosensitivity cause genetic conditions with documented management recommendations, estimating that at least 146 conditions potentially diagnosable by CMA testing have published literature supporting specific clinical management implications. Comparison with an existing clinical CMA database to determine the proportion of cases involving these regions showed that CMA diagnoses associated with such recommendations are found in approximately 7% of all cases (n = 28,526). We conclude that CMA impacts clinical management at a rate similar to other genetic tests for which insurance coverage is more readily approved. The information presented here can be used to address barriers that continue to contribute to inequities in patient access and care in regard to CMA testing.

Quick and inexpensive method to elaborate tissue punches useful in paraffin tissue microarrays / Método rápido y económico para la elaboración de dispositivos de punch útiles en microarreglos de tejidos en parafina

The tissue microarrays (TMAs) were first called multitumor block. In 1998 was described the current technique, that uses an innovated sampling method for more than 1,000 cylindrical paraffin tissue core biopsies in a single paraffin block. TMAs are now considered as a useful powerful research tool in Histology and Pathology laboratories, for the standardization of immunohistochemical techniques along with in situ hybridization. However, one disadvantage to its widespread use is the high cost of professional paraffin tissue punches, and the complexity in the development of homemade devices previously described in other studies. This study describes a step by step process to develop four different home-made devices made with materials that are common in hospitals and offices. These devices are useful in Histopathology laboratories to obtain paraffin blocks with until 360 samples of tissue, investing from two to fifteen dollars in the development of each device described.

Los microarreglos de tejido (TMAs) fueron llamados por primera vez como bloque multitumor. En 1998 se describió la técnica actual, que utiliza un novedoso método de muestreo para obtener más de 1,000 cilindros de biopsias de tejidos incluidos en un solo bloque de parafina. Actualmente, los TMAs se consideran una poderosa herramienta de investigación en laboratorios de Histología y Patología, para la estandarización de técnicas inmunohistoquímica e hibridación in situ entre otras. Sin embargo, uno de los inconvenientes para su uso generalizado es el alto costo de los dispositivos profesionales para tejidos en parafina, y la complejidad en la elaboración de los dispositivos caseros descritos previamente en otros estudios. Este estudio describe paso a paso el proceso de elaboración de cuatro dispositivos caseros útiles para la obtención de matrices de tejido elaborados con materiales que son comunes en hospitales y oficinas. Estos dispositivos son útiles en laboratorios de Histopatología con el fin de obtener bloques de parafina de hasta 360 muestras de tejido, con una inversión de 2 a 15 dólares en la elaboración de cada uno de los dispositivos descritos.

Exploiting parallel R in the cloud with SPRINT.

BACKGROUND: Advances in DNA Microarray devices and next-generation massively parallel DNA sequencing platforms have led to an exponential growth in data availability but the arising opportunities require adequate computing resources. High Performance Computing (HPC) in the Cloud offers an affordable way of meeting this need. OBJECTIVES: Bioconductor, a popular tool for high-throughput genomic data analysis, is distributed as add-on modules for the R statistical programming language but R has no native capabilities for exploiting multi-processor architectures. SPRINT is an R package that enables easy access to HPC for genomics researchers. This paper investigates: setting up and running SPRINT-enabled genomic analyses on Amazon's Elastic Compute Cloud (EC2), the advantages of submitting applications to EC2 from different parts of the world and, if resource underutilization can improve application performance. METHODS: The SPRINT parallel implementations of correlation, permutation testing, partitioning around medoids and the multi-purpose papply have been benchmarked on data sets of various size on Amazon EC2. Jobs have been submitted from both the UK and Thailand to investigate monetary differences. RESULTS: It is possible to obtain good, scalable performance but the level of improvement is dependent upon the nature of the algorithm. Resource underutilization can further improve the time to result. End-user's location impacts on costs due to factors such as local taxation. CONCLUSIONS: Although not designed to satisfy HPC requirements, Amazon EC2 and cloud computing in general provides an interesting alternative and provides new possibilities for smaller organisations with limited funds.

Comparison of dkgB-linked intergenic sequence ribotyping to DNA microarray hybridization for assigning serotype to Salmonella enterica.

Two DNA-based methods were compared for the ability to assign serotype to 139 isolates of Salmonella enterica ssp. I. Intergenic sequence ribotyping (ISR) evaluated single nucleotide polymorphisms occurring in a 5S ribosomal gene region and flanking sequences bordering the gene dkgB. A DNA microarray hybridization method that assessed the presence and the absence of sets of genes was the second method. Serotype was assigned for 128 (92.1%) of submissions by the two DNA methods. ISR detected mixtures of serotypes within single colonies and it cost substantially less than Kauffmann-White serotyping and DNA microarray hybridization. Decreasing the cost of serotyping S. enterica while maintaining reliability may encourage routine testing and research.

Cloud computing approaches to accelerate drug discovery value chain.

Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.

Rapid identification of allergenic and pathogenic molds in environmental air by an oligonucleotide array.

BACKGROUND: Airborne fungi play an important role in causing allergy and infections in susceptible people. Identification of these fungi, based on morphological characteristics, is time-consuming, expertise-demanding, and could be inaccurate. METHODS: We developed an oligonucleotide array that could accurately identify 21 important airborne fungi (13 genera) that may cause adverse health problems. The method consisted of PCR amplification of the internal transcribed spacer (ITS) regions, hybridization of the PCR products to a panel of oligonucleotide probes immobilized on a nylon membrane, and detection of the hybridization signals with alkaline phosphatase-conjugated antibodies. RESULTS: A collection of 72 target and 66 nontarget reference strains were analyzed by the array. Both the sensitivity and specificity of the array were 100%, and the detection limit was 10 pg of genomic DNA per assay. Furthermore, 70 fungal isolates recovered from air samples were identified by the array and the identification results were confirmed by sequencing of the ITS and D1/D2 domain of the large-subunit RNA gene. The sensitivity and specificity of the array for identification of the air isolates was 100% (26/26) and 97.7% (43/44), respectively. CONCLUSIONS: Identification of airborne fungi by the array was cheap and accurate. The current array may contribute to decipher the relationship between airborne fungi and adverse health effect.

Application of cost-effectiveness analysis to demonstrate the potential value of companion diagnostics in chronic myeloid leukemia.

AIM: A cost-effectiveness analysis was performed to assess the potential value of companion diagnostics in supporting treatment decisions for dasatinib and nilotinib in chronic myeloid leukemia. MATERIALS & METHODS: A decision model was developed, and model inputs were taken from the literature and publicly available sources. The perspective of the healthcare sector in the Netherlands was used. Sensitivity and scenario analyses were performed to assess uncertainty in the results. RESULTS: Companion diagnostics could improve health and reduce costs, despite the estimates being uncertain owing to limited evidence for comparative effectiveness between dasatinib and nilotinib. The results were sensitive to the cost of treatment, utility of progression and progression-free survival. CONCLUSION: This case demonstrates the use of cost-effectiveness analysis at an early stage of health technology assessment to generate economic evidence for the use of companion diagnostics in treatment decisions and to support decision-making for their development.

Bulk segregant analysis using single nucleotide polymorphism microarrays.

Bulk segregant analysis (BSA) using microarrays, and extreme array mapping (XAM) have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP) between the cross parents for each new combination of genotypes, which raises the cost of experiments. The availability of the genomic polymorphism data in Arabidopsis thaliana, coupled with the efficient designs of Single Nucleotide Polymorphism (SNP) genotyping arrays removes the requirement for SFP detection and lowers the per array cost, thereby lowering the overall cost per experiment. To demonstrate that these approaches would be functional on SNP arrays and determine confidence intervals, we analyzed hybridizations of natural accessions to the Arabidopsis ATSNPTILE array and simulated BSA or XAM given a variety of gene models, populations, and bulk selection parameters. Our results show a striking degree of correlation between the genotyping output of both methods, which suggests that the benefit of SFP genotyping in context of BSA can be had with the cheaper, more efficient SNP arrays. As a final proof of concept, we hybridized the DNA from bulks of an F2 mapping population of a Sulfur and Selenium ionomics mutant to both the Arabidopsis ATTILE1R and ATSNPTILE arrays, which produced almost identical results. We have produced R scripts that prompt the user for the required parameters and perform the BSA analysis using the ATSNPTILE1 array and have provided them as supplemental data files.

MChip, a low density microarray, differentiates among seasonal human H1N1, North American swine H1N1, and the 2009 pandemic H1N1.

BACKGROUND: The MChip uses data from the hybridization of amplified viral RNA to 15 distinct oligonucleotides that target the influenza A matrix (M) gene segment. An artificial neural network (ANN) automates the interpretation of subtle differences in fluorescence intensity patterns from the microarray. The complete process from clinical specimen to identification including amplification of viral RNA can be completed in <8 hours for under US$10. OBJECTIVES: The work presented here represents an effort to expand and test the capabilities of the MChip to differentiate influenza A/H1N1 of various species origin. METHODS: The MChip ANN was trained to recognize fluorescence image patterns of a variety of known influenza A viruses, including examples of human H1N1, human H3N2, swine H1N1, 2009 pandemic influenza A H1N1, and a wide variety of avian, equine, canine, and swine influenza viruses. Robustness of the MChip ANN was evaluated using 296 blinded isolates. RESULTS: Training of the ANN was expanded by the addition of 71 well-characterized influenza A isolates and yielded relatively high accuracy (little misclassification) in distinguishing unique H1N1 strains: nine human A/H1N1 (88·9% correct), 35 human A/H3N2 (97·1% correct), 31 North American swine A/H1N1 (80·6% correct), 14 2009 pandemic A/H1N1 (87·7% correct), and 23 negative samples (91·3% correct). Genetic diversity among the swine H1N1 isolates may have contributed to the lower success rate for these viruses. CONCLUSIONS: The current study demonstrates the MChip has the capability to differentiate the genetic variations among influenza viruses with appropriate ANN training. Further selective enrichment of the ANN will improve its ability to rapidly and reliably characterize influenza viruses of unknown origin.