Narrowing the diagnostic gap: Genomes, episignatures, long-read sequencing, and health economic analyses in an exome-negative intellectual disability cohort.

PURPOSE: Genome sequencing (GS)-specific diagnostic rates in prospective tightly ascertained exome sequencing (ES)-negative intellectual disability (ID) cohorts have not been reported extensively. METHODS: ES, GS, epigenetic signatures, and long-read sequencing diagnoses were assessed in 74 trios with at least moderate ID. RESULTS: The ES diagnostic yield was 42 of 74 (57%). GS diagnoses were made in 9 of 32 (28%) ES-unresolved families. Repeated ES with a contemporary pipeline on the GS-diagnosed families identified 8 of 9 single-nucleotide variations/copy-number variations undetected in older ES, confirming a GS-unique diagnostic rate of 1 in 32 (3%). Episignatures contributed diagnostic information in 9% with GS corroboration in 1 of 32 (3%) and diagnostic clues in 2 of 32 (6%). A genetic etiology for ID was detected in 51 of 74 (69%) families. Twelve candidate disease genes were identified. Contemporary ES followed by GS cost US$4976 (95% CI: $3704; $6969) per diagnosis and first-line GS at a cost of $7062 (95% CI: $6210; $8475) per diagnosis. CONCLUSION: Performing GS only in ID trios would be cost equivalent to ES if GS were available at $2435, about a 60% reduction from current prices. This study demonstrates that first-line GS achieves higher diagnostic rate than contemporary ES but at a higher cost.

Sequencing projects will screen 200,000 newborns for disease.

U.K. and New York City efforts face cost and ethical issues.

An accessible, efficient and global approach for the large-scale sequencing of bacterial genomes.

We have developed an efficient and inexpensive pipeline for streamlining large-scale collection and genome sequencing of bacterial isolates. Evaluation of this method involved a worldwide research collaboration focused on the model organism Salmonella enterica, the 10KSG consortium. Following the optimization of a logistics pipeline that involved shipping isolates as thermolysates in ambient conditions, the project assembled a diverse collection of 10,419 isolates from low- and middle-income countries. The genomes were sequenced using the LITE pipeline for library construction, with a total reagent cost of less than USD$10 per genome. Our method can be applied to other large bacterial collections to underpin global collaborations.

An economic evaluation of the Whole Genome Sequencing source tracking program in the U.S.

The U.S. Food and Drug Administration (FDA) created the GenomeTrakr Whole Genome Sequencing (WGS) Network in 2013, as a tool to improve food safety. This study presents an analysis of Whole Genome source tracking implementation on potential food contamination and related illnesses through theoretical, empirical, and cost benefit analyses. We conduct empirical tests using data from FDA regulated food commodity outbreaks garnering FDA response from 1999 through 2019 and examine the effect of the National Center for Biotechnology Information (NCBI) Pathogen detection program of source tracking WGS isolates collected in the U.S. on outbreak illnesses for three pilot pathogens (E. coli, Listeria, and Salmonella). Empirical results are consistent with the theoretical model and suggest that each additional 1,000 WGS isolates added to the public NCBI database is associated with a reduction of approximately 6 illnesses per WGS pathogen, per year. Empirical results are connected to existing literature for a Monte Carlo analysis to estimate benefits and costs. By 2019, annual health benefits are estimated at nearly $500 million, compared to an approximately $22 million investment by public health agencies. Even under conservative assumptions, the program likely broke even in its second year of implementation and could produce increasing public health benefits as the GenomeTrakr network matures.

Implementation of whole genome sequencing for tuberculosis diagnostics in a low-middle income, high MDR-TB burden country.

Whole genome sequencing (WGS) is revolutionary for diagnostics of TB and its mutations associated with drug-resistances, but its uptake in low- and middle-income countries is hindered by concerns of implementation feasibility. Here, we provide a proof of concept for its successful implementation in such a setting. WGS was implemented in the Kyrgyz Republic. We estimated needs of up to 55 TB-WGS per week and chose the MiSeq platform (Illumina, USA) because of its capacity of up to 60 TB-WGS per week. The project's timeline was completed in 93-weeks. Costs of large equipment and accompanying costs were 222,065 USD and 8462 USD, respectively. The first 174 WGS costed 277 USD per sequence, but this was skewed by training inefficiencies. Based on real prices and presuming optimal utilization of WGS capacities, WGS costs could drop to 167 and 141 USD per WGS using MiSeq Reagent Kits v2 (500-cycles) and v3 (600-cycles), respectively. Five trainings were required to prepare the staff for autonomous WGS which cost 48,250 USD. External assessment confirmed excellent performance of WGS by the Kyrgyz laboratory in an interlaboratory comparison of 30 M. tuberculosis genomes showing complete agreeance of results.

Whole genome sequencing in oncology: using scenario drafting to explore future developments.

BACKGROUND: In oncology, Whole Genome Sequencing (WGS) is not yet widely implemented due to uncertainties such as the required infrastructure and expertise, costs and reimbursements, and unknown pan-cancer clinical utility. Therefore, this study aimed to investigate possible future developments facilitating or impeding the use of WGS as a molecular diagnostic in oncology through scenario drafting. METHODS: A four-step process was adopted for scenario drafting. First, the literature was searched for barriers and facilitators related to the implementation of WGS. Second, they were prioritized by international experts, and third, combined into coherent scenarios. Fourth, the scenarios were implemented in an online survey and their likelihood of taking place within 5 years was elicited from another group of experts. Based on the minimum, maximum, and most likely (mode) parameters, individual Program Evaluation and Review Technique (PERT) probability density functions were determined. Subsequently, individual opinions were aggregated by performing unweighted linear pooling, from which summary statistics were extracted and reported. RESULTS: Sixty-two unique barriers and facilitators were extracted from 70 articles. Price, clinical utility, and turnaround time of WGS were ranked as the most important aspects. Nine scenarios were developed and scored on likelihood by 18 experts. The scenario about introducing WGS as a clinical diagnostic with a lower price, shorter turnaround time, and improved degree of actionability, scored the highest likelihood (median: 68.3%). Scenarios with low likelihoods and strong consensus were about better treatment responses to more actionable targets (26.1%), and the effect of centralizing WGS (24.1%). CONCLUSIONS: Based on current expert opinions, the implementation of WGS as a clinical diagnostic in oncology is heavily dependent on the price, clinical utility (both in terms of identifying actionable targets as in adding sufficient value in subsequent treatment), and turnaround time. These aspects and the optimal way of service provision are the main drivers for the implementation of WGS and should be focused on in further research. More knowledge regarding these factors is needed to inform strategic decision making regarding the implementation of WGS, which warrants support from all relevant stakeholders.

Early technology assessment of using whole genome sequencing in personalized oncology.

Introduction: Personalized medicine-based treatments in advanced cancer hold the promise to offer substantial health benefits to genetic subgroups, but require efficient biomarker-based patient stratification to match the right treatment and may be expensive. Standard molecular diagnostics are currently very heterogeneous, and tests are often performed sequentially. The alternative to whole genome sequencing (WGS) i.e. simultaneously testing for all relevant DNA-based biomarkers thereby allowing immediate selection of the most optimal therapy, is more costly than current techniques. In the current implementation stage, it is important to explore the added value and cost-effectiveness of using WGS on a patient level and to assess optimal introduction of WGS on the level of the healthcare system.Areas covered: First, an overview of current worldwide initiatives concerning the use of WGS in clinical practice for cancer diagnostics is given. Second, a comprehensive, early health technology assessment (HTA) approach of evaluating WGS in the Netherlands is described, relating to the following aspects: diagnostic value, WGS-based treatment decisions, assessment of long-term health benefits and harms, early cost-effectiveness modeling, nation-wide organization, and Ethical, Legal and Societal Implications.Expert opinion: This study provides evidence to guide further development and implementation of WGS in clinical practice and the healthcare system.

Micro-costing diagnostics in oncology: from single-gene testing to whole- genome sequencing.

Purpose: Predictive diagnostics play an increasingly important role in personalized medicine for cancer treatment. Whole-genome sequencing (WGS)-based treatment selection is expected to rapidly increase worldwide. This study aimed to calculate and compare the total cost of currently used diagnostic techniques and of WGS in treatment of non-small cell lung carcinoma (NSCLC), melanoma, colorectal cancer (CRC), and gastrointestinal stromal tumor (GIST) in the Netherlands.Methods: The activity-based costing (ABC) method was conducted to calculate total cost of included diagnostic techniques based on data provided by Dutch pathology laboratories and the Dutch-centralized cancer WGS facility. Costs were allocated to four categories: capital costs, maintenance costs, software costs, and operational costs.Results: The total cost per cancer patient per technique varied from € 58 (Sanger sequencing, three amplicons) to € 2925 (paired tumor-normal WGS). The operational costs accounted for the vast majority (over 90%) of the total per cancer patient technique costs.Conclusion: This study outlined in detail all costing aspects and cost prices of current and new diagnostic modalities used in treatment of NSCLC, melanoma, CRC, and GIST in the Netherlands. Detailed cost differences and value comparisons between these diagnostic techniques enable future economic evaluations to support decision-making.

Cost of whole genome sequencing for non-typhoidal Salmonella enterica.

BACKGROUND: While whole genome sequencing (WGS) may be more expensive than traditional testing and polymerase chain reaction (PCR), simple cost comparisons ignore the potential for WGS to reduce the societal costs of non-typhoidal Salmonella enterica through public health action to prevent illness. METHODS: We determined how many cases the use of WGS data would need to prevent to be cost-equal to serotyping and MLVA, or culture independent testing based on PCR in Australia. We then examined the costs and cost-savings of current typing methods compared with WGS in outbreak scenarios. RESULTS: A median of 275 (90% CrI -55-775) or 1.9% (90% CrI -0.4%-5.4%) of notified serotyped Salmonella cases would need to be prevented for WGS to be cost-equal to current typing methods and 1,550 (90% CrI 820-2,725) or 9.6% of all notified Salmonella cases would need to be prevented to be cost-equal to PCR. WGS is likely to result in cost savings in prolonged outbreaks, where data can support earlier public health action. CONCLUSIONS: Despite currently having a higher cost per isolate, routine WGS of Salmonella was no more expensive than existing typing methods or PCR where >2% of illness was averted.

Low-coverage sequencing cost-effectively detects known and novel variation in underrepresented populations.

Genetic studies in underrepresented populations identify disproportionate numbers of novel associations. However, most genetic studies use genotyping arrays and sequenced reference panels that best capture variation most common in European ancestry populations. To compare data generation strategies best suited for underrepresented populations, we sequenced the whole genomes of 91 individuals to high coverage as part of the Neuropsychiatric Genetics of African Population-Psychosis (NeuroGAP-Psychosis) study with participants from Ethiopia, Kenya, South Africa, and Uganda. We used a downsampling approach to evaluate the quality of two cost-effective data generation strategies, GWAS arrays versus low-coverage sequencing, by calculating the concordance of imputed variants from these technologies with those from deep whole-genome sequencing data. We show that low-coverage sequencing at a depth of ≥4× captures variants of all frequencies more accurately than all commonly used GWAS arrays investigated and at a comparable cost. Lower depths of sequencing (0.5-1×) performed comparably to commonly used low-density GWAS arrays. Low-coverage sequencing is also sensitive to novel variation; 4× sequencing detects 45% of singletons and 95% of common variants identified in high-coverage African whole genomes. Low-coverage sequencing approaches surmount the problems induced by the ascertainment of common genotyping arrays, effectively identify novel variation particularly in underrepresented populations, and present opportunities to enhance variant discovery at a cost similar to traditional approaches.

Real-World Utilization of Biomarker Testing for Patients with Advanced Non-Small Cell Lung Cancer in a Tertiary Referral Center and Referring Hospitals.

The continued introduction of biomarkers and innovative testing methods makes already complex diagnosis in patients with stage IV non-small-cell lung cancer (NSCLC) even more complex. This study primarily analyzed variations in biomarker testing in clinical practice in patients referred to a comprehensive cancer center in the Netherlands. The secondary aim was to compare the cost of biomarker testing with the cost of whole-genome sequencing. The cohort included 102 stage IV NSCLC patients who received biomarker testing in 2017 or 2018 at the comprehensive cancer center. The complete biomarker testing history of the cohort was identified using linked data from the comprehensive cancer center and the nationwide network and registry of histopathology and cytopathology in the Netherlands. Unique biomarker-test combinations, costs, turnaround times, and test utilization were examined. The results indicate substantial variation in test utilization and sequences. The mean cost per patient of biomarker testing was 2259.92 ± 1217.10 USD, or 1881.23 ± 1013.15 EUR. Targeted gene panels were most frequently conducted, followed by IHC analysis for programmed cell death protein ligand 1. Typically, the most common biomarkers were assessed within the first tests, and emerging biomarkers were tested further down the test sequence. At the cost of current biomarker testing, replacing current testing with whole-genome sequencing would have led to cost-savings in only two patients (2%).

Culture-free genome-wide locus sequence typing (GLST) provides new perspectives on Trypanosoma cruzi dispersal and infection complexity.

Analysis of genetic polymorphism is a powerful tool for epidemiological surveillance and research. Powerful inference from pathogen genetic variation, however, is often restrained by limited access to representative target DNA, especially in the study of obligate parasitic species for which ex vivo culture is resource-intensive or bias-prone. Modern sequence capture methods enable pathogen genetic variation to be analyzed directly from host/vector material but are often too complex and expensive for resource-poor settings where infectious diseases prevail. This study proposes a simple, cost-effective 'genome-wide locus sequence typing' (GLST) tool based on massive parallel amplification of information hotspots throughout the target pathogen genome. The multiplexed polymerase chain reaction amplifies hundreds of different, user-defined genetic targets in a single reaction tube, and subsequent agarose gel-based clean-up and barcoding completes library preparation at under 4 USD per sample. Our study generates a flexible GLST primer panel design workflow for Trypanosoma cruzi, the parasitic agent of Chagas disease. We successfully apply our 203-target GLST panel to direct, culture-free metagenomic extracts from triatomine vectors containing a minimum of 3.69 pg/µl T. cruzi DNA and further elaborate on method performance by sequencing GLST libraries from T. cruzi reference clones representing discrete typing units (DTUs) TcI, TcIII, TcIV, TcV and TcVI. The 780 SNP sites we identify in the sample set repeatably distinguish parasites infecting sympatric vectors and detect correlations between genetic and geographic distances at regional (< 150 km) as well as continental scales. The markers also clearly separate TcI, TcIII, TcIV and TcV + TcVI and appear to distinguish multiclonal infections within TcI. We discuss the advantages, limitations and prospects of our method across a spectrum of epidemiological research.

Study protocol: Whole genome sequencing Implementation in standard Diagnostics for Every cancer patient (WIDE).

BACKGROUND: 'Precision oncology' can ensure the best suitable treatment at the right time by tailoring treatment towards individual patient and comprehensive tumour characteristics. In current molecular pathology, diagnostic tests which are part of the standard of care (SOC) only cover a limited part of the spectrum of genomic changes, and often are performed in an iterative way. This occurs at the expense of valuable patient time, available tissue sample, and interferes with 'first time right' treatment decisions. Whole Genome Sequencing (WGS) captures a near complete view of genomic characteristics of a tumour in a single test. Moreover, WGS facilitates faster implementation of new treatment relevant biomarkers. At present, WGS mainly has been applied in study settings, but its performance in a routine diagnostic setting remains to be evaluated. The WIDE study aims to investigate the feasibility and validity of WGS-based diagnostics in clinical practice. METHODS: 1200 consecutive patients in a single comprehensive cancer centre with (suspicion of) a metastasized solid tumour will be enrolled with the intention to analyse tumour tissue with WGS, in parallel to SOC diagnostics. Primary endpoints are (1) feasibility of implementation of WGS-based diagnostics into routine clinical care and (2) clinical validation of WGS by comparing identification of treatment-relevant variants between WGS and SOC molecular diagnostics. Secondary endpoints entail (1) added clinical value in terms of additional treatment options and (2) cost-effectiveness of WGS compared to SOC diagnostics through a Health Technology Assessment (HTA) analysis. Furthermore, the (3) perceived impact of WGS-based diagnostics on clinical decision making will be evaluated through questionnaires. The number of patients included in (experimental) therapies initiated based on SOC or WGS diagnostics will be reported with at least 3 months follow-up. The clinical efficacy is beyond the scope of WIDE. Key performance indicators will be evaluated after every 200 patients enrolled, and procedures optimized accordingly, to continuously improve the diagnostic performance of WGS in a routine clinical setting. DISCUSSION: WIDE will yield the optimal conditions under which WGS can be implemented in a routine molecular diagnostics setting and establish the position of WGS compared to SOC diagnostics in routine clinical care.

DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework.

Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method for the identification of genetic variants and has been widely used in genome projects and population genetic studies for many years. This was until the Google Brain team developed a new method, DeepVariant, which utilizes deep neural networks to construct an image classification model to identify genetic variants. However, the superior accuracy of DeepVariant comes at the cost of computational intensity, largely constraining its applications. Accordingly, we present DeepVariant-on-Spark to optimize resource allocation, enable multi-GPU support, and accelerate the processing of the DeepVariant pipeline. To make DeepVariant-on-Spark more accessible to everyone, we have deployed the DeepVariant-on-Spark to the Google Cloud Platform (GCP). Users can deploy DeepVariant-on-Spark on the GCP following our instruction within 20 minutes and start to analyze at least ten whole-genome sequencing datasets using free credits provided by the GCP. DeepVaraint-on-Spark is freely available for small-scale genome analysis using a cloud-based computing framework, which is suitable for pilot testing or preliminary study, while reserving the flexibility and scalability for large-scale sequencing projects.

Multiplex High-Resolution Melting Assay for Simultaneous Identification of Molecular Markers Associated with Extended-Spectrum Cephalosporins and Azithromycin Resistance in Neisseria gonorrhoeae.

Antimicrobial resistance in Neisseria gonorrhoeae persists as a major public health concern globally. We developed and evaluated a multiplex assay that relied on high-resolution melting (HRM) technology as a rapid, simple, and cost-effective method for simultaneously detecting and identifying different molecular markers associated with extended-spectrum cephalosporins (ESCs) and azithromycin (AZM) resistance in N. gonorrhoeae. Forty-eight well-characterized N. gonorrhoeae clinical isolates were selected for initial assay establishment. The multiplex HRM assays were able to accurately identify different nucleotide variations of the antimicrobial resistance determinants related to ESCs and AZM resistance. Specificity and cross-reactivity were assessed by testing 15 nongonococcal strains. Then, the assay was validated on 218 archived DNA specimens that had been sequenced using whole-genome sequencing technology. Compared with whole-genome sequencing, these assays had a sensitivity of 98.6%, with a specificity of 99.2%. For further validation of the assay's performance, a total of 338 samples (156 clinical isolates and 182 clinical specimens) were screened using the multiplex HRM assay. The results showed good concordance with the results of PCR sequencing. Given its rapidity (within 90 minutes), ease of performing, and low cost (<$1.00 per sample), this method may be applied to large-scale epidemiologic programs for increasing surveillance of ESCs and AZM resistance in N. gonorrhoeae.

Clinical and Economic Outcomes of Genome Sequencing Availability on Containing a Hospital Outbreak of Resistant Escherichia coli in Australia.

OBJECTIVES: To evaluate the outbreak size and hospital cost effects of bacterial whole-genome sequencing availability in managing a large-scale hospital outbreak. METHODS: We built a hybrid discrete event/agent-based simulation model to replicate a serious bacterial outbreak of resistant Escherichia coli in a large metropolitan public hospital during 2017. We tested the 3 strategies of using whole-genome sequencing early, late (actual outbreak), or not using it and assessed their associated outbreak size and hospital cost. The model included ward dynamics, pathogen transmission, and associated hospital costs during a 5-month outbreak. Model parameters were determined using data from the Queensland Hospital Admitted Patient Data Collection (N = 4809 patient admissions) and local clinical knowledge. Sensitivity analyses were performed to address model and parameter uncertainty. RESULTS: An estimated 197 patients were colonized during the outbreak, with 75 patients detected. The total outbreak cost was A$460 137 (US$317 117), with 6.1% spent on sequencing. Without sequencing, the outbreak was estimated to result in 352 colonized patients, costing A$766 921 (US$528 547). With earlier detection from use of routine sequencing, the estimated outbreak size was 3 patients and cost A$65 374 (US$45 054). CONCLUSIONS: Using whole-genome sequencing in hospital outbreak management was associated with smaller outbreaks and cost savings, with sequencing costs as a small fraction of total hospital costs, supporting the further investigation of the use of routine whole-genome sequencing in hospitals.

SARS-CoV-2 Whole Genome Amplification and Sequencing for Effective Population-Based Surveillance and Control of Viral Transmission.

BACKGROUND: With the gradual reopening of economies and resumption of social life, robust surveillance mechanisms should be implemented to control the ongoing COVID-19 pandemic. Unlike RT-qPCR, SARS-CoV-2 whole genome sequencing (cWGS) has the added advantage of identifying cryptic origins of the virus, and the extent of community-based transmissions versus new viral introductions, which can in turn influence public health policy decisions. However, the practical and cost considerations of cWGS should be addressed before it is widely implemented. METHODS: We performed shotgun transcriptome sequencing using RNA extracted from nasopharyngeal swabs of patients with COVID-19, and compared it to targeted SARS-CoV-2 genome amplification and sequencing with respect to virus detection, scalability, and cost-effectiveness. To track virus origin, we used open-source multiple sequence alignment and phylogenetic tools to compare the assembled SARS-CoV-2 genomes to publicly available sequences. RESULTS: We found considerable improvement in whole genome sequencing data quality and viral detection using amplicon-based target enrichment of SARS-CoV-2. With enrichment, more than 99% of the sequencing reads mapped to the viral genome, compared to an average of 0.63% without enrichment. Consequently, an increase in genome coverage was obtained using substantially less sequencing data, enabling higher scalability and sizable cost reductions. We also demonstrated how SARS-CoV-2 genome sequences can be used to determine their possible origin through phylogenetic analysis including other viral strains. CONCLUSIONS: SARS-CoV-2 whole genome sequencing is a practical, cost-effective, and powerful approach for population-based surveillance and control of viral transmission in the next phase of the COVID-19 pandemic.

Sequencing and imputation in GWAS: Cost-effective strategies to increase power and genomic coverage across diverse populations.

A key aim for current genome-wide association studies (GWAS) is to interrogate the full spectrum of genetic variation underlying human traits, including rare variants, across populations. Deep whole-genome sequencing is the gold standard to fully capture genetic variation, but remains prohibitively expensive for large sample sizes. Array genotyping interrogates a sparser set of variants, which can be used as a scaffold for genotype imputation to capture a wider set of variants. However, imputation quality depends crucially on reference panel size and genetic distance from the target population. Here, we consider sequencing a subset of GWAS participants and imputing the rest using a reference panel that includes both sequenced GWAS participants and an external reference panel. We investigate how imputation quality and GWAS power are affected by the number of participants sequenced for admixed populations (African and Latino Americans) and European population isolates (Sardinians and Finns), and identify powerful, cost-effective GWAS designs given current sequencing and array costs. For populations that are well-represented in existing reference panels, we find that array genotyping alone is cost-effective and well-powered to detect common- and rare-variant associations. For poorly represented populations, sequencing a subset of participants is often most cost-effective, and can substantially increase imputation quality and GWAS power.

Long-Molecule Sequencing: A New Approach for Identification of Clinically Significant DNA Variants in α-Thalassemia and ß-Thalassemia Carriers.

Multiple molecular tests are currently needed for accurate carrier testing for thalassemia. Therefore, long-molecule sequencing (LMS) was evaluated as an alternate on the PacBio Sequel platform for genotyping carriers of α-thalassemia or ß-thalassemia. Multiplex long PCR was used to generate representative amplicons for the α (HBA1/2) and ß (HBB) gene loci. Following LMS, circular consensus sequencing reads were aligned to the hg19 reference genome and variants called using FreeBayes software version 1.2.0. In a blinded study of 64 known carrier samples, all HBA1/2 and HBB variants detected by LMS were concordant with those independently assigned by targeted PCR assays. For HBA1/2 carrier samples, LMS accurately detected the common South East Asian, -α3.7, and -α4.2 deletions and four different rare single-nucleotide variants (SNVs). For HBB carrier samples, LMS accurately detected the most common Chinese insertion and deletion variant c.126_129delCTTT and 14 different SNVs/insertions and deletions and could discriminate compound heterozygous SNVs (trans configuration) and identify variants linked to benign SNPs (cis configuration). Overall, LMS displayed the hallmarks of a scalable, accurate, and cost-effective genotyping method. With further test coverage to additionally include detection of other clinically significant HBA1/2 copy number variations, such as the Thai, Mediterranean, and Filipino deletions, LMS may eventually serve as a comprehensive method for large-scale thalassemia carrier screening.