Are whole Exome and whole Genome Sequencing Approaches Cost-Effective? A Systematic Review of the Literature

ABSTRACTPurposeBiomedical databases combining electronic medical records, phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations.MethodsWe developed and tested algorithms for translation of pre-existing genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by whole genome sequencing, whole exome sequencing and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia.ResultsOur most striking result was that the performance of genotyping arrays is similar to that of whole genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants.ConclusionWe find that microarrays are a cost-effective solution for creating pre-emptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.

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Estimating sequencing error rates using families

BioData Mining ◽

10.1186/s13040-021-00259-6 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Kelley Paskov ◽

Jae-Yoon Jung ◽

Brianna Chrisman ◽

Nate T. Stockham ◽

Peter Washington ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Exome Sequencing ◽

Genome Sequencing ◽

Variant Calling ◽

Error Rates ◽

Sequencing Error ◽

Whole Genome ◽

Sequencing Data ◽

Sequencing Platform ◽

Whole Exome

Abstract Background As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-calling pipelines are continuously evolving, making it difficult to accurately quantify error rates for the particular combination of assay and software parameters used on each sample. Family data provide a unique opportunity for estimating sequencing error rates since it allows us to observe a fraction of sequencing errors as Mendelian errors in the family, which we can then use to produce genome-wide error estimates for each sample. Results We introduce a method that uses Mendelian errors in sequencing data to make highly granular per-sample estimates of precision and recall for any set of variant calls, regardless of sequencing platform or calling methodology. We validate the accuracy of our estimates using monozygotic twins, and we use a set of monozygotic quadruplets to show that our predictions closely match the consensus method. We demonstrate our method’s versatility by estimating sequencing error rates for whole genome sequencing, whole exome sequencing, and microarray datasets, and we highlight its sensitivity by quantifying performance increases between different versions of the GATK variant-calling pipeline. We then use our method to demonstrate that: 1) Sequencing error rates between samples in the same dataset can vary by over an order of magnitude. 2) Variant calling performance decreases substantially in low-complexity regions of the genome. 3) Variant calling performance in whole exome sequencing data decreases with distance from the nearest target region. 4) Variant calls from lymphoblastoid cell lines can be as accurate as those from whole blood. 5) Whole-genome sequencing can attain microarray-level precision and recall at disease-associated SNV sites. Conclusion Genotype datasets from families are powerful resources that can be used to make fine-grained estimates of sequencing error for any sequencing platform and variant-calling methodology.

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Systematic dissection of biases in whole-exome and whole-genome sequencing reveals major determinants of coding sequence coverage

Scientific Reports ◽

10.1038/s41598-020-59026-y ◽

2020 ◽

Vol 10 (1) ◽

Cited By ~ 6

Author(s):

Yury A. Barbitoff ◽

Dmitrii E. Polev ◽

Andrey S. Glotov ◽

Elena A. Serebryakova ◽

Irina V. Shcherbakova ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome ◽

Sequence Coverage ◽

Coding Sequence ◽

Whole Exome

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Whole genome sequencing provides better diagnostic yield and future value than whole exome sequencing

The Medical Journal of Australia ◽

10.5694/mja17.01176 ◽

2018 ◽

Vol 209 (5) ◽

pp. 197-199 ◽

Cited By ~ 10

Author(s):

John S Mattick ◽

Marcel Dinger ◽

Nicole Schonrock ◽

Mark Cowley

Keyword(s):

Whole Genome Sequencing ◽

Exome Sequencing ◽

Whole Exome Sequencing ◽

Genome Sequencing ◽

Diagnostic Yield ◽

Whole Genome ◽

Whole Exome ◽

Future Value

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Evaluation of whole exome sequencing as an alternative to BeadChip and whole genome sequencing in human population genetic analysis

BMC Genomics ◽

10.1186/s12864-018-5168-x ◽

2018 ◽

Vol 19 (1) ◽

Cited By ~ 2

Author(s):

Zoltán Maróti ◽

Zsolt Boldogkői ◽

Dóra Tombácz ◽

Michael Snyder ◽

Tibor Kalmár

Keyword(s):

Genetic Analysis ◽

Whole Genome Sequencing ◽

Exome Sequencing ◽

Whole Exome Sequencing ◽

Genome Sequencing ◽

Population Genetic ◽

Human Population ◽

Whole Genome ◽

Population Genetic Analysis ◽

Whole Exome

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Readability of informed consent forms for whole-exome and whole-genome sequencing

Journal of Community Genetics ◽

10.1007/s12687-017-0324-6 ◽

2017 ◽

Vol 9 (2) ◽

pp. 143-151 ◽

Cited By ~ 10

Author(s):

Emilia Niemiec ◽

Danya F. Vears ◽

Pascal Borry ◽

Heidi Carmen Howard

Keyword(s):

Informed Consent ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome ◽

Consent Forms ◽

Whole Exome

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Whole exome and whole genome sequencing

New Technologies and Perinatal Medicine ◽

10.1201/9781315201955-37 ◽

2019 ◽

pp. 230-238

Author(s):

Mary E. Norton

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome ◽

Whole Exome

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Clinical and Genetic Features in 31 Serial Chinese Children With Gitelman Syndrome

Frontiers in Pediatrics ◽

10.3389/fped.2021.544925 ◽

2021 ◽

Vol 9 ◽

Author(s):

Lingxia Zhang ◽

Ke Huang ◽

Shugang Wang ◽

Haidong Fu ◽

Jingjing Wang ◽

...

Keyword(s):

Early Diagnosis ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Muscle Weakness ◽

Growth Retardation ◽

Gitelman Syndrome ◽

Compound Heterozygous ◽

Whole Genome ◽

Whole Exome ◽

Laboratory Test Results

Gitelman syndrome (GS, OMIM 263800) is a genetic congenital tubulopathy associated with salt loss, which is characterized by hypokalemic metabolic toxicity, hypocalciuria, and hypomagnesemia. GS, which is typically detected in adolescence or adulthood, has long been considered a benign tubular lesion; however, the disease is associated with a significant decrease in the quality of life. In this study, we assessed the genotype–phenotype correlations based on the medical histories, clinical symptoms, laboratory test results, and whole-exome sequencing profiles from pediatric patients with GS. Between January 2014 and December 2020, all 31 consecutively enrolled patients complained of fatigue, salt craving, and muscle weakness. Sixteen patients demonstrated growth retardation, and five patients presented with nocturia and constipation. All patients presented with hypokalemic metabolic alkalosis, normal blood pressure, hyperaldosteronism, and a preserved glomerular filtration rate, and 24 of the 31 (77.4%) patients had hypomagnesemia. Homozygous, compound heterozygous, and heterozygous mutations in SLC12A3 were detected in 4, 24, and 3 patients, respectively. GS patients often present with muscle weakness and fatigue caused by hypokalemia and hypomagnesemia. Therefore, early diagnosis of GS is important in young children to reduce the possibility of growth retardation, tetany, and seizures. Next-generation sequencing such as whole-exome or whole-genome sequencing provides a practical tool for the early diagnosis and improvement of GS prognosis. Further whole-genome sequencing is expected to reveal more variants in SLC123A among GS patients with single heterozygous mutations.

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Using molecular testing and whole-genome sequencing for tuberculosis diagnosis in a low-burden setting: a cost-effectiveness analysis using transmission-dynamic modelling

Thorax ◽

10.1136/thoraxjnl-2019-214004 ◽

2021 ◽

Vol 76 (3) ◽

pp. 281-291 ◽

Cited By ~ 1

Author(s):

Tendai Mugwagwa ◽

Ibrahim Abubakar ◽

Peter J White

Keyword(s):

Cost Effectiveness ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Drug Sensitivity ◽

Cost Effective ◽

Molecular Testing ◽

Whole Genome ◽

Transmission Dynamic ◽

Sensitivity Testing ◽

Combined Use

BackgroundDespite progress in TB control in low-burden countries like England and Wales, there are still diagnostic delays. Molecular testing and/or whole-genome sequencing (WGS) provide more rapid diagnosis but their cost-effectiveness is relatively unexplored in low-burden settings.MethodsAn integrated transmission-dynamic health economic model is used to assess the cost-effectiveness of using WGS to replace culture-based drug-sensitivity testing, versus using molecular testing versus combined use of WGS and molecular testing, for routine TB diagnosis. The model accounts for the effects of faster appropriate treatment in reducing transmission, benefiting health and reducing future treatment costs. Cost-effectiveness is assessed using incremental net benefit (INB) over a 10-year horizon with a quality-adjusted life-year valued at £20 000, and discounting at 3.5% per year.ResultsWGS shortens the time to drug sensitivity testing and treatment modification where necessary, reducing treatment and hospitalisation costs, with an INB of £7.1 million. Molecular testing shortens the time to TB diagnosis and treatment. Initially, this causes an increase in annual costs of treatment, but averting transmissions and future active TB disease subsequently, resulting in cost savings and health benefits to achieve an INB of £8.6 million (GeneXpert MTB/RIF) or £11.1 million (Xpert-Ultra). Combined use of Xpert-Ultra and WGS is the optimal strategy we consider, with an INB of £16.5 million.ConclusionRoutine use of WGS or molecular testing is cost-effective in a low-burden setting, and combined use is the most cost-effective option. Adoption of these technologies can help low-burden countries meet the WHO End TB Strategy milestones, particularly the UK, which still has relatively high TB rates.

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