Gene Variant Databases and Sharing: Creating a Global Genomic Variant Database for Personalized Medicine

Bean, Lora Jh; Hegde, Madhuri

doi:10.1002/humu.23064

Cited by 11 publications

(10 citation statements)

References 29 publications

(35 reference statements)

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“…Some of the most critical information for variant classification, such as inheritance information in an affected family, arises from clinical testing and is often not publicly available. 16 This point was also argued by Pepin et al, who found that internal data were responsible for one-third of discrepant interpretations of collagen gene variation, 2 and by Narravula et al, who demonstrated the importance of a combination of biochemical and clinical data to the interpretation of sequence variation in genes for metabolic disorders. 17 Without a forum for public sharing, this information remains hidden to all but the laboratory in which the tests were performed.…”

Section: Discussionmentioning

confidence: 82%

Reassessment of Genomic Sequence Variation to Harmonize Interpretation for Personalized Medicine

Garber

Vincent²,

Alexander

et al. 2016

The American Journal of Human Genetics

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Accurate interpretation of DNA sequence variation is a prerequisite for implementing personalized medicine. Discrepancies in interpretation between testing laboratories impede the effective use of genetic test results in clinical medicine. To better understand the underpinnings of these discrepancies, we quantified differences in variant classification internally over time and those between our diagnostic laboratory and other laboratories and resources. We assessed the factors that contribute to these discrepancies and those that facilitate their resolution. Our process resolved 72% of nearly 300 discrepancies between pairs of laboratories to within a one-step classification difference and identified key sources of data that facilitate changes in variant interpretation. The identification and harmonization of variant discrepancies will maximize the clinical use of genetic information; these processes will be fostered by the accumulation of additional population data as well as the sharing of data between diagnostic laboratories.

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Section: Discussionmentioning

confidence: 82%

Reassessment of Genomic Sequence Variation to Harmonize Interpretation for Personalized Medicine

Garber

Vincent²,

Alexander

et al. 2016

The American Journal of Human Genetics

Self Cite

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“…Ideally, a set of global genomic variant knowledgebases would reduce the duplication of curation effort across laboratories (whose data is frequently unshared) while also harmonising classi cations across knowledgebases 26 . Although this goal has not yet been realised 27 , there are active efforts by the Global Alliance for Genomic Health (GA4GH) to create such resources 28 . A meta-knowledgebase has been developed by the Variants In Cancer Consortium (VICC) that has aggregated and harmonised six different cancer variant interpretation knowledgebases, including CIViC, to collect actionable clinical interpretations for cancer associated variants 29 .…”

Section: Discussionmentioning

confidence: 99%

Findings from Precision Oncology in the Clinic: Rare, Novel Variants are a Significant Contributor to Scaling Molecular Diagnostics

Doig

Love

Conway

et al. 2021

Preprint

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Background: Next generation sequencing for oncology patient management is now routine in clinical pathology laboratories. Although wet lab, sequencing and pipeline tasks are largely automated, the analysis of variants for clinical reporting remains largely a manual task. The increasing volume of sequencing data and the limited availability of genetic experts to analyse and report on variants in the data is a key scalability limit for molecular diagnostics.Method: To determine the impact and size of the issue, we examined the longitudinally compiled genetic variants from 48,036 cancer patients over a six year period in a large cancer hospital from ten targeted cancer panel tests in germline, solid tumour and haematology contexts using hybridization capture and amplicon assays. This testing generated 24,168,398 sequenced variants of which 23,255 (8,214 unique) were clinically reported. Results: Of the reported variants, 17,240 (74.1%) were identified in more than one assay which allowed curated variant data to be reused in later reports. The remainder, 6,015 (25.9%) were not subsequently seen in later assays and did not provide any reuse benefit. The number of new variants requiring curation has significantly increased over time from 1.72 to 3.73 variants per sample (292 curated variants per month). Analysis of the 23,255 variants reported, showed 28.6%(n=2,356) were not present in common public variant resources and therefore required de novo curation. These in-house only variants were enriched for indels, tumour suppressor genes and from solid tumour assays.Conclusion: This analysis highlights the significant percentage of variants not present within common public variant resources and the level of non-recurrent variants that consequently require greater curation effort. Many of these variants are unique to a single patient and unlikely to appear in other patients reflecting the personalised nature of cancer genomics. This study depicts the real-world situation for pathology laboratories faced with curating increasing numbers low-recurrence variants while needing to expedite the process of manual variant curation. In the absence of suitably accurate automated methods, new approaches are needed to scale oncology diagnostics for future genetic testing volumes.

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“…Although this approach may yield a genetic 21 diagnosis, it is operationally difficult to apply in a laboratory setting where multiple examples with a diversity of complex phenotypes are being analyzed. 9,22 To achieve efficiency of analysis, most laboratories establish a workflow comprising a series of steps that progressively filter and prioritize variants for cross-correlation with phenotype. To the degree possible, laboratories are leveraging either in-house-developed or commercially available software to achieve this aim.…”

Section: Bioinformatics For Wes and Wgsmentioning

confidence: 99%

Development and Validation of Clinical Whole-Exome and Whole-Genome Sequencing for Detection of Germline Variants in Inherited Disease

Hegde

Santani

Mao

et al. 2017

Archives of Pathology &Amp; Laboratory Medicine

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- It is critical that clinical laboratories planning to implement whole-exome and whole-genome sequencing design and validate the assay to specifications and ensure adequate performance prior to implementation. Test design specifications, including variant filtering and annotation, phenotypic consideration, guidance on consenting options, and reporting of incidental findings, are provided. These are important steps a laboratory must take to validate and implement whole-exome and whole-genome sequencing in a clinical setting for germline variants in inherited disorders.

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Gene Variant Databases and Sharing: Creating a Global Genomic Variant Database for Personalized Medicine

Cited by 11 publications

References 29 publications

Reassessment of Genomic Sequence Variation to Harmonize Interpretation for Personalized Medicine

Reassessment of Genomic Sequence Variation to Harmonize Interpretation for Personalized Medicine

Findings from Precision Oncology in the Clinic: Rare, Novel Variants are a Significant Contributor to Scaling Molecular Diagnostics

Development and Validation of Clinical Whole-Exome and Whole-Genome Sequencing for Detection of Germline Variants in Inherited Disease

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