an informatics approach to analyzing the incidentalome j.berg et al. genetics in medicine presented...
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![Page 1: An informatics approach to analyzing the incidentalome J.Berg et al. Genetics in Medicine Presented by Li Changjian](https://reader035.vdocument.in/reader035/viewer/2022062407/56649dce5503460f94ac1cbb/html5/thumbnails/1.jpg)
An informatics approach to analyzing the incidentalome
J.Berg et al. Genetics in MedicinePresented by Li Changjian
![Page 2: An informatics approach to analyzing the incidentalome J.Berg et al. Genetics in Medicine Presented by Li Changjian](https://reader035.vdocument.in/reader035/viewer/2022062407/56649dce5503460f94ac1cbb/html5/thumbnails/2.jpg)
Concept
• Incidentalome: Incidental findings of genetic variants unrelated to presenting symptoms during the genetic diagnosis using whole genome sequencing (WGS)
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Challenge on Incidentalome
• Reducing cost in WGS makes it available for genetic diagnosis
• Vast volume of genomic findings with dubious clinical value is generated, overwhelming of information to physicians and patients
• A good screening/sifting method for the genetic data is needed
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Binning System
• Categories the genetic data
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Subjects & Methods
• Focus: Monogenic Disorders • OMIM genes for provisional binning (12786
genes) • 80 genome sequences used as test sequences,
19 from paints and 61 from presumably healthy individuals
• Database: PostgreSQL 8.4.3, Human Gene Mutation Database (HGMD) and NCBI build 37
• Python script used to determine the zygosity
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Screening Process of OMIM genes Provisional
Binning
Allele Frequency cut-off (AF<5%)
Protein-altering variants
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Further Screening
• Presence in a binned gene• <5% AF (Low Probability Mendelian Disorder) • Either being annotated as diseasing-causing
mutation (DM) in HGMD or predicted to be truncating
• Analyze zygosity to assign heterozygous variants in recessive genes to determine carrier status
• Finally, manual review to assess evidence of pathogenicity, reclassify the binning
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Summarized Results
Screening processes of the informatics algorithm
Significant reduction the number of binned genes
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Example Results
High specificity for bin 1 and bin 2c variants
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Sensitivity and Specificity
• Excluding synonymous variants, noncoding variants scarifies the sensitivity for higher specificity
• No gold standard to definitively estimate the specificity and sensitivity
• The sensitivity and specificity ties to quality of clinical database due to the data querying and predictive algorithms.
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Comparison with other reports
• Substantial difference resulted by different assumptions (ignoring SNPs variants)
• Stringent requirements on genes having clinical utility raise the thresholds results four orders less (0-2 variants versus 2000 variants by Cassa et al.) returned variants in bin 1.
• The specificity of current binning system is higher
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Limitations
• Only monogenic diseases is studied in this paper
• Specificity and Sensitivity needs quantitative estimation
• Number of variants in manual review process in the last step is still large (~100s)
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Future directions
• Extend the method the multifactorial diesease• Subcategorize Bin 2b into disease groups • Establish more granular criteria to determine
the novel variants selected for review• To better understand the penetrance of a
certain variants • To improve and maintain clinical-grade
database of known variants
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Conclusion
• Proof of concept of an framework to organizing the incidental findings during WGS to reduce the number of variants to be hand curated to a manageable number.