Clinical whole genome sequencing as a first-tier test at a resource-limited dysmorphology clinic in Mexico.
Scocchia A, Wigby KM, Masser-Frye D, Del Campo M, Galarreta CI, Thorpe E, McEachern J, Robinson K, Gross A, ICSL Interpretation and Reporting Team, Ajay SS, Rajan V, Perry DL, Belmont JW, Bentley DR, Jones MC, Taft R. NPJ Genom Med. 2019;4:5.
In a resource limited setting, clinical WGS was provided at no-cost to 60 children with a mean age of 7.6 years who met testing criteria. Indications included 77% with suspected pattern of malformation and 23% with primary neurological presentation. The overall diagnostic yield was 68%. 41/60 had a genomic finding consistent with the phenotype. This included 76% of those referred for suspected malformations and 43% referred for primary neurological presentation. (p=0.0455). Post-test counseling was modified for both patient with and without a molecular diagnosis. The absence of diagnosis helpful in 6 of 19 cases without molecular diagnosis.
Gonzaludo N, Belmont JW, Gainullin VG, Taft RJ. Genet Med. 2019. doi: 10.1038/s41436-019-0458-5. Epub ahead of print.
To estimate the economic burden of genetic disease in pediatric patients, the authors analyzed the 2012 KID database, a national all-payer database for children in US that includes 10% of uncomplicated births and 80% of complicated in-hospital births. Genetic disease-linked discharges were associated with higher healthcare utilization, including additional procedures (up to 4 more), longer length of stay (2-18 days) and higher total costs per discharge ($12,000-$77,000). Discharges with multiple genetic disease-linked diagnosis codes yield higher cost per discharge with an incremental increase of $13,999 per code (up to 7th code). Overall genetic disease-linked discharges account for a proportionately larger amount of the “national bill” vs. non genetic disease-linked.
Meta-analysis of the diagnostic and clinical utility of genome and exome sequencing and chromosomal microarray in children with suspected diseases.
Clark MM, Stark Z, Farnaes L, Tan TY, White SM, Dimmock D, Kingsmore SF. NPJ Genom Med. 2018 Jul 9;3:16. doi: 10.1038/s41525-018-0053-8.
This meta-analysis examined 37 studies comprising 20,068 children from January 2011 to August 2017. Overall, the diagnostic utility was 8.3 times greater with WES/WGS (36%/41%) compared to CMA (10%). 25.7% of diagnostic variants identified by WGS were not apparent by WES. WGS detected diagnostic variants beyond the scope of WES, including intronic SNVs, SNVs in noncoding RNA, small CNVs, and mitochondrial DNA mutations, as well as exonic SNVs under-covered by WES.
The NSIGHT1-randomized controlled trial: rapid whole-genome sequencing for accelerated etiologic diagnosis in critically ill infants.
Petrikin JE, Cakici JA, Clark MM, Willig LK, Sweeney NM, Farrow EG, Saunders CJ, Thiffault I, Miller NA, Zellmer L, Herd SM, Holmes AM, Batalov S, Veeraraghavan N, Smith LD, Dimmock DP, Leeder JS, Kingsmore SF. NPJ Genom Med. 2018 Feb 9;3:6. doi: 10.1038/s41525-018-0045-8.
Rapid WGS plus standard clinical testing yielded higher genetic diagnosis rate and shorter time to diagnosis compared to standard clinical testing alone. In this partially blinded, randomized controlled trial, 65 infants (<4 months of age) with highly variable phenotypes had rapid WGS to determine diagnosis at 28 days post enrollment. Median time to diagnosis with WGS was 13 days vs. 107 days with standard clinical testing and median day of life at diagnosis was 25 days with WGS vs. 130 days with standard genetic testing. This study was terminated early due to equipoise and the growing inclusion of NGS in standard clinical testing strategies.
Improved diagnostic yield compared with targeted gene sequencing panels suggests a role for whole-genome sequencing as a first-tier genetic test
Lionel AC, Costain G, Monfared N, Walker S, Reuter MS, Hosseini M, Thiruvahindrapuram B, Merico D, Jobling R, Nalpathamkalam T, Pellecchia G, Sung WWL, Wang Z, Bikangaga P, Boelman C, Carter MT, Cordeiro D, Cytrynbaum C, Dell SD, Dhir P, Dowling JJ, Heon E, Hewson S, Hiraki L, Inbar-Feigenberg M, Klatt R, Kronick J, Laxer RM, Licht C, MacDonald H, Mercimek-Andrews S, Mendoza-Londono R, Piscione T, Schneider R, Schulze A, Silverman E, Siriwardena K, Snead OC, Sondheimer N, Sutherland J, Vincent A, Wasserman JD, Weksberg R, Shuman C, Carew C, Szego MJ, Hayeems RZ, Basran R, Stavropoulos DJ, Ray PN, Bowdin S, Meyn MS, Cohn RD, Scherer SW, Marshall CR. Genet Med. 2017; Aug 3. doi: 10.1038/gim.2017.119.
In this prospective comparison of WGS to standard clinical testing (including NGS panels) in 103 pediatric patients with diverse phenotypes, the authors concluded that WGS is superior given its higher diagnostic yield. WGS confirmed significantly more diagnoses than conventional testing (41% vs 24%; P =0.01). All copy number variants reported by chromosomal microarray were detected by WGS and WGS offered more complete coverage of disease associated genes compared to WES.
Whole genome sequencing expands diagnostic utility and improves clinical management in pediatric medicine
Stavropoulos DJ, Merico D, Jobling R, Bowdin S, Monfared N, Thiruvahindrapuram B, Nalpathamkalam T, Pellecchia G, Yuen RKC, Szego MJ, Hayeems RZ, Shaul RZ, Brudno M, Girdea M, Frey B, Alipanahi B, Ahmed S, Babul-Hirji R, Badilla Porras R, Carter MT, Chad L, Chaudhry A, Chitayat D, Jougheh Doust S, Cytrynbaum C, Dupuis L, Ejaz R, Fishman L, Guerin A, Hashemi B, Helal M, Hewson S, Inbar-Feigenberg M, Kannu P, Karp N, Kim RH, Kronick J, Liston E, MacDonald H, Mercimek-Mahmutoglu S, Mendoza-Londono R, Nasr E, Nimmo G, Parkinson N, Quercia N, Raiman J, Roifman M, Schulze A, Shugar A, Shuman C, Sinajon P, Siriwardena K, Weksberg R, Yoon G, Carew C, Erickson R, Leach RA, Klein R, Ray PN, Meyn MS, Scherer SW, Cohn RD, Marshall CR. NPJ Genomic Medicine, 2016; 1.
A prospective study evaluated the diagnostic yield of WGS compared to standard clinical testing on 100 consecutive children referred for chromosomal microarray. The authors concluded that as a first-tier test, WGS reduces the number of genetic investigations and potentially the time to diagnosis, ultimately acting as a more cost-effective approach. WGS diagnosis rate was 34% compared to 13% for the total from standard clinical testing (CMA plus targeted gene sequencing (P value = 0.0009). CNV resolution is greater for WGS than CMA, typically detecting >1,500 unbalanced changes that cannot be found using CMA. Split read mapping can further reveal complex overlapping CNVs missed by CMA.
Additional Relevant Publications
Krusche P, Trigg L, Boutros PC, Mason CE, De La Vega FM, Moore BL, Gonzalez-Porta M, Eberle MA, Tezak Z, Lababidi S, Truty R, Asimenos G, Funke B, Fleharty M, Chapman BA, Salit M, Zook JM, Global Alliance for Genomics and Health Benchmarking Team. Nat Biotechnol. 2019 May;37(5):555-560. doi: 10.1038/s41587-019-0054-x.
Bick D, Jones, M, Taylor SL, Taft RJ, Belmont J. J Med Genet 2019;0:1–9. doi:10.1136/jmedgenet-2019-106111.
A Rigorous Interlaboratory Examination of the Need to Confirm Next-Generation Sequencing-Detected Variants with an Orthogonal Method in Clinical Genetic Testing.
Lincoln SE, Truty R, Lin CF, Zook JM, Paul J, Ramey VH, Salit M, Rehm HL, Nussbaum RL, Lebo MS. J Mol Diagn. 2019 Mar;21(2):318-329. doi: 10.1016/j.jmoldx.2018.10.009.
Zook JM, McDaniel J, Olson ND, Wagner J, Parikh H, Heaton H, Irvine SA, Trigg L, Truty R, McLean CY, De La Vega FM, Xiao C, Sherry S, Salit M. Nat Biotechnol. 2019;37(5):561-566.
Rapid Paediatric Sequencing (RaPS): comprehensive real-life workflow for rapid diagnosis of critically ill children.
Mestek-Boukhibar l, Clement E, Jones WD, Drury S, Ocaka L, Gagunashvili A, Le Quesne Stabej P, Bacchelli C, Jani N, Rahman S, Jenkins L, Hurst JA, Bitner-Glindzicz M, Peters M, Beales PL, Williams HJ. J Med Genet. 2018; 55:721–728.
Periodic reanalysis of whole-genome sequencing data enhances the diagnostic advantage over standard clinical genetic testing.
Costain G, Jobling R, Walker S, Reuter MS, Snell M, Bowdin S, Cohn RD, Dupuis L, Hewson S, Mercimek-Andrews S, Shuman C, Sondheimer N, Weksberg R, Yoon G, Meyn MS, Stavropoulos DJ, Scherer SW, Mendoza-Londono R, Marshall CR. Eur J Hum Genet. 2018;26(5):740–744. doi:10.1038/s41431-018-0114-6.
Farnaes L, Hildreth A, Sweeney NM, Clark MM, Chowdhury S, Nahas S, Cakici, JA, Benson W, Kaplan RH, Kronick R, Bainbridge MN, Friedman J, Gold JJ, Ding Y, Veeraraghavan N, Dimmock D, Kingsmore SF. NPJ Genom Med. 2018 Apr 4;3:10. doi: 10.1038/s41525- 018-0049-4.
A survey of current practices for genomic sequencing test interpretation and reporting processes in US laboratories.
O’Daniel JM, McLaughlin HM, Amendola LM, Bale SJ, Berg JB, Bick D, Bowling KM, Chao EC, Chung WK, Conlin LK, Cooper GM, Das S, Deignan JL, Dorschner MO, Evans JP, Ghazani AA, Goddard KA, Gornick M, Farwell Hagman KD, Hambuch T, Hedge M, Hindorff LA, Holm IA, Jarvik GP, Knight Johnson A, Mighion L, Morra M, Plon SE, Punj S, Richards CS, Santani A, Shirts BH, Spinner NB, Tang S, Weck KE, Wolf SM, Yang Y, Rehm HL. Genet Med. 2016;19(5):575–582. doi:10.1038/gim.2016.152.
Gargis AS, Kalman L, Bick DP, da Silva C, Dimmock DP, Funke BH, Gowrisankar S, Hedge MR, Kulkarni S, Mason CE, Nagarajan R, Voelkerding KV, Worthey EA, Aziz N, Barnes J, Bennett SF, Bisht H, Church DM, Dimitrova Z, Gargis SR, Hafez N, Hambuch T, Hyland FCL, Luna RA, MacCannell D, Mann T, McCluskey MR, McDaniel TK, Ganova-Raeva LM, Rehm HL, Reid J, Campo DS, Resnick RB, Ridge PG, Salit ML, Skums P, Wong LJC, Zehnbauer BA, Lubin IM. Nat Biotechnol. 2015;33(7):689–693. doi:10.1038/nbt.3237.
Indications for WES/WGS
ACMG published recommendations for when to consider WES/WGS in a phenotypically affected individual. These include:
- Phenotype or family history data strongly implicate a genetic etiology, but the phenotype does not correspond with a specific disorder for which a genetic test targeting a specific gene is available on a clinical basis.
- A patient presents with a defined genetic disorder that demonstrates a high degree of genetic heterogeneity, making WES or WGS analysis of multiple genes simultaneously a more practical approach.
- A likely genetic disorder but specific genetic tests available for that phenotype have failed to arrive at a diagnosis.
- When a fetus presents with a likely genetic disorder in which specific genetic tests, including targeted sequencing tests, available for that phenotype have failed to arrive at a diagnosis.
Clinical Data Sharing
Clinical genomic data sharing is an important aspect of genomic sequencing that has been addressed by multiple societies, including ACMG, AMP, CCMG, ESHG and NSGC. Data-sharing is essential to reduce the number of variants and to improve consistency and accuracy of variant interpretation.
ACMG recommends that reporting and classification should be concise, easy to understand and contain all essential testing elements, supporting evidence and follow up recommendations, if indicated. Careful review of the patient’s phenotype and the method of ascertainment are important in variant classification. Sequence, population, and disease databases can be useful when classifying variants, however, clinical laboratories should be aware of potential limitations of each.
Variant Reevaluation and Reanalysis
Requests for variant reanalysis can come from the patient, healthcare provider or laboratory. Clinical laboratories should have separate policies and protocols for initial variant classification, variant-level reevaluation, and case-level reanalysis, which should be periodically reviewed and updated
There are a range of opinions from ACMG, AMP and CAP about whether confirmation of all pathogenic or likely pathogenic sequence variants is recommended.
American College of Medical Genetics and Genomics (ACMG). Policy statement: updated recommendations regarding analysis and reporting of secondary findings in clinical genome-scale sequencing. Genet Med. 2015;17(1):68-69.
American College of Medical Genetics and Genomics. Points to consider in the clinical application of Genomic Sequencing. a position statement of the American college of medical genetics and genomics. May 2012. epub.
American College of Medical Genetics and Genomics Board of Directors. Laboratory and clinical genomic data sharing is crucial to improving genetic health care: a position statement of the American College of Medical Genetics and Genomics. Genet Med. 2017;19(7):721-722.
American College of Medical Genetics and Genomics Board of Directors. The use of ACMG secondary findings recommendations for general population screening: a policy statement of the American College of Medical Genetics and Genomics (ACMG). Genet Med. 2019; https://doi.org/10.1038/s41436-019-0502-5.
American College of Medical Genetics and Genomics Board of Directors. Clinical utility of genetic and genomic services: A position statement of the American College of Medical Genetics and Genomics. Genet Med. 2015; 17(6): 505-507.
Aziz N, Zhao Q, Bry L, Driscoll DK, Funke B, Gibson JS, Grody WW, Hedge MR, Hoeltge GA, Leonard DGB, Merker JD, Nagarajan R, Palicki LA, Robetorye RS, Schrijver I, Weck KE, Voelkerding KV. College of American Pathologists’ laboratory standards for next-generation sequencing clinical tests. Arch Pathol Lab Med. 2014;doi;10.5858/arpa.2014-0250-CP.
Boycott K, Hartley T, Adam S, Bernier F, Chong K, Fernandez BA, Friedman JM, Geraghty MT, Hume S, Knoppers BM, Laberge AM, Majewski J, Mendoza-Londono R, Meyn MS, Michaud JL, Nelson TN, Richer J, Sadikovic B, Skidmore DL, Stockley T, Taylor S, van Karnebeek C, Zawati MH, Lauzon J, Armour CM on behalf of the Canadian College of Medical Genetics. The clinical application of genome-wide sequencing for monogenic diseases in Canada: Position Statement of the Canadian College of Medical Geneticists. J Med Genet. 2015;52:431-437.
Bush, LW, Beck AE, Biesecker LG, Evans JP, Hamosh A, Holm IA, Martin CL, Richards CS, Rehm HL. Professional responsibilities regarding the provision, publication and dissemination of patietn phenotypes in the context of clinical genetic and genomic testing: Points to consider – a statement of the Amercian College of Medical Genetics and Genomics (ACMG). Genet Med. 2018.
ClinGen. Position Statement on Licensed Databases and Plans for the Global Sharing of Variant Data. 2015. Accessed February 2019.
Deignan JL, Chung WK, Kearney HM, Monaghan KG, Rehder CW, Chao EC, on behalf of the ACMG Laboratory Quality Assurance Committee. Points to consider in the reevaluation and reanalysis of genomic test results: a statement of the American College of Medical Genetics and Genomics (ACMG). On behalf of the ACMG Laboratory Quality Assurance Committee. Genet Med. 2019;
Gibson W, Stavropoulos J, Sinasac D, McCready E, Mahmutoglu S, Nelson TN. Canadian College of Medical Genetics Laboratory Practice Committee. CCMG statement on germline variant classification. 2017.
Green RC, Berg JS, Grody WW, Kalia SS, Korf BR, Martin CL, McGuire A, Nussbaum RL, O’Daniel JM, Ormond KE, Rehm HL, Watson MS, Williams MS, Biesecker LG. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. 2013;15(7):565-574.
Hegde M, Bale S, Bayrak-toydemir P, Gison J, Bone Jeng LJ, Joseph L, Laser J, Lubin IM, Miller CE, Ross LF, Rothberg PG, Tanner AK, VItazka P, Mao R. Reporting Incidental Findings in Genomic Scale Clinical Sequencing d A Clinical Laboratory Perspective A Report of the Association for Molecular Pathology. J Mol Diagnostics. 2015;17(2):107-117. doi:10.1016/j.jmoldx.2014.10.004.
Kalia SS, Adelman K, Bale SJ, Chung WK, Eng C, Evans JP, Herman GE, Hufnagel SB, Klein TE, Korf BR, McKelvey KD, Ormond KE, Richards CS, Vlangos CN, Watson M, Martin CL, Miller DT on behalf of the ACMG Secondary Findings Maintenance Working Group. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med. 2017;19(2):249-255.
Matthijs G, Souche E,, Alders M., Corveleyn A, Eck S, Feenstra I, Race V, Sistermans E, Sturm M, Weiss M, Yntema H, Bakker E, Scheffer H, Bauer P. Guidelines for diagnostic next-generation sequencing. Euro J Hum Genet. 2016;24:2–5.
National Society of Genetic Counselors. Position Statement: Incidental findings in genetic testing. April 2019.
National Society of Genetic Counselors. Clinical data sharing. Position Statement. April 2015.
Rehm HL, Bale SJ, Bayrak-Toydemir P, Berg JS, Brown KK, Deignan JL, Friez MJ, Funke BH, Hedge MR. Lyon E, from the Working Group of the American College of Medical Genetics and Genomics Laboratory Quality Assurance Committee. ACMG clinical laboratory standards for next-generation sequencing. Genet Med. 2013;15:733-47.
Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hedge M, Lyon E, Spector E, Voelkerding K, Rehm HL, on behalf of the ACMG Laboratory Quality Assurance Committee. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405-424.
Schrijver I, Aziz N, Farkas DH, Furtado M, Ferreira Gonzalez A, Greiner TC, Grody WW, Hambuch T, Kalman L, Kant JA, Klein RD, Leonard DGB, Lubin IM, Mao R, Nagan N, Pratt VM, Sobel ME, Voelkerding KV, Gibson JS. Opportunities and challenges associated with clinical diagnostic genome sequencing: A report of the association for molecular pathology. J Mol Diagn. 2012; 14(6): 525-540.
van El CG, Cornel MC, Borry P, Hastings RJ, Fellmann F, Hodgson SV, Howard HC, Cambon-Thomsen A, Knoppers BM, Meijers-Heijboer H, Scheffer H, Tranebjaerg L, Dondorp W, de Wert GMWR on behalf of the ESHG Public and Professional Policy Committee. Whole genome sequencing in health care. Recommendations of the European Society of Human Genetics. Euro J Hum Genet. 2013;21:580-584.
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