Optimizing clinical exome design and parallel gene-testing for recessive genetic conditions in preconception carrier screening: Translational research genomic data from 14,125 exomes
Autoři:
Antonio Capalbo aff001; Roberto Alonso Valero aff003; Jorge Jimenez-Almazan aff003; Pere Mir Pardo aff003; Marco Fabiani aff001; David Jiménez aff003; Carlos Simon aff003; Julio Rodriguez Martin aff003
Působiště autorů:
Igenomix Reproductive Genetic Laboratory, Marostica, Italy
aff001; DAHFMO Unit of Histology and Medical Embryology, Sapienza University of Rome, Italy
aff002; Igenomix, Valencia, Spain
aff003; Department of Obstetrics and Gynecology, Valencia University; and INCLIVA, Valencia, Spain
aff004; Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, California, United States of America
aff005
Vyšlo v časopise:
Optimizing clinical exome design and parallel gene-testing for recessive genetic conditions in preconception carrier screening: Translational research genomic data from 14,125 exomes. PLoS Genet 15(10): e32767. doi:10.1371/journal.pgen.1008409
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1008409
Souhrn
Limited translational genomic research data have been reported on the application of exome sequencing and parallel gene testing for preconception carrier screening (PCS). Here, we present individual-level data from a large PCS program in which exome sequencing was routinely performed on either gamete donors (5,845) or infertile patients (8,280) undergoing in vitro fertilization (IVF) treatment without any known family history of inheritable genetic conditions. Individual-level data on pathogenic variants were used to define conditions for PCS based on criteria for severity, penetrance, inheritance pattern, and age of onset. Fetal risk was defined based on actual carrier frequency data accounting for the specific inheritance pattern (fetal disease risk, FDR). In addition, large-scale application of exome sequencing for PCS allowed a deep investigation of the incidence of medically actionable secondary findings in this population. Exome sequencing achieved remarkable clinical sensitivity for reproductive risk of highly penetrant childhood-onset disorders (1/337 conceptions) through analysis of 114 selected gene-condition pairs. A significant contribution to fetal disease risk was observed for rare (carrier rate < 1:100) and X-linked conditions (16.7% and 41.2% of total FDR, respectively). Subgroup analysis of 776 IVF couples identified 37 at increased reproductive risk (4.8%; 95% CI = 3.4–6.5). Further, two additional couples had increased risk for very rare conditions when both members of a parental pair were treated as a unit and the search was extended to the entire exome. About 2.3% of participants showed at least one pathogenic variant for genes included in the updated American College of Medical Genetics and Genomics v2.0 list of secondary findings. Gamete donors and IVF couples showed similar carrier burden for both carrier screening and secondary findings, indicating no causal relationship to fertility. These translational research data will facilitate development of more effective PCS strategies that maximize clinical sensitivity with minimal counterproductive effects.
Klíčová slova:
Genetic screens – Genetics of disease – Genomic medicine – Heredity – Pathogens – X-linked traits – Gene sequencing – Genome sequencing
Zdroje
1. Archibald AD, Smith MJ, Burgess T, Scarff KL, Elliott J, Hunt CE, et al. Reproductive genetic carrier screening for cystic fibrosis, fragile X syndrome, and spinal muscular atrophy in Australia: outcomes of 12,000 tests. Genet Med. 2018;20: 513–523. doi: 10.1038/gim.2017.134 29261177
2. Haque IS, Lazarin GA, Kang HP, Evans EA, Goldberg JD, Wapner RJ. Modeled Fetal Risk of Genetic Diseases Identified by Expanded Carrier Screening. JAMA. 2016;316: 734. doi: 10.1001/jama.2016.11139 27533158
3. Ben-Shachar R, Svenson A, Goldberg JD, Muzzey D. A data-driven evaluation of the size and content of expanded carrier screening panels. Genet Med. 2019; doi: 10.1038/s41436-019-0466-5
4. Committee on Genetics. Committee Opinion No. 690. Obstet Gynecol. 2017;129: e35–e40. doi: 10.1097/AOG.0000000000001951 28225425
5. Wienke S, Brown K, Farmer M, Strange C. Expanded carrier screening panels-does bigger mean better? J Community Genet. 2014;5: 191–8. doi: 10.1007/s12687-013-0169-6 24062228
6. Henneman L, Borry P, Chokoshvili D, Cornel MC, van El CG, Forzano F, et al. Responsible implementation of expanded carrier screening. Eur J Hum Genet. 2017;25: 1291–1291. doi: 10.1038/ejhg.2017.159
7. Beauchamp KA, Johansen Taber KA, Muzzey D. Clinical impact and cost-effectiveness of a 176-condition expanded carrier screen. Genet Med. 2019; doi: 10.1038/s41436-019-0455-8
8. Kalia SS, Adelman K, Bale SJ, Chung WK, Eng C, Evans JP, et al. 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: 249–255. doi: 10.1038/gim.2016.190 27854360
9. Sallevelt SCEH, de Koning B, Szklarczyk R, Paulussen ADC, de Die-Smulders CEM, Smeets HJM. A comprehensive strategy for exome-based preconception carrier screening. Genet Med. 2017;19: 583–592. doi: 10.1038/gim.2016.153 28492530
10. Punj S, Akkari Y, Huang J, Yang F, Creason A, Pak C, et al. Preconception Carrier Screening by Genome Sequencing: Results from the Clinical Laboratory. Am J Hum Genet. 2018;102: 1078–1089. doi: 10.1016/j.ajhg.2018.04.004 29754767
11. Teeuw M, Waisfisz Q, Zwijnenburg PJG, Sistermans EA, Weiss MM, Henneman L, et al. First steps in exploring prospective exome sequencing of consanguineous couples. Eur J Med Genet. 2014;57: 613–616. doi: 10.1016/j.ejmg.2014.09.003 25281896
12. Hogan GJ, Vysotskaia VS, Beauchamp KA, Seisenberger S, Grauman P V, Haas KR, et al. Validation of an Expanded Carrier Screen that Optimizes Sensitivity via Full-Exon Sequencing and Panel-wide Copy Number Variant Identification. Clin Chem. 2018;64: 1063–1073. doi: 10.1373/clinchem.2018.286823 29760218
13. Edwards JG, Feldman G, Goldberg J, Gregg AR, Norton ME, Rose NC, et al. Expanded carrier screening in reproductive medicine-points to consider: a joint statement of the American College of Medical Genetics and Genomics, American College of Obstetricians and Gynecologists, National Society of Genetic Counselors, Perinatal Quality Foundation, and Society for Maternal-Fetal Medicine. Obstet Gynecol. 2015;125: 653–62. doi: 10.1097/AOG.0000000000000666 25730230
14. Dobyns WB, Filauro A, Tomson BN, Chan AS, Ho AW, Ting NT, et al. Inheritance of most X-linked traits is not dominant or recessive, just X-linked. Am J Med Genet A. 2004;129A: 136–43. doi: 10.1002/ajmg.a.30123 15316978
15. Delatycki MB, Laing N, Kirk E. Expanded reproductive carrier screening—how can we do the most good and cause the least harm? Eur J Hum Genet. 2019;27: 669–670. doi: 10.1038/s41431-019-0356-y 30760884
16. Amendola LM, Dorschner MO, Robertson PD, Salama JS, Hart R, Shirts BH, et al. Actionable exomic incidental findings in 6503 participants: challenges of variant classification. Genome Res. 2015;25: 305–15. doi: 10.1101/gr.183483.114 25637381
17. Dewey FE, Murray MF, Overton JD, Habegger L, Leader JB, Fetterolf SN, et al. Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study. Science. 2016;354: aaf6814. doi: 10.1126/science.aaf6814 28008009
18. Jang M-A, Lee S-H, Kim N, Ki C-S. Frequency and spectrum of actionable pathogenic secondary findings in 196 Korean exomes. Genet Med. 2015;17: 1007–11. doi: 10.1038/gim.2015.26 25856671
19. Natarajan P, Gold NB, Bick AG, McLaughlin H, Kraft P, Rehm HL, et al. Aggregate penetrance of genomic variants for actionable disorders in European and African Americans. Sci Transl Med. 2016;8: 364ra151. doi: 10.1126/scitranslmed.aag2367 27831900
20. Tang CS-M, Dattani S, So M-T, Cherny SS, Tam PKH, Sham PC, et al. Actionable secondary findings from whole-genome sequencing of 954 East Asians. Hum Genet. 2018;137: 31–37. doi: 10.1007/s00439-017-1852-1 29128982
21. Thompson ML, Finnila CR, Bowling KM, Brothers KB, Neu MB, Amaral MD, et al. Genomic sequencing identifies secondary findings in a cohort of parent study participants. Genet Med. 2018;20: 1635–1643. doi: 10.1038/gim.2018.53 29790872
22. Gambin T, Jhangiani SN, Below JE, Campbell IM, Wiszniewski W, Muzny DM, et al. Secondary findings and carrier test frequencies in a large multiethnic sample. Genome Med. 2015;7: 54. doi: 10.1186/s13073-015-0171-1 26195989
23. Bylstra Y, Kuan JL, Lim WK, Bhalshankar JD, Teo JX, Davila S, et al. Population genomics in South East Asia captures unexpectedly high carrier frequency for treatable inherited disorders. Genet Med. 2019;21: 207–212. doi: 10.1038/s41436-018-0008-6 29961769
24. Delanne J, Nambot S, Chassagne A, Putois O, Pelissier A, Peyron C, et al. Secondary findings from whole-exome/genome sequencing evaluating stakeholder perspectives. A review of the literature. Eur J Med Genet. 2018; doi: 10.1016/j.ejmg.2018.08.010
25. De Wert G, Dondorp W, Shenfield F, Devroey P, Tarlatzis B, Barri P, et al. ESHRE Task Force on Ethics and Law22: Preimplantation Genetic Diagnosis. Hum Reprod. 2014;29: 1610–1617. doi: 10.1093/humrep/deu132 24927929
26. De Rycke M. ESHRE PGD Consortium Data Collection 2016. ESHRE PGD Consortium Data. 2018.
27. Vaz-de-Macedo C, Harper J. A closer look at expanded carrier screening from a PGD perspective. Hum Reprod. 2017;32: 1951–1956. doi: 10.1093/humrep/dex272 28938745
28. Truty R, Paul J, Kennemer M, Lincoln SE, Olivares E, Nussbaum RL, et al. Prevalence and properties of intragenic copy-number variation in Mendelian disease genes. Genet Med. 2019;21: 114–123. doi: 10.1038/s41436-018-0033-5 29895855
29. Lelieveld SH, Spielmann M, Mundlos S, Veltman JA, Gilissen C. Comparison of Exome and Genome Sequencing Technologies for the Complete Capture of Protein-Coding Regions. Hum Mutat. 2015;36: 815–822. doi: 10.1002/humu.22813 25973577
30. Adams DR, Eng CM. Next-Generation Sequencing to Diagnose Suspected Genetic Disorders. N Engl J Med. 2018;379: 1353–1362. doi: 10.1056/NEJMra1711801 30281996
31. Amendola LM, Jarvik GP, Leo MC, McLaughlin HM, Akkari Y, Amaral MD, et al. Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium. Am J Hum Genet. 2016;98: 1067–1076. doi: 10.1016/j.ajhg.2016.03.024 27181684
32. Landrum MJ, Lee JM, Benson M, Brown G, Chao C, Chitipiralla S, et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 2016;44: D862–8. doi: 10.1093/nar/gkv1222 26582918
33. Chen R, Shi L, Hakenberg J, Naughton B, Sklar P, Zhang J, et al. Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases. Nat Biotechnol. 2016;34: 531–538. doi: 10.1038/nbt.3514 27065010
34. Ashley EA. Towards precision medicine. Nat Rev Genet. 2016;17: 507–522. doi: 10.1038/nrg.2016.86 27528417
35. Feng R, Sang Q, Kuang Y, Sun X, Yan Z, Zhang S, et al. Mutations in TUBB8 and Human Oocyte Meiotic Arrest. N Engl J Med. 2016;374: 223–32. doi: 10.1056/NEJMoa1510791 26789871
36. Fakhro KA, Elbardisi H, Arafa M, Robay A, Rodriguez-Flores JL, Al-Shakaki A, et al. Point-of-care whole-exome sequencing of idiopathic male infertility. Genet Med. 2018;20: 1365–1373. doi: 10.1038/gim.2018.10 29790874
37. Stewart KFJ, Wesselius A, Schreurs MAC, Schols AMWJ, Zeegers MP. Behavioural changes, sharing behaviour and psychological responses after receiving direct-to-consumer genetic test results: a systematic review and meta-analysis. J Community Genet. 2018;9: 1–18. doi: 10.1007/s12687-017-0310-z 28664264
38. Martin J, Asan Yi Y, Alberola T, Rodríguez-Iglesias B, Jiménez-Almazán J, et al. Comprehensive carrier genetic test using next-generation deoxyribonucleic acid sequencing in infertile couples wishing to conceive through assisted reproductive technology. Fertil Steril. 2015;104: 1286–93. doi: 10.1016/j.fertnstert.2015.07.1166 26354092
39. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25: 1754–1760. doi: 10.1093/bioinformatics/btp324 19451168
40. Li H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics. 2011;27: 2987–93. doi: 10.1093/bioinformatics/btr509 21903627
41. Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. 2012; Available: http://arxiv.org/abs/1207.3907
42. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin). 2012;6: 80–92. doi: 10.4161/fly.19695
43. 1000 Genomes Project Consortium, Abecasis GR, Altshuler D, Auton A, Brooks LD, Durbin RM, et al. A map of human genome variation from population-scale sequencing. Nature. 2010;467: 1061–73. doi: 10.1038/nature09534 20981092
44. Baudhuin LM, Lagerstedt SA, Klee EW, Fadra N, Oglesbee D, Ferber MJ. Confirming Variants in Next-Generation Sequencing Panel Testing by Sanger Sequencing. J Mol Diagnostics. 2015;17: 456–461. doi: 10.1016/j.jmoldx.2015.03.004
45. Beck TF, Mullikin JC, NISC Comparative Sequencing Program LG, Biesecker LG. Systematic Evaluation of Sanger Validation of Next-Generation Sequencing Variants. Clin Chem. 2016;62: 647–54. doi: 10.1373/clinchem.2015.249623 26847218
46. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. 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: 405–24. doi: 10.1038/gim.2015.30 25741868
47. Ceyhan-Birsoy O, Machini K, Lebo MS, Yu TW, Agrawal PB, Parad RB, et al. A curated gene list for reporting results of newborn genomic sequencing. Genet Med. 2017;19: 809–818. doi: 10.1038/gim.2016.193 28079900
48. Rehm HL, Berg JS, Brooks LD, Bustamante CD, Evans JP, Landrum MJ, et al. ClinGen—The Clinical Genome Resource. N Engl J Med. 2015;372: 2235–2242. doi: 10.1056/NEJMsr1406261 26014595
49. Lazarin GA, Hawthorne F, Collins NS, Platt EA, Evans EA, Haque IS. Systematic Classification of Disease Severity for Evaluation of Expanded Carrier Screening Panels. Baak JPA, editor. PLoS One. 2014;9: e114391. doi: 10.1371/journal.pone.0114391 25494330
50. Yrigollen CM, Durbin-Johnson B, Gane L, Nelson DL, Hagerman R, Hagerman PJ, et al. AGG interruptions within the maternal FMR1 gene reduce the risk of offspring with fragile X syndrome. Genet Med. 2012;14: 729–736. doi: 10.1038/gim.2012.34 22498846
51. Kopanos C, Tsiolkas V, Kouris A, Chapple CE, Albarca Aguilera M, Meyer R, et al. VarSome: the human genomic variant search engine. Wren J, editor. Bioinformatics. 2018; doi: 10.1093/bioinformatics/bty897
Štítky
Genetika Reprodukční medicínaČlánek vyšel v časopise
PLOS Genetics
2019 Číslo 10
- Management pacientů s MPN a neobvyklou kombinací genových přestaveb – systematický přehled a kazuistiky
- Management péče o pacientku s karcinomem ovaria a neočekávanou mutací CDH1 – kazuistika
- Primární hyperoxalurie – aktuální možnosti diagnostiky a léčby
- Vliv kvality morfologie spermií na úspěšnost intrauterinní inseminace
- Akutní intermitentní porfyrie
Nejčtenější v tomto čísle
- Spatiotemporal cytoskeleton organizations determine morphogenesis of multicellular trichomes in tomato
- Loss of thymidine kinase 1 inhibits lung cancer growth and metastatic attributes by reducing GDF15 expression
- TSEN54 missense variant in Standard Schnauzers with leukodystrophy
- Viral quasispecies