Supplementary Table S1. Variation found in 56 ACMG genes in whole exome sequences of 232 individuals.
Whole exome sequences from 232 individuals representing 89 families were analyzed for rare (MAF0.01), nonsynonymous and splice variants and indels in the 56 genes on the ACMG list.1 We identified 249 distinct variants, some of which were seen in more than one individual. The number and density of variants (number of variants/kb coding sequence) varied by gene. Some genes had better sequencing coverage than others.
Supplementary Table S2. Discordant classification of variants among databases.
Three databases (HGMD,2,3 ClinVar,4,5 and Emory6,7) were examined for classification of the 249 distinct variants identified in 232 individuals’ whole exome sequences. Of 48 variants which were classified by more than one database, 22 variants were given discordant classifications between databases. We then compared these database classifications to our variant classifications derived from the Dorschner et al. method8 and found that variant classifications given by the ClinVar and Emory databases but not HGMD were generally consistent with our variant classifications. These results show the lack of consensus for variant classification methodologies among currently available databases. (Abbreviations: DM-Disease-causing (pathological) mutation, based on information from the literature; VUS-Variant of Uncertain Significance; N/A- variant was not listed in this database).
REFERENCES
1. Green RC, Berg JS, Grody WW,et al. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med 2013; 15(7): 565-574.
2. Stenson PD, Ball EV, Mort M,et al.The human gene mutation database (HGMD): 2003 update.Hum Mutat2003;21: 577–581.
3. The Human Gene Mutation Database. Available at Accessed April 2013.
4. Landrum MJ, Lee JM, Riley GR, Jang W, Rubinstein WS, Church DM, Maglott DR. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res. 2014; 42(1):D980-5.
5. ClinVar variant database. Accessed June-August 2013.
6. Bean LJH, Tinker SW, da Silva C,Hegde MR. Free the Data: One Laboratory's Approach to Knowledge-Based Genomic Variant Classification and Preparation for EMR Integration of Genomic Data. Hum. Mutat. 2013; 34:1183–1188.
7. Emory Genetics Laboratory. Accessed June-August 2013.
8. Dorschner MO, Amendola LM, Turner EH, et al. Actionable, Pathogenic Incidental Findings in 1,000 Participants’ Exomes. Am J Hum Genet2013; 93: 1-10.
9. Judkins T,Hendrickson BC,Deffenbaugh AM, et al.Application of embryonic lethal or other obvious phenotypes to characterize the clinical significance of genetic variants found in trans with known deleterious mutations.Cancer Res.2005;65:10096‒10103.
10. Tavtigian SV, Deffenbaugh AM, Yin L, Judkins T, Scholl T, Samollow PB, de Silva D, Zharkikh A, Thomas A. Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eight recurrent substitutions as neutral. J Med Genet 2006; 43: 295–305.
11. Phelan CM, Dapic V, Tice B, et al. Classification of BRCA1 missense variants of unknown clinical significance.J Med Gen 2005;42:138–146.
12. Edwards SM, Kote-Jarai Z, Hamoudi R, Eeles RA. An improved high throughput heteroduplex mutation detection system for screeningBRCA2mutations-fluorescent mutation detection (F-MD). Hum Mutat2001; 17: 220–232.
13. Cavallone L, Arcand SL, Maugard CM, Nolet S, Gaboury LA, Mes-Masson AM, Ghadirian P, Provencher D, Tonin PN. Comprehensive BRCA1 and BRCA2 mutation analyses and review of French Canadian families with at least three cases of breast cancer. Fam Cancer2010; 9(4):507–517.
14. ClinVar variant database. Accession numbers SCV000146832, SCV000186080.Accessed June-August 2013.
15. MaloneKE, DalingJR, NealC,et al.Frequency ofBRCA1/BRCA2mutations in a population-based sample of young breast carcinoma cases.Cancer2000;88:1393-1402.
16. ClinVar variant database. Accession numbers SCV000054401, SCV000147537.Accessed June-August 2013.
17. Al-Jassar C,Knowles T, Jeeves M, Kami K, Behr E, Bikker H, Overdiun M, Chidgey M. The nonlinear structure of the desmoplakin plakin domain and the effects of cardiomyopathy-linked mutations.J Mol Biol2011; 411: 1049–1061.
18. Samowitz WS, Curtin K, Lin HH, etal. The colon cancer burden of genetically definedhereditary nonpolyposis colon cancer. Gastroenterology 2001;121:830 –838.
19. ClinVar variant database. Accession number SCV000107764.Accessed June-August 2013.
20. Jaaskelainen P, Kuusisto J, Miettinen R, et al. Mutations in the cardiacmyosin-binding protein C gene are the predominant cause of familialhypertrophic cardiomyopathy in eastern Finland. J Mol Med 2002;80:412–422.
21. Moolman-Smook JC, De Lange WJ, Bruwer EC, Brink PA,Corfield VA. The origins of hypertrophic cardiomyopathy-causingmutations in two South African subpopulations: a unique profile ofboth independent and founder events. Am J Hum Genet 1999;65:1308–1320.
22. Ehlermann P, Weichenhan D, Zehelein J, Steen H, Pribe R, Zeller R, Lehrke S, Zugck C, Ivandic BT, Katus HA. Adverse events in families with hypertrophic or dilated cardiomyopathy and mutations in the MYBPC3 gene. BMC Med Genet 2008; 9:95.
23. Rodriguez-GarciaMI,MonserratL,OrtizM,et al.Screening mutations in myosin binding protein C3 gene in a cohort of patients with Hypertrophic Cardiomyopathy.BMC Med Genet2010;11:67.
24. Olivotto I, Girolami F, Sciagra R, et al.Myofilament protein gene mutation screening and outcome of patients with hypertrophic cardiomyopathy.Mayo Clin Proc 2008;83: 630–638.
25. Richard P, Charron P, Carrier L,et al.Hypertrophic cardiomyopathy: distribution of disease genes, spectrum of mutations, and implications for a molecular diagnosis strategy. Circulation 2003; 107: 2227–2232.