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Genome-wide linkage in Utah autism pedigrees

Abstract

Genetic studies of autism over the past decade suggest a complex landscape of multiple genes. In the face of this heterogeneity, studies that include large extended pedigrees may offer valuable insights, as the relatively few susceptibility genes within single large families may be more easily discerned. This genome-wide screen of 70 families includes 20 large extended pedigrees of 6–9 generations, 6 moderate-sized families of 4–5 generations and 44 smaller families of 2–3 generations. The Center for Inherited Disease Research (CIDR) provided genotyping using the Illumina Linkage Panel 12, a 6K single-nucleotide polymorphism (SNP) platform. Results from 192 subjects with an autism spectrum disorder (ASD) and 461 of their relatives revealed genome-wide significance on chromosome 15q, with three possibly distinct peaks: 15q13.1–q14 (heterogeneity LOD (HLOD)=4.09 at 29 459 872 bp); 15q14–q21.1 (HLOD=3.59 at 36 837 208 bp); and 15q21.1–q22.2 (HLOD=5.31 at 55 629 733 bp). Two of these peaks replicate earlier findings. There were additional suggestive results on chromosomes 2p25.3–p24.1 (HLOD=1.87), 7q31.31–q32.3 (HLOD=1.97) and 13q12.11–q12.3 (HLOD=1.93). Affected subjects in families supporting the linkage peaks found in this study did not reveal strong evidence for distinct phenotypic subgroups.

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References

  1. Rice C, Autism and Developmental Disabilities Monitoring Network Surveillance Year 2002 Principal Investigators. Prevalence of autism spectrum disorders–autism and developmental disabilities monitoring network, 14 sites, US, 2002. MMWR Surveill Summ 2007; 56: 12–28.

    Google Scholar 

  2. Landa RJ, Holman KC, Garrett-Mayer E . Social and communication development in toddlers with early and later diagnosis of autism spectrum disorders. Arch Gen Psychiatry 2007; 64: 853–864.

    Article  Google Scholar 

  3. Landa RJ . Diagnosis of autism spectrum disorders in the first 3 years of life. Nat Clin Pract Neurol 2008; 4: 138–147.

    Article  Google Scholar 

  4. Abrahams BS, Geschwind DH . Advances in autism genetics: on the threshold of a new neurobiology. Nat Rev Genet 2008; 9: 341–355.

    Article  CAS  Google Scholar 

  5. Blangero J, Williams JT, Almasy L . Novel family-based approaches to genetic risk in thrombosis. J Thromb Haemost 2003; 1: 1391–1397.

    Article  CAS  Google Scholar 

  6. Terwilliger JD, Haghighi F, Hiekkalinna TS, Goring HH . A biased assessment of the use of SNPs in human complex traits. Curr Opin Genet Dev 2002; 12: 726–734.

    Article  CAS  Google Scholar 

  7. Allen-Brady K, Miller J, Matsunami N, Stevens J, Block H, Farley M et al. A high-density SNP genome-wide linkage scan in a large autism extended pedigree. Mol Psychiatry 2008; February 19; [e-pub ahead of print].

  8. Ritvo ER, Mason-Brothers A, Jenson WP, Freeman BJ, Mo A, Pingree C et al. A report of one family with four autistic siblings and four families with three autistic siblings. J Am Acad Child Adolesc Psychiatry 1987; 26: 339–341.

    Article  CAS  Google Scholar 

  9. Jorde LB . Inbreeding in the Utah Mormons: an evaluation of estimates based on pedigrees, isonymy, and migration matrices. Ann Hum Genet 1989; 53: 339–355.

    Article  CAS  Google Scholar 

  10. Jorde LB . Consanguinity and prereproductive mortality in the Utah Mormon population. Hum Hered 2001; 52: 61–65.

    Article  CAS  Google Scholar 

  11. Berument SK, Rutter M, Lord C, Pickles A, Bailey A . Autism Screening Questionnaire. Western Psychological Services: Los Angeles, CA, 1999.

    Google Scholar 

  12. Lord C, Rutter M, Le Couteur A . Autism Diagnostic Interview-Revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord 1994; 24: 659–685.

    Article  CAS  Google Scholar 

  13. Baranek GT, Bodfish JW, Gordon AM, Houser MB, Poe MD . Concurrent validity of the ADI-R and SCQ in high functioning autism. In: Collaborative Programs of Excellence in Autism/Studies to Advance Autism. Research and Treatment Annual Meeting; 2004: Bethesda, MD, 2004.

    Google Scholar 

  14. Lord C, Risi S, Lambrecht L, Cook Jr EH, Leventhal BL, DiLavore PC et al. The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord 2000; 30: 205–223.

    Article  CAS  Google Scholar 

  15. Wechsler D . Manual for the Wechsler Intelligence Scale for Children-Third Edition. The Psychological Corporation: San Antonio, TX, 1991.

    Google Scholar 

  16. Wechsler D . Wechsler Adult Intelligence Scale—Third Edition. The Psychological Corporation: San Antonio, TX, 1997.

    Google Scholar 

  17. Elliott C . Differential Ability Scales. The Psychological Corporation: San Antonio, TX, 1990.

    Google Scholar 

  18. Mullen E . Mullen Scales of Early Learning, AGS Edition. American Guidance Service: Circle Pines, MN, 1995.

    Google Scholar 

  19. Dicerbo KE BA . A convergent validity study of the differential ability scales and the Wechsler Intelligence Scale for Children-Third Edition with Hispanic Children. J Psychoed Assess 2000; 344–352.

  20. Dumont R CC, Price L, Whelley P . The relationship between the Differential Ability Scales (DAS) and the Wechsler Intelligence Scale for Children—Third Edition (WISC-III) for students with learning disabilities. Psychol Sch 1996; 203–209.

  21. Sattler J . Assessment of Children: Cognitive Applications. Jerome M Sattler Publisher Inc.: La Mesa, CA, 2001.

    Google Scholar 

  22. O'Connell JR WD . PedCheck: a program for identifying genotype incompatibilities in linkage analysis. Am J Hum Genet 1998; 259–266.

  23. Kong A, Gudbjartsson DF, Sainz J, Jonsdottir GM, Gudjonsson SA, Richardsson B et al. A high-resolution recombination map of the human genome. Nat Genet 2002; 31: 241–247.

    Article  CAS  Google Scholar 

  24. Thomas A, Gutin A, Abkevich V, Bansal, A . Multipoint linkage analysis by blocked Gibbs sampling. Stat Comput 2000; 259–269.

  25. Coon H, Matsunami N, Stevens J, Miller J, Pingree C, Camp NJ et al. Evidence for linkage on chromosome 3q25–27 in a large autism extended pedigree. Hum Hered 2006; 60: 220–226.

    Article  Google Scholar 

  26. Christensen GB, Camp NJ, Farnham JM, Cannon-Albright LA . Genome-wide linkage analysis for aggressive prostate cancer in Utah high-risk pedigrees. Prostate 2007; 67: 605–613.

    Article  CAS  Google Scholar 

  27. Terwilliger JD, Goring HH . Gene mapping in the 20th and 21st centuries: statistical methods, data analysis, and experimental design. Hum Biol 2000; 72: 63–132.

    CAS  PubMed  Google Scholar 

  28. Goring HH, Terwilliger JD . Linkage analysis in the presence of errors I: complex-valued recombination fractions and complex phenotypes. Am J Hum Genet 2000; 66: 1095–1106.

    Article  CAS  Google Scholar 

  29. Greenberg DA, Abreu P, Hodge SE . The power to detect linkage in complex disease by means of simple LOD-score analyses. Am J Hum Genet 1998; 63: 870–879.

    Article  CAS  Google Scholar 

  30. Abkevich V, Camp NJ, Gutin A, Farnham JM, Cannon-Albright L, Thomas A . A robust multipoint linkage statistic (tlod) for mapping complex trait loci. Genet Epidemiol 2001; 21: S492–S497.

    Article  Google Scholar 

  31. Goldin LR . Detection of linkage under heterogeneity: comparison of the two-locus vs. admixture models. Genet Epidemiol 1992; 9: 61–66.

    Article  CAS  Google Scholar 

  32. Abreu PC, Greenberg DA, Hodge SE . Direct power comparisons between simple LOD scores and NPL scores for linkage analysis in complex diseases. Am J Hum Genet 1999; 65: 847–857.

    Article  CAS  Google Scholar 

  33. Hunt SC, Abkevich V, Hensel CH, Gutin A, Neff CD, Russell DL et al. Linkage of body mass index to chromosome 20 in Utah pedigrees. Hum Genet 2001; 109: 279–285.

    Article  CAS  Google Scholar 

  34. Christensen GB, Cannon-Albright LA, Thomas A, Camp NJ . Extracting disease risk profiles from expression data for linkage analysis: application to prostate cancer. BMC Proc 2007; 1: S82.

    Article  Google Scholar 

  35. Goode EL, Jarvik GP . Assessment and implications of linkage disequilibrium in genome-wide single-nucleotide polymorphism and microsatellite panels. Genet Epidemiol 2005; 29: S72–S76.

    Article  Google Scholar 

  36. Huang Q, Shete S, Amos CI . Ignoring linkage disequilibrium among tightly linked markers induces false-positive evidence of linkage for affected sib pair analysis. Am J Hum Genet 2004; 75: 1106–1112.

    Article  CAS  Google Scholar 

  37. Levinson DF, Holmans P . The effect of linkage disequilibrium on linkage analysis of incomplete pedigrees. BMC Genet 2005; 6: S6.

    Article  Google Scholar 

  38. Chen WV, Amos CI, Etzel CJ, Shete S, Gregersen PK . Comparison of genome-wide single-nucleotide polymorphism linkage analyses in Caucasian and Hispanic NARAC families. BMC Proc 2007; 1: S97.

    Article  Google Scholar 

  39. Allen-Brady K, Horne BD, Malhotra A, Teerlink C, Camp NJ, Thomas A . Analysis of high-density single-nucleotide polymorphism data: three novel methods that control for linkage disequilibrium between markers in a linkage analysis. BMC Proc 2007; 1: S160.

    Article  Google Scholar 

  40. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007; 81: 559–575.

    Article  CAS  Google Scholar 

  41. Lander E, Kruglyak L . Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nat Genet 1995; 11: 241–247.

    Article  CAS  Google Scholar 

  42. Trikalinos TA, Karvouni A, Zintzaras E, Ylisaukko-oja T, Peltonen L, Järvelä I et al. A heterogeneity-based genome search meta-analysis for autism-spectrum disorders. Mol Psychiatry 2006; 11: 29–36.

    Article  CAS  Google Scholar 

  43. Schellenberg GD, Dawson G, Sung YJ, Estes A, Munson J, Rosenthal E et al. Evidence for multiple loci from a genome scan of autism kindreds. Mol Psychiatry 2006; 11: 1049–1060, 979.

    Article  CAS  Google Scholar 

  44. Marshall CR, Noor A, Vincent JB, Lionel AC, Feuk L, Skaug J et al. Structural variation of chromosomes in autism spectrum disorder. Am J Hum Genet 2008; 82: 477–488.

    Article  CAS  Google Scholar 

  45. Christian SL, Brune CW, Sudi J, Kumar RA, Liu S, Karamohamed S et al. Novel submicroscopic chromosomal abnormalities detected in autism spectrum disorder. Biol Psychiatry 2008; 63: 1111–1117.

    Article  CAS  Google Scholar 

  46. Liu XQ, Paterson AD, Szatmari P . Genome-wide linkage analyses of quantitative and categorical autism subphenotypes. Biol Psychiatry 2008; 64: 561–570.

    Article  CAS  Google Scholar 

  47. Szatmari P, Paterson AD, Zwaigenbaum L, Roberts W, Brian J, Liu XQ et al. Mapping autism risk loci using genetic linkage and chromosomal rearrangements. Nat Genet 2007; 39: 319–328.

    Article  CAS  Google Scholar 

  48. Lamb JA, Barnby G, Bonora E, Sykes N, Bacchelli E, Blasi F et al. Analysis of IMGSAC autism susceptibility loci: evidence for sex limited and parent of origin specific effects. J Med Genet 2005; 42: 132–137.

    Article  CAS  Google Scholar 

  49. Rajcan-Separovic E, Harvard C, Liu X, McGillivray B, Hall JG, Qiao Y et al. Clinical and molecular cytogenetic characterisation of a newly recognised microdeletion syndrome involving 2p15-16.1. J Med Genet 2007; 44: 269–276.

    Article  CAS  Google Scholar 

  50. Kim HG, Kishikawa S, Higgins AW, Seong IS, Donovan DJ, Shen Y et al. Disruption of neurexin 1 associated with autism spectrum disorder. Am J Hum Genet 2008; 82: 199–207.

    Article  CAS  Google Scholar 

  51. International Molecular Genetic Study of Autism Consortium. A full genome screen for autism with evidence for linkage to a region on chromosome 7q. Hum Mol Genet 1998; 7: 571–578.

    Article  CAS  Google Scholar 

  52. International Molecular Genetic Study of Autism Consortium. A genomewide screen for autism: strong evidence for linkage to chromosomes 2q, 7q, and 16p. Am J Hum Genet 2001; 69: 570–581.

    Article  Google Scholar 

  53. Schellenberg GD, Dawson G, Sung YJ, Estes A, Munson J, Rosenthal E et al. Evidence for multiple loci from a genome scan of autism kindreds. Mol Psychiatry 2006; 11: 1049–1060.

    Article  CAS  Google Scholar 

  54. Further characterization of the autism susceptibility locus AUTS1 on chromosome 7q. Hum Mol Genet 2001; 10: 973–982.

  55. Persico AM, D'Agruma L, Maiorano N, Totaro A, Militerni R, Bravaccio C et al. Reelin gene alleles and haplotypes as a factor predisposing to autistic disorder. Mol Psychiatry 2001; 6: 150–159.

    Article  CAS  Google Scholar 

  56. Bonora E, Beyer KS, Lamb JA, Parr JR, Klauck SM, Benner A et al. Analysis of reelin as a candidate gene for autism. Mol Psychiatry 2003; 8: 885–892.

    Article  CAS  Google Scholar 

  57. Skaar DA, Shao Y, Haines JL, Stenger JE, Jaworski J, Martin ER et al. Analysis of the RELN gene as a genetic risk factor for autism. Mol Psychiatry 2005; 10: 563–571.

    Article  CAS  Google Scholar 

  58. Serajee FJ, Zhong H, Mahbubul Huq AH . Association of Reelin gene polymorphisms with autism. Genomics 2006; 87: 75–83.

    Article  CAS  Google Scholar 

  59. Sadakata T, Washida M, Iwayama Y, Shoji S, Sato Y, Ohkura T et al. Autistic-like phenotypes in Cadps2-knockout mice and aberrant CADPS2 splicing in autistic patients. J Clin Invest 2007; 117: 931–943.

    Article  CAS  Google Scholar 

  60. Campbell DB, D'Oronzio R, Garbett K, Ebert PJ, Mirnics K, Levitt P et al. Disruption of cerebral cortex MET signaling in autism spectrum disorder. Ann Neurol 2007; 62: 243–250.

    Article  Google Scholar 

  61. Campbell DB, Sutcliffe JS, Ebert PJ, Militerni R, Bravaccio C, Trillo S et al. A genetic variant that disrupts MET transcription is associated with autism. Proc Natl Acad Sci USA 2006; 103: 16834–16839.

    Article  CAS  Google Scholar 

  62. Barrett S, Beck JC, Bernier R, Bisson E, Braun TA, Casavant TL et al. An autosomal genomic screen for autism. Collaborative linkage study of autism. Am J Med Genet 1999; 88: 609–615.

    Article  CAS  Google Scholar 

  63. Bartlett CW, Flax JF, Logue MW, Vieland VJ, Bassett AS, Tallal P et al. A major susceptibility locus for specific language impairment is located on 13q21. Am J Hum Genet 2002; 71: 45–55.

    Article  CAS  Google Scholar 

  64. Bartlett CW, Flax JF, Logue MW, Smith BJ, Vieland VJ, Tallal P et al. Examination of potential overlap in autism and language loci on chromosomes 2, 7, and 13 in two independent samples ascertained for specific language impairment. Hum Hered 2004; 57: 10–20.

    Article  Google Scholar 

  65. Castermans D, Wilquet V, Parthoens E, Huysmans C, Steyaert J, Swinnen L et al. The neurobeachin gene is disrupted by a translocation in a patient with idiopathic autism. J Med Genet 2003; 40: 352–356.

    Article  CAS  Google Scholar 

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Acknowledgements

This work was supported by R01 MH06359, the Utah Autism Foundation, the Carmen B Pingree School for Children with Autism and GCRC M01-RR025764 from the National Center for Research Resources. Partial support for all data sets within the Utah Population Database (UPDB) was provided by the University of Utah Huntsman Cancer Institute. We thank our staff whose countless hours of work have made this study possible. We also greatly appreciate the time and effort given by the family members who participated in this study.

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Correspondence to H Coon.

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Drs Coon, McMahon, Miller, and Leppert received partial salary support from Lineagen Inc. (www.lineagen.com). Lineagen is funding University of Utah research in biomarker discovery for multiple sclerosis, osteoporosis, chronic obstructive pulmonary disease, and autism.

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Allen-Brady, K., Robison, R., Cannon, D. et al. Genome-wide linkage in Utah autism pedigrees. Mol Psychiatry 15, 1006–1015 (2010). https://doi.org/10.1038/mp.2009.42

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