Pauline Chaste1, Lambertus Klei2, Stephan J Sanders3, Vanessa Hus4, Michael T Murtha5, Jennifer K Lowe6, A Jeremy Willsey3, Daniel Moreno-De-Luca7, Timothy W Yu8, Eric Fombonne9, Daniel Geschwind6, Dorothy E Grice10, David H Ledbetter11, Shrikant M Mane12, Donna M Martin13, Eric M Morrow14, Christopher A Walsh15, James S Sutcliffe16, Christa Lese Martin11, Arthur L Beaudet17, Catherine Lord18, Matthew W State3, Edwin H Cook19, Bernie Devlin2. 1. Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; FondaMental Foundation, Créteil; Centre Hospitalier Sainte Anne, Paris, France. Electronic address: p.chaste@ch-sainte-anne.fr. 2. Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania. 3. Department of Genetics, Yale University School of Medicine, New Haven, Connecticut; Department of Psychiatry, University of California at San Francisco, San Francisco, California. 4. Department of Psychology, University of Michigan, Ann Arbor, Michigan. 5. Program on Neurogenetics, Yale University School of Medicine, New Haven, Connecticut. 6. Neurogenetics Program, Department of Neurology and Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California. 7. Program on Neurogenetics, Yale University School of Medicine, New Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut. 8. Division of Genetics, Children's Hospital Boston, Harvard Medical School, Boston, Massachusetts. 9. Department of Psychiatry and Institute for Development and Disability, Oregon Health & Science University, Portland, Oregon. 10. Department of Psychiatry, Mount Sinai School of Medicine, New York, New York. 11. Autism and Developmental Medicine Institute, Geisinger Health System, Danville, Pennsylvania. 12. Yale Center for Genome Analysis, Orange, Connecticut. 13. Departments of Pediatrics and Human Genetics, University of Michigan Medical Center, Ann Arbor, Michigan. 14. Department of Molecular Biology, Cell Biology and Biochemistry, and Department of Psychiatry and Human Behavior, Brown University, Providence, Rhode Island. 15. Howard Hughes Medical Institute and Division of Genetics, Children's Hospital Boston, and Neurology and Pediatrics, Harvard Medical School Center for Life Sciences, Boston, Massachusetts. 16. Departments of Molecular Physiology & Biophysics and Psychiatry, Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee. 17. Department of Human and Molecular Genetics, Baylor College of Medicine, Houston, Texas. 18. Center for Autism and the Developing Brain, Weill Cornell Medical College, White Plains, New York. 19. Institute for Juvenile Research, Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois.
Abstract
BACKGROUND: Phenotypic heterogeneity in autism has long been conjectured to be a major hindrance to the discovery of genetic risk factors, leading to numerous attempts to stratify children based on phenotype to increase power of discovery studies. This approach, however, is based on the hypothesis that phenotypic heterogeneity closely maps to genetic variation, which has not been tested. Our study examines the impact of subphenotyping of a well-characterized autism spectrum disorder (ASD) sample on genetic homogeneity and the ability to discover common genetic variants conferring liability to ASD. METHODS: Genome-wide genotypic data of 2576 families from the Simons Simplex Collection were analyzed in the overall sample and phenotypic subgroups defined on the basis of diagnosis, IQ, and symptom profiles. We conducted a family-based association study, as well as estimating heritability and evaluating allele scores for each phenotypic subgroup. RESULTS: Association analyses revealed no genome-wide significant association signal. Subphenotyping did not increase power substantially. Moreover, allele scores built from the most associated single nucleotide polymorphisms, based on the odds ratio in the full sample, predicted case status in subsets of the sample equally well and heritability estimates were very similar for all subgroups. CONCLUSIONS: In genome-wide association analysis of the Simons Simplex Collection sample, reducing phenotypic heterogeneity had at most a modest impact on genetic homogeneity. Our results are based on a relatively small sample, one with greater homogeneity than the entire population; if they apply more broadly, they imply that analysis of subphenotypes is not a productive path forward for discovering genetic risk variants in ASD.
BACKGROUND: Phenotypic heterogeneity in autism has long been conjectured to be a major hindrance to the discovery of genetic risk factors, leading to numerous attempts to stratify children based on phenotype to increase power of discovery studies. This approach, however, is based on the hypothesis that phenotypic heterogeneity closely maps to genetic variation, which has not been tested. Our study examines the impact of subphenotyping of a well-characterized autism spectrum disorder (ASD) sample on genetic homogeneity and the ability to discover common genetic variants conferring liability to ASD. METHODS: Genome-wide genotypic data of 2576 families from the Simons Simplex Collection were analyzed in the overall sample and phenotypic subgroups defined on the basis of diagnosis, IQ, and symptom profiles. We conducted a family-based association study, as well as estimating heritability and evaluating allele scores for each phenotypic subgroup. RESULTS: Association analyses revealed no genome-wide significant association signal. Subphenotyping did not increase power substantially. Moreover, allele scores built from the most associated single nucleotide polymorphisms, based on the odds ratio in the full sample, predicted case status in subsets of the sample equally well and heritability estimates were very similar for all subgroups. CONCLUSIONS: In genome-wide association analysis of the Simons Simplex Collection sample, reducing phenotypic heterogeneity had at most a modest impact on genetic homogeneity. Our results are based on a relatively small sample, one with greater homogeneity than the entire population; if they apply more broadly, they imply that analysis of subphenotypes is not a productive path forward for discovering genetic risk variants in ASD.
Authors: J D Buxbaum; J Silverman; M Keddache; C J Smith; E Hollander; N Ramoz; J G Reichert Journal: Mol Psychiatry Date: 2004-02 Impact factor: 15.992
Authors: Veronica J Vieland; Joachim Hallmayer; Yungui Huang; Alistair T Pagnamenta; Dalila Pinto; Hameed Khan; Anthony P Monaco; Andrew D Paterson; Stephen W Scherer; James S Sutcliffe; Peter Szatmari Journal: J Neurodev Disord Date: 2011-01-19 Impact factor: 4.025
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Authors: Amy Hewitt; Jennifer Hall-Lande; Kristin Hamre; Amy N Esler; Judy Punyko; Joe Reichle; Anab A Gulaid Journal: J Autism Dev Disord Date: 2016-08
Authors: Arija Jansen; Gwen C Dieleman; August B Smit; Matthijs Verhage; Frank C Verhulst; Tinca J C Polderman; Danielle Posthuma Journal: Eur J Hum Genet Date: 2017-04-19 Impact factor: 4.246
Authors: F Kyle Satterstrom; Jack A Kosmicki; Jiebiao Wang; Michael S Breen; Silvia De Rubeis; Joon-Yong An; Minshi Peng; Ryan Collins; Jakob Grove; Lambertus Klei; Christine Stevens; Jennifer Reichert; Maureen S Mulhern; Mykyta Artomov; Sherif Gerges; Brooke Sheppard; Xinyi Xu; Aparna Bhaduri; Utku Norman; Harrison Brand; Grace Schwartz; Rachel Nguyen; Elizabeth E Guerrero; Caroline Dias; Catalina Betancur; Edwin H Cook; Louise Gallagher; Michael Gill; James S Sutcliffe; Audrey Thurm; Michael E Zwick; Anders D Børglum; Matthew W State; A Ercument Cicek; Michael E Talkowski; David J Cutler; Bernie Devlin; Stephan J Sanders; Kathryn Roeder; Mark J Daly; Joseph D Buxbaum Journal: Cell Date: 2020-01-23 Impact factor: 41.582