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Table of Contents
Vol. 70, No. 4, 2010
Issue release date: February 2011
Open Access Gateway
Hum Hered 2010;70:232–244
(DOI:10.1159/000320367)

Increasing Genotype-Phenotype Model Determinism: Application to Bivariate Reading/Language Traits and Epistatic Interactions in Language-Impaired Families

Simmons T.R.a · Flax J.F.b, c · Azaro M.A.c · Hayter J.E.c · Justice L.M.d · Petrill S.A.e · Bassett A.S.f · Tallal P.b · Brzustowicz L.M.c · Bartlett C.W.a
aBattelle Center for Mathematical Medicine, Research Institute at Nationwide Children’s Hospital and Department of Pediatrics, Ohio State University, Columbus, Ohio, bCenter for Molecular and Behavioral Neuroscience, Rutgers University, Newark, N.J., cDepartment of Genetics, Rutgers University, Piscataway, N.J., dSchool of Teaching and Learning and eDepartment of Human Development and Family Science, Ohio State University, Columbus, Ohio, USA; fDepartment of Psychiatry, University of Toronto, and Schizophrenia Research Program, Queen Street Division, Centre for Addiction and Mental Health, Toronto, Ont., Canada
email Corresponding Author

Abstract

While advances in network and pathway analysis have flourished in the era of genome-wide association analysis, understanding the genetic mechanism of individual loci on phenotypes is still readily accomplished using genetic modeling approaches. Here, we demonstrate two novel genotype-phenotype models implemented in a flexible genetic modeling platform. The examples come from analysis of families with specific language impairment (SLI), a failure to develop normal language without explanatory factors such as low IQ or inadequate environment. In previous genome-wide studies, we observed strong evidence for linkage to 13q21 with a reading phenotype in language-impaired families. First, we elucidate the genetic architecture of reading impairment and quantitative language variation in our samples using a bivariate analysis of reading impairment in affected individuals jointly with language quantitative phenotypes in unaffected individuals. This analysis largely recapitulates the baseline analysis using the categorical trait data (posterior probability of linkage (PPL) = 80%), indicating that our reading impairment phenotype captured poor readers who also have low language ability. Second, we performed epistasis analysis using a functional coding variant in the brain-derived neurotrophic factor (BDNF) gene previously associated with reduced performance on working memory tasks. Modeling epistasis doubled the evidence on 13q21 and raised the PPL to 99.9%, indicating that BDNF and 13q21 susceptibility alleles are jointly part of the genetic architecture of SLI. These analyses provide possible mechanistic insights for further cognitive neuroscience studies based on the models developed herein.


 goto top of outline Key Words

  • Genetic epistasis
  • Genetic association study
  • Genetic linkage
  • Penetrance
  • Bayesian analysis

 goto top of outline Abstract

While advances in network and pathway analysis have flourished in the era of genome-wide association analysis, understanding the genetic mechanism of individual loci on phenotypes is still readily accomplished using genetic modeling approaches. Here, we demonstrate two novel genotype-phenotype models implemented in a flexible genetic modeling platform. The examples come from analysis of families with specific language impairment (SLI), a failure to develop normal language without explanatory factors such as low IQ or inadequate environment. In previous genome-wide studies, we observed strong evidence for linkage to 13q21 with a reading phenotype in language-impaired families. First, we elucidate the genetic architecture of reading impairment and quantitative language variation in our samples using a bivariate analysis of reading impairment in affected individuals jointly with language quantitative phenotypes in unaffected individuals. This analysis largely recapitulates the baseline analysis using the categorical trait data (posterior probability of linkage (PPL) = 80%), indicating that our reading impairment phenotype captured poor readers who also have low language ability. Second, we performed epistasis analysis using a functional coding variant in the brain-derived neurotrophic factor (BDNF) gene previously associated with reduced performance on working memory tasks. Modeling epistasis doubled the evidence on 13q21 and raised the PPL to 99.9%, indicating that BDNF and 13q21 susceptibility alleles are jointly part of the genetic architecture of SLI. These analyses provide possible mechanistic insights for further cognitive neuroscience studies based on the models developed herein.

Copyright © 2010 S. Karger AG, Basel


 goto top of outline References
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 goto top of outline Author Contacts

Assistant Prof. Christopher W. Bartlett, PhD, Battelle Center for
Mathematical Medicine, Research Institute at Nationwide Children’s Hospital and Ohio State University, JW3926, 700 Children’s Drive, Columbus, OH 43205 (USA)
Tel. +1 614 722 2688, Fax +1 614 355 2728
E-Mail christopher.bartlett@nationwidechildrens.org


 goto top of outline Article Information

Received: May 14, 2010
Accepted after revision: August 13, 2010
Published online: October 14, 2010
Number of Print Pages : 13
Number of Figures : 3, Number of Tables : 2, Number of References : 102
Additional supplementary material is available online - Number of Parts : 1


 goto top of outline Publication Details

Human Heredity (International Journal of Human and Medical Genetics)

Vol. 70, No. 4, Year 2010 (Cover Date: February 2011)

Journal Editor: Devoto M. (Philadelphia, Pa.)
ISSN: 0001-5652 (Print), eISSN: 1423-0062 (Online)

For additional information: http://www.karger.com/HHE


Open Access License / Drug Dosage / Disclaimer

Open Access License: This is an Open Access article licensed under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported license (CC BY-NC) (www.karger.com/OA-license), applicable to the online version of the article only. Distribution permitted for non-commercial purposes only.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in goverment regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

Abstract

While advances in network and pathway analysis have flourished in the era of genome-wide association analysis, understanding the genetic mechanism of individual loci on phenotypes is still readily accomplished using genetic modeling approaches. Here, we demonstrate two novel genotype-phenotype models implemented in a flexible genetic modeling platform. The examples come from analysis of families with specific language impairment (SLI), a failure to develop normal language without explanatory factors such as low IQ or inadequate environment. In previous genome-wide studies, we observed strong evidence for linkage to 13q21 with a reading phenotype in language-impaired families. First, we elucidate the genetic architecture of reading impairment and quantitative language variation in our samples using a bivariate analysis of reading impairment in affected individuals jointly with language quantitative phenotypes in unaffected individuals. This analysis largely recapitulates the baseline analysis using the categorical trait data (posterior probability of linkage (PPL) = 80%), indicating that our reading impairment phenotype captured poor readers who also have low language ability. Second, we performed epistasis analysis using a functional coding variant in the brain-derived neurotrophic factor (BDNF) gene previously associated with reduced performance on working memory tasks. Modeling epistasis doubled the evidence on 13q21 and raised the PPL to 99.9%, indicating that BDNF and 13q21 susceptibility alleles are jointly part of the genetic architecture of SLI. These analyses provide possible mechanistic insights for further cognitive neuroscience studies based on the models developed herein.



 goto top of outline Author Contacts

Assistant Prof. Christopher W. Bartlett, PhD, Battelle Center for
Mathematical Medicine, Research Institute at Nationwide Children’s Hospital and Ohio State University, JW3926, 700 Children’s Drive, Columbus, OH 43205 (USA)
Tel. +1 614 722 2688, Fax +1 614 355 2728
E-Mail christopher.bartlett@nationwidechildrens.org


 goto top of outline Article Information

Received: May 14, 2010
Accepted after revision: August 13, 2010
Published online: October 14, 2010
Number of Print Pages : 13
Number of Figures : 3, Number of Tables : 2, Number of References : 102
Additional supplementary material is available online - Number of Parts : 1


 goto top of outline Publication Details

Human Heredity (International Journal of Human and Medical Genetics)

Vol. 70, No. 4, Year 2010 (Cover Date: February 2011)

Journal Editor: Devoto M. (Philadelphia, Pa.)
ISSN: 0001-5652 (Print), eISSN: 1423-0062 (Online)

For additional information: http://www.karger.com/HHE


Open Access License / Drug Dosage

Open Access License: This is an Open Access article licensed under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported license (CC BY-NC) (www.karger.com/OA-license), applicable to the online version of the article only. Distribution permitted for non-commercial purposes only.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in goverment regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

References

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  2. Tomblin JB, Records NL, Buckwalter P, Zhang X, Smith E, O’Brien M: Prevalence of specific language impairment in kindergarten children. J Speech Lang Hear Res 1997;40:1245–1260.
  3. Dale PS, Price TS, Bishop DV, Plomin R: Outcomes of early language delay: I. Predicting persistent and transient language difficulties at 3 and 4 years. J Speech Lang Hear Res 2003;46:544–560.
  4. Snowling M, Bishop DV, Stothard SE: Is preschool language impairment a risk factor for dyslexia in adolescence? J Child Psychol Psychiatry 2000;41:587–600.
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