Login to MyKarger

New to MyKarger? Click here to sign up.

Login with Facebook

Forgot your password?

Authors, Editors, Reviewers

For Manuscript Submission, Check or Review Login please go to Submission Websites List.

Submission Websites List

Institutional Login
(Shibboleth or Open Athens)

For the academic login, please select your country in the dropdown list. You will be redirected to verify your credentials.

Original Paper

Free Access

A Bayesian Hierarchical Model for Detecting Haplotype-Haplotype and Haplotype-Environment Interactions in Genetic Association Studies

Li J. · Zhang K. · Yi N.

Author affiliations

Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Ala., USA

Corresponding Author

Nengjun Yi

Department of Biostatistics

University of Alabama at Birmingham

Birmingham, AL 35294-0022 (USA)

Tel. +1 205 934 4924, E-Mail nyi@ms.soph.uab.edu

Related Articles for ""

Hum Hered 2011;71:148–160

Do you have an account?

Login Information

Contact Information

I have read the Karger Terms and Conditions and agree.


Objective: Genetic association studies based on haplotypes are powerful in the discovery and characterization of the genetic basis of complex human diseases. However, statistical methods for detecting haplotype-haplotype and haplotype-environment interactions have not yet been fully developed owing to the difficulties encountered: large numbers of potential haplotypes and unknown haplotype pairs. Furthermore, methods for detecting the association between rare haplotypes and disease have not kept pace with their counterpart of common haplotypes. Methods/Results: We herein propose an efficient and robust method to tackle these problems based on a Bayesian hierarchical generalized linear model. Our model simultaneously fits environmental effects, main effects of numerous common and rare haplotypes, and haplotype-haplotype and haplotype-environment interactions. The key to the approach is the use of a continuous prior distribution on coefficients that favors sparseness in the fitted model and facilitates computation. We develop a fast expectation-maximization algorithm to fit models by estimating posterior modes of coefficients. We incorporate our algorithm into the iteratively weighted least squares for classical generalized linear models as implemented in the R package glm. We evaluate the proposed method and compare its performance to existing methods on extensive simulated data. Conclusion: The results show that the proposed method performs well under all situations and is more powerful than existing approaches.

© 2011 S. Karger AG, Basel


  1. Botstein D, Risch N: Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease. Nat Genet 2003;33(suppl):228–237.
  2. Risch N, Merikangas K: The future of genetic studies of complex human diseases. Science 1996;273:1616–1617.
    External Resources
  3. Chapman NH, Wijsman EM: Genome screens using linkage disequilibrium tests: optimal marker characteristics and feasibility. Am J Hum Genet 1998;63:1872–1885.
  4. Clark AG: The role of haplotypes in candidate gene studies. Genet Epidemiol 2004;27:321–333.
  5. Davidson S: Research suggests importance of haplotypes over SNPs. Nat Biotechnol 2000;18:1134–1135.
  6. Schaid DJ: Evaluating associations of haplotypes with traits. Genet Epidemiol 2004;27:348–364.
  7. Schaid DJ, Rowland CM, Tines DE, Jacobson RM, Poland GA: Score tests for association between traits and haplotypes when linkage phase is ambiguous. Am J Hum Genet 2002;70:425–434.
  8. Fitze G, Cramer J, Ziegler A, Schierz M, Schreiber M, Kuhlisch E, Roesner D, Schackert HK: Association between c135G/A genotype and RET proto-oncogene germline mutations and phenotype of Hirschsprung’s disease. Lancet 2002;359:1169–1170.
  9. Morris RW, Kaplan NL: On the advantage of haplotype analysis in the presence of multiple disease susceptibility alleles. Genet Epidemiol 2002;23:221–233.
  10. Kaplan NL, Morris RW: Issues concerning association studies for fine mapping a susceptibility gene for a complex disease. Genet Epidemiol 2001;20:432–457.
  11. Akey J, Jin L, Xiong M: Haplotypes vs. single marker linkage disequilibrium tests: what do we gain? Eur J Hum Genet 2001;9:291–300.
  12. Zaykin DV, Westfall PH, Young SS, Karnoub MA, Wagner MJ, Ehm MG: Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals. Hum Hered 2002;53:79–91.
  13. Zhao LP, Li SS, Khalid N: A method for the assessment of disease associations with single-nucleotide polymorphism haplotypes and environmental variables in case-control studies. Am J Hum Genet 2003;72:1231–1250.
  14. Becker T, Schumacher J, Cichon S, Baur MP, Knapp M: Haplotype interaction analysis of unlinked regions. Genet Epidemiol 2005;29:313–322.
  15. Guo W, Lin S: Generalized linear modeling with regularization for detecting common disease rare haplotype association. Genet Epidemiol 2009;33:308–316.
    External Resources
  16. Cheverund JM, Routman EJ: Epistasis and its contribution to genetic variance components. Genetics 1995;139:1455–1461.
  17. Wolf JB, Brodie ED III, Wade MJ: Epistasis and the Evolutionary Process. New York, Oxford University Press, 2000.
  18. Moore JH: The ubiquitous nature of epistasis in determining susceptibility to common human diseases. Hum Hered 2003;56:73–82.
  19. Carlborg Ö, Haley CS: Epistasis: too often neglected in complex trait studies? Nat Rev Genet 2004;5:618–625.
  20. Moore JH: A global view of epistasis. Nat Genet 2005;37:13–14.
  21. Lake SL, Lyon H, Tantisira K, Silverman EK, Weiss ST, Laird NM, Schaid DJ: Estimation and tests of haplotype-environment interaction when linkage phase is ambiguous. Hum Hered 2003;55:56–65.
  22. Lin DY, Zeng D, Millikan R: Maximum likelihood estimation of haplotype effects and haplotype-environment interactions in association studies. Genet Epidemiol 2005;29:299–312.
  23. Spinka C, Carroll RJ, Chatterjee N: Analysis of case-control studies of genetic and environmental factors with missing genetic information and haplotype-phase ambiguity. Genet Epidemiol 2005;29:108–127.
  24. Kraft P, Cox DG, Paynter RA, Hunter D, De Vivo I: Accounting for haplotype uncertainty in matched association studies: a comparison of simple and flexible techniques. Genet Epidemiol 2005;28:261–272.
  25. Lin DY, Zeng D: Likelihood-based inference on haplotype effects in genetic association studies. J Am Stat Assoc 2006;101:89–118.
  26. Kwee LC, Epstein MP, Manatunga AK, Duncan R, Allen AS, Satten GA: Simple methods for assessing haplotype-environment interactions in case-only and case-control studies. Genet Epidemiol 2007;31:75–90.
  27. Chen YH, Chatterjee N, Carroll RJ: Retrospective analysis of haplotype-based case control studies under a flexible model for gene environment association. Biostatistics 2008;9:81–99.
  28. Excoffier L, Slatkin M: Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population. Mol Biol Evol 1995;12:921–927.
  29. Niu T, Qin Z, Xu X, Liu JS: Bayesian haplotype inference for multiple linked single-nucleotide polymorphisms. Am J Hum Genet 2002;70:157–159.
  30. Stephens M, Smith NJ, Donnelly P: A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 2001;68:978–989.
  31. Seltman H, Roeder K, Devlin B: Transmission/disequilibrium test meets measured haplotype analysis: family-based association analysis guided by evolution of haplotypes. Am J Hum Genet 2001;68:1250–1263.
  32. Sha Q, Dong J, Jiang R, Zhang S: Tests of association between quantitative traits and haplotypes in a reduced-dimensional space. Ann Hum Genet 2005;69:715–732.
  33. Tzeng JY: Evolutionary-based grouping of haplotypes in association analysis. Genet Epidemiol 2005;28:220–231.
    External Resources
  34. Liu J, Papasian C, Deng HW: Incorporating single-locus tests into haplotype cladistic analysis in case-control studies. PLoS Genet 2007;3:e46.
    External Resources
  35. Liu PY, Zhang YY, Lu Y, Long JR, Shen H, Zhao LJ, Xu FH, Xiao P, Xiong DH, Liu YJ, Recker RR, Deng HW: A survey of haplotype variants at several disease candidate genes: the importance of rare variants for complex diseases. J Med Genet 2005;42:221–227.
  36. Zhu X, Fejerman L, Luke A, Adeyemo A, Cooper RS: Haplotypes produced from rare variants in the promoter and coding regions of angiotensinogen contribute to variation in angiotensinogen levels. Hum Mol Genet 2005;14:639–643.
  37. Yende S, Angus DC, Ding J, Newman AB, Kellum JA, Li R, Ferrell RE, Zmuda J, Kritchevsky SB, Harris TB, Garcia M, Yaffe K, Wunderink RG, for the Health ABC Study: 4G/5G plasminogen activator inhibitor-1 polymorphisms and haplotypes are associated with pneumonia. Am J Respir Crit Care Med 2007;176:1129–1137.
  38. Semsei AF, Erdélyi DJ, Ungvári I, Kámory E, Csókay B, Andrikovics H, Tordai A, Cságoly E, Falus A, Kovács GT, Szalai C: Association of some rare haplotypes and genotype combinations in the MDR1 gene with childhood acute lymphoblastic leukaemia. Leuk Res 2008;32:1214–1220.
  39. Kitsios GD, Zintzaras E: An NOS3 haplotype is protective against hypertension in a Caucasian population. Int J Hypertens 2010;2010:865031.
  40. Molitor J, Marjoram P, Thomas D: Application of Bayesian spatial statistical methods to analysis of haplotypes effects and gene mapping. Genet Epidemiol 2003;25:95–105.
  41. McCullagh P, Nelder JA: Generalized Linear Models, ed 2. London, Chapman & Hall, 1989.
  42. Stram DO, Pearce CL, Bretsky P, Freedman M, Hirschhorn JN, Altshuler D, Kolonel LN, Henderson BE, Thomas DC: Modeling and E-M estimation of haplotype-specific relative risks from genotype data for a case-control study of unrelated individuals. Hum Hered 2003;55:179–190.
  43. Gelman A, Jakulin A, Pittau MG, Su YS: A weakly informative default prior distribution for logistic and other regression models. Ann Appl Stat 2008;2:1360–1383.
    External Resources
  44. Yi N, Banerjee S: Hierarchical generalized linear models for multiple quantitative trait locus mapping. Genetics 2009;181:1101–1113.
  45. Yi N, Kaklamani VG, Pasche B: Bayesian analysis of genetic interactions in case-control studies, with application to adiponectin genes and colorectal cancer risk. Ann Hum Genet 2011;75:90–104.
    External Resources
  46. Gelman A, Carlin JB, Stern HS, Rubin DB: Bayesian Data Analysis, ed 2. London, Chapman & Hall, 2003.
  47. Lei Z, Liu RY, Zhao J, Liu Z, Jiang X, You W, Chen X, Liu X, Zhang K, Pasche B, Zhang H: TGFBR1 haplotypes and risk of non-small-cell lung cancer. Cancer Res 2009;69:7046–7052.
  48. Albert A, Anderson JA: On the existence of maximum likelihood estimates in logistic regression models. Biometrika 1984;71:1–10.
    External Resources
  49. Lesaffre E, Albert A: Partial separation in logistic discrimination. J R Stat Soc Ser B 1989;51:109–116.
  50. Luan JA, Wong MY, Day NE, Wareham NJ: Sample size determination for studies of gene-environment interaction. Int J Epidemiol 2001;30:1035–1040.
  51. Boks MP, Schipper M, Schubart CD, Sommer IE, Kahn RS, Ophoff RA: Investigating gene environment interaction in complex diseases: increasing power by selective sampling for environmental exposure. Int J Epidemiol 2007;36:1363–1369.
  52. Mukherjee B, Ahn J, Gruber SB, Rennert G, Moreno V, Chatterjee N: Tests for gene-environment interaction from case-control data: a novel study of type I error, power and designs. Genet Epidemiol 2008;32:615–626.
  53. Cordell HJ: Genome-wide association studies: detecting gene-gene interactions that underlie human diseases. Nat Rev Genet 2009;10:392–404.
  54. Thomas D: Methods for investigating gene-environment interactions in candidate pathway and genome-wide association studies. Annu Rev Public Health 2010;31:21–36.
    External Resources
  55. Hein R, Beckmann L, Chang-Claude J: Comparison of different haplotype-based association methods for gene-environment (G×E) interactions in case-control studies when haplotype-phase is ambiguous. Hum Hered 2009;68:252–267.
  56. Souverein OW, Zwinderman AH, Jukema JW, Tanck MW: Estimating effects of rare haplotypes on failure time using a penalized Cox proportional hazards regression model. BMC Genet 2008;9:9.
    External Resources
  57. Seltman H, Roeder K, Devlin B: Evolutionary-based association analysis using haplotype data. Genet Epidemiol 2003;25:48–58.
  58. Durrant C, Zondervan KT, Cardon LR, Hunt S, Deloukas P, Morris AP: Linkage disequilibrium mapping via cladistic analysis of single-nucleotide polymorphism haplotypes. Am J Hum Genet 2004;75:35–43.

Article / Publication Details

First-Page Preview
Abstract of Original Paper

Received: September 27, 2010
Accepted: February 03, 2011
Published online: July 20, 2011
Issue release date: July 2011

Number of Print Pages: 13
Number of Figures: 3
Number of Tables: 3

ISSN: 0001-5652 (Print)
eISSN: 1423-0062 (Online)

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

Copyright / Drug Dosage / Disclaimer

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher.
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 government 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.