Home LiteratureArticle Details
PMID: 23684009 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Sequence kernel association tests for the combined effect of rare and common variants.

American journal of human genetics ·Vol. 92 ·No. 6 ·2013-06-06 ·Pages 841-53

Ionita-Laza I, Lee S, Makarov V, Buxbaum JD, Lin X

Abstract

Recent developments in sequencing technologies have made it possible to uncover both rare and common genetic variants. Genome-wide association studies (GWASs) can test for the effect of common variants, whereas sequence-based association studies can evaluate the cumulative effect of both rare and common variants on disease risk. Many groupwise association tests, including burden tests and variance-component tests, have been proposed for this purpose. Although such tests do not exclude common variants from their evaluation, they focus mostly on testing the effect of rare variants by upweighting rare-variant effects and downweighting common-variant effects and can therefore lose substantial power when both rare and common genetic variants in a region influence trait susceptibility. There is increasing evidence that the allelic spectrum of risk variants at a given locus might include novel, rare, low-frequency, and common genetic variants. Here, we introduce several sequence kernel association tests to evaluate the cumulative effect of rare and common variants. The proposed tests are computationally efficient and are applicable to both binary and continuous traits. Furthermore, they can readily combine GWAS and whole-exome-sequencing data on the same individuals, when available, and are also applicable to deep-resequencing data of GWAS loci. We evaluate these tests on data simulated under comprehensive scenarios and show that compared with the most commonly used tests, including the burden and variance-component tests, they can achieve substantial increases in power. We next show applications to sequencing studies for Crohn disease and autism spectrum disorders. The proposed tests have been incorporated into the software package SKAT.

MeSH Terms
Algorithms Child Development Disorders, Pervasive/genetics Computer Simulation Crohn Disease/genetics Data Interpretation, Statistical Gene Frequency Genetic Association Studies/methods Genetic Predisposition to Disease Genetic Testing Humans Logistic Models Low Density Lipoprotein Receptor-Related Protein-2/genetics Models, Genetic Nod2 Signaling Adaptor Protein/genetics Risk Software
Chemicals
Low Density Lipoprotein Receptor-Related Protein-2 NOD2 protein, human Nod2 Signaling Adaptor Protein
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Ionita-Laza Iuliana
Department of Biostatistics, Columbia University, New York, NY 10032, USA. Electronic address: [email protected].
Lee Seunggeun
Makarov Vlad
Buxbaum Joseph D
Lin Xihong
References (41)
41 references, click to expand
  1. Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data.
    Am J Hum Genet. 2008 Sep;83(3):311-21 PMID: 18691683
  2. Pooled association tests for rare variants in exon-resequencing studies.
    Am J Hum Genet. 2010 Jun 11;86(6):832-8 PMID: 20471002
  3. Fast and accurate long-read alignment with Burrows-Wheeler transform.
    Bioinformatics. 2010 Mar 1;26(5):589-95 PMID: 20080505
  4. Joint association testing of common and rare genetic variants using hierarchical modeling.
    Genet Epidemiol. 2012 Sep;36(6):642-51 PMID: 22807252
  5. A new testing strategy to identify rare variants with either risk or protective effect on disease.
    PLoS Genet. 2011 Feb 03;7(2):e1001289 PMID: 21304886
  6. Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.
    Am J Hum Genet. 2012 Nov 2;91(5):823-38 PMID: 23063622
  7. Exome sequencing and the genetic basis of complex traits.
    Nat Genet. 2012 May 29;44(6):623-30 PMID: 22641211
  8. A general framework for detecting disease associations with rare variants in sequencing studies.
    Am J Hum Genet. 2011 Sep 9;89(3):354-67 PMID: 21885029
  9. De novo gene disruptions in children on the autistic spectrum.
    Neuron. 2012 Apr 26;74(2):285-99 PMID: 22542183
  10. Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies.
    Am J Hum Genet. 2012 Aug 10;91(2):224-37 PMID: 22863193
  11. Hypothesis testing in semiparametric additive mixed models.
    Biostatistics. 2003 Jan;4(1):57-74 PMID: 12925330
  12. Annotating non-coding regions of the genome.
    Nat Rev Genet. 2010 Aug;11(8):559-71 PMID: 20628352
  13. Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations.
    Nature. 2012 Apr 04;485(7397):246-50 PMID: 22495309
  14. Five years of GWAS discovery.
    Am J Hum Genet. 2012 Jan 13;90(1):7-24 PMID: 22243964
  15. Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease.
    Nat Genet. 2011 Oct 09;43(11):1066-73 PMID: 21983784
  16. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.
    Genome Res. 2010 Sep;20(9):1297-303 PMID: 20644199
  17. A multiple testing correction method for genetic association studies using correlated single nucleotide polymorphisms.
    Genet Epidemiol. 2008 May;32(4):361-9 PMID: 18271029
  18. Family-based association tests for sequence data, and comparisons with population-based association tests.
    Eur J Hum Genet. 2013 Oct;21(10):1158-62 PMID: 23386037
  19. A groupwise association test for rare mutations using a weighted sum statistic.
    PLoS Genet. 2009 Feb;5(2):e1000384 PMID: 19214210
  20. An exponential combination procedure for set-based association tests in sequencing studies.
    Am J Hum Genet. 2012 Dec 7;91(6):977-86 PMID: 23159251
  21. Comparison of maximum statistics for hypothesis testing when a nuisance parameter is present only under the alternative.
    Biometrics. 2005 Mar;61(1):254-8 PMID: 15737101
  22. Optimal tests for rare variant effects in sequencing association studies.
    Biostatistics. 2012 Sep;13(4):762-75 PMID: 22699862
  23. Rare, low-frequency, and common variants in the protein-coding sequence of biological candidate genes from GWASs contribute to risk of rheumatoid arthritis.
    Am J Hum Genet. 2013 Jan 10;92(1):15-27 PMID: 23261300
  24. A framework for variation discovery and genotyping using next-generation DNA sequencing data.
    Nat Genet. 2011 May;43(5):491-8 PMID: 21478889
  25. Testing for an unusual distribution of rare variants.
    PLoS Genet. 2011 Mar;7(3):e1001322 PMID: 21408211
  26. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3.
    Fly (Austin). 2012 Apr-Jun;6(2):80-92 PMID: 22728672
  27. Scan-statistic approach identifies clusters of rare disease variants in LRP2, a gene linked and associated with autism spectrum disorders, in three datasets.
    Am J Hum Genet. 2012 Jun 8;90(6):1002-13 PMID: 22578327
  28. Calibrating a coalescent simulation of human genome sequence variation.
    Genome Res. 2005 Nov;15(11):1576-83 PMID: 16251467
  29. Diagnostic exome sequencing in persons with severe intellectual disability.
    N Engl J Med. 2012 Nov 15;367(20):1921-9 PMID: 23033978
  30. Common genetic variants, acting additively, are a major source of risk for autism.
    Mol Autism. 2012 Oct 15;3(1):9 PMID: 23067556
  31. CARD15/NOD2 mutational analysis and genotype-phenotype correlation in 612 patients with inflammatory bowel disease.
    Am J Hum Genet. 2002 Apr;70(4):845-57 PMID: 11875755
  32. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder.
    Nature. 2009 Aug 6;460(7256):748-52 PMID: 19571811
  33. A novel adaptive method for the analysis of next-generation sequencing data to detect complex trait associations with rare variants due to gene main effects and interactions.
    PLoS Genet. 2010 Oct 14;6(10):e1001156 PMID: 20976247
  34. PLINK: a tool set for whole-genome association and population-based linkage analyses.
    Am J Hum Genet. 2007 Sep;81(3):559-75 PMID: 17701901
  35. Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs.
    Nat Genet. 2012 Feb 19;44(3):247-50 PMID: 22344220
  36. A data-adaptive sum test for disease association with multiple common or rare variants.
    Hum Hered. 2010;70(1):42-54 PMID: 20413981
  37. Rare-variant association testing for sequencing data with the sequence kernel association test.
    Am J Hum Genet. 2011 Jul 15;89(1):82-93 PMID: 21737059
  38. Comparison of statistical tests for disease association with rare variants.
    Genet Epidemiol. 2011 Nov;35(7):606-19 PMID: 21769936
  39. The Sequence Alignment/Map format and SAMtools.
    Bioinformatics. 2009 Aug 15;25(16):2078-9 PMID: 19505943
  40. Common SNPs explain a large proportion of the heritability for human height.
    Nat Genet. 2010 Jul;42(7):565-9 PMID: 20562875
  41. Studying gene and gene-environment effects of uncommon and common variants on continuous traits: a marker-set approach using gene-trait similarity regression.
    Am J Hum Genet. 2011 Aug 12;89(2):277-88 PMID: 21835306
Article Info
Journal
American journal of human genetics
Abbr.
Am J Hum Genet
ISSN
1537-6605
Published
2013-06-06
Epub
2013-00-16
Pages
841-53
Language
English
Region
United States
NLM ID
0370475
PMCID
PMC3675243
Subset
IM
Grants
NHGRI NIH HHS · R03 HG005908 · United States
NCI NIH HHS · R37 CA076404 · United States
NHLBI NIH HHS · K99-HL113164 · United States
NIMH NIH HHS · MH089025 · United States
NIMH NIH HHS · R01MH095797 · United States
NHGRI NIH HHS · 1R03HG005908 · United States
NIMH NIH HHS · R01 MH089025 · United States
NCI NIH HHS · P01CA134294 · United States
NIMH NIH HHS · R01 MH095797 · United States
NIMH NIH HHS · U01 MH100233 · United States
NCI NIH HHS · R35 CA197449 · United States
NIMH NIH HHS · MH100233 · United States
NHLBI NIH HHS · K99 HL113164 · United States
NCI NIH HHS · P01 CA134294 · United States
Analysis Services
Analysis Services

Contact

No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong

Qilu Normal University · Genelibs Bioinformatics Lab

750 Shunhua Rd, Jinan

2F, Bldg F, University Science Park

Tel: 0531-88819269

WeChat Official Account

Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.


Business Email

E-mail: [email protected]