Testing for an Unusual Distribution of Rare Variants

English version České info

Technological advances make it possible to use high-throughput sequencing as a primary discovery tool of medical genetics, specifically for assaying rare variation. Still this approach faces the analytic challenge that the influence of very rare variants can only be evaluated effectively as a group. A further complication is that any given rare variant could have no effect, could increase risk, or could be protective. We propose here the C-alpha test statistic as a novel approach for testing for the presence of this mixture of effects across a set of rare variants. Unlike existing burden tests, C-alpha, by testing the variance rather than the mean, maintains consistent power when the target set contains both risk and protective variants. Through simulations and analysis of case/control data, we demonstrate good power relative to existing methods that assess the burden of rare variants in individuals.

Vyšlo v časopise: Testing for an Unusual Distribution of Rare Variants. PLoS Genet 7(3): e32767. doi:10.1371/journal.pgen.1001322
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1001322

Souhrn

Zdroje

1. CohenJ

PertsemlidisA

KotowskiIK

GrahamR

GarciaCK

2005 Low ldl cholesterol in individuals of african descent resulting from frequent nonsense mutations in pcsk9. Nat Genet 37 2 161 165

2. CohenJC

BoerwinkleE

MosleyTH

HobbsHH

2006 Sequence variations in PCSK9, low ldl, and protection against coronary heart disease. N Engl J Med 354 12 1264 1272

3. KathiresanS

MelanderO

AnevskiD

GuiducciC

BurttNP

2008 Polymorphisms associated with cholesterol and risk of cardiovascular events. N Engl J Med 358 12 1240 9, PMID 18354102

4. CohenJC

KissRS

PertsemlidisA

MarcelYL

McPhersonR

2005 Multiple rare alleles contribute to low plasma levels of hdl cholesterol. Science 305 5685 869 872

5. MorgenthalerS

ThillyWG

2007 A strategy to discover genes that carry multi-allelic or mono-allelic risk for common diseases: a cohort allelic sums test (cast). Mutat Res 615 1-2 28 56

6. LiB

LealSM

2008 Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. Am J Hum Genet 83 3 311 321

7. MadsenBE

BrowningSR

2009 A groupwise association test for rare mutations using a weighted sum statistic. PLoS Genet 5 e1000384 doi:10.1371/journal.pgen.1000384

8. AbifadelM

RabesJP

DevillersM

MunnichA

ErlichD

2009 Mutations and polymorphisms in the proprotein convertase subtilisin kexin 9 (PCSK9) gene in cholesterol metabolism and disease. Hum Mutat 30 4 520 529

9. BennM

2009 Apolipoprotein b levels, apob alleles, and risk of ischemic cardiovascular disease in the general population, a review. Atherosclerosis 206 1 17 30

10. Newton-ChehC

ShahR

2007 Genetic determinants of qt interval variation and sudden cardiac death. Curr Opin Genet Dev 17 3 213 221

11. NeymanJ

ScottE

1966 On the use of c(α) optimal tests of composite hypotheses. Bulletin of the International Statistical Institute 41 477 497

12. ZeltermanD

ChenC

1988 Homogeneity tests against central-mixture alternatives. Journal of the American Statistical Association 83 401 179 182

13. KotowskiIK

PertsemlidisA

LukeA

CooperRS

VegaGL

2006 A spectrum of PCSK9 alleles contributes to plasma levels of low-density lipoprotein cholesterol. Am J Hum Genet 78 3 410 422

14. PriceAL

KryukovGV

deBakkerPIW

PurcellSM

StaplesJ

2010 Pooled Association Tests for Rare Variants in Exon-Resequencing Studies. Am J Hum Genet 86 6 832 838

15. KryukovGV

ShpuntA

StamatoyannopoulosJA

SunyaevSR

2009 Power of deep, all-exon resequencing for discovery of human trait genes. Proc Natl Acad Sci U S A 106 10 3871 3876

16. FisherRA

1918 The correlation between relatives on the supposition of Mendelian inheritance. Trans R Soc Edinburgh 52 399 433

17. CheverudJM

2001 A simple correction for multiple comparisons in interval mapping genome scans. Heredity 87 52 58

18. NgSB

BuckinghamKJ

LeeC

BinghamAW

TaborHK

2010 Exome sequencing identifies the cause of a mendelian disorder Nature Genetics 42 30 35

19. PriceAL

PattersonNJ

PlengeR

WeinblattM

ShadickN

2006 Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38 8 904 909

20. LucaD

RingquistS

KleiL

LeeAB

GiegerC

2008 On the use of general control samples for genome-wide association studies: genetic matching highlights causal variants. Am J Hum Genet 82 2 453 63

21. DevlinB

RoederK

1999 Genomic control for association studies. Biometrics 55 4 997 1004

22. LeeAB

LucaD

KleiL

DevlinB

RoederK

2010 Discovering genetic ancestry using spectral graph theory. Genet Epidemiol 34 1 51 59

23. LindsayBG

RoederK

1992 Residual diagnostics for mixture models. Journal of the American Statistical Association 87 419 785 794, 1992

24. MortM

EvaniUS

KrishnanVG

KamatiKK

BaenzigerPH

2010 In Silico Functional Profiling of Human Disease-Associated and Polymorphic Amino Acid Substitutions. Human Mutation 31 3 335 46

25. SunyaevS

RamenskyV

KochI

LatheW

KondrashovAS

2001 Prediction of deleterious human alleles. Hum Mol Genet 10 6 591 597

26. NgPC

HenikoffS

2001 Predicting deleterious amino acid substitutions. Genome Res 11 5 863 874

27. YueP

MelamudE

MoultJ

2006 Snps3d: candidate gene and snp selection for association studies. BMC Bioinformatics 7 166

28. Ferrer-CostaC

GelpiJL

ZamakolaL

ParragaI

de la CruzX

2005 Pmut: a web-based tool for the annotation of pathological mutations on proteins. Bioinformatics 21 14 3176 3178

29. MignoneF

GrilloG

LicciulliF

IaconoM

LiuniS

2005 Utrdb and utrsite: a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mrnas. Nucleic Acids Res 33 Database issue D141 6