SNP Association Studies with Case-Parent Trios

Transcription

1 SNP Association Studies with Case-Parent Trios Department of Biostatistics Johns Hopkins Bloomberg School of Public Health July, 00 Acknowledgments Collaborators: Qing Li, Rob Scharpf, Holger Schwender, Margaret Taub Dani Fallin, Katja Ickstadt, Rafael Irizarry, Giovanni Parmigiani, Jon Pevsner. Terri Beaty, Ann Pulver. Computing support: Marvin Newhouse, Jiong Yang. Funding: NIH R0 DK0666, GM08084, HL090577, and a CTSA grant to the Johns Hopkins Medical Institutions.

2 iruczins/ Der Ring des Nibelungen Unknown Father Erda Unknown Mother Wotan Fricka Norns Gerhilde Ortlinde Waltraute Siegmund Sieglinde Hunding Schwertleite Helmwige Siegrune Grimgerde Rossweisse Siegfried Gutrune Bruennhilde Funded by a grant from the State of Bavaria (PO: King Ludwig II)

3 Case-parent trios Recruitment Site CL CLP CP Total Utah Norway Korea Maryland Pittsburgh Singapore Taiwan Iowa Denmark Philippines WuHan Shandong Province Western China Total Family-based designs: disadvantages Typically less power per SNP typed than case-control studies. Pedigrees maybe hard to get except for childhood diseases, and may not be feasible for late-onset diseases. Can be a lot more expensive. Highly sensitive to genotyping errors. Might be computationally more demanding, especially for studies with large pedigrees. Software may be an issue.

4 Family-based designs: advantages Robust to possible effects of population stratification and genetic heterogeneity. Parent-of-origin effects (imprinting) can be assessed. Data quality control is usually more thorough (e. g. genotyping errors and sample swaps are easier to catch). Distinction between de-novo and inherited events (copy number changes) is possible. Logistically easier for childhood diseases. In case-parent data, low minor allele frequencies are of less worry (genotyping errors are still possible). Case-parent designs do not require phenotyping parents. Linkage information from previous family studies can be employed in association studies. Case-parent trios F : M : C : F : M : C : F : M : C : F : M : C : F : M : C : F : M : C : F : M : C :

5 Allelic TDT The transmission disequilibrium test measures the over-transmission of an allele from parents to affected offsprings. For a set of nparents with alleles and at a genetic locus, each parent can be summarized by the transmitted and the non-transmitted allele: Non-TA a b a+b TA c d c+d a+c b+d n Only the heterozygous parents contribute information! Under the null of no association, (b c) b+c χ Even better, use binom.test() in R. GWAs results [BEA RUC SCO NAT GEN 00 ]

6 Parent-of-origin effects [ S UL RUC B EA G EN E PI 008 ] P-value distribution pmajor!allele!transmission observed! log0 (p value) expected! log0 (p value) p value

7 Transmission distortion Santos et al (009). Eur J Hum Gen. 7: 8-9. Deletion General Cytogenetics Information

8 De novo deletion Prediction regions for copy number SNP_A A B [SCH RUC IRI BIOSTAT 00 ]

9 Vanilla and ICE HMMs for genotype and copy number 5 4 Deletion Normal LOH Amplification A D B C E Van ICE A D B E Van ICE Mb [SCH PAR PEV RUC AOAS 008 ] Open source software [SCH TIN PEV RUC BIOINF 007 ] [SCH RUC M MOL BIO 00 ]

10 Mendelian error HMMs chromosome 0 BPI UPI F UPI M MI D MI S non BPI BPI position (Mb) DNA sources

11 Candidate genes Biological and statistical interactions BB Bb bb AA Aa aa (SNP A D SNP B R ) (SNP B D SNP A R ) Statistical interaction: Deviation from additivity in a linear statistical model. Epistasis: Masking of phenotype expressed by one gene by the effects of another gene. [RUC KOO LEB JCGS 00 ] [KOO RUC GEN EPI 005 ]

12 Results SZ study Logic model exp( ˆβ) 0.67 I { } 0 D I { } 0 D 66 D.4.5 I { } 0 D 66 D 48 D I { } 0 D 66 D 48 D 68 R.65 SNP 0 Chromosome NOS 789 SNP 66 Chromosome 8 CHRNB SNP 48 Chromosome 8 PNOC 7576 SNP 68 Chromosome COMT [LI FAL LOU RUC GEN EPI 00 ] Results SZ study exp( ˆβ) ˆβ(se) z p Marginal 0 D (0.6) 4. 4e D (0.) Logic 0 D 66 D (0.8) 4.89 e-06 Additive 0 D (0.6) 4.5 e D. 0.9 (0.) D (0.9) 4.86 e-06 Additive 66 D (0.) D : 66 D (0.4) [LI FAL LOU RUC GEN EPI 00 ]

13 Results SZ study 0.67 I { 0 D} I {66D } 0 D 0 D D main effects only Results SZ study 0.90 I { 0 D} I {66D }.09 I{ 0 D :66 D} 0 D 0 D D main effects + interaction

14 Results SZ study 0.89 I { 0 D 66 D} 0 D 0 D D logic regression Results SZ study 0.90 I { 0 D } I { 66 D }.09 I { 0 D :66 D } 0 D 0 D 0 D 0 D 0 D 0 D D 66 D 66 D main effects only main effects + interaction logic regression 0.67 I { 0 D } I { 66 D } 0.89 I { 0 D 66 D } [LI FAL LOU RUC GEN EPI 00 ]

15 Simulation G SNP R SNP R 4 SNPR 5 (SNP R SNPD 6 ) SNPR 4 (SNP R SNPD 5 ) SNPR 7 5 (SNP D 4 SNPR 8 ) (SNPR 5 SNPD 6 ) 6 ((SNP R 4 SNPR 7 ) SNPR 8 ) (SNPR 9 SNPR 6 ) 7 (SNP R SNPR ) (SNPR 5 4 SNPR 5 ) (SNPR 9 SNPR 8 ) P(G) Haplotypes / block #ofhaplotypes #matingtablerows , ,, , 5, , 5, 5, , 8, 5,,, , 4, 5, 5,, 5 4,500 0 [LI LOU FAL RUC TEC REP 009 ] Simulation When using conditional logistic regression to compare cases and pseudo-controls, the expected value of the parameter estimates is not the logs odds ratio β, butthelogrelativerisk (Schaid 996). RR = P(D I G = ) P(D I G = 0) = exp(α + β)/( + exp(α + β)) exp(α)/( + exp(α)) = exp(β) ( ) + exp(α + β) + exp(α) Therefore log(rr) = β log ( ) + exp(α + β) + exp(α)

16 Simulation log(rr) =β log ( ) + exp(α + β) + exp(α) 4 "^ 0 # " Simulations based on an interaction between SNPs. [ LI LOU FAL RUC TEC REP 009 ] Genotypic TDT Assume that at a certain locus the father has alleles and the mother has alleles. The four Mendelian children thus have alleles,,, and. Assume the affected proband has genotype. The three Pseudo controls then have the genotypes,, and. Y X Affected proband Pseudo control # 0 Pseudo control # 0 Pseudo control # 0 We can use conditional logistic regression to analyze the data.

17 Trio logic regression [LI LOU FAL RUC TEC REP 009 ] Software The trio logic regression method are implemented, and will be avaiable soon as an augmentation to the logic regression R package LogicReg. The R package trio contains functions to generate logic regression input from pedigree or genotype files, to check for Mendelian errors, to impute missing data, and to simulate case-parent trios. The trio package also contains some other useful functions, for example Cordell s 4df test for SNP-SNP interactions in case-parent trios, and methods to infer LD blocks from the parent data on CRAN. Asoftwarevignetteisalreadyavailable. The R package logicfs to find variable and interaction importances will be augmented to handle case-parent trios. [SCH RUC ICK BIOSTAT 00 ] [SCH BOW FAL RUC TEC REP 00 ]

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