PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-3 (3)
 

Clipboard (0)
None
Journals
Authors
more »
Year of Publication
Document Types
1.  Anorectal atresia and variants at predicted regulatory sites in candidate genes 
Annals of human genetics  2012;77(1):31-46.
SUMMARY
Anorectal atresia is a serious birth defect of largely unknown etiology but candidate genes have been identified in animal studies and human syndromes. Because alterations in the activity of these genes might lead to anorectal atresia, we selected 71 common variants predicted to be in transcription factor binding sites, CpG windows, splice sites, and miRNA target sites of 25 candidate genes, and tested for their association with anorectal atresia. The study population comprised 150 anorectal atresia cases and 623 control infants without major malformations. Variants predicted to affect transcription factor binding, splicing, and DNA methylation in WNT3A, PCSK5, TCF4, MKKS, GLI2, HOXD12, and BMP4 were associated with anorectal atresia based on a nominal P value <0.05. The GLI2 and BMP4 variants are reported to be moderately associated with gene expression changes (Spearman’s rank correlation coefficients between −0.260 and 0.226). We did not find evidence for interaction between maternal pre-pregnancy obesity and variants in MKKS, a gene previously associated with obesity, on the risk of anorectal atresia. Our results for MKKS support previously suggested associations with anorectal malformations. Our findings suggest that more research is needed to determine whether altered GLI2 and BMP4 expression is important in anorectal atresia in humans.
doi:10.1111/j.1469-1809.2012.00734.x
PMCID: PMC3535506  PMID: 23127126
anorectal malformations; imperforate anus; hindgut; congenital abnormalities
2.  Correction for Multiplicity in Genetic Association Studies of Triads: The Permutational TDT 
Annals of human genetics  2010;75(2):284-291.
Summary
New technology for large-scale genotyping has created new challenges for statistical analysis. Correcting for multiple comparison without discarding true positive results and extending methods to triad studies are among the important problems facing statisticians. We present a one-sample permutation test for testing transmission disequilibrium hypotheses in triad studies, and show how this test can be used for multiple single nucleotide polymorphism (SNP) testing. The resulting multiple comparison procedure is shown in the case of the transmission disequilibrium test to control the familywise error. Furthermore, this procedure can handle multiple possible modes of risk inheritance per SNP. The resulting permutational procedure is shown through simulation of SNP data to be more powerful than the Bonferroni procedure when the SNPs are in linkage disequilibrium. Moreover, permutations implicitly avoid any multiple comparison correction penalties when the SNP has a rare allele. The method is illustrated by analyzing a large candidate gene study of neural tube defects and an independent study of oral clefts, where the smallest adjusted p-values using the permutation procedure are approximately half those of the Bonferroni procedure. We conclude that permutation tests are more powerful for identifying disease-associated SNPs in candidate gene studies and are useful for analysis of triad studies.
doi:10.1111/j.1469-1809.2010.00626.x
PMCID: PMC3117224  PMID: 21108625
Exchangeable; familywise error rate; linkage disequilibrium; power
3.  Testing for Genetic Association With Constrained Models Using Triads 
Annals of human genetics  2009;73(2):225-230.
Wang and Sheffield (2005) showed that it is preferable to use a robust model that incorporated constraints on the genotype relative risk rather than rely on a model that assumes the disease operates in a recessive or dominant fashion. Wang and Sheffield’s method is applicable to case-control studies, but not to family based studies of case children along with their parents (triads). We show here how to implement analogous constraints while analyzing triad data. The likelihood, conditional on the parents genotype, is maximized over the appropriately constrained parameter space. The asymptotic distribution for the maximized likelihood ratio statistic is found and used to estimate the null distribution of the test statistics. The properties of several methods of testing for association are compared by simulation. The constrained method provides higher power across a wide range of genetic models with little cost when compared to methods that restrict to a dominant, recessive, or multiplicative model, or make no modeling restriction. The methods are applied to two SNPs on the methylenetetrahy-drofolate reductase (MTHFR) gene with neural tube defect (NTD) triads.
doi:10.1111/j.1469-1809.2008.00494.x
PMCID: PMC2657230  PMID: 19178434
conditional distribution; genetic risk model; likelihood ratio test; power

Results 1-3 (3)