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A genetic association study detects haplotypes associated with obstructive heart defects.

ABSTRACT: The development of congenital heart defects (CHDs) involves a complex interplay between genetic variants, epigenetic variants, and environmental exposures. Previous studies have suggested that susceptibility to CHDs is associated with maternal genotypes, fetal genotypes, and maternal-fetal genotype (MFG) interactions. We conducted a haplotype-based genetic association study of obstructive heart defects (OHDs), aiming to detect the genetic effects of 877 SNPs involved in the homocysteine, folate, and transsulfuration pathways. Genotypes were available for 285 mother-offspring pairs with OHD-affected pregnancies and 868 mother-offspring pairs with unaffected pregnancies. A penalized logistic regression model was applied with an adaptive least absolute shrinkage and selection operator (lasso), which dissects the maternal effect, fetal effect, and MFG interaction effects associated with OHDs. By examining the association between 140 haplotype blocks, we identified 9 blocks that are potentially associated with OHD occurrence. Four haplotype blocks, located in genes MGMT, MTHFS, CBS, and DNMT3L, were statistically significant using a Bayesian false-discovery probability threshold of 0.8. Two blocks in MGMT and MTHFS appear to have significant fetal effects, while the CBS and DNMT3L genes may have significant MFG interaction effects.

SUBMITTER: Li M

PROVIDER: S-EPMC4313870 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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A genetic association study detects haplotypes associated with obstructive heart defects.

Li Ming M Cleves Mario A MA Mallick Himel H Erickson Stephen W SW Tang Xinyu X Nick Todd G TG Macleod Stewart L SL Hobbs Charlotte A CA

Human genetics 20140604 9

The development of congenital heart defects (CHDs) involves a complex interplay between genetic variants, epigenetic variants, and environmental exposures. Previous studies have suggested that susceptibility to CHDs is associated with maternal genotypes, fetal genotypes, and maternal-fetal genotype (MFG) interactions. We conducted a haplotype-based genetic association study of obstructive heart defects (OHDs), aiming to detect the genetic effects of 877 SNPs involved in the homocysteine, folate, ...[more]

PMID: 24894164

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Project description:Multilocus analysis of single nucleotide polymorphism haplotypes is a promising approach to dissecting the genetic basis of complex diseases. We propose a coalescent-based model for association mapping that potentially increases the power to detect disease-susceptibility variants in genetic association studies. The approach uses Bayesian partition modelling to cluster haplotypes with similar disease risks by exploiting evolutionary information. We focus on candidate gene regions with densely spaced markers and model chromosomal segments in high linkage disequilibrium therein assuming a perfect phylogeny. To make this assumption more realistic, we split the chromosomal region of interest into sub-regions or windows of high linkage disequilibrium. The haplotype space is then partitioned into disjoint clusters, within which the phenotype-haplotype association is assumed to be the same. For example, in case-control studies, we expect chromosomal segments bearing the causal variant on a common ancestral background to be more frequent among cases than controls, giving rise to two separate haplotype clusters. The novelty of our approach arises from the fact that the distance used for clustering haplotypes has an evolutionary interpretation, as haplotypes are clustered according to the time to their most recent common ancestor. Our approach is fully Bayesian and we develop a Markov Chain Monte Carlo algorithm to sample efficiently over the space of possible partitions. We compare the proposed approach to both single-marker analyses and recently proposed multi-marker methods and show that the Bayesian partition modelling performs similarly in localizing the causal allele while yielding lower false-positive rates. Also, the method is computationally quicker than other multi-marker approaches. We present an application to real genotype data from the CYP2D6 gene region, which has a confirmed role in drug metabolism, where we succeed in mapping the location of the susceptibility variant within a small error.

Dataset Information

A genetic association study detects haplotypes associated with obstructive heart defects.

Publications

A genetic association study detects haplotypes associated with obstructive heart defects.

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