SNPs in the neural cell adhesion molecule 1 gene (NCAM1) may be associated with human neural tube defects
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Neural tube defects (NTDs) are common birth defects, occurring in approximately 1/1,000 births; both genetic and environmental factors are implicated. To date, no major genetic risk factors have been identified. Throughout development, cell adhesion molecules are strongly implicated in cell–cell interactions, and may play a role in the formation and closure of the neural tube. To evaluate the role of neural cell adhesion molecule 1 (NCAM1) in risk of human NTDs, we screened for novel single-nucleotide polymorphisms (SNPs) within the gene. Eleven SNPs across NCAM1 were genotyped using TaqMan. We utilized a family-based approach to evaluate evidence for association and/or linkage disequilibrium. We evaluated American Caucasian simplex lumbosacral myelomeningocele families (n=132 families) using the family based association test (FBAT) and the pedigree disequilibrium test (PDT). Association analysis revealed a significant association between risk for NTDs and intronic SNP rs2298526 using both the FBAT test (P=0.0018) and the PDT (P=0.0025). Using the HBAT version of the FBAT to look for haplotype association, all pairwise comparisons with SNP rs2298526 were also significant. A replication study set, consisting of 72 additional families showed no significant association; however, the overall trend for overtransmission of the less common allele of SNP rs2298526 remained significant in the combined sample set. In addition, we analyzed the expression pattern of the NCAM1 protein in human embryos, and while NCAM1 is not expressed within the neural tube at the time of closure, it is expressed in the surrounding and later in differentiated neurons of the CNS. These results suggest variations in NCAM1 may influence risk for human NTDs.
KeywordsNeural Tube Neural Tube Defect Neural Tube Closure Denature High Performance Liquid Chromatography Migrate Neural Crest Cell
The authors wish to thank the families who participated in this study; without their interest, this work could not be performed. We also thank Silke Schmidt for helpful comment on this manuscript and Pat Hurban and Paradigm Genetics for bioinformatics support. We gratefully acknowledge support from grants HD39948, ES11375, NS39818, ES011961, and NS26630.
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