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Biomedical subjects

Stacy J Caillier

Publications and source records attributed to Stacy J Caillier.

4 recordsLinked to original sources
PubMed2006

Complex gene-gene interactions in multiple sclerosis: a multifactorial approach reveals associations with inflammatory genes.

The complex inheritance involved in multiple sclerosis (MS) risk has been extensively investigated, but our understanding of MS genetics remains rudimentary. In this study, we explore 51 single nucleotide polymorphisms (SNPs) in 36 candidate genes from the inflammatory pathway and test for gene-gene interactions using complementary case-control, discordant sibling pair, and trio family study designs. We used a sample of 421 carefully diagnosed MS cases and 96 unrelated, healthy controls; discordant sibling pairs from 146 multiplex families; and 275 trio families. We used multifactor dimensionality reduction to explore gene-gene interactions. Based on our analyses, we have identified several statistically significant models including both main effect models and two-locus, three-locus, and four-locus epistasis models that predict MS disease risk with between approximately 61% and 85% accuracy. These results suggest that significant epistasis, or gene-gene interactions, may exist even in the absence of statistically significant individual main effects.

Case-Control Studies↗
PubMed2004

Transcription-based prediction of response to IFNbeta using supervised computational methods.

Changes in cellular functions in response to drug therapy are mediated by specific transcriptional profiles resulting from the induction or repression in the activity of a number of genes, thereby modifying the preexisting gene activity pattern of the drug-targeted cell(s). Recombinant human interferon beta (rIFNbeta) is routinely used to control exacerbations in multiple sclerosis patients with only partial success, mainly because of adverse effects and a relatively large proportion of nonresponders. We applied advanced data-mining and predictive modeling tools to a longitudinal 70-gene expression dataset generated by kinetic reverse-transcription PCR from 52 multiple sclerosis patients treated with rIFNbeta to discover higher-order predictive patterns associated with treatment outcome and to define the molecular footprint that rIFNbeta engraves on peripheral blood mononuclear cells. We identified nine sets of gene triplets whose expression, when tested before the initiation of therapy, can predict the response to interferon beta with up to 86% accuracy. In addition, time-series analysis revealed potential key players involved in a good or poor response to interferon beta. Statistical testing of a random outcome class and tolerance to noise was carried out to establish the robustness of the predictive models. Large-scale kinetic reverse-transcription PCR, coupled with advanced data-mining efforts, can effectively reveal preexisting and drug-induced gene expression signatures associated with therapeutic effects.

Adolescent↗
PubMed2004

Linkage and association with the NOS2A locus on chromosome 17q11 in multiple sclerosis.

A large body of research supports a multifactorial cause in multiple sclerosis (MS), with an underlying genetic susceptibility likely acting in concert with undefined environmental exposures. Here, we used a highly efficient multilocus genotyping assay to study single nucleotide polymorphisms representing variation in 34 genes from inflammatory pathways in a well-characterized MS familial data set. Evidence of transmission distortion was present for several polymorphisms. Results for the NOS2A locus (exon 10 C/T, D346D) on chromosome 17q11 remained significant after correction for multiple testing and were reproduced in a second independent African American MS data set. In addition, linkage to a NOS2A promoter region polymorphism, (CCTTT)(n), was present in a third data set of multicase MS families. Our results provide strong evidence for linkage and association to a new candidate disease gene on chromosome 17q11 in MS and suggest that variation within NOS2A or a nearby locus contributes to disease susceptibility.

Adult↗