Biomedical subjects

Eric Schadt

Publications and source records attributed to Eric Schadt.

4 recordsLinked to original sources

PubMed2003

A family-based test for correlation between gene expression and trait values.

Advances in microarray technology have made it attractive to combine information on clinical traits, marker genotypes, and comprehensive gene expression from family studies to dissect complex disease genetics. Without accounting for family structure, methods that test for association between a trait and gene-expression levels can be misleading. We demonstrate that the standard unstratified test based on Pearson's correlation coefficient can produce spurious results when applied to family data, and we present a stratified family expression association test (FEXAT). We illustrate the utility of the FEXAT via simulation and an application to gene-expression data from lymphoblastoid cell lines from four CEPH families. The FEXAT has a smaller estimated false-discovery rate than the standard test when within-family correlations are of interest, and it detects biologically plausible correlations between beta catenin and genes in the WNT-activation pathway in humans that the standard test does not.

Adenomatous Polyposis Coli Protein↗

PubMed2003

Genetic loci for diet-induced atherosclerotic lesions and plasma lipids in mice.

Genetic factors independent of those affecting plasma lipid levels are a major contributor to risk for atherosclerosis in humans, yet the basis for these is poorly understood. This study examined plasma lipids and diet-induced atherosclerosis in 16-month-old female mice of strains C56BL/6J and DBA/2J. Mice of the parental strains, from recombinant inbred strains derived from these (BXD RI), and F(2) progeny were fed an atherogenic diet for 16 weeks, beginning at 1 year of age. This induced atherosclerotic lesion formation in both parental strains, accompanied by increased plasma LDL levels. However, individual BXD RI strains and the BXD F(2) mice demonstrated a range of atherosclerotic lesion formation that was not or at best weakly correlated with plasma lipid levels. Quantitative trait locus (QTL) analysis of the BXD F(2) mice identified a locus with significant linkage (lod 4.5) for aortic lesion size on Chromosome (Chr) 10 that was independent of plasma lipids. Other loci with suggestive or significant linkage for various plasma lipid measures were identified on Chr 2, 3, 4, 5, 6, 7, 11, and 17. In this intercross, the genes primarily influencing atherosclerosis are distinct from those controlling plasma lipid levels.

Animals↗

PubMed2002

Gene-microarray analysis of multiple sclerosis lesions yields new targets validated in autoimmune encephalomyelitis.

Microarray analysis of multiple sclerosis (MS) lesions obtained at autopsy revealed increased transcripts of genes encoding inflammatory cytokines, particularly interleukin-6 and -17, interferon-gamma and associated downstream pathways. Comparison of two poles of MS pathology--acute lesions with inflammation versus 'silent' lesions without inflammation--revealed differentially transcribed genes. Some products of these genes were chosen as targets for therapy of experimental autoimmune encephalomyelitis (EAE) in mice. Granulocyte colony-stimulating factor is upregulated in acute, but not in chronic, MS lesions, and the effect on ameliorating EAE is more pronounced in the acute phase, in contrast to knocking out the immunoglobulin Fc receptor common gamma chain where the effect is greatest on chronic disease. These results in EAE corroborate the microarray studies on MS lesions. Large-scale analysis of transcripts in MS lesions elucidates new aspects of pathology and opens possibilities for therapy.

Acute Disease↗

PubMed2002

Codon and rate variation models in molecular phylogeny.

This article generalizes previous models for codon substitution and rate variation in molecular phylogeny. Particular attention is paid to (1) reversibility, (2) acceptance and rejection of proposed codon changes, (3) varying rates of evolution among codon sites, and (4) the interaction of these sites in determining evolutionary rates. To accommodate spatial variation in rates, Markov random fields rather than Markov chains are introduced. Because these innovations complicate maximum likelihood estimation in phylogeny reconstruction, it is necessary to formulate new algorithms for the evaluation of the likelihood and its derivatives with respect to the underlying kinetic, acceptance, and spatial parameters. To derive the most from maximum likelihood analysis of sequence data, it is useful to compute posterior probabilities assigning residues to internal nodes and evolutionary rate classes to codon sites. It is also helpful to search through tree space in a way that respects accepted phylogenetic relationships. Our phylogeny program LINNAEUS implements algorithms realizing these goals. Readers may consult our companion article in this issue for several examples.

Algorithms↗