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Biomedical subjects

Eleanor Feingold

Publications and source records attributed to Eleanor Feingold.

30 records · Page 2Linked to original sources
PubMed2004

Genetic variation in uncoupling protein 3 is associated with dietary intake and body composition in females.

The uncoupling proteins (UCPs) are a family of mitochondrial transport proteins that promote proton leakage across the inner mitochondrial membrane, uncoupling oxidative phosphorylation from adenosine triphosphate (ATP) production and releasing energy as heat. Variation in these genes may disrupt biochemical pathways influencing thermogenesis, energy metabolism, and fuel substrate partitioning and oxidation, which may in turn predispose to obesity. We genotyped polymorphisms in UCP2 and UCP3 in a sample of nondiabetic participants (n = 722) of the San Luis Valley Diabetes Study (SLVDS) and found female-specific associations between UCP3 polymorphisms and measures of dietary intake and body composition. The UCP3-5 variant was statistically significantly associated with total caloric intake (P =.012), fat intake (P =.011), fat mass (P =.004), and lean mass (P =.013), with the C allele corresponding to higher dietary intake and lower fat mass and lean mass. The UCP3p-55 and the UCP3-3 polymorphisms, which were in high linkage disequilibrium (D' = 0.9776), showed similar patterns of association with total caloric intake (P =.031 and P =.042, respectively) and lean mass (P =.035 and P =.059, respectively), with the rare alleles corresponding to higher total intake and lean mass. No statistically significant associations were detected between the outcome variables and polymorphisms in UCP2. Two-way analysis of covariance (ANCOVA), used to evaluate the multi-locus effects and interactions between UCP3-5 and UCP3p-55, showed association with the main effect terms, but no evidence for statistically significant interaction between UCP3-5 and UCP3p-55 in regard to dietary intake. The UCP3-5 polymorphism was the only statistically significant genetic predictor of fat mass. The lean mass model showed no statistically significant association with either UCP3 variant. These results support a role for UCP3 in fuel substrate management and energy metabolism, which may influence body weight regulation.

Alleles↗
PubMed2003

An empirical bayesian method for differential expression studies using one-channel microarray data.

Gene expression microarrays have become powerful tools in many areas of biological and biomedical research. These technologies allow researchers to measure the expression levels of thousands of genes in a tissue or cell sample simultaneously. One of the most common types of microarray experiments is simply an exploratory study to compare two samples (e.g. tumor and normal tissue) and look for a list of genes that might be differentially expressed between the two. Differential expression is typically measured by computing a t-statistic or similar statistic for each gene. The genes are then ranked according to the absolute value of the t-statistic, and the twenty or fifty best candidates might be studied in follow-up experiments. When sample sizes are small, the t-statistic can be problematic, because variances are estimated poorly and the "top 20" list is often dominated by the genes with the lowest variance estimates. Lönnstedt and Speed (2001) proposed an empirical Bayes method for avoiding this problem, and showed that their approach has lower false positive and false negative rates than t-statistic-based methods. However, their method was designed mainly for the two-channel microarray, which produces paired data. It is not suitable for technologies such as one-channel arrays that produce unpaired data. We propose a simplification for Lönnstedt and Speed's method, and then extend it to unpaired data with two or more independent treatments. We demonstrate our method on both simulated and real data. When the number of replicates is small, gene rankings based on our statistic appear to be much more reliable than rankings based on the t-statistic.

Journal Article↗
PubMed2003

Recent advances in human quantitative-trait-locus mapping: comparison of methods for selected sibling pairs.

During the past few years, there has been a great deal of new work on methods for mapping quantitative-trait loci by use of sibling pairs and sibships. There are several new methods based on linear regression, as well as several more that are based on score statistics. In theory, most of the new methods should be relatively robust to violations of distributional assumptions and to selected sampling, but, in practice, there has been little evaluation of how the methods perform on selected samples. We survey most of the new regression-based statistics and score statistics and propose a few minor variations on the score statistics. We use simulation to evaluate the type I error and the power of all of the statistics, considering (a) population samples of sibling pairs and (b) sibling pairs ascertained on the basis of at least one sibling with a trait value in the top 10% of the distribution. Most of the statistics have correct type I error for selected samples. The statistics proposed by Xu et al. and by Sham and Purcell are generally the most powerful, along with one of our score statistic variants. Even among the methods that are most powerful for "nice" data, some are more robust than others to non-Gaussian trait models and/or misspecified trait parameters.

Chromosome Mapping↗
PubMed2003

Recent advances in human quantitative-trait-locus mapping: comparison of methods for discordant sibling pairs.

Extreme discordant sibling pairs (EDSPs) are theoretically powerful for the mapping of quantitative-trait loci (QTLs) in humans. EDSPs have not been used much in practice, however, because of the need to screen very large populations to find enough pairs that are extreme and discordant. Given appropriate statistical methods, another alternative is to use moderately discordant sibling pairs (MDSPs)--pairs that are discordant but not at the far extremes of the distribution. Such pairs can be powerful yet far easier to collect than extreme discordant pairs. Recent work on statistical methods for QTL mapping in humans has included a number of methods that, though not developed specifically for discordant pairs, may well be powerful for MDSPs and possibly even EDSPs. In the present article, we survey the new statistics and discuss their applicability to discordant pairs. We then use simulation to study the type I error and the power of various statistics for EDSPs and for MDSPs. We conclude that the best statistic(s) for discordant pairs (moderate or extreme) is (are) to be found among the new statistics. We suggest that the new statistics are appropriate for many other designs as well-and that, in fact, they open the way for the exploration of entirely novel designs.

Genetics, Population↗
PubMed2003

Variation in the FABP2 promoter alters transcriptional activity and is associated with body composition and plasma lipid levels.

The fatty acid-binding proteins (FABPs) are cytoplasmic proteins involved in intracellular fatty acid transport and metabolism. FABP2, the intestinal-type FABP, is expressed exclusively in enterocytes in the small intestine. In previous studies of an Ala54Thr substitution in FABP2, the Thr-allele showed association with increased lipid oxidation, elevated plasma lipids, and impaired insulin sensitivity. We screened roughly 1 kb 5' of the FABP2 initiation codon and identified three insertion/deletion polymorphisms and four single nucleotide polymorphisms (SNPs). Three of the SNPs were in complete linkage disequilibrium with the three insertion/deletion polymorphisms, defining exactly two haplotypes (FABP2p-ID). We tested the hypothesis that this variation alters gene expression by transfecting Caco-2 cells with pGL3-Basic constructs containing opposite FABP2p-ID haplotypes. Luciferase assays showed a statistically significant two-fold increase in gene expression of the pGL3-insertion construct over the pGL3-deletion construct (P<0.001; n=5). We also tested for association between three FABP2 variants and measurements of body composition, plasma lipids, and insulin sensitivity in non-diabetic control subjects from the San Luis Valley Diabetes Study (n=714). The only informative variant, FABP2p-ID, was statistically significantly associated with body mass index (P=0.042) and marginally associated with fat mass (P=0.084), cholesterol (P=0.066), and HOMA IR (a derived measure of insulin resistance; P=0.062) in the entire cohort. Similar associations were seen only in non-Hispanics when the analysis was stratified by ethnicity. Within the non-Hispanic subgroup, the effects of FABP2p-ID on plasma lipids were sex-specific. These results suggest that genetic variation in the 5' region of FABP2 affects transcriptional activity, presumably leading to alterations in body composition and lipid processing.

Analysis of Variance↗
PubMed2003

Age of onset in hereditary lymphedema.

OBJECTIVE: To characterize age of onset patterns and penetrance in hereditary lymphedema, including differences caused by sex and genetic heterogeneity. STUDY DESIGN: Kaplan-Meier analysis of three family cohorts with autosomal dominant lymphedema: (1) five families with unique mutations in FLT4, (2) 16 families with unique mutations in FOXC2, and (3) 77 families with no mutations yet identified in any gene (the heterogeneous group). RESULTS: Age of onset was typically congenital among FLT4 mutation families and pubertal among FOXC2 mutation families, with similar male and female penetrance in both groups. Age of onset was highly variable in the families with no identified mutation, with substantially higher penetrance among female patients than male patients. In addition, male patients and female patients in the heterogeneous group had very different overall age of onset profiles. CONCLUSIONS: The two genes identified to date that cause hereditary lymphedema have equal male and female effects, but each displays a different pattern of onset age and penetrance. The heterogeneous group represents a genetically heterogeneous population and has phenotypic overlaps with the FLT4 and FOXC2 mutation families.

Age of Onset↗
PubMed2002

Systemic delivery of a high-capacity adenoviral vector expressing mouse CTLA4Ig improves skeletal muscle gene therapy.

Adenoviral vectors (AdV) are promising vectors for gene transfer of skeletal muscle. To alleviate humoral and cellular immune responses that limit successful gene transfer, the present study determined the route of administration of AdmCTLA4Ig (an adenovirus that encodes a fusion protein of mouse cytotoxic T lymphocyte-associated protein 4 (CTLA4) and the Fc protion of immunoglobulin G (IgG), CTLA4Ig) that provided optimal AdV-mediated immunosuppression. AdmCTLA4Ig was administered either intramuscularly (i.m.), intravenously (i.v.), or in the footpad (f.p.) of mice that simultaneously received an i.m. injection of an AdV encoding enhanced green fluorescent protein (AdEGFP). EGFP expression in muscle and serum levels of CTLA4Ig were higher in the i.v. and f.p. groups than the i.m. group 30 days after treatment. The i.v. and f.p. groups showed lower levels of CD4(+) and CD8(+) T-cell infiltration and decreased interferon-gamma (IFN-gamma) and interleukin 2 (IL-2) production by splenocytes. The T helper cell (Th) 2 cytokine, interleukin 4 (IL-4), was increased 30 days after treatment in the i.v. group. Neutralizing antibodies to AdV were lower in the i.v. and f.p. groups, whereas total antibodies to AdV and EGFP were lower only in the f.p. group. Our results suggest that the optimal route of administration of AdmCTLA4Ig is i.v., providing at least 2 months of stable transgene expression in muscle. The inhibition of the cellular immune response, especially the Th1 response, appeared to play a critical role in prolonging transgene expression. These results suggest that AdV-mediated delivery of targeted immune suppression will be a useful adjunct to muscle gene delivery.

Abatacept↗
PubMed2002

Methods for analyzing the spatial distribution of chiasmata during meiosis based on recombination data.

Using genetic recombination data to make inferences about chiasmata on the tetrad during meiosis is a classic problem dating back to Weinstein's paper in 1936 (Genetics 21, 155-199). In the last few years, Weinstein's methods have been revived and applied to new problems, but a number of important statistical issues remain unresolved. Recently, we developed improved statistical methods for studying the frequency distribution of the number of chiasmata (Yu and Feingold, 2001, Biometrics 57, 427-434). In the current article, we develop methods for the complementary issue of studying the spatial distribution of chiasmata. Somewhat different statistical approaches are needed for the spatial problem than for the frequency problem because different scientific questions are of interest. We explore the properties of the maximum likelihood estimate (MLE) for chiasma spatial distributions and propose improvements to the estimation procedures. We develop a class of statistical tests for comparing chiasma patterns in tetrads that have undergone normal meiosis and tetrads that have had a nondisjunction event. Finally, we propose an EM algorithm to find the MLE when the observed data is ambiguous, as is often the case in human datasets. We apply our improved methods to reanalyze a dataset from the literature studying the association between crossover location and meiotic nondisjunction of chromosome 21.

Algorithms↗
PubMed2001

Statistics for nonparametric linkage analysis of X-linked traits in general pedigrees.

We have compared the power of several allele-sharing statistics for "nonparametric" linkage analysis of X-linked traits in nuclear families and extended pedigrees. Our rationale was that, although several of these statistics have been implemented in popular software packages, there has been no formal evaluation of their relative power. Here, we evaluate the relative performance of five test statistics, including two new test statistics. We considered sibships of sizes two through four, four different extended pedigrees, 15 different genetic models (12 single-locus models and 3 two-locus models), and varying recombination fractions between the marker and the trait locus. We analytically estimated the sample sizes required for 80% power at a significance level of.001 and also used simulation methods to estimate power for a sample size of 10 families. We tried to identify statistics whose power was robust over a wide variety of models, with the idea that such statistics would be particularly useful for detection of X-linked loci associated with complex traits. We found that a commonly used statistic, S(all), generally performed well under various conditions and had close to the optimal sample sizes in most cases but that there were certain cases in which it performed quite poorly. Our two new statistics did not perform any better than those already in the literature. We also note that, under dominant and additive models, regardless of the statistic used, pedigrees with all-female siblings have very little power to detect X-linked loci.

Alleles↗