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Biomedical subjects

Yuedong Wang

Publications and source records attributed to Yuedong Wang.

4 recordsLinked to original sources
PubMed2004

Genomic alterations in the endometrium may be a proximate cause for endometriosis.

OBJECTIVE: To test the hypothesis that endometriosis may originate from genomic alterations in the endometrium by genomic analysis of endometrial tissues in patients with endometriosis and compare them with those from normal controls. METHODS: Endometrial tissue samples were taken from five women with endometriosis. For controls, we used endometrial tissue samples from four women who underwent elective abortions and one sample from placenta. Using array-based comparative genomic hybridization (CGH), we determined the normal range of variation in CGH signals using normal controls. CGH results were further confirmed by real-time quantitative PCR and loss of heterozygosity analysis. RESULTS: We identified several regions of genomic alterations in all five patients. Some of these regions were the same regions identified previously in endometriotic lesions. For select markers, the genomic alterations were confirmed by real-time PCR and LOH analyses. CONCLUSIONS: There is evidence that the endometrium in women with endometriosis has genomic alterations. This is consistent with numerous reports that the endometrium of women with endometriosis differ from those of women without. Our finding suggests that genomic alterations in the endometrium may be a proximate cause for endometriosis.

Adult↗
PubMed2004

Statistical methods for detecting genomic alterations through array-based comparative genomic hybridization (CGH).

Array-based comparative genomic hybridization (ABCGH) is an emerging high-resolution and high-throughput molecular genetic technique that allows genome-wide screening for chromosome alterations associated with tumorigenesis. Like the cDNA microarrays, ABCGH uses two differentially labeled test and reference DNAs which are cohybridized to cloned genomic fragments immobilized on glass slides. The hybridized DNAs are then detected in two different fluorochromes, and the significant deviation from unity in the ratios of the digitized intensity values is indicative of copy-number differences between the test and reference genomes. Proper statistical analyses need to account for many sources of variation besides genuine differences between the two genomes. In particular, spatial correlations, the variable nature of the ratio variance and non-Normal distribution call for careful statistical modeling. We propose two new statistics, the standard t-statistic and its modification with variances smoothed along the genome, and two tests for each statistic, the standard t-test and a test based on the hybrid adaptive spline (HAS). Simulations indicate that the smoothed t-statistic always improves the performance over the standard t-statistic. The t-tests are more powerful in detecting isolated alterations while those based on HAS are more powerful in detecting a cluster of alterations. We apply the proposed methods to the identification of genomic alterations in endometrium in women with endometriosis.

Chromosome Aberrations↗
PubMed2003

Shape-invariant modeling of circadian rhythms with random effects and smoothing spline ANOVA decompositions.

Medical studies often collect physiological and/or psychological measurements over time from multiple subjects, to study dynamics such as circadian rhythms. Under the assumption that the expected response functions of all subjects are the same after shift and scale transformations, shape-invariant models have been applied to analyze this kind of data. The shift and scale parameters provide efficient and interpretable data summaries, while the common shape function is usually modeled nonparametrically, to provide flexibility. However, due to the deterministic nature of the shift and scale parameters, potential correlations within a subject are ignored. Furthermore, the shape of the common function may depend on other factors, such as disease. In this article, we propose shape-invariant mixed effects models. A second-stage model with fixed and random effects is used to model individual shift and scale parameters. A second-stage smoothing spline ANOVA model is used to study potential covariate effects on the common shape function. We apply our methods to a real data set to investigate disease effects on circadian rhythms of cortisol, a hormone that is affected by stress. We find that patients with Cushing's syndrome lost circadian rhythms and their 24-hour means were elevated to very high levels. Patients with major depression had the same circadian shape and phases as normal subjects. However, their 24-hour mean levels were elevated and amplitudes were dampened for some patients.

Analysis of Variance↗