Search PubMed⌕ Search

Biomedical subjects

Yuedong Wang

Publications and source records attributed to Yuedong Wang.

9 recordsLinked to original sources
PubMed2006

Sources of heterogeneities in estimating the prevalence of endometriosis in infertile and previously fertile women.

OBJECTIVE: To identify possible sources of heterogeneity in estimates of the prevalence of endometriosis in previously fertile women and in women with infertility. DESIGN: A pooled analysis of previously published studies reporting prevalence estimates. SETTING: Academic. PATIENTS: None. INTERVENTIONS: None. MAIN OUTCOME MEASURES: None. RESULTS: There were tremendous heterogeneities in prevalence estimates for both the fertile and infertile groups. In addition, the prevalence estimates increased with the year of publication, but decreased with sample size. For previously fertile women, the heterogeneity in prevalence estimates was no longer significant after the effects of sample size and year of publication on estimates were taken into account. In the infertile group, however, there was still a sizeable heterogeneity unaccounted for after both sample size and year of publication were taken into account. CONCLUSIONS: A single prevalence estimate for the entire fertile or infertile group may be too simplistic at best. More precise prevalence estimates, likely to be age-dependent, await carefully designed and executed studies that will also record covariates such as age at surgery and referral patterns.

Adolescent↗
PubMed2006

Genomic alterations in ectopic and eutopic endometria of women with endometriosis.

BACKGROUND/AIMS: Ectopic and eutopic endometria of women with endometriosis have been shown to contain genomic alterations. In this study, we sought to identify genomic alterations in both ectopic and eutopic endometria of 5 women with endometriosis and to examine whether the two tissues share any genomic alterations. We also attempted to classify tissue samples based on the alteration profiles. METHODS: Laser capture microdissection was used to harvest epithelial cells. High-resolution comparative genomic hybridization microarrays were used to identify genomic alterations in eutopic and ectopic endometria from 5 women with endometriosis. The results were validated by real-time RT-PCR and loss of heterozygosity analysis. RESULTS: All 5 patients had genomic alterations in their eutopic and ectopic endometria. The ectopic and eutopic endometria shared a sizable portion of genomic alterations. Cluster analysis of the genomic alteration profile correctly and consistently classified tissue samples from the 5 patients into two groups: peritoneal implants and ovarian cysts. CONCLUSIONS: The correct classification of tissue samples into two groups suggests that these two subtypes of endometriosis may have distinct genomic alteration profiles and are thus distinct entities, as previously proposed. The shared alterations are likely the ones that harbor genes responsible for an increased propensity of endometrial debris to implant to the ectopic sites and for early events that lead to the establishment of lesions. Alternatively, these shared alterations may harbor genes that are dysregulated in both eutopic and ectopic endometria. The identified genomic alterations should help to zero in genes involved in the pathogenesis of endometriosis in future studies.

Adult↗
PubMed2006

The prevalence of endometriosis in women with chronic pelvic pain.

BACKGROUND: The 2004 American College of Obstetrics and Gynecology clinical management guideline states that the prevalence of endometriosis is approximately 33% in women with chronic pelvic pain (CPP). This estimate came from a review showing that 28% of adult women with CPP were found to have endometriosis. The prevalence of 28% in adult women was arrived based on a compilation of 11 published studies. Yet even within the 11 studies, the reported prevalence of endometriosis varies wildly, ranging from 2 to 74%. Such an astounding variation or heterogeneity raises the question whether it is appropriate to use a single prevalence of endometriosis for all women with CPP. METHODS: We sought to identify possible sources of heterogeneities in the estimation of prevalence of endometriosis in women with CPP. We included more studies that reported prevalence estimates than the review, and examined the effect of sample size and the year of publication on the heterogeneity. RESULTS: The year of publication is positively associated with the prevalence estimate, which may indicate an increasing awareness of various appearances of endometriosis, or the prevalence of endometriosis may have increased among women with CPP. An alternative analysis with removal of four studies reporting highest prevalence estimates indicated that sample size is negatively associated with the prevalence estimates while the year of publication became only marginally significant. CONCLUSIONS: There are identifiable sources of heterogeneity in prevalence estimates, with the year of publication, sample size, and difference in evaluation of CPP being three apparent sources. Having a single prevalence estimate for all women with CPP may be too simplistic at best. The true prevalence is very likely to be higher than 33%.

Adult↗
PubMed2006

Detecting pulsatile hormone secretions using nonlinear mixed effects partial spline models.

Neuroendocrine ensembles communicate with their remote and proximal target cells via an intermittent pattern of chemical signaling. The identification of episodic releases of hormonal pulse signals constitutes a major emphasis of endocrine investigation. Estimating the number, temporal locations, secretion rate, and elimination rate from hormone concentration measurements is of critical importance in endocrinology. In this article, we propose a new flexible statistical method for pulse detection based on nonlinear mixed effects partial spline models. We model pulsatile secretions using biophysical models and investigate biological variation between pulses using random effects. Pooling information from different pulses provides more efficient and stable estimation for parameters of interest. We combine all nuisance parameters including a nonconstant basal secretion rate and biological variations into a baseline function that is modeled nonparametrically using smoothing splines. We develop model selection and parameter estimation methods for the general nonlinear mixed effects partial spline models and an R package for pulse detection and estimation. We evaluate performance and the benefit of shrinkage by simulations and apply our methods to data from a medical experiment.

Animals↗
PubMed2005

Transcriptional characterizations of differences between eutopic and ectopic endometrium.

Endometriosis, defined as the presence of endometrial glandular and stromal cells outside the uterine cavity, is a common gynecological disease with poorly understood pathogenesis. Using laser capture microdissection and a cDNA microarray with 9600 genes/expressed sequence tags (ESTs), we have conducted a comprehensive profiling of gene expression differences between the ectopic and eutopic endometrium taken from 12 women with endometriosis adjusted for menstrual phase and the location of the lesions. With dye-swapping and replicated arrays, we found 904 genes/ESTs that are differentially expressed. We validated the gene expression using real-time RT-PCR. We found that the expression patterns of these genes/ESTs correctly classified the 12 patients into ovarian and nonovarian endometriosis. We identified gene clusters that are location-specific. In addition, we identified several biological themes using Expression Analysis Systematic Explorer. Finally, we identified 79 pathways with over 100 genes with known functions, which include oxidative stress, focal adhesion, Wnt signaling, and MAPK signaling. The identification of these genes and their associated pathways provides new insight. Our findings will stimulate future investigations on molecular genetic mechanisms underlying the pathogenesis of endometriosis.

Base Sequence↗
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↗