Discovery of Blood Transcriptional Endotypes in Women with Pelvic Inflammatory Disease

Zheng, Xiaojing; O’Connell, Catherine M.; Zhong, Wujuan; Nagarajan, Uma M.; Tripathy, Manoj K.; Lee, De’Ashia; Russell, Ali N.; Wiesenfeld, Harold C.; Hillier, Sharon L.; Darville, Toni

doi:10.4049/jimmunol.1701658

Cited by 19 publications

(35 citation statements)

References 63 publications

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“…The Anaerobes and Clearance of Endometritis (ACE) cohort was comprised of symptomatic women with clinically diagnosed PID, according to the Centers for Disease Control and Prevention diagnostic criteria (Workowski et al, 2015), who participated in a clinical trial (NCT01160640) comparing antibiotic regimens for PID treatment (Zheng et al, 2018). Diagnostic criteria included one or more of the following present on pelvic examination: cervical motion tenderness, or uterine tenderness or adnexal tenderness, in a sexually active young woman experiencing pelvic or lower abdominal pain (Workowski et al, 2015).…”

Section: Methodsmentioning

confidence: 99%

“…Cervical swabs were collected for microbiological molecular testing. Blood was collected for transcriptional profiling, and endometrial sampling was performed for microbiologic and histologic evaluation (Zheng et al, 2018); endometritis was defined according to published criteria (Kiviat et al, 1990). Chlamydial cervical burden was estimated via quantitative PCR using DNA extracted from reserved cervical swab eluates (Russell et al, 2016).…”

Section: Methodsmentioning

confidence: 99%

“…Total RNA was isolated from blood of TECH-N participants and analyzed via microarray (Illumina Human HT12 v3.0 expression bead chip) in the Genomics and Proteomics Core Laboratories at the University of Pittsburgh as described previously (Zheng et al, 2018) for ACE and TRAC participants and can be accessed from GEO (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE110106). Transcripts were quantile normalized (Irizarry et al, 2003) and log2 transformed.…”

Section: Methodsmentioning

confidence: 99%

“…Cases were previously defined as women with a clinical PID diagnosis and biopsy-confirmed endometrial CT/GC (STI) and endometritis, and controls as study participants who did not display symptoms of PID, lacked endometrial infection and inflammation, and included women with cervical CT/GC and uninfected women (Zheng et al, 2018). For this study, two-thirds of cases and controls were assigned to a training dataset and the remaining one-third to a testing dataset based on the temporal order in which they were enrolled (Figure 1).…”

Section: Methodsmentioning

confidence: 99%

“…We reported a distinct blood-derived mRNA profile in women with symptomatic PID and endometritis caused by GC and/or CT. Women with STI-induced endometritis exhibited enhanced expression of myeloid cell genes with suppression of genes involved in protein synthesis, mitochondrial oxidative phosphorylation, and T-cell responses compared to uninfected women or women with cervical infection only (Zheng et al, 2018). Women solely infected with CT expressed elevated levels of type I and type II interferon genes.…”

Section: Introductionmentioning

confidence: 99%

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Gene Expression Signatures Can Aid Diagnosis of Sexually Transmitted Infection-Induced Endometritis in Women

Zheng

O’Connell

Zhong

et al. 2018

Front. Cell. Infect. Microbiol.

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Sexually transmitted infection (STI) of the upper reproductive tract can result in inflammation and infertility. A biomarker of STI-induced upper tract inflammation would be significant as many women are asymptomatic and delayed treatment increases risk of sequelae. Blood mRNA from 111 women from three cohorts was profiled using microarray. Unsupervised analysis revealed a transcriptional profile that distinguished 9 cases of STI-induced endometritis from 18 with cervical STI or uninfected controls. Using a hybrid feature selection algorithm we identified 21 genes that yielded maximal classification accuracy within our training dataset. Predictive accuracy was evaluated using an independent testing dataset of 5 cases and 10 controls. Sensitivity was evaluated in a separate test set of 12 women with asymptomatic STI-induced endometritis in whom cervical burden was determined by PCR; and specificity in an additional test set of 15 uninfected women with pelvic pain due to unknown cause. Disease module preservation was assessed in 42 women with a clinical diagnosis of pelvic inflammatory disease (PID). We also tested the ability of the biomarker to discriminate STI-induced endometritis from other diseases. The biomarker was 86.7% (13/15) accurate in correctly distinguishing cases from controls in the testing dataset. Sensitivity was 83.3% (5/6) in women with high cervical Chlamydia trachomatis burden and asymptomatic endometritis, but 0% (0/6) in women with low burden. Specificity in patients with non-STI-induced pelvic pain was 86.7% (13/15). Disease modules were preserved in all 8 biomarker predicted cases. The 21-gene biomarker was highly discriminatory for systemic infections, lupus, and appendicitis, but wrongly predicted tuberculosis as STI-induced endometritis in 52.4%. A 21-gene biomarker can identify asymptomatic women with STI-induced endometritis that places them at risk for chronic disease development and discriminate STI-induced endometritis from non-STI pelvic pain and other diseases.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Gene Expression Signatures Can Aid Diagnosis of Sexually Transmitted Infection-Induced Endometritis in Women

Zheng

O’Connell

Zhong

et al. 2018

Front. Cell. Infect. Microbiol.

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Pathogenic Interplay Between Chlamydia trachomatis and Neisseria gonorrhoeae that Influences Management and Control Efforts—More Questions than Answers?

Leonard

Schoborg

Low

et al. 2019

Curr Clin Micro Rpt

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Purpose of Review To emphasize key gaps in knowledge impacting efforts to control single infection and co-infections with Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG), the most common bacterial sexually transmitted infections (STIs) worldwide. Recent Findings Clinical and epidemiological studies describe gaps in understanding about female rectal CT infection, screening effectiveness, pelvic inflammatory disease, and influence of the microbiome. For NG, gaps in knowledge include factors increasing incidence in men who have sex with men, correlations between treatment and antibiotic resistance, the role of pharyngeal infection, and microbiome influence. CT/NG co-infections are poorly understood, and adequate models to explore pathophysiological consequences of co-infection urgently needed. The sole existing CT/NG co-infection mouse model showed that CT/NG interactions in vivo modulate host response and NG load/shedding-encouraging further consideration of this model and potential alternatives. Summary We stress key challenges in controlling these important STIs. Appropriate, quality-assured animal models are essential to improve understanding of the pathogenic interplay in CT/NG co-infections. Keywords Chlamydia trachomatis. Neisseria gonorrhoeae. Co-infection. Mouse model This article is part of the Topical Collection on Influences of Hormones and Other Microorganisms on Genital Tract Pathogens

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Semi-CAM: A semi-supervised deconvolution method for bulk transcriptomic data with partial marker gene information

Kollipara

Darville

et al. 2020

Sci Rep

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Deconvolution of bulk transcriptomics data from mixed cell populations is vital to identify the cellular mechanism of complex diseases. existing deconvolution approaches can be divided into two major groups: supervised and unsupervised methods. Supervised deconvolution methods use cell typespecific prior information including cell proportions, reference cell type-specific gene signatures, or marker genes for each cell type, which may not be available in practice. Unsupervised methods, such as non-negative matrix factorization (nMf) and convex Analysis of Mixtures (cAM), in contrast, completely disregard prior information and thus are not efficient for data with partial cell type-specific information. in this paper, we propose a semi-supervised deconvolution method, semi-cAM, that extends cAM by utilizing marker information from partial cell types. Analysis of simulation and two benchmark data have demonstrated that semi-cAM outperforms cAM by yielding more accurate cell proportion estimations when markers from partial/all cell types are available. in addition, when markers from all cell types are available, semi-cAM achieves better or similar accuracy compared to the supervised method using signature genes, ciBeRSoRt, and the marker-based supervised methods semi-nMf and DSA. furthermore, analysis of human chlamydia-infection data with bulk expression profiles from six cell types and prior marker information of only three cell types suggests that semi-CAM achieves more accurate cell proportion estimations than cAM.

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Discovery of Blood Transcriptional Endotypes in Women with Pelvic Inflammatory Disease

Cited by 19 publications

References 63 publications

Gene Expression Signatures Can Aid Diagnosis of Sexually Transmitted Infection-Induced Endometritis in Women

Gene Expression Signatures Can Aid Diagnosis of Sexually Transmitted Infection-Induced Endometritis in Women

Pathogenic Interplay Between Chlamydia trachomatis and Neisseria gonorrhoeae that Influences Management and Control Efforts—More Questions than Answers?

Semi-CAM: A semi-supervised deconvolution method for bulk transcriptomic data with partial marker gene information

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