Browsing by Subject "Pelvic pain"

Now showing 1 - 3 of 3
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    Acyloxyacyl hydrolase is a host determinant of gut microbiome-mediated pelvic pain
    (The American Physiological Society, 2021) Rahman-Enyart, Afrida; Yang, Wenbin; Yaggie, Ryan E.; White, Bryan A.; Welge, Michael; Auvil, Loretta; Berry, Matthew; Bushell, Colleen; Rosen, John M.; Rudick, Charles N.; Schaeffer, Anthony J.; Klumpp, David J.; Pharmacology and Toxicology, School of Medicine
    Dysbiosis of gut microbiota is associated with many pathologies, yet host factors modulating microbiota remain unclear. Interstitial cystitis/bladder pain syndrome (IC/BPS) is a debilitating condition of chronic pelvic pain often with comorbid urinary dysfunction and anxiety/depression, and recent studies find fecal dysbiosis in patients with IC/BPS. We identified the locus encoding acyloxyacyl hydrolase, Aoah, as a modulator of pelvic pain severity in a murine IC/BPS model. AOAH-deficient mice spontaneously develop rodent correlates of pelvic pain, increased responses to induced pelvic pain models, voiding dysfunction, and anxious/depressive behaviors. Here, we report that AOAH-deficient mice exhibit dysbiosis of gastrointestinal (GI) microbiota. AOAH-deficient mice exhibit an enlarged cecum, a phenotype long associated with germ-free rodents, and a "leaky gut" phenotype. AOAH-deficient ceca showed altered gene expression consistent with inflammation, Wnt signaling, and urologic disease. 16S sequencing of stool revealed altered microbiota in AOAH-deficient mice, and GC-MS identified altered metabolomes. Cohousing AOAH-deficient mice with wild-type mice resulted in converged microbiota and altered predicted metagenomes. Cohousing also abrogated the pelvic pain phenotype of AOAH-deficient mice, which was corroborated by oral gavage of AOAH-deficient mice with stool slurry of wild-type mice. Converged microbiota also alleviated comorbid anxiety-like behavior in AOAH-deficient mice. Oral gavage of AOAH-deficient mice with anaerobes cultured from IC/BPS stool resulted in exacerbation of pelvic allodynia. Together, these data indicate that AOAH is a host determinant of normal gut microbiota, and dysbiosis associated with AOAH deficiency contributes to pelvic pain. These findings suggest that the gut microbiome is a potential therapeutic target for IC/BPS.
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    Big Data and Dysmenorrhea: What Questions Do Women and Men Ask About Menstrual Pain?
    (Mary Ann Liebert, 2018-10) Chen, Chen X.; Groves, Doyle; Miller, Wendy R.; Carpenter, Janet S.; School of Nursing
    BACKGROUND: Menstrual pain is highly prevalent among women of reproductive age. As the general public increasingly obtains health information online, Big Data from online platforms provide novel sources to understand the public's perspectives and information needs about menstrual pain. The study's purpose was to describe salient queries about dysmenorrhea using Big Data from a question and answer platform. MATERIALS AND METHODS: We performed text-mining of 1.9 billion queries from ChaCha, a United States-based question and answer platform. Dysmenorrhea-related queries were identified by using keyword searching. Each relevant query was split into token words (i.e., meaningful words or phrases) and stop words (i.e., not meaningful functional words). Word Adjacency Graph (WAG) modeling was used to detect clusters of queries and visualize the range of dysmenorrhea-related topics. We constructed two WAG models respectively from queries by women of reproductive age and bymen. Salient themes were identified through inspecting clusters of WAG models. RESULTS: We identified two subsets of queries: Subset 1 contained 507,327 queries from women aged 13-50 years. Subset 2 contained 113,888 queries from men aged 13 or above. WAG modeling revealed topic clusters for each subset. Between female and male subsets, topic clusters overlapped on dysmenorrhea symptoms and management. Among female queries, there were distinctive topics on approaching menstrual pain at school and menstrual pain-related conditions; while among male queries, there was a distinctive cluster of queries on menstrual pain from male's perspectives. CONCLUSIONS: Big Data mining of the ChaCha® question and answer service revealed a series of information needs among women and men on menstrual pain. Findings may be useful in structuring the content and informing the delivery platform for educational interventions.
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    Symptoms-Based Phenotypes Among Women With Dysmenorrhea: A Latent Class Analysis
    (SAGE, 2018-10) Chen, Chen X.; Ofner, Susan; Bakoyannis, Giorgos; Kwekkeboom, Kristine L.; Carpenter, Janet S.; Biostatistics, School of Public Health
    Dysmenorrhea is highly prevalent and may increase women’s risk for developing other chronic pain conditions. Although it is highly variable, symptom-based dysmenorrhea phenotypes have not been identified. The study aims were to identify symptom-based dysmenorrhea phenotypes and examine their relationships with demographic and clinical characteristics. In a cross-sectional study, 762 women with dysmenorrhea rated severity of 14 dysmenorrhea-related symptoms. Using latent class analysis, we identified three distinctive phenotypes. Women in the “mild localized pain” phenotype (n=202, 26.51%) had mild abdominal cramps and dull abdominal pain/discomfort. Women in the “severe localized pain” phenotype (n=412 54.07%) had severe abdominal cramps. Women in the “multiple severe symptoms” phenotype (n=148, 19.42%) had severe pain at multiple locations and multiple gastrointestinal symptoms. Race, ethnicity, age, and comorbid chronic pain conditions were significantly associated with phenotypes. Identification of these symptom-based phenotypes provides a foundation for research examining genotype-phenotype associations, etiologic mechanisms, and/or variability in treatment responses.