Browsing by Author "Trinh, Alan"

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    Clinical and Quality of Life Benefits for End-Stage Workers' Compensation Chronic Pain Claimants following H-Wave® Device Stimulation: A Retrospective Observational Study with Mean 2-Year Follow-Up
    (MDPI, 2023-02-01) Trinh, Alan; Williamson, Tyler K.; Han, David; Hazlewood, Jeffrey E.; Norwood, Stephen M.; Gupta, Ashim; Medicine, School of Medicine
    Previously promising short-term H-Wave® device stimulation (HWDS) outcomes prompted this retrospective cohort study of the longer-term effects on legacy workers’ compensation chronic pain claimants. A detailed chart-review of 157 consecutive claimants undergoing a 30-day HWDS trial (single pain management practice) from February 2018 to November 2019 compiled data on pain, restoration of function, quality of life (QoL), and polypharmacy reduction into a summary spreadsheet for an independent statistical analysis. Non-beneficial trials in 64 (40.8%) ended HWDS use, while 19 (12.1%) trial success charts lacked adequate data for assessing critical outcomes. Of the 74 final treatment study group charts, missing data points were removed for a statistical analysis. Pain chronicity was 7.8 years with 21.6 ± 12.2 months mean follow-up. Mean pain reduction was 35%, with 89% reporting functional improvement. Opioid consumption decreased in 48.8% of users and 41.5% completely stopped; polypharmacy decreased in 36.8% and 24.4% stopped. Zero adverse events were reported and those who still worked usually continued working. An overall positive experience occurred in 66.2% (p < 0.0001), while longer chronicity portended the risk of trial or treatment failure. Positive outcomes in reducing pain, opioid/polypharmacy, and anxiety/depression, while improving function/QoL, occurred in these challenging chronic pain injury claimants.
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    Method Development Involving Modeling Bacterial Metabolite Regulation of Vaginal Epithelial Cell Signaling in Bacterial Vaginosis
    (2022-04-28) Trinh, Alan; Brubaker, Douglas
    BACKGROUND Bacterial vaginosis, which is the imbalance of normal vaginal microbiota, contributes to preterm delivery, vaginitis, and decreased drug efficacy. Despite metronidazole efficacy in reducing BV contributing organisms, BV continues to recur in 50% of patients. Previous studies showing imidazole propionate’s role in the pathogenesis of type II diabetes suggest that similar metabolite-regulated pathways in vaginal microbiomes may be the key in pathogenesis of uterine diseases such as BV. Thus, the purpose of this study was to observe the relationship between vaginal metabolites, host or microbiome-derived, and transcriptomic responses in vaginal epithelial tissues stratified by vaginal microbiome composition (“microbiome group”). The hypothesis was that differences in vaginal microbiome composition result in differential regulation of metabolite-host pathway functional relationships. METHODS Transcript levels and metabolite concentrations precollected from 23 East African women were processed and analyzed via R. Transcriptomic data were converted into KEGG pathway enrichment scores via ssGSEA2.0, a package within R. Enrichment scores were correlated (Spearman) with metabolite levels by microbiome group and lactobacillus dominant phenotypes, and relationships were visualized via Heatmap3 and Cytoscape. RESULTS The results showed varying strengths in correlation among metabolites and KEGG pathway enrichment scores after filtering for strong correlations (R > |0.5|) and significance (p< 0.05). Nonlactobacillus dominant microbiomes showed fewer strongly associated metabolite-KEGG pathway relationships compared to the lactobacillus dominant microbiome group, specifically the imidazole-related networks. CONCLUSIONS In this study, variations in significant correlations among metabolites and KEGG pathways suggests that microbiome diversity may contribute to how metabolites regulate host pathways in vaginal epithelial cells. The reduced pathway interactions observed in imidazole compounds suggests that dysregulation may contribute to recurrence of bacterial vaginosis. This method of modelling could be used to characterize the regulation of critical pathways associated with the pathogenesis of bacterial vaginosis.
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    Systems Modeling of Gut Microbiome Regulation of Estrogen Receptor Beta Signaling in Ulcerative Colitis
    (2023-04-28) Trinh, Alan; Munoz, Javier; Cross, Tzu-Wen; Brubaker, Doug
    Introduction: The pathogenesis of ulcerative colitis (UC), a chronic inflammatory disorder, involves interactions between gut microbiome dysbiosis, epithelial cell barrier disruption, and immune hyperactivity. Men are 20% more likely to develop UC and 60% more likely to progress to colitis-associated cancer than women. A possible explanation for this may be the anti-inflammatory and epithelial-protective role of estrogen via estrogen receptor beta (ESR2) in the gut. However, extracting insights into how microbiomes regulate host cell signaling is challenged by high-dimensional data integrations across kingdoms and the need to extract interpretable biological information from complex models. To address these challenges and understand microbiome regulation of ESR2 signaling, we developed a partial least squares path modeling (PLS-PM)-inspired microbiome multi-omic modeling framework. Materials and Methods: Gut metabolomic, colorectal transcriptomic, and stool 16S rRNA-seq data from unique UC or non-IBD controls subjects (n=35) were obtained from the Inflammatory Bowel Disease Multi-Omics Database. Single sample gene set enrichment analysis was used to calculate pathway scores for genes up or down-regulated by ESR2 (ESR2UP/ESR2DN respectively).Latent variables (LV) obtained via regularized sparse partial least square regression (sPLSR) mdoels were extracted and used as predictors in two linear regression meta-models with dependent variables of ESR2UP or ESR2DN scores, and independent variables in each model consisting of patient LV scores on metabolites and 16S LVs along with sex and UC status. Significance testing on regression coefficients identified LV interactions synergistically predictive of ER Beta pathway activity. Results and Discussion: The first two LVs from each single-omic sPLSR models were extracted to create terms in the multi-omic meta-model accounting for sex and disease status. The meta-model was predictive of ESR2UP pathway score, implicating UC status (p=0.046), microbiota LV1 (p=0.0006), metabolites LV2 (p=0.045), and interactions of metabolite LV1:microbiota LV1 (p=0.003), microbiota LV1:UC (p=0.0008), and microbiota LV2:sex (p=0.019) in predicting ESR2UP pathway status. For ESR2DN, the 16S model clustered by ESR2DN activity while the metabolomic model clustering was best illustrated by disease status. The ESR2DN meta-model was predictive of ESR2DN pathway activity, implicating main effects of microbiota LV1 (p =0.004), metabolites LV2 (p=0.004), and diagnosis and the interaction effects of metabolites LV1:microbiota LV1 (p=0.005), microbiota LV1:UC (p=0.014), microbiota LV2:sex (p=0.017), and metabolites LV2:UC (p=0.035) in predicting ESR2DN pathway status. Acesulfame, an artificial sweetener, and oxymetazoline, a nasal decongestant, were some of the metabolites predicted by our model to have a differential effect on ESR2 activity based on patient sex. The metabolites predicted in our models are tested in cancer cell lines to understand estrogen regulatory effects on inflammation observed in UC. Method developed in this study can be applied to gain insight regarding regulation of signaling pathways in pathologies not limited to UC. Conclusions: We demonstrate the effectiveness of a PLS-PM based method for modeling relationships between host signaling and microbiome multi-omics data via this investigation of ER Beta activity in UC patients. We quantified significant multi-omic microbiome interactions with disease status and sex that impact ER Beta signaling which may aid in identifying new microbiome-targeted UC therapeutics stratified by sex-specific disease characteristics.