---
title: "Extracellular microRNAs in serum and EVs as candidate biomarkers for Chlamydia trachomatis reinfec"
id: "plos-one-15-evaluation-of-extracellular-micrornas-as-potential-biomarker-candidates-for"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-15-evaluation-of-extracellular-micrornas-as-potential-biomarker-candidates-for"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356267"
published_at: "2026-08-18T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Extracellular microRNAs in serum and EVs as candidate biomarkers for Chlamydia trachomatis reinfec
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-15-evaluation-of-extracellular-micrornas-as-potential-biomarker-candidates-for
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356267)
- **Published At:** 2026-08-18T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- This study evaluated **extracellular microRNAs (miRNAs)** from serum and serum-derived **extracellular vesicles (EVs)** as candidate biomarkers to predict risk of Chlamydia trachomatis reinfection in treated women. - Samples came from a previously described cohort of non-pregnant women presenting to a sexual health clinic after a positive C. trachomatis NAAT; enrollment spanned March 27, 2012 to October 11, 2018. - Participants received directly observed azithromycin 1 g at the baseline visit and were re-evaluated at a scheduled 3-month follow-up with repeat NAAT to determine reinfection status. - After exclusion for co-urogenital infections and hemolyzed samples, EV miRNAs were profiled from 53 serum EV samples (42 women) and whole-serum miRNAs from 49 samples (35 women); samples were categorized as RB, RF, NRB, or NRF based on baseline/follow-up infection status. - MiRNA profiling used Bruker nCounter microarrays, with positive ligation normalization; miRNAs were classified as detected versus not detected. Fisher’s exact test was used for nominal significance. Predicted mRNA targets were analyzed using Qiagen Ingenuity Pathway Analysis (IPA). - Key associations: detection of EV-derived **miR-888-5p** at baseline correlated with reinfection at 3 months. In whole serum, detection at baseline of **miR-1285-5p**, **miR-548aa + 548t-3p**, and **miR-575** correlated with absence of reinfection at follow-up. - IPA mapping suggested miR-888-5p aligned strongly with mRNA targets related to **CD8+ T-cell** functions, whereas miR-548aa aligned largely with **CD4+ T-cell** responses. - The authors emphasize these are preliminary findings requiring validation in independent cohorts; limitations include limited sample availability, stringent exclusions, and prioritized testing of EVs when volume was limiting. - Data from this study are available in GEO under accession GSE343618. - No commercially available miRNA biomarkers for C. trachomatis currently exist; these candidate miRNAs could inform future targeted testing strategies if validated.
## Clinical Analysis & Structured Key Points
Evaluation of extracellular microRNAs as potential biomarker candidates for assessing chlamydia reinfection risk | PLOS One Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Article Authors Metrics Comments Media Coverage Reader Comments Figures Figures Abstract Chlamydia trachomatis infection remains prevalent, with high rates of reinfection. Most infections are asymptomatic, and without treatment, women are at risk for reproductive and perinatal complications that are exacerbated with repeat infections. Currently, no C. trachomatis vaccine is available nor are there clinical biomarkers to predict reinfection risk. Small, non-coding microRNAs (miRNAs) are promising biomarker candidates because of their easy isolation, high stability, and role as molecular messengers. MiRNAs can be intracellular and/or extracellular, with the latter being released from cells and either packaged into extracellular vesicles (EVs) or freely circulating in association with proteins. We identified miRNAs from serum EVs and whole serum collected from 42 women (53 samples) and 35 women (49 samples), respectively. Sera were collected at a baseline treatment visit and a 3-month follow-up visit, where women were determined to be reinfected or not reinfected by nucleic acid amplification test. MiRNA profiles were evaluated using Bruker nCounter microarrays, data were positive ligation normalized, miRNAs were categorized as detected or not detected, nominal significance was calculated using Fisher’s exact test, and predicted target mRNAs were assessed with Qiagen’s Ingenuity Pathway Analysis (IPA). Detection of EV-derived miR-888-5p at baseline was associated with reinfection at the follow-up visit. For whole serum, detection of miR-1285-5p, −548aa + 548t-3p, and −575 at baseline were associated with absence of reinfection at follow-up. MiRs-888-5p and −548aa aligned with varying degrees to mRNA targets associated with CD8+ and CD4 + T-cell functions, with miR-888-5p demonstrating strong CD8 + T-cell associations while miR-548aa was largely associated with CD4 + T-cell responses. Distinct EV and whole serum miRNAs were identified as potential biomarker candidates that are associated with reinfection risk. Our findings are preliminary, and future work includes validation studies to confirm whether these miRNAs can predict C. trachomatis reinfection risk. Citation: Lewis CM, Gupta K, Wiener H, Tiwari HK, Geisler WM (2026) Evaluation of extracellular microRNAs as potential biomarker candidates for assessing chlamydia reinfection risk. PLoS One 21(8): e0356267. https://doi.org/10.1371/journal.pone.0356267 Editor: David M. Ojcius, University of the Pacific, UNITED STATES OF AMERICA Received: April 20, 2026; Accepted: August 2, 2026; Published: August 18, 2026 Copyright: © 2026 Lewis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All miRNA data from this study are available in the NCBI Gene Expression Omnibus (GEO) repository under accession number GSE343618 . Funding: This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (2R01AI093692 to WMG). Competing interests: W.M.G. reports receiving consulting fees or honoraria from Abbott, GSK, Merck, and LimmaTech, as well as research funding from Sanofi and Abbott. This does not alter our adherence to PLOS One policies on sharing data and materials. Introduction Chlamydia trachomatis causes the globally prevalent sexually transmitted infection, chlamydia [ 1 ]. Most infections are asymptomatic and if untreated, can potentially result in complications like pelvic inflammatory disease, infertility, chronic pelvic pain, and increased ectopic pregnancy risk [ 2 , 3 ]. In addition to high infection rates, reinfection is common within a year following treatment and exacerbates risk for reproductive complications [ 4 ]. In the absence of a C. trachomatis vaccine, improved clinical management strategies could help address these high infection and reinfection rates. One novel strategy to address this need is to utilize biomarkers to guide testing for repeat infections so that treatment can be provided before the onset of sequelae. Extracellular microRNAs (miRNAs) have emerged as promising biomarker candidates in infectious diseases [ 5 ]. These RNAs are small, non-coding posttranscriptional gene expression regulators that are specific for tissue or cell types, and their levels may vary with disease progression and response to therapy [ 6 ]. They can be present inside and/or outside a cell, the latter where they either circulate freely, are associated with proteins, or are packaged into membrane-bound extracellular vesicles (EVs) [ 7 ]. Extracellular miRNAs are ideal biomarkers because they are stable and easy to isolate from non-invasive bodily fluids like serum [ 6 , 8 ]. While EV isolation can be tedious, EVs offer protection from RNA degradation and are an enriched source of miRNAs compared to whole serum, which captures both EV-derived and free-floating miRNAs [ 9 ]. Although there are currently no commercially available miRNA biomarkers, findings from infectious disease research have been promising [ 5 ], especially with Mycobacterium tuberculosis tuberculosis, where serum miRNAs have been reported to distinguish latent versus active infection and predict risk for developing an active infection upon exposure [ 10 , 11 ]. With respect to chlamydia, there are limited murine and human miRNA studies [ 12 ]. Promising murine work has demonstrated miRNAs can predict pathology and exhibit dysregulation in different infection outcomes including reinfection [ 13 , 14 ]. Sparse human work includes one biomarker study conducted in patients with the chlamydia eye infection, trachoma, that found candidate miRNAs could not predict trachoma progression or scarring [ 15 – 17 ]. Additionally, two clinical genital chlamydia studies identified miRNAs associated with infection and reported distinct miRNA profiles between symptomatic and asymptomatic infections [ 18 , 19 ]. Thus far, no C. trachomatis human study has investigated miRNA biomarkers as predictors for reinfection risk; such biomarkers could be implemented in C. trachomatis testing strategies to improve the clinical management of chlamydia. To address this knowledge gap and determine whether miRNAs can be used to assess reinfection risk, we performed a comparative assessment of miRNA profiles from serum-derived EVs and whole serum in women treated for C. trachomatis infection who were then determined to have or not have reinfection at a 3-month follow-up visit. Materials and methods Cohort design and sample collection Serum EV derived miRNAs and whole serum miRNAs were evaluated in 42 and 35 women, respectively, from a previously described study cohort of non-pregnant women presenting to the Jefferson County Department of Health (JCDH) Sexual Health Clinic in Birmingham, Alabama, USA, for treatment of a recent positive C. trachomatis nucleic acid amplification test (NAAT) [ 20 , 21 ]. Women with prior hysterectomy or antibiotic use in the past 30 days were excluded. Women were enrolled in the cohort from the 27th of March 2012 till the 11th of October 2018. At the baseline treatment visit (time of enrollment), the following were obtained: clinical information by an interview, a vaginal swab for wet mount, an endocervical swab for C. trachomatis and Neisseria gonorrhea NAAT, and blood for serum isolation. All participants were given azithromycin 1g orally as directly observed treatment, which was a first-line Center for Disease Control and Prevention (CDC) recommended chlamydia treatment at the time of the original study [ 22 ]; expedited partner therapy was not offered as it was not part of the clinic’s standard practice at that time. Participants were scheduled for a 3-month follow-up visit for another interview and for repeat collection of the same specimens and testing as was done for the baseline visit. The follow-up interview also included a question on whether the participant had been sexually active since the last study visit. All participants provided written informed consent. The study was approved by the University of Alabama at Birmingham (UAB) Institutional Review Board (IRB) and JCDH. The IRB also approved participation of minors 16 years of age or older without parental consent. Sample selection for miRNA testing and categorization of analysis groups For this study, we excluded samples from miRNA testing consideration if the participant had a co-urogenital infection (gonorrhea, candidiasis, trichomoniasis, and/or bacterial vaginosis) or if there was red blood cell contamination in a serum sample, both of which could impact miRNA expression. Samples were categorized a priori into four groups for analysis purposes: (1) RB: baseline visit for those with reinfection at follow-up ( C. trachomatis NAAT positive at both baseline and follow-up visits), (2) RF: follow-up visit for those with reinfection at follow-up, (3) NRB: baseline visit for those without reinfection at follow-up ( C. trachomatis NAAT positive at baseline and C. trachomatis NAAT negative at follow-up), and (4) NRF: follow-up visit for those without reinfection at follow-up. Our primary analysis was the baseline comparison between NRB and RB, to identify potential miRNA biomarkers for further validation in additional cohorts. Secondary analyses included comparisons between (1) RB and RF to assess miRNA changes from baseline to follow-up, and (2) RF and NRF to determine differences in miRNA profiles at follow-up in women with and without C. trachomatis reinfection. Of 53 EV samples tested for miRNAs (collected from 42 women at baseline and/or follow-up), 24 were from the baseline visit (13 from NRB and 11 from RB) and 29 from the 3-month follow-up visit (19 from NRF and 10 from RF). For the 49 whole serum samples (collected from 35 women at baseline and/or follow-up), 26 were from baseline (14 from NRB and 12 from RB), and 23 from follow-up (15 from NRF and 8 from RF). For EV samples, 11 out of 53 were from the same women at both baseline and follow-up, while 14 of 49 whole serum samples were from the same women at baseline and follow-up. Limited sample availability, stringent sample exclusion criteria, and adequacy of miRNA yield for testing accounted for the difference in the number of samples tested for miRNA in EVs compared to whole serum and for baseline versus follow-up visits. When sample volume only allowed for miRNA testing in either EV or whole sera but not both, we prioritized EV over whole serum testing because EVs offer a more stable, specific source (vesicular-derived) for miRNAs [ 6 – 8 ]. EV and RNA isolation 1 mL of serum was spun at 2,000 g to pellet any debris, and EVs were isolated using Qiagen’s exoEasy Maxi Kit (Qiagen, Hilden, Germany). Following isolation, EVs were spun in Amicon Ultra-3 KDa cutoff columns (MilliporeSigma, Burlington, MA) to remove exoEasy kit buffers. EVs were suspended in phosphate-buffered saline, and the Norgen Exosomal RNA isolation kit (Norgen Biotek Corp., Ontario, Canada) was used to isolate total RNA. Isolated RNA was cleaned and concentrated to 20 ul using Amicon Ultra-3KDa cutoff columns. Whole serum RNA isolation Total RNA was isolated from 1 ml of serum using the Norgen Plasma/Serum Circulating and Exosomal RNA Purification Kit (Slurry Format) (Norgen Biotek Corp., Ontario, Canada). Isolated RNA was cleaned and concentrated to 20 ul using Amicon Ultra-3KDa cutoff columns. nCounter microarray Eppendorf vacufuge (Eppendorf, Hamburg, Germany) was used to further concentrate approximately 20 ul of isolated RNA to 6 ul for serum EV RNA and 9 ul for whole serum RNA. From the final concentrated volume, 3 ul was utilized for miRNA quantification using nCounter Human v3 miRNA panels (Bruker Corp., Massachusetts, USA) that include 798 human miRNAs. nCounter Digital Analyzer, MaxFlex, detected and counted miRNAs after sample hybridization for 21 hours with nCounter Prep Station in accordance with the manufacturer’s protocol [ 23 ]. Data processing and statistical analysis Raw data were uploaded to nSolver version 4.0 (Bruker Corp., Billerica, MA) for quality control (QC) to assess imaging, binding density, positive controls, limit of detection, and ligation. Following QC, data set was positive ligation normalized using nSolver version 4.0 (Bruker Corp., Massachusetts, USA). To determine the appropriate detection threshold, we looked at the greatest negative control count across both datasets [ 24 ], which was 44 counts. We then set our cut-off to counts and performed a receiver operating characteristic (ROC) curve analysis using positive ( ) and negative (<50) values, and the area under the curve (AUC) was 0.99, indicating almost perfect distinction between positive and negative groups. Youden’s index found 49 counts to be the optimal threshold for the EV dataset and 50 counts to be the optimal threshold for the WS dataset; therefore, our cut-off was set at for both EV and WS datasets to maximize sensitivity and specificity for differentiating positive from negative samples ( S1 File ) [ 25 ]. Differences in baseline participant characteristics and infection outcomes were assessed using Fisher’s exact or Wilcoxon rank-sum tests, as appropriate. Differences in the detection of specific miRNAs between the reinfection and no reinfection analysis groups were analyzed using Fisher’s exact test. Statistical correction for multiple comparisons was calculated using the Bonferroni correction ( ), but given the preliminary nature of this work, nominal p -values ( p < 0.05) are presented. All analyses were conducted using R version 4.5.0. Ingenuity pathway analysis Nominally significant baseline miRNAs and their corresponding P-values were uploaded into Qiagen’s Ingenuity Pathway Analysis (IPA) to predict their target mRNAs and identify associated biological functions. Ingenuity’s Knowledge Base served as the reference set, and the Functional Analysis tool identified biological functions and diseases most relevant to the input miRNA dataset. IPA nominal significance was calculated using right-tailed Fisher’s exact test to determine the probability of biological functions being assigned to respective mRNAs due to chance. Biological functions associated with CD4+ and CD8 + /cytotoxic T-cell responses were summarized due to their known importance in protective immunity against C. trachomatis [ 20 , 26 – 28 ] Unfiltered IPA biological function data is provided in full in the supplementary materials ( S2 - S4 Files ). Results Participant characteristics Samples tested for EV-derived miRNAs came from young women (median age = 22), in whom 98% reported African American race, none reported Hispanic ethnicity, 62% reported prior C. trachomatis infection, and 57% were asymptomatic ( S1 Table ). Similarly, samples tested for whole serum-derived miRNAs came from young women (median age = 22), in whom 97% reported African American race, 3% identified as Hispanic, 54% reported prior C. trachomatis infection, and 46% were asymptomatic ( S1 Table ). At the follow-up visit, most women reported being sexually active since the previous study visit. For EV and WS groups, all women with reinfection reported sexual activity, compared to 92% (1/13) of women without reinfection in the EV group and 86% (2/14) without reinfection in the WS group. For both EV and WS samples, baseline characteristics did not differ significantly between reinfection and no reinfection outcomes (all ) ( S5 File ). Differential detection of EV-derived miRNAs At the baseline visit, only one EV miRNA, miR-888-5p, had nominally significant differential detection ( p = 0.031) ( Table 1 and S1 Fig ). In the follow-up visit comparison, NRF versus RF, 26 miRNAs had nominally significant differences in detection frequency; the five most nominally significant were miRs-767-5p, −1286, −495-5p, -548g-3p, and -548q ( p = 0.009, 0.011, 0.030, 0.030, and 0.030, respectively), with all five having more frequent detection in RF ( Table 1 ). When comparing the reinfection groups across both visits, miRs-203a-5p, -30e-3p, and 495-5p were nominally significantly detected ( p = 0.035, 0.035, and 0.012, respectively) for RB versus RF, with detection only at follow-up ( Table 1 ). No associations were significant after applying the Bonferroni correction and no miRNAs had nominally significant differential detection in the no reinfection group across both visits (NRB versus NRF). Download: PNG larger image TIFF original image Table 1. Differential detection of extracellular vesicle-derived MicroRNAs (miRNAs) in relation to study visit and chlamydia reinfection status. https://doi.org/10.1371/journal.pone.0356267.t001 Differential detection of whole serum-derived miRNAs Nominally significant detection differences were observed for miRs-1285-5p, −548aa + 548t-3p, and −575 ( p = 0.045, 0.032, and 0.001, respectively) at the baseline visit in NRB versus RB, with more frequent detection in NRB ( Table 2 and S2 Fig ); miR-548aa + 548t-3p are two separate miRNAs that were detected by a single nCounter probe due to high sequence similarity. For NRF versus RF at the follow-up visit, miRs-1246, −1290, −191-5p, -320e, −4516, and −496 were nominally significant ( p = 0.009, 0.039, 0.027, 0.008, 0.039, and 0.026, respectively), with more frequent detection in NRF ( Table 2 ). Within the reinfection group, miR-1246 was more frequently detected in RB than RF ( p = 0.004), while miR-575 ( p = 0.014) was only detected in RF and not in RB ( Table 2 ). Similar to EVs, no associations were significant after applying the Bonferroni correction and no miRNAs had nominally significant differential detection in the no reinfection group across both visits. Download: PNG larger image TIFF original image Table 2. Differential detection of whole serum-derived MicroRNAs (miRNAs) in relation to study visit and chlamydia reinfection status. https://doi.org/10.1371/journal.pone.0356267.t002 Associated T-cell functions based on IPA IPA-predicted target mRNA biological functions were determined for miRs-888-5p, −1285-5p, and −548aa, which were exclusively detected in NRB versus RB samples, and thus potentially associated with reinfection risk ( S2 - S4 Files ). IPA predicted various biological functions across all datasets, including inflammation and responses involving T and B lymphocytes ( S2 - S4 Files ). IPA also identified several predicted target mRNA associations with both CD4+ and CD8 + T-cell functions. MiR-888-5p had more target mRNAs associated with CD8 + T-cell or cytotoxic functions ( Table 3 ). In contrast, miR-548aa was mainly associated with CD4 + T-cell functions, including Th1 and Th17 responses ( Table 3 ). Download: PNG larger image TIFF original image Table 3. Significant T-cell annotations for miR-888-5p and miR-548aa with corresponding target mRNAs determined by ingenuity pathway analysis. https://doi.org/10.1371/journal.pone.0356267.t003 Discussion This is the first study to profile human miRNAs in relation to C. trachomatis reinfection risk. Our main findings were from our primary analysis comparing the baseline visits in those who did or did not have reinfection at their follow-up visit. We found that detection of EV-derived miR-888-5p and whole serum miRs-1285-5p, −548aa + 548t-3p, and −575 at the baseline visit were nominally significantly associated with reinfection status at follow-up, suggesting these miRNAs should be further assessed for their potential as biomarkers for determining reinfection risk. Detection of miR-888-5p at baseline in some women with r
## Related Clinical Research

- [Tuberculosis screening and tuberculin skin test performance in adults with inborn errors of immuni](https://medichelpline.com/clinical-feed/frontiers-in-immunology-11-tuberculosis-screening-in-adult-patients-with-inborn-errors-of-immunity-a.md)
- [Genomic epidemiology and emerging antimicrobial resistance in Salmonella Paratyphi A from Australi](https://medichelpline.com/clinical-feed/medrxiv-13-genomic-epidemiology-and-emerging-antimicrobial-resistance-profiles-of.md)
- [Azithromycin versus doxycycline with beta-lactams for hospitalised community-acquired pneumonia: t](https://medichelpline.com/clinical-feed/bmj-open-4-azithromycin-versus-doxycycline-in-hospitalised-adult-patients-with-community.md)
- [In vitro activity of gepotidacin combinations against Neisseria gonorrhoeae isolates](https://medichelpline.com/clinical-feed/pubmed-42390436.md) (DOI: 10.1128/aac.00059-26)
- [Five-year biannual azithromycin MDA did not lower overall enteric fever seroincidence in Niger](https://medichelpline.com/clinical-feed/medrxiv-2-effect-of-five-years-of-biannual-azithromycin-mass-drug-administration-on.md)

## Navigation
- [← Back to Infectious Disease Feed](https://medichelpline.com/clinical-feed/infectious-disease.md)
- [← All Clinical Specialties](https://medichelpline.com/clinical-feed.md)
## Medical & Regulatory Disclaimer

> [!CAUTION]
> MedicHelpline content is structured for research, educational, and professional discovery purposes. It does not constitute individual medical advice, clinical diagnosis, or treatment recommendations.
> Always verify dosing, contraindications, and regulatory alerts against official product labeling and primary regulatory sources before clinical decision-making.