{"paper_id":"21c935b3-ebbf-4a97-bd5e-07fe638b1fbb","body_text":"Dicer-independent miR-451a is Upregulated in Periodontitis and Potentiates Inflammation by Impairing Macrophage Polarization and SOCS Activity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dicer-independent miR-451a is Upregulated in Periodontitis and Potentiates Inflammation by Impairing Macrophage Polarization and SOCS Activity Raza Ali Naqvi, Jack Maddalozzo, Kreena Amin, Kristelle Capistrano, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9361339/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Periodontitis is characterized by localized inflammatory tissue destruction, yet the lesion-specific microRNA networks that shape host immune responses remain incompletely defined. Using a split-mouth design, we profiled miRNA expression in gingival biopsies obtained from periodontal lesions and clinically healthy sites within the same individuals to identify disease-associated regulatory signatures. Microarray analysis revealed 48 differentially expressed miRNAs, including several upregulated non-canonical species, and selected candidates were validated by RT-qPCR. Among these, the Dicer-independent miRNAs miR-451a and miR-1228 showed dose- and time-dependent induction in response to periodontal bacterial challenge. Functional studies demonstrated that miR-451a, but not miR-1228, promoted a pro-inflammatory M1-like macrophage phenotype, characterized by increased HLA-DR and CD32 expression and reduced CD206 and CD163. Consistent with this, miR-451a directly targeted multiple genes associated with M2 polarization, and its expression in inflamed gingival tissues inversely correlated with M2 marker expression. Moreover, miR-451a overexpression impaired bacterial phagocytosis and enhanced inflammatory cytokine production. Mechanistically, miR-451a suppressed SOCS3 and SOCS5, key negative regulators of JAK/STAT signaling, in TLR4-stimulated cells. Collectively, these findings identify miR-451a as a pathogen-responsive, periodontitis-associated miRNA that reprograms macrophage polarization, weakens antibacterial defense, and amplifies inflammation through suppression of SOCS-mediated immune regulation. Periodontal disease split-mouth macrophage noncanonical microRNAs polarization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Periodontal diseases (PD) are inflammatory conditions of tooth-supporting tissues initiated by microbial dysbiosis and sustained by an overt host immune-inflammatory response. 1 – 3 Accumulating evidence, including work from our laboratory, shows that recruitment and persistence of pro-inflammatory immune cells in gingiva are closely linked to disease onset and progression. Diseased gingiva consistently contains more myeloid cells, T and B cells than healthy tissue, 4–6 along with increased production of immunoglobulins, cytokines, and other inflammatory mediators. 7 Macrophages (Mφ) are key myeloid cells in oral mucosa and are actively recruited to periodontal lesions during disease progression. Their role in PD pathogenesis and resolution are well established. 6 , 8 , 9 Early in disease, Mφ sense microbial challenge through PRRs, including TLR2 and TLR4, and help activate adaptive immunity for pathogen clearance. 10 , 11 In PD, Mφ exist along a continuum from pro-inflammatory M1 to pro-reparative M2 states. Studies from our group and others show that diseased patients display an increased M1/M2 ratio that declines after non-surgical periodontal therapy, 6,12,13 supporting their role in both inflammation and resolution. Persistent M1-like activation promotes pro-inflammatory cytokine release and metalloproteinase activity, driving collagen destruction and alveolar bone loss. 14 In contrast, M2 Mφ produce anti-inflammatory mediators such as IL-10 and TGF-β, suppress osteolysis, and promote tissue repair. 15 , 16 In murine periodontal tissues, adoptive transfer of M2 Mφ increased Treg abundance and reduced osteoclast activity, a central mediator of alveolar bone loss. 17 Together, these findings underscore the importance of identifying molecular regulators of Mφ polarization. MicroRNAs (miRNAs) are approximately 22-nucleotide non-coding RNAs that regulate gene expression post-transcriptionally. 18 – 20 In the canonical pathway, primary miRNAs are transcribed, processed, and exported into the cytoplasm where they are cleaved by Dicer to generate a mature duplex. Some miRNAs are generated through non-canonical pathways, including mirtrons, Dicer-independent miRNAs, and species derived from tRNAs or snoRNAs. A well-known example is miR-451a, which bypasses Dicer and is processed directly through AGO2 after DROSHA-DGCR8 cleavage and nuclear export. 21 , 22 Regardless of biogenesis route, mature miRNAs regulate target transcripts through the same core AGO/RISC-mediated mechanisms. Although the role of miRNAs in immune disorders is increasingly recognized, their regulatory and therapeutic functions in periodontal inflammation remain unclear. Our group and other reports have demonstrated differential miRNA expressions in inflamed gingiva and tooth pulps. 25 – 28 Moreover, the functional roles and mechanistic impact of non-canonical miRNAs in PD have never been investigated. This study functionally evaluates the role of non-canonical miRNAs miR-451 and miR-1228 and their impact on Mφ polarization, a key event in PD pathogenesis, and further unravels novel molecular mechanisms regulating expression of anti-inflammatory molecules associated immune activity. 2. Materials and Methods 2.1 Study population and sample collection This study protocol was approved by the institutional review board of the University of North Carolina at Chapel Hill (#13-1279). Systemically healthy adults aged 18–70 years who presented to the Postgraduate Periodontics Clinic, Adams School of Dentistry, UNC Chapel Hill, between March 2013 and May 2015 were recruited. Participants were excluded if they had uncontrolled systemic conditions (e.g., hypertension, heart disease, bleeding disorders), were pregnant, had diabetes, or were current smokers. Periodontally healthy sites had probing depths (PPD) ≤ 3 mm, no bleeding on probing, no clinical attachment loss (CAL), no radiographic alveolar bone loss, and ≥ 4 mm of attached keratinized gingiva. Periodontally diseased sites met criteria for stage III, grade B disease, including ≥ 4 teeth with PPD ≥ 6 mm, CAL ≥ 5 mm, and radiographic bone loss extending to the middle third of the root and beyond, with ≥ 4 mm attached keratinized gingiva, as previously described. 28 , 29 Table 1 combines demographic and clinical data of the cohort. Table 1 Subject demographics and clinical parameters. *Paired t-test Age (mean ± SD) (years) 56.78 ± 11.28 Gender (M/F) 5/4 Clinical site variables Periodontitis site (n = 9) Non-periodontitis site (n = 9) p-value* PPD (mean ± SD) (mm) 7.33 ± 1.85 2.56 ± 0.73 < 0.001 CAL (mean ± SD) (mm) 6.67 ± 1.80 2.33 ± 0.87 < 0.001 Participants with PD had 1–2 mm² of gingiva removed from the tooth with the deepest probing site when undergoing surgical treatment. Additionally, a second sample of identical size was collected from a clinically healthy site elsewhere in the oral cavity during the same surgical intervention. The harvested tissue samples were placed in sterile round bottom polypropylene tubes and immediately immersed in 1.0 mL RNAlater (Applied Biosystems/Ambion, Austin, TX, USA) solution and incubated at 4℃ for at least 24 hours. The processed samples were then transferred to a -80℃ freezer for long-term storage. 2.2 MicroRNA microarray profiling Tissue samples were lysed using the TissueLyzer (Qiagen, Germantown, MD, USA) and total RNA isolated using the miRNeasy (Qiagen) kit as we previously reported. 29 , 30 The microarray assay was performed using a service provider (LC Sciences; Houston, TX, USA) and detailed in Supplemental Materials and Methods. 2.3 Total RNA isolation and quantitative RT-PCR Total RNA was isolated using the miRNeasy kit (Qiagen). For mature miRNA quantification, miScript primers and miScript II RT Kit were purchased from Qiagen (details in Supplemental Materials and Methods). 2.4 Transient miRNA transfection Transient transfections were carried out using Lipofectamine 2000 reagent (Life Technologies, San Diego, CA, USA) following manufacturer instructions (details in Supplemental Materials and Methods). 2.5 Primary human macrophage differentiation and challenge with periodontal bacteria Monocytes were isolated from freshly prepared buffy coats collected from healthy donors (n ≥ 4, Sylvan N. Goldman Oklahoma Blood Institute, Oklahoma City, OK, USA) by density gradient centrifugation and CD14 + cells were sorted by magnetic bead sorting as previously described. 31 – 33 For Mφ differentiation, monocytes were plated at 2 × 10 6 /ml in DMEM supplemented with penicillin (100 U/ml) and streptomycin (100 µg/ml). After 2 h the media was substituted with media containing 10% FBS (Life Technologies, Carlsbad, CA, USA), and rhM-CSF (50 ng/mL; Peprotech, Rocky Hill, NJ, USA). Cells were challenged with live Aggregatibacter actinomycetemcomitans ( Aa , strain Y4, serotype B) or Porphyromonas gingivalis ( Pg , strain W83) at 100 MOI. 2.6 Flow cytometry and TLR stimulation Cells were stained for different antibodies and analyzed using BD Accuri C6 flow cytometer as described before 32 , 33 and detailed in Supplemental Materials and Methods. Cells were treated with TLR4 ( E. coli LPS, 50 ng/ml) stimulation and flow cytometry was performed as described previously. 33 2.7 Phagocytosis assays Cells transfected with miRNA or control mimics were assayed for phagocytosis using rhodamine labelled E. coli as described before 32 and detailed in Supplemental Materials and Methods. 2.8 Cell viability assay Cell viability was determined by use of the CellTiter 96 AQueous Cell Proliferation Assay Kit (Promega). In brief, Mφ were plated at 400,000/well in 96-well plates and transfected as described above and assays performed after 36 h, according to the manufacturer's instructions. 6 2.9 Bioinformatic target prediction, cloning of gene 3' UTRs, and dual luciferase assays Gene targets were identified using miRWalk ( http://mirwalk.umm.uni-heidelberg.de/ ). For miRNA pathway analysis, DIANA tool mirPath v.3 ( https://dianalab.e-ce.uth.gr/html/mirpathv3 ) was used to identify significantly overrepresented pathways and functional categories. Cloning of predicted gene 3′ untranslated region (UTR) and dual luciferase assays were performed as previously described 31 , 34 and detailed in Supplemental Materials and Methods. 2.10 Cytokine analysis Supernatants were collected from miR-451a or control mimic transfected Mφ challenged with E. coli at 4 and 24 h. Multiplex analysis of four different cytokines (IL-1β, IL-6, IL-8 and TNF-α) was performed using Milliplex (Millipore, Billerica, MA, USA). Data was collected on Bio-Plex flow cytometer (Bio-Rad, Hercules, CA, USA) for analysis. 2.11 Statistical analysis Data was analyzed on Prism software (GraphPad, LaJolla, CA, USA). The results are represented as mean ± SEM of 3–5 independent replicates and experiments were conducted at least three times. p-Values were calculated using Student’s t-test or ANOVA, and p < 0.05 were considered significant. 3. Results 3.1 Gingival microRNA profiles reveal site-specific molecular changes drive periodontal disease The cohort included adults with a mean age of 56.78 ± 11.28, including 5 males and 4 females. Using a split-mouth design, we collected one gingival tissue biopsy from a periodontally diseased and non-diseased site (n = 9 per site type) from each subject. Diseased sites had greater PPD (7.33 ± 1.85 mm) than non-diseased sites (2.56 ± 0.73 mm, p < 0.001) (Table 1 ). CAL was also higher at diseased sites (6.67 ± 1.80 mm) than at non-diseased sites (2.33 ± 0.87 mm, p < 0.001), confirming clear separation between PD and non-diseased sites. Microarray profiling identified 48 differentially expressed miRNAs between inflamed and healthy gingiva, showing clear site-specific dysregulation. Heatmap analysis demonstrated distinct clusters of upregulated and downregulated miRNAs that separated diseased from healthy sites (Fig. 1 A). Overall, 32 miRNAs were upregulated and 16 were downregulated in inflamed gingiva. The most upregulated included miR-191a-3p, miR-150-5p, miR-451a, miR-4646-3p, miR-6851-3p, and miR-202-5p, whereas miR-23a/b, miR-27a/b, miR-224, miR-1275, and miR-1233 were among the most downregulated (Table 2 ). Table 2 Differentially expressed miRNAs in periodontally healthy and diseased gingival biopsies. Mean signal intensity, fold change, and p-values (significance threshold p < 0.05) are shown for miRNAs significantly dysregulated between healthy and inflamed gingiva. miRNAs are ordered by ascending p-value. miRNA Healthy (Mean Intensity) Disease (Mean Intensity) P-value Fold Change hsa-miR-200c-3p 752 252 1.53E-05 0.34 hsa-miR-200b-3p 475 177 1.03E-04 0.37 hsa-miR-23b-3p 3,648 2,015 1.44E-04 0.55 hsa-miR-23a-3p 4,033 2,491 3.58E-04 0.62 hsa-miR-199a-3p 661 1,716 3.73E-04 2.60 hsa-miR-203a-3p 2,899 434 4.83E-04 0.15 hsa-miR-27b-3p 720 363 8.47E-04 0.50 hsa-miR-143-3p 202 424 4.01E-03 2.10 hsa-miR-199a-5p 320 816 4.60E-03 2.55 hsa-miR-451a 4,284 11,244 5.88E-03 2.62 hsa-miR-27a-3p 1,127 647 6.02E-03 0.57 hsa-miR-29a-3p 619 1,165 8.55E-03 1.88 hsa-miR-145-5p 371 703 1.06E-02 1.90 hsa-miR-29c-3p 243 625 1.11E-02 2.58 hsa-miR-150-5p 193 347 1.13E-02 1.79 hsa-miR-3178 248 102 1.16E-02 0.41 hsa-miR-7977 326 175 1.48E-02 0.54 hsa-miR-1233-5p 225 23 1.75E-02 0.10 hsa-miR-29b-3p 315 768 1.81E-02 2.44 hsa-let-7i-5p 419 748 3.27E-02 1.79 hsa-miR-21-5p 3,431 5,245 4.76E-02 1.53 hsa-miR-148a-3p 362 808 5.49E-02 2.23 hsa-miR-140-3p 217 337 7.14E-02 1.55 hsa-miR-1246 257 342 7.92E-02 1.33 hsa-miR-223-3p 113 478 8.15E-02 4.25 hsa-miR-4530 168 266 8.33E-02 1.59 hsa-miR-205-5p 3,294 1,273 8.49E-02 0.39 hsa-miR-455-3p 50 91 6.29E-04 1.83 hsa-miR-3065-3p 1 10 9.02E-04 19.57 hsa-miR-224-5p 68 28 2.69E-03 0.41 hsa-miR-4301 108 290 5.46E-03 2.68 hsa-miR-708-5p 73 37 5.75E-03 0.51 hsa-miR-4800-3p 14 43 1.00E-02 3.04 hsa-miR-210-3p 19 8 1.13E-02 0.42 hsa-miR-185-5p 24 54 1.15E-02 2.22 hsa-miR-6775-5p 14 47 1.21E-02 3.32 hsa-miR-200a-3p 157 73 1.37E-02 0.47 hsa-miR-1275 138 57 1.42E-02 0.41 hsa-miR-483-5p 18 38 1.62E-02 2.11 hsa-miR-7851-3p 11 49 1.66E-02 4.58 hsa-miR-34a-5p 33 61 1.66E-02 1.84 hsa-miR-92a-3p 263 170 1.76E-02 0.65 hsa-miR-1237-5p 20 38 1.89E-02 1.95 hsa-miR-374c-5p 32 68 2.22E-02 2.12 hsa-miR-145-3p 9 47 2.43E-02 5.02 hsa-miR-144-5p 14 42 2.49E-02 2.90 hsa-miR-650 9 45 2.51E-02 4.86 hsa-miR-6769b-5p 13 24 2.56E-02 1.91 hsa-miR-4687-3p 56 124 2.70E-02 2.23 hsa-miR-6731-5p 3 9 3.52E-02 3.12 hsa-miR-382-5p 6 18 4.40E-02 3.33 hsa-miR-4646-3p 6 17 4.45E-02 2.85 hsa-miR-6730-5p 7 20 4.78E-02 2.74 hsa-miR-619-5p 19 52 4.95E-02 2.69 Several non-canonical miRNAs were also elevated in inflamed gingiva, including miR-451a (2.6-fold), miR-1228 (1.3-fold), miR-142-5p (2.3-fold), miR-28-3p (1.8-fold), miR-28-5p (2.2-fold), miR-484 (1.3-fold), and miR-320-5p (2.6-fold) (Fig. 1 B). Their average signal intensities also trended higher in inflamed tissue (Fig. 1 C-I). RT-qPCR validation confirmed significantly increased miR-451a (~ 8-fold) and miR-1228 (~ 2-fold) expression in inflamed biopsies relative to clinically healthy controls (Fig. 1 J, K). Together, these results show that Dicer-independent miRNAs display a distinct expression pattern in inflamed gingiva, supporting a role for site-specific miRNA dysregulation in periodontal pathogenesis. 3.2 miR-451a and miR-1228 is responsive to periodontal bacteria Periodontal pathogens modulate innate immune programs in Mφ, including dysregulation of noncoding RNA expression that can rapidly shape inflammatory outputs and resolution. To examine if expression of non-canonical, Dicer-indepedent miRNAs miR-451a and miR-1228 are responsive to periodontal bacteria, we quantified their expression in M1 and M2 Mφ challenged with 100 MOI live Pg and Aa at 24 and 48 h. miR-451a in M1 Mφ exhibited a time-dependent induction across both bacterial challenges, increasing at 24 h ( Pg : 4.98 ± 0.58 fold; Aa : 3.42 ± 0.40 fold) and further at 48 h ( Pg : 7.4 ± 0.45 fold; Aa : 5.0 ± 0.21) (Fig. 1 L, M). In contrast, miR-1228 expression in M1 Mφ showed no appreciable change at 24 h ( Pg : 1.05 ± 0.06 fold; Aa : 0.97 ± 0.02 fold) but was elevated at 48 h ( Pg : 2.31 ± 0.20 fold; Aa : 1.83 ± 0.30 fold) (Fig. 1 N, O). These results indicate that miR-451a is induced rapidly and remains persistently elevated, whereas miR-1228 shows a delayed induction pattern. Together, the data suggests that non-canonical miRNAs are responsive to periodontal pathogens. 3.3 miR-451a regulates macrophage polarization by skewing a shift towards M1 phenotype Macrophages are central to both the persistence and resolution of gingival inflammation, coordinating pro-inflammatory and reparative responses. 6 , 35 To identify endogenous regulators of Mφ polarization, we examined the effects of the Dicer-independent miRNAs miR-451a and miR-1228. These candidates were selected based on high expression, significant differential regulation, and predicted targeting of immune and inflammatory pathways (Supplementary file 2). Primary CD14 + monocytes were transfected on day 3 of differentiation with miR-451a, miR-1228, control mimics, or inhibitors, and M1/M2 surface markers analyzed by flow cytometry after 72 h. miR-451a overexpression, but not miR-1228, promoted M1 polarization while suppressing M2-like features (Fig. 2 A,D). Compared with control mimic, miR-451a increased the percentage of HLA-DR+ cells from 80.5 ± 3.15% to 91.3 ± 4.38% and CD32 + cells from 63.6 ± 4.62% to 79.2 ± 4.10% (Fig. 2 B). In contrast, CD163 + cells decreased from 71.1 ± 2.38% to 36.4 ± 2.95%, and CD206 + cells from 67.1 ± 7.23% to 56.9 ± 3.44% (Fig. 2 E). Normalized geometric mean fluorescence intensity showed similar changes, with increased HLA-DR (119.5 ± 6.36%) and CD32 (117.6 ± 2.25%) and reduced CD206 (70.3 ± 5.45%) and CD163 (81.4 ± 2.93%) (Fig. 2 C,F). Overall, these results indicate that miR-451 enhances Mφ pro-inflammatory polarization through upregulation of M1-associated surface markers. 3.4 miR-451a directly binds to the 3' UTR and suppresses multiple M2 marker genes To determine whether miR-451a regulates M2-associated markers, we screened the 3′UTRs of MRC1, FN1, TGFB2, and TGFBR1 using RNA hybrid analysis. Putative miR-451a binding sites were identified in all four genes and cloned into reporter plasmids. A schematic of the dual-luciferase assay is shown in Fig. 3 A, and sequence alignments with the 3′UTRs of MRC1/CD206, FN1, TGFB2, and TGFBR1 are presented in Fig. 3 B-E (upper panels). To validate these sites, HEK293 cells were co-transfected with psiCHECK2 alone or psiCHECK2 containing the cloned 3′UTRs together with miR-451a or control mimics. Compared with control mimic, miR-451a significantly reduced Renilla luciferase activity for MRC1, TGFB2, TGFBR1, and FN1 3′UTR constructs by ~ 30–50% (p < 0.05) (Fig. 3 B-E, lower panels), identifying these genes as novel miR-451a targets linked to the M2 phenotype. Consistent with these findings, gingival tissues from inflamed sites showed reduced MRC1 (0.68 ± 0.12 fold), FN1 (0.47 ± 0.07 fold), TGFBR1 (0.77 ± 0.09 fold), and TGFB2 (0.65 ± 0.12 fold) expression versus healthy controls (Fig. 3 F-I). Together, these data support a model in which miR-451a suppresses M2-associated genes, limiting pro-resolving Mφ function in PD. 3.5 miR-451a overexpression in macrophages attenuates bacterial phagocytosis Macrophage phagocytosis of microbes and apoptotic cells is essential for periodontal tissue defense and homeostasis. 36,37 To examine the role of miR-451a in Mφ function, M1 Mφ were transiently transfected with miR-451a mimic, control mimic, or inhibitor, and phagocytosis measured using rhodamine-labeled E. coli bioparticles. Fluorescence microscopy showed reduced E. coli uptake in miR-451a mimic-transfected cells compared with control mimic or inhibitor-treated cells (Fig. 4 A). Flow cytometry confirmed this result, with E. coli uptake decreasing from 83.6 ± 5.15% in controls to 60.9 ± 5.5% in miR-451a-transfected cells (Fig. 4 B, C). In contrast, miR-451a inhibitor-transfected cells showed uptake similar to controls (83.6 ± 3.2%) (Fig. 4 C). Geometric mean fluorescence intensity of phrodo+ cells also fell to 70.8 ± 3.89% (P < 0.0005) with miR-451a and increased to 117.0 ± 5.38% with inhibitor (Fig. 4 D). These findings indicate that miR-451a suppresses Mφ phagocytosis. 3. 6 miR-451 potentiates inflammation by suppressing SOCS-mediated feedback regulation To determine whether miR-451a modulates inflammatory responses, Mφ were transfected with miR-451a mimic or control mimic and challenged with periodontal pathogens. Overexpression of miR-451a significantly enhanced pathogen-induced cytokine production. In response to Pg , miR-451a increased supernatant levels of IL-1β (2760.42 ± 257.30 vs 1711.36 ± 427.59 pg/mL), TNF-α (3632.52 ± 311.43 vs 2590.19 ± 326.47 pg/mL), IL-6 (2996.59 ± 752.69 vs 1800.22 ± 351.83 pg/mL), and CXCL8 (11735.52 ± 1733.31 vs 8361.21 ± 1351.42 pg/mL) relative to control mimic (Fig. 5 A-D). Similar effects were observed with Aa challenge, where miR-451a increased IL-1β (2505.08 ± 535.64 vs 1698.23 ± 328.40 pg/mL), TNF-α (3522.65 ± 680.64 vs 2537.30 ± 428.55 pg/mL), IL-6 (2700.33 ± 622.40 vs 1961.17 ± 472.09 pg/mL), and CXCL8 (8504.17 ± 1393.25 vs 6020.96 ± 282.33 pg/mL) (Fig. 5 A-D). These findings indicate that miR-451a amplifies pathogen-induced pro-inflammatory cytokine production. Pathway analysis identified immune signaling pathways as major miR-451a targets (Supplementary file 2). Because TLR signaling converges on the JAK-STAT pathway and SOCS proteins serve as key negative regulators, we examined the SOCS family for predicted miR-451a binding sites. 38 , 39 SOCS3 contained one predicted site at 1854–1872, SOCS5 contained two predicted sites at 3282–3300 and 3302–3324, and SOCS6 contained two predicted sites at 2326–2343 and 2422–2439 (Supplementary files 3–9). No predicted binding sites were identified in the remaining SOCS genes. Figure 5 E summarizes the anti-inflammatory role of SOCS proteins in JAK-STAT signaling and the predicted miR-451a target sites in SOCS3, SOCS5, and SOCS6. To validate these predictions, Mφ were transfected with miR-451a or control mimic and then stimulated with TLR4 agonists. SOCS expression was measured by flow cytometry. miR-451a significantly reduced the proportions of SOCS3-positive and SOCS5-positive Mφ compared with controls (Fig. 5 F,G), while SOCS6 showed a modest but non-significant decrease (Fig. 5 H). After TLR4 stimulation, the percentage of SOCS3-positive Mφ was lower in miR-451a-transfected cells than in controls (12.4 ± 1.7% vs. 33.02 ± 4.7%, p < 0.0001; Fig. 5 F). A similar reduction was observed for SOCS5-positive Mφ (10.4 ± 4.2% vs. 28.1 ± 5.2%; Fig. 5 G). In contrast, SOCS6 expression was not significantly altered (10.3 ± 1.02% vs. 11.3 ± 2.9%; Fig. 5 H). As expected, TLR4 stimulation induced SOCS expression under control conditions. Together, these results show that miR-451a selectively suppresses SOCS3 and SOCS5 after TLR4 activation, supporting a role for miR-451a in limiting SOCS-mediated negative feedback within the JAK-STAT inflammatory pathway. 4. Discussion Large-scale transcriptomic and miRNA profiling increasingly implicate post-transcriptional regulation in periodontal pathogenesis, 40 but the contribution of non-canonical miRNAs remains poorly understood. In this study, we identify Dicer-independent miRNAs as potential regulators of periodontal immunity and tissue remodeling. Multiple non-canonical miRNAs, including miR-451a, miR-1228, miR-142-5p, miR-28-3p/5p, and miR-484, were markedly upregulated in inflamed gingiva, indicating that alternative miRNA maturation pathways are selectively engaged during disease. To our knowledge, this is the first evidence that non-canonical miRNAs are altered in PD and can polarize Mφ function. Similar stress-adaptive reprogramming of small RNA biogenesis has been reported in other inflamed tissues and may reflect the effects of microbial products, hypoxia, or inflammatory cytokines on miRNA processing. 41 , 42 Non-canonical miRNA dysregulation is also documented in other inflammatory diseases. For example, miR-451a is elevated in Systemic Lupus Erythematosus, Hashimoto thyroiditis, rheumatoid arthritis, sepsis, and Gram-positive bacterial infection, supporting its broader association with inflammatory activation. 43 – 46 Our findings suggest that bacterial virulence factors and oxidative stress in PD may similarly induce miR-451a and related non-canonical miRNAs. tissues. Macrophages accumulate in periodontal lesions and acquire M1-like transcriptional features that enhance cytokine production and bone-resorptive pathways. 49 , 50 Our earlier work linked miRNA dysregulation to oral mucosal immunity, including Mφ polarization and PD-associated noncoding RNA networks. 6 , 28 , 29 The present study extends those observations by identifying a non-canonical regulatory axis centered on miR-451a. We show that miR-451a is elevated in PD, correlates with M1 marker induction, and suppresses M2-associated markers in inflamed gingiva. Overexpression of miR-451a increased M1-associated markers HLA-DR and CD32, while reducing the M2-associated markers CD206 and CD163. This combined enhancement of M1 traits and repression of M2 features suggests that miR-451a polarizes Mφ toward a more inflammatory phenotype while limiting reparative programs. Mechanistically, miR-451a directly targeted several genes associated with M2 polarization and tissue repair. Dual-luciferase assays confirmed MRC1, FN1, TGFB2, and TGFBR1 as direct miR-451a targets. These genes are integral to Mφ alternative activation, matrix remodeling, and TGF-β signaling, all of which are important for resolution of inflammation and tissue repair. Consistent with these findings, expression of MRC1, FN1, TGFB2, and TGFBR1 was reduced in inflamed gingival tissues compared with healthy controls. These data support a model in which elevated miR-451a suppresses pro-resolving pathways in periodontal lesions, thereby sustaining inflammation and impairing its resolution. Efficient phagocytosis is essential for microbial clearance and removal of apoptotic cells in periodontal tissues. 37 , 38 We found that miR-451a overexpression significantly reduced uptake of labeled E. coli bioparticles, whereas inhibition of miR-451a had little effect. This indicates that increased miR-451a is sufficient to impair Mφ phagocytic capacity. In PD, such impairment could reduce bacterial clearance, prolong microbial persistence, and further amplify inflammatory signaling. Thus, miR-451a may contribute not only to inflammatory skewing but also to defective innate immune function. Supporting this, we demonstrate that miR-451a is responsive to periodontal pathogens and amplifies inflammatory cytokine production. Exposure of Mφ to Pg and Aa induced miR-451a expression indicating it is pathogen responsive. Functionally, miR-451a overexpression enhanced production of IL-1β, TNF-α, IL-6, and CXCL8. This allows miR-451a to augment feed-forward inflammatory loops in which microbial challenge induces miR-451a, which in turn amplifies Mφ inflammatory output. Such a mechanism could be relevant in PD, where ongoing bacterial stimulation sustains local immune activation and tissue injury. To understand how miR-451a enhances inflammatory signaling, we examined its impact on the SOCS family, a key negative feedback system in cytokine and TLR signaling. Bioinformatic analysis identified predicted miR-451a binding sites in SOCS3, SOCS5, and SOCS6, and functional studies showed that miR-451a selectively reduced SOCS3 and SOCS5, but not SOCS6 expression after TLR4 stimulation. Because SOCS proteins restrain JAK-STAT and related inflammatory pathways, repression of SOCS3 and SOCS5 would be expected to prolong or intensify inflammatory signaling. Indeed, this mechanism is consistent with the observed increase in pathogen-induced cytokine production and suggests that miR-451a weakens endogenous anti-inflammatory checkpoints. Thus, miR-451a may act as pro-inflammatory miRNA driving inflammation by suppressing inhibitory pathways. For example, miR-155 promotes Mφ activation by targeting SOCS1 and SHIP1, contributing to inflammatory disorders including PD, rheumatoid arthritis, inflammatory bowel disease, and sepsis. 51 – 54 miR-21 enhances inflammatory signaling by targeting PDCD4, whereas miR-34a promotes obesity-associated inflammation by repressing Klf4. 55 , 56 Likewise, miR-30b and miR-181d aggravate myocardial inflammation through repression of SOCS3, relieving negative regulation of cytokine signaling. 57 Our findings suggest that miR-451a acts in a comparable way in PD. Specifically, miR-451a appears to promote gingival inflammation through two complementary mechanisms: suppression of M2-associated reparative programs and removal of SOCS-dependent inhibitory control over inflammatory signaling. Several limitations should be noted. The sample size was relatively small, which may limit statistical power and generalizability. Although the split-mouth design reduced inter-individual variability, it may not fully account for site-specific heterogeneity. In addition, most mechanistic experiments were conducted in vitro and may not capture the full complexity of the in vivo periodontal immune microenvironment. Validation in larger clinical cohorts and animal models are required. In summary, this study identifies a distinct miRNA landscape in diseased gingiva enriched for Dicer-independent and other non-canonical species, with miR-451a emerging as a central regulator. Periodontal pathogen-responsive miR-451a promotes M1Mφ polarization, suppresses M2-associated genes, reduces bacterial phagocytosis, and enhances inflammatory signaling through suppression of SOCS3 and SOCS5. These findings support miR-451a as both a potential biomarker and a therapeutic target in PD, with possible relevance for host-response modulation, microbial clearance, and tissue repair. Declarations Ethics approval statement The study protocol involving human participants was reviewed and approved by the Institutional Review Board of the University of Illinois Chicago and The University of North Carolina at Chapel Hill Adams School of Dentistry and was conducted in accordance with the Declaration of Helsinki and institutional guidelines. Patient consent statement Written informed consent was obtained from all participants prior to study enrollment and sample collection. Author Contributions All authors have made substantial contributions to conception, design of the study and given final approval of the version to be published. AM, SZ and SN were calibrated and performed clinical data measurements, as well as obtained biomaterials from the patients. RAN, JM, KA, AM, SZ, SN, MP, AV and ARN were involved in data collection and data analysis. RAN, JM, KA, KC, AV, SZ, SN and ARN were involved in data interpretation, and drafting the manuscript. Acknowledgements The authors gratefully acknowledge the staff of the UNC Adams School of Dentistry at the University of North Carolina at Chapel Hill and the study participants for their valuable contributions to this research. Funding This study was supported by Contract grant sponsor: NIDCR/NIH; contract graft numbers: DE027980 (ARN) and DE027147 (ARN) and DE021052 (SN). Conflicts of Interest The authors declare no conflicts of interest. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Disclosure The authors assure that no generative AI tools were used for drafting the scientific content, data analysis or generation of results. Language editing was limited to conventional grammar and spellchecking tools. References Dye BA. Global periodontal disease epidemiology. Periodontol 2000. 2012;58:1:10–25. Morelli T, Moss KL, Preisser JS, Beck JD, Divaris K, Wu D, Offenbacher S. 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Profiling circulating microRNA expression in experimental sepsis using cecal ligation and puncture. PLoS ONE. 2013;8:10: e77936. Wang FX, Mu G, Yu ZH, et al. MiR–451 in inflammatory diseases: molecular mechanisms, biomarkers, and therapeutic applications—A comprehensive review beyond oncology. Curr Issues Mol Biol. 2025;47:2: 127. Hsieh CH, Rau CS, Jeng JC, et al. Whole blood-derived microRNA signatures in mice exposed to lipopolysaccharides. J Biomed Sci. 2012;19:1: 69. Hsieh CHJC, Yang, Jeng JC, et al. Circulating microRNA signatures in mice exposed to lipoteichoic acid. J Biomed Sci. 2013;20:1: 2. Alexander M, Hu R, Runtsch MC, et al. Exosome-delivered microRNAs modulate the inflammatory response to endotoxin. Nat Communication. 2015;6:7321. Dang CP, Leelahavanichkul A. Over-expression of miR-223 induces M2 macrophage through glycolysis alteration and attenuates LPS-induced sepsis mouse model, the cell-based therapy in sepsis. PLoS ONE. 2020;15:7: e0236038. Garlet G. Destructive and protective roles of cytokines in PD: A re-appraisal from host defense and tissue destruction viewpoints. J Dent Res. 2010;89:12: 1349–63. Huang C, Alimova Y, Ebersole J. Macrophage polarization in response to oral commensals and pathogens. Pathogens Disease. 2016;74:3: ftw011. Daily ZA, Al-Ghurabi BH, Al-Qarakhli AMA, R., Moseley. MicroRNA-155 (miR-155) as an accurate biomarker of periodontal status and coronary heart disease severity: a case-control study. BMC Oral Health. 2023;23:1:868. Pathak S, Grillo AR, Scarpa M, et al. MiR-155 modulates the inflammatory phenotype of intestinal myofibroblasts by targeting SOCS1 in ulcerative colitis. Experimental Mol Med. 2015;47:5:e164. O'Connell RM, Taganov KD, Boldin MP, Cheng G, D., Baltimore. MicroRNA-155 is induced during the macrophage inflammatory response. Proc Natl Acad Sci U S A. 2007;104:5:1604–9. Kurowska-Stolarska M, Alivernini LE, L. E., Ballantine, et al. MicroRNA-155 as a proinflammatory regulator in clinical and experimental arthritis. Proc Natl Acad Sci U S A. 2011;108:27:11193–8. Sheedy FJ, Palsson-McDermott E, Hennessy EJ, C., et al. Negative regulation of TLR4 via targeting of the proinflammatory tumor suppressor PDCD4 by the microRNA miR-21. Nat Immunol. 2010;11:2:141–7. Pan Y, Hui H, Hoo R, Feng T, Lam KS. A., Xu. 2018. miR-34a aggravates obesity-induced adipose inflammation and metabolic dysfunction via blocking polarization of anti-inflammatory M2 macrophage. Diabetes 67, (Supplement_1): 2025–P. Fan K-L, Li M-F, Cui F, et al. Altered exosomal miR-181d and miR-30a related to the pathogenesis of CVB3 induced myocarditis by targeting SOCS3. Eur Rev Med Pharmacol Sci. 2019;23:2208–15. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFile103072026.docx SupplementaryFile2miR451aPathwayList.docx SupplementaryFile3miRWalkmiRNATargetSOCS1.csv SupplementaryFile5miRWalkmiRNATargetSOCS3.csv SupplementaryFile7miRWalkmiRNATargetSOCS5.csv SupplementaryFile8miRWalkmiRNATargetSOCS6.csv SupplementaryFile6miRWalkmiRNATargetSOCS4.csv SupplementaryFile9miRWalkmiRNATargetSOCS7.csv SupplementaryFile4miRWalkmiRNATargetSOCS2.csv Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 27 Apr, 2026 Reviewers agreed at journal 26 Apr, 2026 Reviewers invited by journal 24 Apr, 2026 Editor assigned by journal 10 Apr, 2026 Submission checks completed at journal 10 Apr, 2026 First submitted to journal 08 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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22:38:54\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-9361339/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9361339/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":108808005,\"identity\":\"90b44b26-969c-4e3c-9e24-ce2f8969f08b\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:38:35\",\"extension\":\"jpeg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1148031,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eSplit-mouth miRNA profiling reveals distinct expression signatures in inflamed versus healthy gingiva and identified periodontopathogen-induced Dicer-independent miRNAs. \\u003c/strong\\u003e(A) Total RNA isolated from clinically healthy (n = 9) and inflamed (n = 8) gingival biopsies from a split-mouth design was subjected to global miRNA profiling using microarray analysis. Heatmaps depict significantly upregulated and downregulated miRNAs in inflamed gingiva compared with healthy sites. (B) Fold-change values for selected non-canonical miRNAs in inflamed versus healthy gingiva. (C–I) Average signal intensities for individual miRNAs, including (C) miR-451a, (D) miR-1228, (E) miR-28-5p, (F) miR-28-3p, (G) miR-142-5p, (H) miR-320-5p, and (I) miR-484, in healthy and inflamed gingival tissues. Validation of Dicer-independent miRNAs was performed by RT-qPCR. Relative expressions of (J) miR-451a and (K) miR-1228 in healthy versus inflamed gingiva were quantified using RNU6 as an endogenous control. Data are presented as mean ± SEM. Dicer-independent miRNAs are responsive to periodontal pathogens. Primary M1- and M2-like macrophages (Mφ) were challenged with 100 MOI of \\u003cem\\u003eP. gingivalis\\u003c/em\\u003e or \\u003cem\\u003eA. actinomycetemcomitans\\u003c/em\\u003e for 24 h and 48 h, and the expression of (L, M) miR-451a and (N, O) miR-1228 was quantified by RT-qPCR. RNU6 was used as endogenous control. Data are presented as mean ± SEM from n = 4 independent donors. Statistical significance was determined by ANOVA; p values are indicated as *p \\u0026lt; 0.05, **p \\u0026lt; 0.01, ***p\\u0026lt;0.001; ****p\\u0026lt;0.0001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/38ac8817735f197c3f370e68.jpeg\"},{\"id\":108807940,\"identity\":\"e66f47f9-3fa6-433a-a62e-62ae2da8ea94\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:37:51\",\"extension\":\"jpeg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1407208,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eOverexpression of miR-451a impairs macrophage polarization by promoting M1 and suppressing M2 surface markers.\\u003c/strong\\u003ePrimary human M1- and M2-polarized macrophages were transfected on day 2 with miR-451a, miR-1228, or control miRNA mimics or inhibitors. After 36 h, cells were analyzed by flow cytometry for canonical M1 and M2 surface markers. Overlaid histograms show surface expression of the M1-associated markers (A) HLA-DR and (D) CD32, and the M2-associated markers (G) CD206 and (J) CD163 under each treatment condition. Representative scatter plots illustrate the proportions of cells positive for (B) HLA-DR, (E) CD32, (H) CD206, and (K) CD163, with percentages indicating the fraction of cells within each gated quadrant. Gating excluded debris and doublets, and analysis was restricted to viable cells within the main population gate. Normalized percent geometric mean fluorescence intensity (GeoMFI) for M1 and M2 markers in miR-451a-, miR-1228-, or control mimic–transfected cells is shown. GeoMFI values calculated relative to scramble control and expressed as percentages. Data is presented as mean ± SEM from three independent donors. Student’s t-test was used to calculate p values; statistical significance is indicated as **p \\u0026lt; 0.01, ***p \\u0026lt; 0.001, ****p \\u0026lt; 0.0001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/f9d69610d9922456997bc03e.jpeg\"},{\"id\":108807933,\"identity\":\"d66850df-8cd6-4917-b631-3abaa1d75c5c\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:37:18\",\"extension\":\"jpeg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":822596,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003emiR-451a-mediated repression of M2 macrophage markers correlates with altered expression in inflamed gingiva.\\u003c/strong\\u003e(A) Schematic overview of the miRNA target-screening strategy using dual-luciferase reporter assays. Predicted miR-451a binding sites within the 3′UTR of (B) MRC1, (C) TGFBR1, (D) TGFB2, and (E) FN1 are shown as sequence alignments; only sites with minimum free energy (mfe) \\u0026lt; −15 kcal/mol are displayed. HEK293 cells were co-transfected with dual-luciferase reporter plasmids containing the 3′UTR of MRC1, TGFBR1, TGFB2, FN1, or empty control vector, together with miR-451a mimic, control mimic, or miR-451a inhibitor. After 36 h, cell lysates were collected and Renilla and firefly luciferase activities were measured. Renilla activity was normalized to firefly activity, and the resulting ratios were further normalized to the empty vector + control mimic condition, which was set to 1. Data are presented as mean ± SEM from four independent transfections (*p \\u0026lt; 0.05 versus control mimic; Student’s t-test). Total RNA was isolated from healthy (n = 8) and inflamed (n = 8) human gingival biopsies. Expression of validated miR-451a target genes (F) MRC1, (G) TGFBR1, (H) TGFB2, and (I) FN1 was quantified by RT-qPCR. Bar graphs depict relative gene expression in periodontally healthy versus inflamed gingiva. Statistical significance was evaluated by ANOVA (**p \\u0026lt; 0.01, ***p \\u0026lt; 0.001).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/cacd4e09db4eca1790a2c172.jpeg\"},{\"id\":108808028,\"identity\":\"f2dbf69f-2bf9-41d7-8d1e-13a198cdbd29\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:39:08\",\"extension\":\"jpeg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1179398,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003emiR-451a overexpression attenuates bacterial phagocytosis by macrophages. \\u003c/strong\\u003eM1-polarized human monocyte-derived macrophages were transfected with miR-451a or control miRNA mimics or inhibitors, and phagocytic activity was assessed using rhodamine-labeled \\u003cem\\u003eE. coli\\u003c/em\\u003e bioparticles. (A) Representative fluorescence microscopy images showing bacterial uptake, visualized by rhodamine signal within macrophages (final magnification 40×; scale bar = 100 μm). (B) After 2–4 h of incubation with \\u003cem\\u003eE. coli\\u003c/em\\u003e bioparticles, cells were harvested for flow cytometric analysis. Overlaid histograms demonstrate reduced rhodamine signal in miR-451a–transfected cells, indicating attenuated phagocytosis. (C) Representative scatter plots showing the percentage of Rhodamine⁺cells, reflecting the proportion of macrophages that internalized rhodamine-labeled \\u003cem\\u003eE. coli\\u003c/em\\u003e. (D) Bar graphs depict normalized percent geometric mean fluorescence intensity (GeoMFI) of rhodamine in macrophages, expressed relative to control-transfected cells.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/7358852416fc870b5abaad59.jpeg\"},{\"id\":108811792,\"identity\":\"84c6e6a1-a5ee-4bb2-aa6a-b84b5d53098e\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 16:07:08\",\"extension\":\"jpeg\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":862946,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003emiR-451a potentiates pathogen-induced cytokine production by suppressing SOCS3 and SOCS5 expression in macrophages\\u003c/strong\\u003e. Macrophages were transfected with miR-451a or control mimic and after 36 h challenged with \\u003cem\\u003eE. coli\\u003c/em\\u003e LPS (50 ng/ml). Culture supernatants were collected after 4 and 24 h and analyzed for secreted cytokines. Bar graphs show levels of (A) IL-6, (B) TNF-α, (C) IL-8, and (D) IL-1β. Data are presented as mean ± SEM from four independent donors. Statistical significance was determined by unpaired two-tailed Student’s t-test. p \\u0026lt; 0.05 was considered significant. (E) Schematic summary of the anti-inflammatory role of SOCS proteins in the JAK-STAT pathway and the predicted miR-451a binding sites in SOCS3, SOCS5, and SOCS6. Macrophages were transfected with miR-451a or control mimic using Lipofectamine 2000. After 36 h, cells were stimulated with a TLR4 agonist for 12 h and stained for SOCS proteins. Upper panels show representative scatter plots of (F) SOCS3, (G) SOCS5, and (H) SOCS6 expression, with percentages indicating the proportion of positive cells within the indicated gates. Lower right panel (F-H): Bar graphs showing normalized geometric mean fluorescence intensity (geo. MFI) values expressed as percentages relative to scramble control. Data is presented as mean ± SEM from three independent donors. Statistical significance was determined by Student’s t-test. *p \\u0026lt; 0.01, **p \\u0026lt; 0.001, ***p \\u0026lt; 0.0001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/a0bb04f58a27fe9bff596c7f.jpeg\"},{\"id\":108816322,\"identity\":\"0ba20ce7-925d-498e-922f-71a62c002d90\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 16:24:11\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":5906504,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/e7b5b79f-5d4e-4f64-8716-43be9015213b.pdf\"},{\"id\":108807934,\"identity\":\"cd26a8f9-74a5-42ce-a484-ca1652da6e12\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:37:19\",\"extension\":\"docx\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":20259,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryFile103072026.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/a3fc3a553caeaf039a33465b.docx\"},{\"id\":108809750,\"identity\":\"ade6650a-3a86-4cea-8fef-7d8ec76363d2\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:55:17\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":30280,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryFile2miR451aPathwayList.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/6a3732412428c2af04569be9.docx\"},{\"id\":108808025,\"identity\":\"478198e2-d0d9-4e6b-bda8-6899e3d66026\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:39:07\",\"extension\":\"csv\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":269374,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryFile3miRWalkmiRNATargetSOCS1.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/ae778903b41453e65f3c03c4.csv\"},{\"id\":108808006,\"identity\":\"0ca1149c-0f6a-4062-aca3-90c7cacfda6e\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:38:35\",\"extension\":\"csv\",\"order_by\":3,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":489368,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryFile5miRWalkmiRNATargetSOCS3.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/bf30b12869518cd017cd92fe.csv\"},{\"id\":108807936,\"identity\":\"93f04f11-0673-44aa-b004-c8c8c23fd79d\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:37:20\",\"extension\":\"csv\",\"order_by\":4,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":997730,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryFile7miRWalkmiRNATargetSOCS5.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/f78dbe898ab4277d1a6bf297.csv\"},{\"id\":108808027,\"identity\":\"53175340-9cc1-4d15-91fc-d24da2415ea2\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:39:07\",\"extension\":\"csv\",\"order_by\":5,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":1210398,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryFile8miRWalkmiRNATargetSOCS6.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/1966c4e3bb96347384ab1c99.csv\"},{\"id\":108808020,\"identity\":\"8a488fc0-cf7a-49dd-87e5-e1f50aaef3e7\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:39:02\",\"extension\":\"csv\",\"order_by\":6,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":1432598,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryFile6miRWalkmiRNATargetSOCS4.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/869da4b45ecaa4d841ab569e.csv\"},{\"id\":108807939,\"identity\":\"1c2a881a-765f-4b08-a0b1-709e6f0096ec\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:37:51\",\"extension\":\"csv\",\"order_by\":7,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":1577764,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryFile9miRWalkmiRNATargetSOCS7.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/29d0a554271006c0659512d6.csv\"},{\"id\":108807935,\"identity\":\"0a207400-59a8-4519-9b94-515ab2e7dbd2\",\"added_by\":\"auto\",\"created_at\":\"2026-05-08 15:37:20\",\"extension\":\"csv\",\"order_by\":8,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":2321377,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryFile4miRWalkmiRNATargetSOCS2.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9361339/v1/bcde23f7f1bda29ead6c7afa.csv\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Dicer-independent miR-451a is Upregulated in Periodontitis and Potentiates Inflammation by Impairing Macrophage Polarization and SOCS Activity\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003ePeriodontal diseases (PD) are inflammatory conditions of tooth-supporting tissues initiated by microbial dysbiosis and sustained by an overt host immune-inflammatory response.\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR2\\\" citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u003c/sup\\u003e Accumulating evidence, including work from our laboratory, shows that recruitment and persistence of pro-inflammatory immune cells in gingiva are closely linked to disease onset and progression. Diseased gingiva consistently contains more myeloid cells, T and B cells than healthy tissue,\\u003csup\\u003e4\\u0026ndash;6\\u003c/sup\\u003e along with increased production of immunoglobulins, cytokines, and other inflammatory mediators.\\u003csup\\u003e\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003eMacrophages (Mφ) are key myeloid cells in oral mucosa and are actively recruited to periodontal lesions during disease progression. Their role in PD pathogenesis and resolution are well established.\\u003csup\\u003e\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u003c/sup\\u003e Early in disease, Mφ sense microbial challenge through PRRs, including TLR2 and TLR4, and help activate adaptive immunity for pathogen clearance.\\u003csup\\u003e\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003e In PD, Mφ exist along a continuum from pro-inflammatory M1 to pro-reparative M2 states. Studies from our group and others show that diseased patients display an increased M1/M2 ratio that declines after non-surgical periodontal therapy,\\u003csup\\u003e6,12,13\\u003c/sup\\u003e supporting their role in both inflammation and resolution. Persistent M1-like activation promotes pro-inflammatory cytokine release and metalloproteinase activity, driving collagen destruction and alveolar bone loss.\\u003csup\\u003e\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u003c/sup\\u003e In contrast, M2 Mφ produce anti-inflammatory mediators such as IL-10 and TGF-β, suppress osteolysis, and promote tissue repair.\\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u003c/sup\\u003e In murine periodontal tissues, adoptive transfer of M2 Mφ increased Treg abundance and reduced osteoclast activity, a central mediator of alveolar bone loss.\\u003csup\\u003e\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e\\u003c/sup\\u003e Together, these findings underscore the importance of identifying molecular regulators of Mφ polarization.\\u003c/p\\u003e \\u003cp\\u003eMicroRNAs (miRNAs) are approximately 22-nucleotide non-coding RNAs that regulate gene expression post-transcriptionally.\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR19\\\" citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e\\u003c/sup\\u003e In the canonical pathway, primary miRNAs are transcribed, processed, and exported into the cytoplasm where they are cleaved by Dicer to generate a mature duplex. Some miRNAs are generated through non-canonical pathways, including mirtrons, Dicer-independent miRNAs, and species derived from tRNAs or snoRNAs. A well-known example is miR-451a, which bypasses Dicer and is processed directly through AGO2 after DROSHA-DGCR8 cleavage and nuclear export.\\u003csup\\u003e\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e\\u003c/sup\\u003e Regardless of biogenesis route, mature miRNAs regulate target transcripts through the same core AGO/RISC-mediated mechanisms.\\u003c/p\\u003e \\u003cp\\u003eAlthough the role of miRNAs in immune disorders is increasingly recognized, their regulatory and therapeutic functions in periodontal inflammation remain unclear. Our group and other reports have demonstrated differential miRNA expressions in inflamed gingiva and tooth pulps.\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR26 CR27\\\" citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e\\u003c/sup\\u003e Moreover, the functional roles and mechanistic impact of non-canonical miRNAs in PD have never been investigated. This study functionally evaluates the role of non-canonical miRNAs miR-451 and miR-1228 and their impact on Mφ polarization, a key event in PD pathogenesis, and further unravels novel molecular mechanisms regulating expression of anti-inflammatory molecules associated immune activity.\\u003c/p\\u003e\"},{\"header\":\"2. Materials and Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 Study population and sample collection\\u003c/h2\\u003e \\u003cp\\u003e This study protocol was approved by the institutional review board of the University of North Carolina at Chapel Hill (#13-1279). Systemically healthy adults aged 18\\u0026ndash;70 years who presented to the Postgraduate Periodontics Clinic, Adams School of Dentistry, UNC Chapel Hill, between March 2013 and May 2015 were recruited. Participants were excluded if they had uncontrolled systemic conditions (e.g., hypertension, heart disease, bleeding disorders), were pregnant, had diabetes, or were current smokers. Periodontally healthy sites had probing depths (PPD)\\u0026thinsp;\\u0026le;\\u0026thinsp;3 mm, no bleeding on probing, no clinical attachment loss (CAL), no radiographic alveolar bone loss, and \\u0026ge;\\u0026thinsp;4 mm of attached keratinized gingiva. Periodontally diseased sites met criteria for stage III, grade B disease, including\\u0026thinsp;\\u0026ge;\\u0026thinsp;4 teeth with PPD\\u0026thinsp;\\u0026ge;\\u0026thinsp;6 mm, CAL\\u0026thinsp;\\u0026ge;\\u0026thinsp;5 mm, and radiographic bone loss extending to the middle third of the root and beyond, with \\u0026ge;\\u0026thinsp;4 mm attached keratinized gingiva, as previously described.\\u003csup\\u003e\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e\\u003c/sup\\u003e Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e combines demographic and clinical data of the cohort.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSubject demographics and clinical parameters.\\u003c/b\\u003e \\u003cem\\u003e*Paired t-test\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge (mean\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026plusmn;\\u003c/span\\u003e\\u0026nbsp;SD) (years)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e56.78\\u0026thinsp;\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026plusmn;\\u003c/span\\u003e\\u0026thinsp;11.28\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGender (M/F)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e5/4\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eClinical site variables\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003ePeriodontitis site (n\\u0026thinsp;=\\u0026thinsp;9)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eNon-periodontitis site (n\\u0026thinsp;=\\u0026thinsp;9)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003ep-value*\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePPD (mean\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026plusmn;\\u003c/span\\u003e\\u0026nbsp;SD) (mm)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e7.33\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026plusmn;\\u003c/span\\u003e\\u0026nbsp;1.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.56\\u0026thinsp;\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026plusmn;\\u003c/span\\u003e\\u0026thinsp;0.73\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCAL (mean\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026plusmn;\\u003c/span\\u003e\\u0026nbsp;SD) (mm)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6.67\\u0026thinsp;\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026plusmn;\\u003c/span\\u003e\\u0026thinsp;1.80\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.33\\u0026thinsp;\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026plusmn;\\u003c/span\\u003e\\u0026thinsp;0.87\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eParticipants with PD had 1\\u0026ndash;2 mm\\u0026sup2; of gingiva removed from the tooth with the deepest probing site when undergoing surgical treatment. Additionally, a second sample of identical size was collected from a clinically healthy site elsewhere in the oral cavity during the same surgical intervention. The harvested tissue samples were placed in sterile round bottom polypropylene tubes and immediately immersed in 1.0 mL RNAlater (Applied Biosystems/Ambion, Austin, TX, USA) solution and incubated at 4℃ for at least 24 hours. The processed samples were then transferred to a -80℃ freezer for long-term storage.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 MicroRNA microarray profiling\\u003c/h2\\u003e \\u003cp\\u003eTissue samples were lysed using the TissueLyzer (Qiagen, Germantown, MD, USA) and total RNA isolated using the miRNeasy (Qiagen) kit as we previously reported.\\u003csup\\u003e\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e\\u003c/sup\\u003e The microarray assay was performed using a service provider (LC Sciences; Houston, TX, USA) and detailed in Supplemental Materials and Methods.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Total RNA isolation and quantitative RT-PCR\\u003c/h2\\u003e \\u003cp\\u003eTotal RNA was isolated using the miRNeasy kit (Qiagen). For mature miRNA quantification, miScript primers and miScript II RT Kit were purchased from Qiagen (details in Supplemental Materials and Methods).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4 Transient miRNA transfection\\u003c/h2\\u003e \\u003cp\\u003eTransient transfections were carried out using Lipofectamine 2000 reagent (Life Technologies, San Diego, CA, USA) following manufacturer instructions (details in Supplemental Materials and Methods).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.5 Primary human macrophage differentiation and challenge with periodontal bacteria\\u003c/h2\\u003e \\u003cp\\u003eMonocytes were isolated from freshly prepared buffy coats collected from healthy donors (n\\u0026thinsp;\\u0026ge;\\u0026thinsp;4, Sylvan N. Goldman Oklahoma Blood Institute, Oklahoma City, OK, USA) by density gradient centrifugation and CD14\\u0026thinsp;+\\u0026thinsp;cells were sorted by magnetic bead sorting as previously described.\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR32\\\" citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e\\u003c/sup\\u003e For Mφ differentiation, monocytes were plated at 2 \\u0026times; 10\\u003csup\\u003e6\\u003c/sup\\u003e/ml in DMEM supplemented with penicillin (100 U/ml) and streptomycin (100 \\u0026micro;g/ml). After 2 h the media was substituted with media containing 10% FBS (Life Technologies, Carlsbad, CA, USA), and rhM-CSF (50 ng/mL; Peprotech, Rocky Hill, NJ, USA). Cells were challenged with live \\u003cem\\u003eAggregatibacter actinomycetemcomitans\\u003c/em\\u003e (\\u003cem\\u003eAa\\u003c/em\\u003e, strain Y4, serotype B) or \\u003cem\\u003ePorphyromonas gingivalis\\u003c/em\\u003e (\\u003cem\\u003ePg\\u003c/em\\u003e, strain W83) at 100 MOI.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.6 Flow cytometry and TLR stimulation\\u003c/h2\\u003e \\u003cp\\u003eCells were stained for different antibodies and analyzed using BD Accuri C6 flow cytometer as described before\\u003csup\\u003e\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e\\u003c/sup\\u003e and detailed in Supplemental Materials and Methods. Cells were treated with TLR4 (\\u003cem\\u003eE. coli\\u003c/em\\u003e LPS, 50 ng/ml) stimulation and flow cytometry was performed as described previously.\\u003csup\\u003e\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.7 Phagocytosis assays\\u003c/h2\\u003e \\u003cp\\u003eCells transfected with miRNA or control mimics were assayed for phagocytosis using rhodamine labelled \\u003cem\\u003eE. coli\\u003c/em\\u003e as described before \\u003csup\\u003e\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e\\u003c/sup\\u003e and detailed in Supplemental Materials and Methods.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.8 Cell viability assay\\u003c/h2\\u003e \\u003cp\\u003eCell viability was determined by use of the CellTiter 96 AQueous Cell Proliferation Assay Kit (Promega). In brief, Mφ were plated at 400,000/well in 96-well plates and transfected as described above and assays performed after 36 h, according to the manufacturer's instructions.\\u003csup\\u003e\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.9 Bioinformatic target prediction, cloning of gene 3' UTRs, and dual luciferase assays\\u003c/h2\\u003e \\u003cp\\u003eGene targets were identified using miRWalk (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://mirwalk.umm.uni-heidelberg.de/\\u003c/span\\u003e\\u003cspan address=\\\"http://mirwalk.umm.uni-heidelberg.de/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). For miRNA pathway analysis, DIANA tool mirPath v.3 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://dianalab.e-ce.uth.gr/html/mirpathv3\\u003c/span\\u003e\\u003cspan address=\\\"https://dianalab.e-ce.uth.gr/html/mirpathv3\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) was used to identify significantly overrepresented pathways and functional categories. Cloning of predicted gene 3\\u0026prime; untranslated region (UTR) and dual luciferase assays were performed as previously described\\u003csup\\u003e\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e\\u003c/sup\\u003e and detailed in Supplemental Materials and Methods.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.10 Cytokine analysis\\u003c/h2\\u003e \\u003cp\\u003eSupernatants were collected from miR-451a or control mimic transfected Mφ challenged with \\u003cem\\u003eE. coli\\u003c/em\\u003e at 4 and 24 h. Multiplex analysis of four different cytokines (IL-1β, IL-6, IL-8 and TNF-α) was performed using Milliplex (Millipore, Billerica, MA, USA). Data was collected on Bio-Plex flow cytometer (Bio-Rad, Hercules, CA, USA) for analysis.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.11 Statistical analysis\\u003c/h2\\u003e \\u003cp\\u003eData was analyzed on Prism software (GraphPad, LaJolla, CA, USA). The results are represented as mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SEM of 3\\u0026ndash;5 independent replicates and experiments were conducted at least three times. p-Values were calculated using Student\\u0026rsquo;s t-test or ANOVA, and p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 were considered significant.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Gingival microRNA profiles reveal site-specific molecular changes drive periodontal disease\\u003c/h2\\u003e \\u003cp\\u003eThe cohort included adults with a mean age of 56.78\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.28, including 5 males and 4 females. Using a split-mouth design, we collected one gingival tissue biopsy from a periodontally diseased and non-diseased site (n\\u0026thinsp;=\\u0026thinsp;9 per site type) from each subject. Diseased sites had greater PPD (7.33\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.85 mm) than non-diseased sites (2.56\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.73 mm, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). CAL was also higher at diseased sites (6.67\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.80 mm) than at non-diseased sites (2.33\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.87 mm, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), confirming clear separation between PD and non-diseased sites.\\u003c/p\\u003e \\u003cp\\u003eMicroarray profiling identified 48 differentially expressed miRNAs between inflamed and healthy gingiva, showing clear site-specific dysregulation. Heatmap analysis demonstrated distinct clusters of upregulated and downregulated miRNAs that separated diseased from healthy sites (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eA). Overall, 32 miRNAs were upregulated and 16 were downregulated in inflamed gingiva. The most upregulated included miR-191a-3p, miR-150-5p, miR-451a, miR-4646-3p, miR-6851-3p, and miR-202-5p, whereas miR-23a/b, miR-27a/b, miR-224, miR-1275, and miR-1233 were among the most downregulated (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eDifferentially expressed miRNAs in periodontally healthy and diseased gingival biopsies.\\u003c/b\\u003e Mean signal intensity, fold change, and p-values (significance threshold p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) are shown for miRNAs significantly dysregulated between healthy and inflamed gingiva. miRNAs are ordered by ascending p-value.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003emiRNA\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHealthy\\u003c/p\\u003e \\u003cp\\u003e(Mean Intensity)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eDisease\\u003c/p\\u003e \\u003cp\\u003e(Mean Intensity)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eP-value\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eFold Change\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-200c-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e752\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e252\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.53E-05\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.34\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-200b-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e475\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e177\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.03E-04\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.37\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-23b-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3,648\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2,015\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.44E-04\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.55\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-23a-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4,033\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2,491\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.58E-04\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-199a-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e661\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1,716\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.73E-04\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.60\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-203a-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2,899\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e434\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.83E-04\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.15\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-27b-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e720\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e363\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8.47E-04\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.50\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-143-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e202\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e424\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.01E-03\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.10\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-199a-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e320\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e816\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.60E-03\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.55\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-451a\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4,284\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e11,244\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.88E-03\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-27a-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1,127\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e647\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.02E-03\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.57\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-29a-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e619\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1,165\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd 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char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e748\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.27E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-21-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3,431\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5,245\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.76E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.53\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e 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colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-223-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e113\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e478\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8.15E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e4.25\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-4530\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e168\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e266\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8.33E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.59\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-205-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3,294\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1,273\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8.49E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.39\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-455-3p\\u003c/p\\u003e 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\\u003cp\\u003e108\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e290\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.46E-03\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.68\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-708-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e73\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e37\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.75E-03\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.51\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-4800-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e14\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e43\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.00E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.04\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-210-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e19\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.13E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.42\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-185-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e54\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.15E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.22\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-6775-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e14\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e47\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.21E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.32\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-200a-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e157\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e73\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.37E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.47\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-1275\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e138\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e57\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.42E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.41\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-483-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.62E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-7851-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e11\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e49\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.66E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e4.58\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-34a-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e33\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e61\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.66E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.84\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-92a-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e263\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e170\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.76E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-1237-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.89E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.95\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-374c-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e32\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e68\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.22E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-145-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e47\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.43E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e5.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-144-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e14\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e42\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.49E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.90\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-650\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e45\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.51E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e4.86\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-6769b-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e13\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.56E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.91\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-4687-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e124\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.70E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.23\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-6731-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.52E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-382-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.40E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-4646-3p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e17\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.45E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-6730-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e20\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.78E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.74\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ehsa-miR-619-5p\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e19\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e52\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.95E-02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.69\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eSeveral non-canonical miRNAs were also elevated in inflamed gingiva, including miR-451a (2.6-fold), miR-1228 (1.3-fold), miR-142-5p (2.3-fold), miR-28-3p (1.8-fold), miR-28-5p (2.2-fold), miR-484 (1.3-fold), and miR-320-5p (2.6-fold) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eB). Their average signal intensities also trended higher in inflamed tissue (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eC-I). RT-qPCR validation confirmed significantly increased miR-451a (~\\u0026thinsp;8-fold) and miR-1228 (~\\u0026thinsp;2-fold) expression in inflamed biopsies relative to clinically healthy controls (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eJ, K). Together, these results show that Dicer-independent miRNAs display a distinct expression pattern in inflamed gingiva, supporting a role for site-specific miRNA dysregulation in periodontal pathogenesis.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2 miR-451a and miR-1228 is responsive to periodontal bacteria\\u003c/h2\\u003e \\u003cp\\u003ePeriodontal pathogens modulate innate immune programs in Mφ, including dysregulation of noncoding RNA expression that can rapidly shape inflammatory outputs and resolution. To examine if expression of non-canonical, Dicer-indepedent miRNAs miR-451a and miR-1228 are responsive to periodontal bacteria, we quantified their expression in M1 and M2 Mφ challenged with 100 MOI live \\u003cem\\u003ePg\\u003c/em\\u003e and \\u003cem\\u003eAa\\u003c/em\\u003e at 24 and 48 h. miR-451a in M1 Mφ exhibited a time-dependent induction across both bacterial challenges, increasing at 24 h (\\u003cem\\u003ePg\\u003c/em\\u003e: 4.98\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.58 fold; \\u003cem\\u003eAa\\u003c/em\\u003e: 3.42\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.40 fold) and further at 48 h (\\u003cem\\u003ePg\\u003c/em\\u003e: 7.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.45 fold; \\u003cem\\u003eAa\\u003c/em\\u003e: 5.0\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.21) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eL, M). In contrast, miR-1228 expression in M1 Mφ showed no appreciable change at 24 h (\\u003cem\\u003ePg\\u003c/em\\u003e: 1.05\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.06 fold; \\u003cem\\u003eAa\\u003c/em\\u003e: 0.97\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.02 fold) but was elevated at 48 h (\\u003cem\\u003ePg\\u003c/em\\u003e: 2.31\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.20 fold; \\u003cem\\u003eAa\\u003c/em\\u003e: 1.83\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.30 fold) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eN, O). These results indicate that miR-451a is induced rapidly and remains persistently elevated, whereas miR-1228 shows a delayed induction pattern. Together, the data suggests that non-canonical miRNAs are responsive to periodontal pathogens.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 miR-451a regulates macrophage polarization by skewing a shift towards M1 phenotype\\u003c/h2\\u003e \\u003cp\\u003eMacrophages are central to both the persistence and resolution of gingival inflammation, coordinating pro-inflammatory and reparative responses.\\u003csup\\u003e\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e\\u003c/sup\\u003e To identify endogenous regulators of Mφ polarization, we examined the effects of the Dicer-independent miRNAs miR-451a and miR-1228. These candidates were selected based on high expression, significant differential regulation, and predicted targeting of immune and inflammatory pathways (Supplementary file 2).\\u003c/p\\u003e \\u003cp\\u003ePrimary CD14\\u0026thinsp;+\\u0026thinsp;monocytes were transfected on day 3 of differentiation with miR-451a, miR-1228, control mimics, or inhibitors, and M1/M2 surface markers analyzed by flow cytometry after 72 h. miR-451a overexpression, but not miR-1228, promoted M1 polarization while suppressing M2-like features (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA,D). Compared with control mimic, miR-451a increased the percentage of HLA-DR+ cells from 80.5\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.15% to 91.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.38% and CD32\\u0026thinsp;+\\u0026thinsp;cells from 63.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.62% to 79.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.10% (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB). In contrast, CD163\\u0026thinsp;+\\u0026thinsp;cells decreased from 71.1\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.38% to 36.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.95%, and CD206\\u0026thinsp;+\\u0026thinsp;cells from 67.1\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;7.23% to 56.9\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.44% (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eE). Normalized geometric mean fluorescence intensity showed similar changes, with increased HLA-DR (119.5\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6.36%) and CD32 (117.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.25%) and reduced CD206 (70.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.45%) and CD163 (81.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.93%) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eC,F). Overall, these results indicate that miR-451 enhances Mφ pro-inflammatory polarization through upregulation of M1-associated surface markers.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.4 miR-451a directly binds to the 3' UTR and suppresses multiple M2 marker genes\\u003c/h2\\u003e \\u003cp\\u003eTo determine whether miR-451a regulates M2-associated markers, we screened the 3\\u0026prime;UTRs of MRC1, FN1, TGFB2, and TGFBR1 using RNA hybrid analysis. Putative miR-451a binding sites were identified in all four genes and cloned into reporter plasmids. A schematic of the dual-luciferase assay is shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA, and sequence alignments with the 3\\u0026prime;UTRs of MRC1/CD206, FN1, TGFB2, and TGFBR1 are presented in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB-E (upper panels).\\u003c/p\\u003e \\u003cp\\u003eTo validate these sites, HEK293 cells were co-transfected with psiCHECK2 alone or psiCHECK2 containing the cloned 3\\u0026prime;UTRs together with miR-451a or control mimics. Compared with control mimic, miR-451a significantly reduced Renilla luciferase activity for MRC1, TGFB2, TGFBR1, and FN1 3\\u0026prime;UTR constructs by ~\\u0026thinsp;30\\u0026ndash;50% (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB-E, lower panels), identifying these genes as novel miR-451a targets linked to the M2 phenotype.\\u003c/p\\u003e \\u003cp\\u003eConsistent with these findings, gingival tissues from inflamed sites showed reduced MRC1 (0.68\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12 fold), FN1 (0.47\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.07 fold), TGFBR1 (0.77\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.09 fold), and TGFB2 (0.65\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12 fold) expression versus healthy controls (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eF-I). Together, these data support a model in which miR-451a suppresses M2-associated genes, limiting pro-resolving Mφ function in PD.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.5 miR-451a overexpression in macrophages attenuates bacterial phagocytosis\\u003c/h2\\u003e \\u003cp\\u003eMacrophage phagocytosis of microbes and apoptotic cells is essential for periodontal tissue defense and homeostasis.\\u003csub\\u003e36,37\\u003c/sub\\u003e To examine the role of miR-451a in Mφ function, M1 Mφ were transiently transfected with miR-451a mimic, control mimic, or inhibitor, and phagocytosis measured using rhodamine-labeled \\u003cem\\u003eE. coli\\u003c/em\\u003e bioparticles. Fluorescence microscopy showed reduced \\u003cem\\u003eE. coli\\u003c/em\\u003e uptake in miR-451a mimic-transfected cells compared with control mimic or inhibitor-treated cells (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eA). Flow cytometry confirmed this result, with \\u003cem\\u003eE. coli\\u003c/em\\u003e uptake decreasing from 83.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.15% in controls to 60.9\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.5% in miR-451a-transfected cells (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eB, C). In contrast, miR-451a inhibitor-transfected cells showed uptake similar to controls (83.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.2%) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eC). Geometric mean fluorescence intensity of phrodo+ cells also fell to 70.8\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.89% (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.0005) with miR-451a and increased to 117.0\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.38% with inhibitor (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eD). These findings indicate that miR-451a suppresses Mφ phagocytosis.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003e3. 6 miR-451 potentiates inflammation by suppressing SOCS-mediated feedback regulation\\u003c/h3\\u003e\\n\\u003cp\\u003eTo determine whether miR-451a modulates inflammatory responses, Mφ were transfected with miR-451a mimic or control mimic and challenged with periodontal pathogens. Overexpression of miR-451a significantly enhanced pathogen-induced cytokine production. In response to \\u003cem\\u003ePg\\u003c/em\\u003e, miR-451a increased supernatant levels of IL-1β (2760.42\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;257.30 vs 1711.36\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;427.59 pg/mL), TNF-α (3632.52\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;311.43 vs 2590.19\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;326.47 pg/mL), IL-6 (2996.59\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;752.69 vs 1800.22\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;351.83 pg/mL), and CXCL8 (11735.52\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1733.31 vs 8361.21\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1351.42 pg/mL) relative to control mimic (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eA-D). Similar effects were observed with \\u003cem\\u003eAa\\u003c/em\\u003e challenge, where miR-451a increased IL-1β (2505.08\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;535.64 vs 1698.23\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;328.40 pg/mL), TNF-α (3522.65\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;680.64 vs 2537.30\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;428.55 pg/mL), IL-6 (2700.33\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;622.40 vs 1961.17\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;472.09 pg/mL), and CXCL8 (8504.17\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1393.25 vs 6020.96\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;282.33 pg/mL) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eA-D). These findings indicate that miR-451a amplifies pathogen-induced pro-inflammatory cytokine production.\\u003c/p\\u003e \\u003cp\\u003ePathway analysis identified immune signaling pathways as major miR-451a targets (Supplementary file 2). Because TLR signaling converges on the JAK-STAT pathway and SOCS proteins serve as key negative regulators, we examined the SOCS family for predicted miR-451a binding sites.\\u003csup\\u003e\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e\\u003c/sup\\u003e SOCS3 contained one predicted site at 1854\\u0026ndash;1872, SOCS5 contained two predicted sites at 3282\\u0026ndash;3300 and 3302\\u0026ndash;3324, and SOCS6 contained two predicted sites at 2326\\u0026ndash;2343 and 2422\\u0026ndash;2439 (Supplementary files 3\\u0026ndash;9). No predicted binding sites were identified in the remaining SOCS genes. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eE summarizes the anti-inflammatory role of SOCS proteins in JAK-STAT signaling and the predicted miR-451a target sites in SOCS3, SOCS5, and SOCS6.\\u003c/p\\u003e \\u003cp\\u003eTo validate these predictions, Mφ were transfected with miR-451a or control mimic and then stimulated with TLR4 agonists. SOCS expression was measured by flow cytometry. miR-451a significantly reduced the proportions of SOCS3-positive and SOCS5-positive Mφ compared with controls (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eF,G), while SOCS6 showed a modest but non-significant decrease (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eH). After TLR4 stimulation, the percentage of SOCS3-positive Mφ was lower in miR-451a-transfected cells than in controls (12.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.7% vs. 33.02\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.7%, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.0001; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eF). A similar reduction was observed for SOCS5-positive Mφ (10.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.2% vs. 28.1\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.2%; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eG). In contrast, SOCS6 expression was not significantly altered (10.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.02% vs. 11.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.9%; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eH). As expected, TLR4 stimulation induced SOCS expression under control conditions. Together, these results show that miR-451a selectively suppresses SOCS3 and SOCS5 after TLR4 activation, supporting a role for miR-451a in limiting SOCS-mediated negative feedback within the JAK-STAT inflammatory pathway.\\u003c/p\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cp\\u003eLarge-scale transcriptomic and miRNA profiling increasingly implicate post-transcriptional regulation in periodontal pathogenesis,\\u003csup\\u003e40\\u003c/sup\\u003e but the contribution of non-canonical miRNAs remains poorly understood. In this study, we identify Dicer-independent miRNAs as potential regulators of periodontal immunity and tissue remodeling. Multiple non-canonical miRNAs, including miR-451a, miR-1228, miR-142-5p, miR-28-3p/5p, and miR-484, were markedly upregulated in inflamed gingiva, indicating that alternative miRNA maturation pathways are selectively engaged during disease. To our knowledge, this is the first evidence that non-canonical miRNAs are altered in PD and can polarize Mφ function. Similar stress-adaptive reprogramming of small RNA biogenesis has been reported in other inflamed tissues and may reflect the effects of microbial products, hypoxia, or inflammatory cytokines on miRNA processing.\\u003csup\\u003e\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e\\u003c/sup\\u003e Non-canonical miRNA dysregulation is also documented in other inflammatory diseases. For example, miR-451a is elevated in Systemic Lupus Erythematosus, Hashimoto thyroiditis, rheumatoid arthritis, sepsis, and Gram-positive bacterial infection, supporting its broader association with inflammatory activation.\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR44 CR45\\\" citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e\\u003c/sup\\u003e Our findings suggest that bacterial virulence factors and oxidative stress in PD may similarly induce miR-451a and related non-canonical miRNAs.\\u003c/p\\u003e \\u003cp\\u003etissues.\\u003c/p\\u003e \\u003cp\\u003eMacrophages accumulate in periodontal lesions and acquire M1-like transcriptional features that enhance cytokine production and bone-resorptive pathways.\\u003csup\\u003e\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e\\u003c/sup\\u003e Our earlier work linked miRNA dysregulation to oral mucosal immunity, including Mφ polarization and PD-associated noncoding RNA networks.\\u003csup\\u003e\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e\\u003c/sup\\u003e The present study extends those observations by identifying a non-canonical regulatory axis centered on miR-451a. We show that miR-451a is elevated in PD, correlates with M1 marker induction, and suppresses M2-associated markers in inflamed gingiva. Overexpression of miR-451a increased M1-associated markers HLA-DR and CD32, while reducing the M2-associated markers CD206 and CD163. This combined enhancement of M1 traits and repression of M2 features suggests that miR-451a polarizes Mφ toward a more inflammatory phenotype while limiting reparative programs. Mechanistically, miR-451a directly targeted several genes associated with M2 polarization and tissue repair. Dual-luciferase assays confirmed MRC1, FN1, TGFB2, and TGFBR1 as direct miR-451a targets. These genes are integral to Mφ alternative activation, matrix remodeling, and TGF-β signaling, all of which are important for resolution of inflammation and tissue repair. Consistent with these findings, expression of MRC1, FN1, TGFB2, and TGFBR1 was reduced in inflamed gingival tissues compared with healthy controls. These data support a model in which elevated miR-451a suppresses pro-resolving pathways in periodontal lesions, thereby sustaining inflammation and impairing its resolution.\\u003c/p\\u003e \\u003cp\\u003eEfficient phagocytosis is essential for microbial clearance and removal of apoptotic cells in periodontal tissues.\\u003csup\\u003e\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e\\u003c/sup\\u003e We found that miR-451a overexpression significantly reduced uptake of labeled \\u003cem\\u003eE. coli\\u003c/em\\u003e bioparticles, whereas inhibition of miR-451a had little effect. This indicates that increased miR-451a is sufficient to impair Mφ phagocytic capacity. In PD, such impairment could reduce bacterial clearance, prolong microbial persistence, and further amplify inflammatory signaling. Thus, miR-451a may contribute not only to inflammatory skewing but also to defective innate immune function. Supporting this, we demonstrate that miR-451a is responsive to periodontal pathogens and amplifies inflammatory cytokine production. Exposure of Mφ to \\u003cem\\u003ePg\\u003c/em\\u003e and \\u003cem\\u003eAa\\u003c/em\\u003e induced miR-451a expression indicating it is pathogen responsive. Functionally, miR-451a overexpression enhanced production of IL-1β, TNF-α, IL-6, and CXCL8. This allows miR-451a to augment feed-forward inflammatory loops in which microbial challenge induces miR-451a, which in turn amplifies Mφ inflammatory output. Such a mechanism could be relevant in PD, where ongoing bacterial stimulation sustains local immune activation and tissue injury.\\u003c/p\\u003e \\u003cp\\u003eTo understand how miR-451a enhances inflammatory signaling, we examined its impact on the SOCS family, a key negative feedback system in cytokine and TLR signaling. Bioinformatic analysis identified predicted miR-451a binding sites in SOCS3, SOCS5, and SOCS6, and functional studies showed that miR-451a selectively reduced SOCS3 and SOCS5, but not SOCS6 expression after TLR4 stimulation. Because SOCS proteins restrain JAK-STAT and related inflammatory pathways, repression of SOCS3 and SOCS5 would be expected to prolong or intensify inflammatory signaling. Indeed, this mechanism is consistent with the observed increase in pathogen-induced cytokine production and suggests that miR-451a weakens endogenous anti-inflammatory checkpoints. Thus, miR-451a may act as pro-inflammatory miRNA driving inflammation by suppressing inhibitory pathways. For example, miR-155 promotes Mφ activation by targeting SOCS1 and SHIP1, contributing to inflammatory disorders including PD, rheumatoid arthritis, inflammatory bowel disease, and sepsis.\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR52 CR53\\\" citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e\\u003c/sup\\u003e miR-21 enhances inflammatory signaling by targeting PDCD4, whereas miR-34a promotes obesity-associated inflammation by repressing Klf4.\\u003csup\\u003e\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e\\u003c/sup\\u003e Likewise, miR-30b and miR-181d aggravate myocardial inflammation through repression of SOCS3, relieving negative regulation of cytokine signaling.\\u003csup\\u003e\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e\\u003c/sup\\u003e Our findings suggest that miR-451a acts in a comparable way in PD. Specifically, miR-451a appears to promote gingival inflammation through two complementary mechanisms: suppression of M2-associated reparative programs and removal of SOCS-dependent inhibitory control over inflammatory signaling.\\u003c/p\\u003e \\u003cp\\u003eSeveral limitations should be noted. The sample size was relatively small, which may limit statistical power and generalizability. Although the split-mouth design reduced inter-individual variability, it may not fully account for site-specific heterogeneity. In addition, most mechanistic experiments were conducted in vitro and may not capture the full complexity of the in vivo periodontal immune microenvironment. Validation in larger clinical cohorts and animal models are required.\\u003c/p\\u003e \\u003cp\\u003eIn summary, this study identifies a distinct miRNA landscape in diseased gingiva enriched for Dicer-independent and other non-canonical species, with miR-451a emerging as a central regulator. Periodontal pathogen-responsive miR-451a promotes M1Mφ polarization, suppresses M2-associated genes, reduces bacterial phagocytosis, and enhances inflammatory signaling through suppression of SOCS3 and SOCS5. These findings support miR-451a as both a potential biomarker and a therapeutic target in PD, with possible relevance for host-response modulation, microbial clearance, and tissue repair.\\u003c/p\\u003e \"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval statement\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe study protocol involving human participants was reviewed and approved by the Institutional Review Board of the University of Illinois Chicago and The University of North Carolina at Chapel Hill Adams School of Dentistry and was conducted in accordance with the Declaration of Helsinki and institutional guidelines.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePatient consent statement\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWritten informed consent was obtained from all participants prior to study enrollment and sample collection.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor Contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll authors have made substantial contributions to conception, design of the study and given final approval of the version to be published. AM, SZ and SN were calibrated and performed clinical data measurements, as well as obtained biomaterials from the patients. RAN, JM, KA, AM, SZ, SN, MP, AV and ARN were involved in data collection and data analysis. RAN, JM, KA, KC, AV, SZ, SN and ARN were involved in data interpretation, and drafting the manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors gratefully acknowledge the staff of the UNC Adams School of Dentistry at the University of North Carolina at Chapel Hill and the study participants for their valuable contributions to this research.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was supported by Contract grant sponsor: NIDCR/NIH; contract graft numbers: DE027980 (ARN) and DE027147 (ARN) and DE021052 (SN).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConflicts of Interest\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no conflicts of interest.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData Availability Statement\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDisclosure\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors assure that no generative AI tools were used for drafting the scientific content, data analysis or generation of results. Language editing was limited to conventional grammar and spellchecking tools.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eDye BA. Global periodontal disease epidemiology. Periodontol 2000. 2012;58:1:10\\u0026ndash;25.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMorelli T, Moss KL, Preisser JS, Beck JD, Divaris K, Wu D, Offenbacher S. Periodontal profile classes predict periodontal disease progression and tooth loss. J Periodontol. 2018;89:2: 148\\u0026ndash;56.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCekici A, Kantarci A, Hasturk H, Van Dyke TE. Inflammatory and immune pathways in the pathogenesis of periodontal disease. Periodontology. 2014;64:1: 57\\u0026ndash;80.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNares S, Moutsopoulos NM, Angelov N, Rangel ZG, Munson PJ, Sinha N, Wahl SM. 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Eur Rev Med Pharmacol Sci. 2019;23:2208\\u0026ndash;15.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"inflammation-research\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"inre\",\"sideBox\":\"Learn more about [Inflammation Research](http://link.springer.com/journal/11)\",\"snPcode\":\"11\",\"submissionUrl\":\"https://submission.nature.com/new-submission/11/3\",\"title\":\"Inflammation Research\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"Periodontal disease, split-mouth, macrophage, noncanonical microRNAs, polarization\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9361339/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9361339/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003ePeriodontitis is characterized by localized inflammatory tissue destruction, yet the lesion-specific microRNA networks that shape host immune responses remain incompletely defined. Using a split-mouth design, we profiled miRNA expression in gingival biopsies obtained from periodontal lesions and clinically healthy sites within the same individuals to identify disease-associated regulatory signatures. Microarray analysis revealed 48 differentially expressed miRNAs, including several upregulated non-canonical species, and selected candidates were validated by RT-qPCR. Among these, the Dicer-independent miRNAs miR-451a and miR-1228 showed dose- and time-dependent induction in response to periodontal bacterial challenge. Functional studies demonstrated that miR-451a, but not miR-1228, promoted a pro-inflammatory M1-like macrophage phenotype, characterized by increased HLA-DR and CD32 expression and reduced CD206 and CD163. Consistent with this, miR-451a directly targeted multiple genes associated with M2 polarization, and its expression in inflamed gingival tissues inversely correlated with M2 marker expression. Moreover, miR-451a overexpression impaired bacterial phagocytosis and enhanced inflammatory cytokine production. Mechanistically, miR-451a suppressed SOCS3 and SOCS5, key negative regulators of JAK/STAT signaling, in TLR4-stimulated cells. Collectively, these findings identify miR-451a as a pathogen-responsive, periodontitis-associated miRNA that reprograms macrophage polarization, weakens antibacterial defense, and amplifies inflammation through suppression of SOCS-mediated immune regulation.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Dicer-independent miR-451a is Upregulated in Periodontitis and Potentiates Inflammation by Impairing Macrophage Polarization and SOCS Activity\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-05-05 10:51:52\",\"doi\":\"10.21203/rs.3.rs-9361339/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"reviewerAgreed\",\"content\":\"254410837371676000704329580825493635209\",\"date\":\"2026-04-27T07:45:42+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"3685370834650574523289402755559100585\",\"date\":\"2026-04-26T15:04:58+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2026-04-24T14:55:19+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2026-04-10T21:47:35+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2026-04-10T21:47:14+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Inflammation Research\",\"date\":\"2026-04-08T22:23:04+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"inflammation-research\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"inre\",\"sideBox\":\"Learn more about [Inflammation Research](http://link.springer.com/journal/11)\",\"snPcode\":\"11\",\"submissionUrl\":\"https://submission.nature.com/new-submission/11/3\",\"title\":\"Inflammation Research\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"d78a629e-4a06-4fe6-9023-8262c0f3100f\",\"owner\":[],\"postedDate\":\"May 5th, 2026\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-05-05T10:51:52+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-05-05 10:51:52\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-9361339\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-9361339\",\"identity\":\"rs-9361339\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}