Effect of Non-chirurgical Periodontal Treatment on the Immune System From a Gender Perspective
NCT ID: NCT06261723
Last Updated: 2026-01-14
Study Results
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Basic Information
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COMPLETED
100 participants
OBSERVATIONAL
2024-04-15
2025-05-31
Brief Summary
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* If non-surgical periodontal treatment of patients with chronic periodontitis can modulate the innate and adaptive immune response taking into account patient gender and the coexistence of obesity
* If there are specific miRNAs that can regulate this immune response and can be considered as suitable biomarkers and therapeutic targets.
Obese or non-obese participants with periodontitis will receive non-surgical periodontal treatment, consisting of oral health guidance and mechanical periodontal debridement throughout the mouth using an ultrasonic device and manual curettes. Researchers will compare four groups: obese women, non-obese women, obese men, and non-obese men, to clarify the involment of immune response after treatment, considering the coexistence of obesity and potential gender differences.
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Detailed Description
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Clinical periodontal parameters of probing pockets depth (PD), millimetres of clinical attachment level (CAL), bleeding on probing (BOP), simplified plaque index of Silness and Löe, and simplified calculus index of Greene and Vermillion will be determined using a conventional manual periodontal probe (UNC-15 PCP). A periodontal examination will be performed to measure PD, CAL, and BOP at six sites per tooth for all teeth, excluding third molars, as previously described. Patients will be interviewed about their medical history, lifestyle habits (smoking, frequency of tooth brushing, physical activity), and sociodemographic characteristics. Weight, height, and blood pressure will be measured using standardized methods. Biochemical parameters of carbohydrate metabolism - glucose, insulin, glycated hemoglobin (A1c) -, lipid profile - total cholesterol, LDL, HDL, triglycerides (TG), apolipoproteins AI and B -, emerging inflammatory and cardiovascular risk markers - C-Reactive Protein (CRP), C3c, and retinol-binding protein 4 (RBP4) -, and complete blood count will be determined at the hospital's Clinical Analysis Service.
For detection of differences in protein expression, cells will be incubated in lysis buffer with protease and phosphatase inhibitors (RIPA Buffer) for 15 minutes at 4 degrees celsius (°C). The supernatant will be collected after centrifugation for 15 minutes at 16,000g. The total protein concentration will be quantified using a bicinchoninic acid (BCA) protein assay. Aliquots of 25 µg of protein will be resolved on 8-16% gradient SDS-polyacrylamide gels and transferred to nitrocellulose membranes. Target proteins will be detected by incubating the membranes with anti-actin, JNK, NFkB, MCP1, GPX-1, NLRP3, ASC, procaspase 1, caspase 1, NADPH oxidase, catalase, GPX1, SOD1, Beclin, ATG5-ATG12, p62, LC3 I, LC3 II, Pink1, GRP78, eIF2alpha, IRE1 alpha, ATF6, CHOP, PGC1 alpha, mTFA, VDAC, Complex I, II, III, IV and V. The protein signal will be detected by chemiluminescence and analyzed by densitometry.
Inflammasome complex assembly (first stage of activation) through co-localization studies of NLRP3-ASC in PBMCs will be conducted using the confocal and/or fluorescence microscopy. Briefly, PBMCs will be seeded on coverslips coated with Poly-D-Lysine, fixed with paraformaldehyde (PFA) 4% for 20 minutes, permeabilized with Triton X-100 for 20 minutes and blocking with Phosphate-buffered saline buffer-Bovine serum albumn (PBS-BSA) 3% for 1 hour at room temperature. Hybridization with specific primary antibodies (diluted in PBS-BSA 1%) will be carry out overnight at 4 ºC and then, secondary antibodies conjugated with AlexaFluor fluorophores will be incubated for 1 hour in the dark at room temperature. Stained samples will be transferred the coverslip onto microscope slide and conserved in anti-fade fluorescence mounting medium.
Circulating levels of cytokines, adhesion molecules and serum oxidative stress markers will be measured in serum samples, but for secretome studies 1x10\^6 PBMCs will be previously incubated in 1 mL RPMI with 10% fetal bovine serum (FBS) for 4 hours (37°C, 5% CO2) to obtain the supernatant. Both serums and supernatants will be analyzed with a Luminex® 200 analyzer system following the Milliplex® MAP Kit manufacturer's procedure. These same determinations will be carried out on GCF and serum/plasma samples from patients.
The quantification of functional autophagosomes in PBMCs will be performed using flow cytometry on our BD Accuri equipment with the CYTO-ID® Autophagy detection kit following manufacturer's procedure. In parallel, leucocyte from whole blood samples will be incubated with redox status detecting fluorescent probes for 15 minutes and then, they will be analysed using flow cytometry. Additionally, a multicolor panels for flow cytometry based on cluster of differentiation (CD) antigens detection, CD3/CD4/CD8/CD45RA/CCR7/CD38 and CD14/CD16, will be designed to analyze the percentage of lymphocyte T subpopulations (naive T cells (TN), central memory (TCM), effector memory (TEM) and terminally differentiated (TEMRA) cells) and, monocytes subpopulations (classical, non-classical, and intermediate), respectively in blood samples. In both procedures 10000 events will be acquired and single staining and FMO controls for all fluorochrome-conjugated antibodies in the panels will be performed to establish adequate compensation and define positive signals.
A parallel plate flow chamber, connected to an inverted microscope, will enable the researchers to measure neutrophil-endothelial cell interactions in vitro. Through this system, the leukocyte suspension obtained from patients will be perfused over a monolayer of immortalized endothelial cells (HUVEC/TERT 2) under conditions simulating blood flow. Videos will be analyzed afterward to determine flow, rolling velocity, and firm adhesion of leukocytes to endothelial cells, as previously described (Antioxidants. 2020 Aug 11;9(8):734).
Changes in gene expression levels will be evaluated using Nanostring® technology for nCounter®. To sum up, total RNA will be extracted from PBMCs using the GeneAllR RibospinTM total kit, and starting from 100-200 ng of total RNA, Diagnostica Longwood, S.L. will analyze the differential gene expression response, thus obtaining the multiplex metabolism panel.
For differential gene expression analysis of miRNAs (DEGs), RNA will be extracted using the miRNeasy Serum/Plasma kit (Qiagen). After short-chain RNA extraction, libraries will be prepared for sequencing using the TruSeq Small RNA library preparation kit (Illumina, Inc). Libraries will be pooled equimolarly and quantified using the KAPA SYBR FAST Universal qPCR kit with Illumina Primer Premix, and group size will be measured using a Bioanalyzer (Agilent). Finally, 2 nanomoles of the group will be sequenced on the Illumina NovaSeq6000 platform with a 1% PhiX control in the FISABIO facilities. Libraries will be sequenced using 2x100 bp chemistry in an SP flow cell (Illumina, Inc). After multiplexing, raw data will be processed using the "COMPSRA: a COMprehensive Platform for Small RNA-Seq data Analysis" pipeline.
DNA will also be extracted from plasma according to the "blood and body fluid protocol" of the QIAamp blood reagent set (QIAgen, Hilden, Germany); 400 μL of plasma will be applied to each column, DNA will be eluted in 200 μL of supplied buffer and will be stored at -20°C until use. mtDNA will be quantified with reverse transcription-quantitative polymerase chain reaction (RT-qPCR) using specific primers for obtaining circulating mtDNA levels.
Data analysis will be performed with SPSS 17.0. Groups will be compared using unpaired Student's t-tests or Mann-Whitney U tests for parametric and non-parametric data, respectively. Changes after intervention will be evaluated using paired Student's t-tests or Wilcoxon tests, depending on the variable distribution. Pearson or Spearman correlation coefficients will be used to measure the strength of association between variables. In multivariable regression models, the relationship between two or more explanatory variables (independent variables) and a response variable (dependent variable) will be evaluated by fitting a linear equation to the obtained data. Qualitative data will be expressed in percentages, and proportions will be compared using a Chi-square test. All tests will use a 95% confidence interval, and differences will be considered statistically significant when p \<0.05.
Conditions
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Study Design
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CASE_CONTROL
CROSS_SECTIONAL
Study Groups
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Control Group without obesity
Control Group with periodontitis and without obesity
non-chirurgical periodontal treatment
The non-chirurgical periodontal treatment (scaling and root planing) is the gold standard procedure in therapy for periodontitis. It involves the mechanical removal of plaque and bacterial deposits, creating a local microbial environment in harmony with periodontal health and promoting the replacement of damaged periodontal tissues with collagen-rich connective tissues. This favors a shift in the composition of the oral microbiota from a community dominated by Gram-negatives to one dominated by Gram-positives.
Obesity Group
Obesity Group with periodontitis
non-chirurgical periodontal treatment
The non-chirurgical periodontal treatment (scaling and root planing) is the gold standard procedure in therapy for periodontitis. It involves the mechanical removal of plaque and bacterial deposits, creating a local microbial environment in harmony with periodontal health and promoting the replacement of damaged periodontal tissues with collagen-rich connective tissues. This favors a shift in the composition of the oral microbiota from a community dominated by Gram-negatives to one dominated by Gram-positives.
Interventions
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non-chirurgical periodontal treatment
The non-chirurgical periodontal treatment (scaling and root planing) is the gold standard procedure in therapy for periodontitis. It involves the mechanical removal of plaque and bacterial deposits, creating a local microbial environment in harmony with periodontal health and promoting the replacement of damaged periodontal tissues with collagen-rich connective tissues. This favors a shift in the composition of the oral microbiota from a community dominated by Gram-negatives to one dominated by Gram-positives.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* Periodontitis will be diagnosed according to the definition of the Centers for Disease Control and Prevention / American Academy of Periodontology (CDC/AAP).
2. Men/Women with obesity:
* Body mass index (BMI) ≥30 kg/m2 (WHO 2000)
Exclusion Criteria
* Having infectious diseases
* Having other oral inflammatory diseases,
* Having received periodontal treatment in the past six months or antibiotics in the previous three months, undergoing systemic anti-inflammatory treatment,
* Pregnancy or lactation
* Serious illnesses, congenital adrenal hyperplasia, virilizing tumors, hypothyroidism, Cushing's syndrome, prolactinomas, cardiovascular diseases, or diabetes mellitus.
* Alcohol or drug abuse
* Psychiatric disorders.
18 Years
69 Years
ALL
Yes
Sponsors
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Instituto de Salud Carlos III
OTHER_GOV
Milagros Rocha Barajas
OTHER
Responsible Party
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Milagros Rocha Barajas
Senior Postdoctoral Researcher
Principal Investigators
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Milagros Rocha, PhD
Role: PRINCIPAL_INVESTIGATOR
FISABIO-HOSPITAL DR PESET
Locations
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University Hospital Dr Peset
Valencia, Valencia, Spain
University Hospital Dr. Peset
Valencia, Valencia, Spain
Countries
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References
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Fruhbeck G. Obesity: Screening for the evident in obesity. Nat Rev Endocrinol. 2012 Oct;8(10):570-2. doi: 10.1038/nrendo.2012.165. Epub 2012 Sep 4. No abstract available.
Rocha VZ, Libby P. Obesity, inflammation, and atherosclerosis. Nat Rev Cardiol. 2009 Jun;6(6):399-409. doi: 10.1038/nrcardio.2009.55. Epub 2009 Apr 28.
Tonetti MS. Periodontitis and risk for atherosclerosis: an update on intervention trials. J Clin Periodontol. 2009 Jul;36 Suppl 10:15-9. doi: 10.1111/j.1600-051X.2009.01417.x.
Virto L, Cano P, Jimenez-Ortega V, Fernandez-Mateos P, Gonzalez J, Esquifino AI, Sanz M. Obesity and periodontitis: An experimental study to evaluate periodontal and systemic effects of comorbidity. J Periodontol. 2018 Feb;89(2):176-185. doi: 10.1902/jop.2017.170355. Epub 2018 Feb 16.
Isaza-Guzman DM, Medina-Piedrahita VM, Gutierrez-Henao C, Tobon-Arroyave SI. Salivary Levels of NLRP3 Inflammasome-Related Proteins as Potential Biomarkers of Periodontal Clinical Status. J Periodontol. 2017 Dec;88(12):1329-1338. doi: 10.1902/jop.2017.170244. Epub 2017 Jul 10.
Trexler M, Patthy L. Residues Cys-1 and Cys-79 are not essential for refolding of reduced-denatured kringle 4 fragment of human plasminogen. Biochim Biophys Acta. 1984 Jun 28;787(3):275-80. doi: 10.1016/0167-4838(84)90320-0.
Moura MF, Navarro TP, Silva TA, Cota LOM, Soares Dutra Oliveira AM, Costa FO. Periodontitis and Endothelial Dysfunction: Periodontal Clinical Parameters and Levels of Salivary Markers Interleukin-1beta, Tumor Necrosis Factor-alpha, Matrix Metalloproteinase-2, Tissue Inhibitor of Metalloproteinases-2 Complex, and Nitric Oxide. J Periodontol. 2017 Aug;88(8):778-787. doi: 10.1902/jop.2017.170023. Epub 2017 May 11.
Martinez-Herrera M, Lopez-Domenech S, Silvestre FJ, Silvestre-Rangil J, Banuls C, Victor VM, Rocha M. Chronic periodontitis impairs polymorphonuclear leucocyte-endothelium cell interactions and oxidative stress in humans. J Clin Periodontol. 2018 Dec;45(12):1429-1439. doi: 10.1111/jcpe.13027. Epub 2018 Nov 20.
Chapple IL, Matthews JB. The role of reactive oxygen and antioxidant species in periodontal tissue destruction. Periodontol 2000. 2007;43:160-232. doi: 10.1111/j.1600-0757.2006.00178.x. No abstract available.
Kanzaki H, Wada S, Narimiya T, Yamaguchi Y, Katsumata Y, Itohiya K, Fukaya S, Miyamoto Y, Nakamura Y. Pathways that Regulate ROS Scavenging Enzymes, and Their Role in Defense Against Tissue Destruction in Periodontitis. Front Physiol. 2017 May 30;8:351. doi: 10.3389/fphys.2017.00351. eCollection 2017.
Park MH, Jeong SY, Na HS, Chung J. Porphyromonas gingivalis induces autophagy in THP-1-derived macrophages. Mol Oral Microbiol. 2017 Feb;32(1):48-59. doi: 10.1111/omi.12153. Epub 2016 Feb 24.
Tonetti MS, D'Aiuto F, Nibali L, Donald A, Storry C, Parkar M, Suvan J, Hingorani AD, Vallance P, Deanfield J. Treatment of periodontitis and endothelial function. N Engl J Med. 2007 Mar 1;356(9):911-20. doi: 10.1056/NEJMoa063186.
Luan X, Zhou X, Naqvi A, Francis M, Foyle D, Nares S, Diekwisch TGH. MicroRNAs and immunity in periodontal health and disease. Int J Oral Sci. 2018 Aug 6;10(3):24. doi: 10.1038/s41368-018-0025-y.
Yoneda T, Tomofuji T, Ekuni D, Azuma T, Maruyama T, Fujimori K, Sugiura Y, Morita M. Serum microRNAs and chronic periodontitis: A case-control study. Arch Oral Biol. 2019 May;101:57-63. doi: 10.1016/j.archoralbio.2019.03.009. Epub 2019 Mar 13.
Other Identifiers
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PI22/1009
Identifier Type: -
Identifier Source: org_study_id
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