xml: <clinical_study>
    <!-- This xml conforms to an XML Schema at:
      https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
    <required_header>
      <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
      <link_text>Link to the current ClinicalTrials.gov record.</link_text>
      <url>https://clinicaltrials.gov/ct2/show/NCT06040164</url>
    </required_header>
    <id_info>
      <org_study_id>SMILE</org_study_id>
      <nct_id>NCT06040164</nct_id>
    </id_info>
    <brief_title>Oral Endocannabinoids in People With Prediabetes and Diabetes</brief_title>
    <acronym>SMILE</acronym>
    <official_title>Molecular Study of Oral Dysbacteriosis in People With Prediabetes and Diabetes</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Fundación Pública Andaluza para la Investigación de Málaga en Biomedicina y Salud</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>Fundación Pública Andaluza para la Investigación de Málaga en Biomedicina y Salud</source>
    <oversight_info>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        This study evaluates the relationship of endocannabinoids in saliva with inflammation and&#xD;
        oral dysbacteriosis present in people with periodontal disease and prediabetes/type 2&#xD;
        diabetes&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        Diabetes is a disease that affects millions of people worldwide, and the number of cases is&#xD;
        expected to continue to increase in the coming years. Type 2 diabetes (T2D) is the most&#xD;
        common form of diabetes and is closely related to prediabetes, a condition in which blood&#xD;
        glucose levels are high but not high enough to be diagnosed as diabetes. Both prediabetes and&#xD;
        T2D increase the risk of cardiovascular disease and are also associated with diseases of the&#xD;
        oral cavity, such as dental caries and periodontal disease. The presence of pathogenic&#xD;
        bacteria in the mouth has been linked to these diseases. The endocannabinoid system, a&#xD;
        signaling system in the body that regulates various biological processes, has been found to&#xD;
        play an important role in energy homeostasis and is implicated in obesity, prediabetes, and&#xD;
        T2D. This study seeks to investigate the role of endocannabinoids and related lipids in&#xD;
        diseases of the oral cavity in the context of prediabetes and T2D. A bidirectional&#xD;
        relationship has been observed between periodontitis and T2D, with inflammation playing a&#xD;
        central role in both diseases. Although subtle differences in the microbial composition of&#xD;
        the mouth have been identified in people with diabetes, the exact mechanisms remain unclear.&#xD;
        Our findings could open up a promising line of research on the therapeutic potential of&#xD;
        cannabinoid drugs for the treatment of this type of complications in people with&#xD;
        prediabetes/T2D.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">October 1, 2023</start_date>
    <completion_date type="Anticipated">December 31, 2024</completion_date>
    <primary_completion_date type="Anticipated">June 30, 2024</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Case-Only</observational_model>
      <time_perspective>Cross-Sectional</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>Change in 2-arachidonoyl-glycerol (2-AG) levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in N-arachidonoylethanolamine (AEA) levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in N-palmitoylethanolamine (PEA) levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in N-oleoylethanolamine (OEA) levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in N-palmitoylethanolamine (DHEA) levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in 2-linoleoyl-glycerol (2-LG) levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in 2-oleoyl-glycerol (2-OG) levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Change in interleukin-1β levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in interleukin-6 levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in interleukin-8 levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in interleukin-10 levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in interleukin-17 levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in leptin levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in vascular endothelial growth factor (VEGF) levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in Interferon gamma (IFN)-γ levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in Tumor necrosis factor alpha (TNF)-α levels in saliva and plasma</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in pmol/ml</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in oral bacteriological profile</measure>
      <time_frame>Basal</time_frame>
      <description>Bacterial 16S rRNA amplicon of the following bacterial strains: Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Prevotella intermedia, Fusobacterium nucleatum, Parvimonas micra, Campylobacter rectus, Eikenella corroe, Veillonella parvula and Actinomyces naeslundii for periodontal disease; and Streptococcus mutans, S. sanguis, S. mitior, S. salivarius and S. milleri for dental caries. Unit of Measurement: Fold-increase over reference genes, delta-delta Ct method.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in Fasting glucose levels</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in mg/dl</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in insulin levels</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in mUI/mL</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes from baseline HOMA-IR levels</measure>
      <time_frame>Basal</time_frame>
      <description>HOMA-IR = [blood insulin (mu/L) × Blood glucose (mmol/L)]/22.5</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes from baseline HOMA2-IR levels</measure>
      <time_frame>Basal</time_frame>
      <description>The homeostasis model assessment computational method is used to estimate insulin resistance (HOMA2-IR) from fasting plasma glucose and insulin. The HOMA2-IR is the reciprocal of insulin sensitivity (%S), as a percentage of a normal reference population (normal young adult). A higher score indicates a lower insulin sensitivity.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes from baseline HOMA2%S levels</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in %</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes from baseline HOMA2%B levels</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in %</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes from baseline QUICKY levels</measure>
      <time_frame>Basal</time_frame>
      <description>QUICKY = 1 / (log(fasting insulin μU/mL) + log(fasting glucose mg/dL))</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes from baseline HbA1c levels</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in %</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>BMI (body mass index) changes</measure>
      <time_frame>Basal</time_frame>
      <description>Calculated as weight ⁄ height (kg/m2)</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in waist circumference</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in cm</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in waist/hip ratio</measure>
      <time_frame>Basal</time_frame>
      <description>Calculated as waist measurement (cm) divided by hip measurement (cm) (W⁄H)</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in waist/height ratio</measure>
      <time_frame>Basal</time_frame>
      <description>Calculated as waist measurement (cm) divided by height measurement (cm), (W/He)</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in blood pressure</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in mmHg</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in triglycerides</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in mg/dL</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in total cholesterol</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in mg/dL</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in HDL cholesterol</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in mg/dL</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in LDL cholesterol</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in mg/dL</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in sialometry</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in mL/min</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in salivary viscosity</measure>
      <time_frame>Basal</time_frame>
      <description>Measured in poise (1 g·(s·cm)-1)</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Changes in salivary pH</measure>
      <time_frame>Basal</time_frame>
      <description>Logarithm of hydrogen ion concentration</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Oral health impact profile</measure>
      <time_frame>Basal</time_frame>
      <description>The Oral Health Impact Profile will be assessed by using the OHIP-14sp questionnaire, which is one of the most internationally spread indicators of oral health-related quality of life and it is used to measure the impact of oral conditions on quality of life to complement clinical data in cross-sectional and longitudinal studies. The OHIP-14 is a self-filled questionnaire that focuses on seven dimensions of impact (functional limitation, pain, psychological discomfort, physical disability, psychological disability, social disability and handicap) with participants being asked to respond according to frequency of impact on a 5-point Likert scale coded never (score 0), hardly ever (score 1), occasionally (score2), fairly often (score 3) and very often (score 4) using a twelve-months recall period.</description>
    </secondary_outcome>
    <number_of_groups>4</number_of_groups>
    <enrollment type="Anticipated">60</enrollment>
    <condition>PreDiabetes</condition>
    <condition>Diabetes Mellitus, Type 2</condition>
    <condition>Obesity</condition>
    <condition>Oral Dysbiosis</condition>
    <condition>Mouth Disease</condition>
    <arm_group>
      <arm_group_label>Ob/Pre/H</arm_group_label>
      <description>obesity, prediabetes and healthy mouth</description>
    </arm_group>
    <arm_group>
      <arm_group_label>Ob/Pre/OCD</arm_group_label>
      <description>obesity, prediabetes and oral cavity disease</description>
    </arm_group>
    <arm_group>
      <arm_group_label>Ob/Diab/H</arm_group_label>
      <description>obesity, diabetes and healthy mouth</description>
    </arm_group>
    <arm_group>
      <arm_group_label>Ob/Diab/OCD</arm_group_label>
      <description>obesity, diabetes and oral cavity disease</description>
    </arm_group>
    <intervention>
      <intervention_type>Other</intervention_type>
      <intervention_name>Observational study</intervention_name>
      <description>No intervention will be performed</description>
      <arm_group_label>Ob/Diab/H</arm_group_label>
      <arm_group_label>Ob/Diab/OCD</arm_group_label>
      <arm_group_label>Ob/Pre/H</arm_group_label>
      <arm_group_label>Ob/Pre/OCD</arm_group_label>
    </intervention>
    <biospec_retention>Samples With DNA</biospec_retention>
    <biospec_descr>
      <textblock>
        Saliva samples will be collected under resting conditions using the passive drooling method,&#xD;
        in 15 mL tubes, every 1 min, for 5 min in the same tube. Along with the saliva samples,&#xD;
        trained personnel will collect 9 ml of blood samples, under resting conditions, in&#xD;
        ethylenediaminetetraacetic acid (EDTA) tubes.&#xD;
      </textblock>
    </biospec_descr>
    <eligibility>
      <study_pop>
        <textblock>
          The patients to enroll will come from three clinical studies led by our unit: The Pizarra&#xD;
          study, an epidemiological study of the Endocrinology and Nutrition unit of the Regional&#xD;
          Hospital of Malaga that has provided detailed information on anthropometric and biochemical&#xD;
          parameters, eating habits and lifestyle in a cohort of about 1700 subjects; the di@bet.es&#xD;
          study, a national epidemiological study carried out on a sample of more than 5,000 people;&#xD;
          and the April study, a nutritional intervention study in people with obesity and&#xD;
          prediabetes. In addition, the obesity databases of the Endocrinology and Nutrition unit of&#xD;
          the Regional Hospital of Malaga will also be used.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Adults, both sexes (40-65 years)&#xD;
  &#xD;
            -  With obesity and prediabetes: BMI 30-40 and HbA1c 5.7-6.4&#xD;
  &#xD;
            -  With obesity and diabetes: BMI 30-40 and previous diagnosis of diabetes&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Pregnant women&#xD;
  &#xD;
            -  Diagnosis of some type of neoplasia or treated with radiotherapy and/or chemotherapy&#xD;
               in the last year.&#xD;
  &#xD;
            -  Ongoing inflammatory diseases (Crohn's disease, ulcerative colitis, arthritis, etc.)&#xD;
               and/or anti-inflammatory treatments&#xD;
  &#xD;
            -  Presence of systemic diseases of vital organs&#xD;
  &#xD;
            -  Participants in treatment with drugs that could alter salivary flow&#xD;
  &#xD;
            -  Smokers&#xD;
  &#xD;
            -  Participants who have not followed the specifications prior to sampling&#xD;
  &#xD;
            -  Participants who did not sign the informed consent&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>40 Years</minimum_age>
      <maximum_age>65 Years</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Francisco J Bermúdez-Silva, PhD</last_name>
      <role>Principal Investigator</role>
      <affiliation>Hospital Regional Universitario de Málaga - FIMABIS</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Rodolfo M Ortiz Flores, PhD</last_name>
      <phone>951 29 03 43 / 951 03 01 17</phone>
      <email>rodolfo.ortiz@ibima.eu</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>Francisco J Bermúdez-Silva, PhD</last_name>
      <phone>951 29 03 43 / 951 03 01 17</phone>
      <email>javier.bermudez@ibima.eu</email>
    </overall_contact_backup>
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    <reference>
      <citation>Prestifilippo JP, Fernandez-Solari J, de la Cal C, Iribarne M, Suburo AM, Rettori V, McCann SM, Elverdin JC. Inhibition of salivary secretion by activation of cannabinoid receptors. Exp Biol Med (Maywood). 2006 Sep;231(8):1421-9. doi: 10.1177/153537020623100816.</citation>
      <PMID>16946411</PMID>
    </reference>
    <reference>
      <citation>Matias I, Gatta-Cherifi B, Tabarin A, Clark S, Leste-Lasserre T, Marsicano G, Piazza PV, Cota D. Endocannabinoids measurement in human saliva as potential biomarker of obesity. PLoS One. 2012;7(7):e42399. doi: 10.1371/journal.pone.0042399. Epub 2012 Jul 31.</citation>
      <PMID>22860123</PMID>
    </reference>
    <reference>
      <citation>Piscitelli F, Di Marzo V. &quot;Redundancy&quot; of endocannabinoid inactivation: new challenges and opportunities for pain control. ACS Chem Neurosci. 2012 May 16;3(5):356-63. doi: 10.1021/cn300015x. Epub 2012 Feb 27.</citation>
      <PMID>22860203</PMID>
    </reference>
    <reference>
      <citation>Andreis K, Billingsley J, Naimi Shirazi K, Wager-Miller J, Johnson C, Bradshaw H, Straiker A. Cannabinoid CB1 receptors regulate salivation. Sci Rep. 2022 Aug 19;12(1):14182. doi: 10.1038/s41598-022-17987-2.</citation>
      <PMID>35986066</PMID>
    </reference>
    <reference>
      <citation>Oral health. Global Burden of Disease Study 2019. Published 2019. Accessed September 30, 2022. https://www.who.int/news-room/fact-sheets/detail/oral-health</citation>
    </reference>
    <reference>
      <citation>Ramfjord SP. The Periodontal Disease Index (PDI). J Periodontol. 1967 Nov-Dec;38(6):Suppl:602-10. doi: 10.1902/jop.1967.38.6.602. No abstract available.</citation>
      <PMID>5237683</PMID>
    </reference>
    <verification_date>March 2023</verification_date>
    <study_first_submitted>July 19, 2023</study_first_submitted>
    <study_first_submitted_qc>September 13, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">September 15, 2023</study_first_posted>
    <last_update_submitted>September 13, 2023</last_update_submitted>
    <last_update_submitted_qc>September 13, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">September 15, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>Endocannabinoids</keyword>
    <keyword>Prediabetes</keyword>
    <keyword>Diabetes Mellitus Type 2</keyword>
    <keyword>Obesity</keyword>
    <keyword>Oral Dysbiosis</keyword>
    <keyword>Oral Disease</keyword>
    <keyword>Cannabinoids</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Mouth Diseases</mesh_term>
      <mesh_term>Diabetes Mellitus</mesh_term>
      <mesh_term>Diabetes Mellitus, Type 2</mesh_term>
      <mesh_term>Prediabetic State</mesh_term>
      <mesh_term>Glucose Intolerance</mesh_term>
      <mesh_term>Dysbiosis</mesh_term>
    </condition_browse>
    <provided_document_section>
      <provided_document>
        <document_type>Study Protocol</document_type>
        <document_has_protocol>Yes</document_has_protocol>
        <document_has_icf>No</document_has_icf>
        <document_has_sap>No</document_has_sap>
        <document_date>June 29, 2023</document_date>
        <document_url>https://ClinicalTrials.gov/ProvidedDocs/64/NCT06040164/Prot_000.pdf</document_url>
      </provided_document>
    </provided_document_section>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: download date: ClinicalTrials.gov processed this data on September 20, 2023
  link text: Link to the current ClinicalTrials.gov record.
  url: https://clinicaltrials.gov/ct2/show/NCT06040164
  org study id: SMILE
  nct id: NCT06040164
  lead sponsor: 
  is fda regulated drug: No
  is fda regulated device: No
  This study evaluates the relationship of endocannabinoids in saliva with inflammation and
        oral dysbacteriosis present in people with periodontal disease and prediabetes/type 2
        diabetes
  Diabetes is a disease that affects millions of people worldwide, and the number of cases is
        expected to continue to increase in the coming years. Type 2 diabetes (T2D) is the most
        common form of diabetes and is closely related to prediabetes, a condition in which blood
        glucose levels are high but not high enough to be diagnosed as diabetes. Both prediabetes and
        T2D increase the risk of cardiovascular disease and are also associated with diseases of the
        oral cavity, such as dental caries and periodontal disease. The presence of pathogenic
        bacteria in the mouth has been linked to these diseases. The endocannabinoid system, a
        signaling system in the body that regulates various biological processes, has been found to
        play an important role in energy homeostasis and is implicated in obesity, prediabetes, and
        T2D. This study seeks to investigate the role of endocannabinoids and related lipids in
        diseases of the oral cavity in the context of prediabetes and T2D. A bidirectional
        relationship has been observed between periodontitis and T2D, with inflammation playing a
        central role in both diseases. Although subtle differences in the microbial composition of
        the mouth have been identified in people with diabetes, the exact mechanisms remain unclear.
        Our findings could open up a promising line of research on the therapeutic potential of
        cannabinoid drugs for the treatment of this type of complications in people with
        prediabetes/T2D.
  observational model: Case-Only
  time perspective: Cross-Sectional
  measure: Change in 2-arachidonoyl-glycerol (2-AG) levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in N-arachidonoylethanolamine (AEA) levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in N-palmitoylethanolamine (PEA) levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in N-oleoylethanolamine (OEA) levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in N-palmitoylethanolamine (DHEA) levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in 2-linoleoyl-glycerol (2-LG) levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in 2-oleoyl-glycerol (2-OG) levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in interleukin-1β levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in interleukin-6 levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in interleukin-8 levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in interleukin-10 levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in interleukin-17 levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in leptin levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in vascular endothelial growth factor (VEGF) levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in Interferon gamma (IFN)-γ levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Change in Tumor necrosis factor alpha (TNF)-α levels in saliva and plasma
  time frame: Basal
  description: Measured in pmol/ml
  measure: Changes in oral bacteriological profile
  time frame: Basal
  description: Bacterial 16S rRNA amplicon of the following bacterial strains: Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Prevotella intermedia, Fusobacterium nucleatum, Parvimonas micra, Campylobacter rectus, Eikenella corroe, Veillonella parvula and Actinomyces naeslundii for periodontal disease; and Streptococcus mutans, S. sanguis, S. mitior, S. salivarius and S. milleri for dental caries. Unit of Measurement: Fold-increase over reference genes, delta-delta Ct method.
  measure: Changes in Fasting glucose levels
  time frame: Basal
  description: Measured in mg/dl
  measure: Changes in insulin levels
  time frame: Basal
  description: Measured in mUI/mL
  measure: Changes from baseline HOMA-IR levels
  time frame: Basal
  description: HOMA-IR = [blood insulin (mu/L) × Blood glucose (mmol/L)]/22.5
  measure: Changes from baseline HOMA2-IR levels
  time frame: Basal
  description: The homeostasis model assessment computational method is used to estimate insulin resistance (HOMA2-IR) from fasting plasma glucose and insulin. The HOMA2-IR is the reciprocal of insulin sensitivity (%S), as a percentage of a normal reference population (normal young adult). A higher score indicates a lower insulin sensitivity.
  measure: Changes from baseline HOMA2%S levels
  time frame: Basal
  description: Measured in %
  measure: Changes from baseline HOMA2%B levels
  time frame: Basal
  description: Measured in %
  measure: Changes from baseline QUICKY levels
  time frame: Basal
  description: QUICKY = 1 / (log(fasting insulin μU/mL) + log(fasting glucose mg/dL))
  measure: Changes from baseline HbA1c levels
  time frame: Basal
  description: Measured in %
  measure: BMI (body mass index) changes
  time frame: Basal
  description: Calculated as weight ⁄ height (kg/m2)
  measure: Changes in waist circumference
  time frame: Basal
  description: Measured in cm
  measure: Changes in waist/hip ratio
  time frame: Basal
  description: Calculated as waist measurement (cm) divided by hip measurement (cm) (W⁄H)
  measure: Changes in waist/height ratio
  time frame: Basal
  description: Calculated as waist measurement (cm) divided by height measurement (cm), (W/He)
  measure: Changes in blood pressure
  time frame: Basal
  description: Measured in mmHg
  measure: Changes in triglycerides
  time frame: Basal
  description: Measured in mg/dL
  measure: Changes in total cholesterol
  time frame: Basal
  description: Measured in mg/dL
  measure: Changes in HDL cholesterol
  time frame: Basal
  description: Measured in mg/dL
  measure: Changes in LDL cholesterol
  time frame: Basal
  description: Measured in mg/dL
  measure: Changes in sialometry
  time frame: Basal
  description: Measured in mL/min
  measure: Changes in salivary viscosity
  time frame: Basal
  description: Measured in poise (1 g·(s·cm)-1)
  measure: Changes in salivary pH
  time frame: Basal
  description: Logarithm of hydrogen ion concentration
  measure: Oral health impact profile
  time frame: Basal
  description: The Oral Health Impact Profile will be assessed by using the OHIP-14sp questionnaire, which is one of the most internationally spread indicators of oral health-related quality of life and it is used to measure the impact of oral conditions on quality of life to complement clinical data in cross-sectional and longitudinal studies. The OHIP-14 is a self-filled questionnaire that focuses on seven dimensions of impact (functional limitation, pain, psychological discomfort, physical disability, psychological disability, social disability and handicap) with participants being asked to respond according to frequency of impact on a 5-point Likert scale coded never (score 0), hardly ever (score 1), occasionally (score2), fairly often (score 3) and very often (score 4) using a twelve-months recall period.
  arm group label: Ob/Pre/H
  description: obesity, prediabetes and healthy mouth
  arm group label: Ob/Pre/OCD
  description: obesity, prediabetes and oral cavity disease
  arm group label: Ob/Diab/H
  description: obesity, diabetes and healthy mouth
  arm group label: Ob/Diab/OCD
  description: obesity, diabetes and oral cavity disease
  intervention type: Other
  intervention name: Observational study
  description: No intervention will be performed
  arm group label: Ob/Diab/H
  arm group label: Ob/Diab/OCD
  arm group label: Ob/Pre/H
  arm group label: Ob/Pre/OCD
  Saliva samples will be collected under resting conditions using the passive drooling method,
        in 15 mL tubes, every 1 min, for 5 min in the same tube. Along with the saliva samples,
        trained personnel will collect 9 ml of blood samples, under resting conditions, in
        ethylenediaminetetraacetic acid (EDTA) tubes.
  study pop: 
  sampling method: Probability Sample
  criteria: 
  gender: All
  minimum age: 40 Years
  maximum age: 65 Years
  healthy volunteers: No
  last name: Francisco J Bermúdez-Silva, PhD
  role: Principal Investigator
  affiliation: Hospital Regional Universitario de Málaga - FIMABIS
  last name: Rodolfo M Ortiz Flores, PhD
  phone: 951 29 03 43 / 951 03 01 17
  email: rodolfo.ortiz@ibima.eu
  last name: Francisco J Bermúdez-Silva, PhD
  phone: 951 29 03 43 / 951 03 01 17
  email: javier.bermudez@ibima.eu
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  PMID: 12666949
  citation: Prestifilippo JP, Fernandez-Solari J, de la Cal C, Iribarne M, Suburo AM, Rettori V, McCann SM, Elverdin JC. Inhibition of salivary secretion by activation of cannabinoid receptors. Exp Biol Med (Maywood). 2006 Sep;231(8):1421-9. doi: 10.1177/153537020623100816.
  PMID: 16946411
  citation: Matias I, Gatta-Cherifi B, Tabarin A, Clark S, Leste-Lasserre T, Marsicano G, Piazza PV, Cota D. Endocannabinoids measurement in human saliva as potential biomarker of obesity. PLoS One. 2012;7(7):e42399. doi: 10.1371/journal.pone.0042399. Epub 2012 Jul 31.
  PMID: 22860123
  citation: Piscitelli F, Di Marzo V. "Redundancy" of endocannabinoid inactivation: new challenges and opportunities for pain control. ACS Chem Neurosci. 2012 May 16;3(5):356-63. doi: 10.1021/cn300015x. Epub 2012 Feb 27.
  PMID: 22860203
  citation: Andreis K, Billingsley J, Naimi Shirazi K, Wager-Miller J, Johnson C, Bradshaw H, Straiker A. Cannabinoid CB1 receptors regulate salivation. Sci Rep. 2022 Aug 19;12(1):14182. doi: 10.1038/s41598-022-17987-2.
  PMID: 35986066
  citation: Oral health. Global Burden of Disease Study 2019. Published 2019. Accessed September 30, 2022. https://www.who.int/news-room/fact-sheets/detail/oral-health
  citation: Ramfjord SP. The Periodontal Disease Index (PDI). J Periodontol. 1967 Nov-Dec;38(6):Suppl:602-10. doi: 10.1902/jop.1967.38.6.602. No abstract available.
  PMID: 5237683
  responsible party type: Sponsor
  mesh term: Mouth Diseases
  mesh term: Diabetes Mellitus
  mesh term: Diabetes Mellitus, Type 2
  mesh term: Prediabetic State
  mesh term: Glucose Intolerance
  mesh term: Dysbiosis
  provided document: 