UNIVERSIDAD COMPLUTENSE DE MADRID FACULTAD DE ODONTOLOGÍA TESIS DOCTORAL Asociación entre periodontitis y depresión: mecanismos moleculares Association of periodontitis and depression: molecular mechanisms MEMORIA PARA OPTAR AL GRADO DE DOCTOR PRESENTADA POR María Martínez Ferrero Directores Elena Figuero Ruiz David Herrera González Madrid © María Martínez Ferrero, 2023 1 UNIVERSIDAD COMPLUTENSE DE MADRID DOCTORADO EN CIENCIAS ODONTOLÓGICAS FACULTAD DE ODONTOLOGÍA TESIS DOCTORAL Asociación entre periodontitis y depresión: mecanismos moleculares. - Association of periodontitis and depression: molecular mechanisms. MEMORIA PARA OPTAR AL GRADO DE DOCTOR PRESENTADO POR María Martínez Ferrero Directores Elena Figuero Ruiz David Herrera González 2 3 A mi familia 4 5 AGRADECIMIENTOS Hace años me enseñaron que se debe disfrutar de los procesos y no solo de los resultados. Eso he intentado hacer durante el transcurso de esta tesis, durante el que he sido tremendamente feliz. Por ello, quiero agradecer a todo el mundo que me lo ha hecho posible. En primer lugar, me gustaría dar las gracias a la Prof. Elena Figuero por confiar siempre en mi. Cuando me propusiste hace 5 años participar en un estudio de experimentación animal jamás pensé que este tema llegaría a apasionarme tanto, pero me sentía tan segura “de tu mano” que sabía que solo podría traer éxitos. Gracias Elena por haberme dejado disfrutar de la investigación y de tus enseñanzas. Al Prof. David Herrera, por animarme a esforzarme para intentar que todo el mundo entendiera los resultados de esta tesis. Te agradezco infinitamente tus siempre sinceros consejos, que me han sido de gran ayuda. Al Prof. Mariano Sanz, por su ejemplo de dedicación y esfuerzo como parte fundamental del éxito, por su confianza y porque en su labor como docente hace que sus alumnos nos apasionemos por la periodoncia. Es un honor formar parte de este increíble grupo que has formado. Al equipo del Laboratorio de Investigación de la Facultad de Odontología de la UCM, en especial a Leire Virto, quien me enseñó todo lo que sé sobre este modelo animal; y a María José Marín y Nagore Ambrosio, quienes me enseñaron a interpretar con mucha paciencia los resultados microbiológicos de este estudio. Además, gracias a las tres por vuestra amistad y estar siempre disponibles para mi. 6 Al grupo del Prof. Juan Carlos Leza, que tanta luz nos ha dado en el curso de los experimentos que conforman esta tesis. En especial a David Martín y Borja García, por estar siempre dispuestos a todo y regalarnos siempre una sonrisa en las largas mañanas del animalario. Os admiro muchísimo como investigadores, y os tengo un gran cariño en lo personal. Esperemos que lo que esta tesis ha unido, nada lo separe, y que esta colaboración científica y amistad duren mucho tiempo. Un agradecimiento especial también a Stefanie Mallan-Müller, por permitirme tan amablemente colaborar en su trabajo de revisión. Gracias a todos mis profesores del Máster de Periodoncia de la UCM. Habéis sido una gran inspiración. En especial a la Dra. Bettina Alonso, porque desde su tutoría de mi TFG me enseñó la manera rigurosa de trabajar en este grupo de investigación, la fuerza con la que se deben perseguir los sueños, y probablemente gracias a ella tomara las decisiones que me han llevado a presentar esta tesis; al Dr. Eduardo Montero por acompañarme y enseñarme tanto en mis primeros pasos en la investigación y ayudarme tantos días en el animalario a pesar de sus muchas otras obligaciones; a la Dra. Merche López-Durán, quien siempre ha tenido un buen consejo para darme; y a los Dres. Ion Zabalegui, María Riobóo e Ignacio Sanz, quienes me han hecho ilusionarme con nuevos proyectos para mi etapa post- doctoral. Gracias a todos por vuestra confianza. Thanks to Prof. Francesco D´Aiuto, for allowing me to do a research traineeship at Eastman Dental Institute, for inspiring me, and encouraging me to continue enjoying data analysis despite not finding the expected results. Gracias a todos mis compañeros del Máster de Periodoncia, con los que tantas horas he compartido en estos últimos años. Cada uno de vosotros sois únicos y especiales y os llevaré siempre a mi lado. En especial, a Carolina, Jaime, David y Víctor por haber sido mi gran apoyo, por entenderme con la mirada bajo la mascarilla, por 7 permitirme ser tal y como soy, por las risas y los momentos de confidencias. También sois mi familia. A mis amigas, a las que siempre han estado ahí y a las que la vida ha ido presentándome en los últimos años. Muchas gracias por haberos alegrado tanto en cada uno de mis éxitos y haberme acompañado en mis fracasos. Gracias a mis padres, Carmen y Joaquín, por haberme enseñado la importancia de la constancia y el trabajo duro, y porque su orgullo hacia mi es mi mejor motivación. Gracias a Bea, por todo, porque tenerte cerca es la mayor suerte de mi vida. Gracias a los Ninos, por quererme incondicionalmente. Gracias a toda mi familia por estar siempre disponibles para mi a pesar de las horas que yo no les he podido dedicar en los últimos años. Soy la más afortunada por teneros. Gracias a Gon, por recomendar los mejores podcasts de la historia, esenciales para esta tesis, pero, sobre todo, por acompañarme siempre al fin del mundo. 8 9 PREFACE Conducting and preparing the present project was possible, among other collaborations and supports, thanks to a research grant from Santander-University Complutense of Madrid Projects in 2017 (PR41/17-20979; principal investigator: Elena Figuero), a MINECO-FEDER grant (PD2019-109033RB-100, principal investigators: Juan Carlos Leza and Elena Figuero), and a Training of Research Personnel Contract (Complutense University of Madrid CT82/20-CT83/20), during which a three-month online collaboration and three-month research stay in the Periodontology Department, Eastman Dental Institute, University College, London (United Kingdom), under the supervision of Prof. Francesco D´Aiuto, was done. The present project is based on the following articles: Study #1: Martínez M., Postolache T.T., García-Bueno B., Leza J.C., Figuero E., Lowry C.A., Malan-Müller S. The Role of the Oral Microbiota Related to Periodontal Diseases in Anxiety, Mood and Trauma- and Stress-Related Disorders. Frontiers in Psychiatry. 2022 Jan; 12:814177. doi: 10.3389/fpsyt.2021.814177. Study #2: Martínez M., Martín-Hernández D., Virto L., MacDowell K.S., Montero E., González-Bris A., Marín M.J., Ambrosio N., Herrera D., Leza J.C., Sanz M., García-Bueno B., Figuero E. Periodontal diseases and depression: A pre-clinical in vivo study. Journal of Clinical Periodontology. 2021 Jan; 00:1-25. doi: 10.1111/jcpe.13420. Study #3: Martín-Hernández D., Martínez M., Robledo-Montaña J., Muñoz-López M., Virto L., Ambrosio N., Marín M.J., Montero E., Herrera D., Sanz M., Leza J.C., Figuero E., García-Bueno B. Blood-brain barrier dysfunction and the sphingosine-1- phosphate pathways as mechanisms contributing to neuroinflammation in a pre- 10 clinical experimental in vivo model of periodontitis and depression. Journal of Clinical Periodontology. 2023 Jan; doi: 10.1111/jcpe.13780. 11 INDEX Abbreviations ....................................................................................................................... 13 ABSTRACT ......................................................................................................................... 17 RESUMEN .......................................................................................................................... 20 INTRODUCTION .............................................................................................................. 25 1- Central Nervous System Disorders .................................................................... 25 2- Depressive Disorders ............................................................................................ 26 2.1. Classification and prevalence ........................................................................... 27 2.2. Diagnostic criteria .............................................................................................. 29 2.3. Etiopathogenesis: inflammatory theory of psychiatric disorders. .............. 31 2.4. Depression models in rodents .......................................................................... 38 3- Periodontal diseases .............................................................................................. 40 3.1- Classification and prevalence ........................................................................... 40 3.2. Etiopathogenesis ................................................................................................. 42 3.3. Interaction between periodontal and systemic diseases .............................. 44 3.4. Periodontitis models in rodents ....................................................................... 47 4- Association of periodontitis and depression ..................................................... 49 4.1. Epidemiology ...................................................................................................... 49 4.2. Biologic Plausibility ........................................................................................... 50 JUSTIFICATION ................................................................................................................ 61 HYPOTHESIS AND OBJECTIVES .................................................................................. 65 MATERIALS AND METHODS. RESULTS .................................................................... 70 Study #1 .......................................................................................................................... 73 Study #2 .......................................................................................................................... 97 Study #3 ........................................................................................................................ 125 12 DISCUSSION ................................................................................................................... 145 1- Theoretical basis of the association between periodontitis and depression 145 2- Developing an experimental model of periodontitis and depression ......... 148 3- Neuroinflammation: the key point of the association .................................... 152 4- Far beyond inflammatory markers: BBB and microglial alterations ........... 153 5- Strengths and limitations ................................................................................... 155 6- Future research .................................................................................................... 156 CONCLUSIONS ............................................................................................................... 159 REFERENCES .................................................................................................................. 161 13 Abbreviations AD: Alzheimer´s Disease APA: American Psychiatric Association APAF1: Apoptosis protease activator factor AVD: Atherosclerotic vascular disease BBB: Blood-brain barrier BDNF: Brain-derived neurotrophic factor BC: Before Christ BOP: Bleeding on probing CAL: Clinical attachment level CI: Confidence interval CMS: Chronic Mild Stress CNS: Central nervous system CRF: Corticotropin-releasing factor CRP: C reactive protein DALYs: Disability-adjusted life years DAMPs: Damage-Associated Molecular Patterns DSM: Diagnostic and Statistical Manual of Mental Disorders HPA: Hypothalamic-pituitary-adrenal hsCRP: High sensitivity CRP ICD: International Classification of Diseases IFN: Interferon Ig: Immunoglobulin IL: Interleukin LBP: Lipopolysaccharide binding protein LPS: Lipopolysaccharide MAPKs: Mitogen activated protein kinases MCP-1: Macrophage chemoattractant protein-1 MyD88: Myeloid differentiation primary response 88 (MyD88) 14 OR: Odds ratio P: Periodontitis (used in relation to the periodontitis groups of the preclinical in vivo study) PAI-1: Plasminogen activator inhibitor 1 PAMPs: Pathogen-Associated Molecular Patterns PPD: Probing pocket depth PRRs: Pathogen Recognition Receptors RR: Relative risk sICAM-1: Soluble intracellular adhesion molecule-1 S1P: Sphingosine-1-phosphate Sphk: Sphingosine kinase SGPL: Sphingosine lyase SGPP: Sphingosine phosphatase TLR: Toll-like receptors TNF- 𝜶: Tumour necrosis factor 𝛼 TrkB: Receptor tyrosine kinase B UI: Uncertainty interval WHO: World Health Organization WMD: Weighted mean difference YLDs: Years of healthy life lost due to disability ZO: Zonula occludens 15 16 17 ABSTRACT “Association of periodontitis and depression: molecular mechanisms”. Background: Depression is one of the most prevalent neuropsychiatric diseases, and it is associated to important disability consequences. However, different challenges in its study have not allowed for a full description of its pathophysiology. In the last two decades, one of the focuses of attention has been the inflammatory theory of neuropsychiatric diseases, as it was found that systemic inflammation and neuroinflammation play an important role in the etiopathogenesis of these conditions. Nevertheless, it is necessary to characterize more precisely what may be the possible origins of these inflammatory pathways. Periodontitis, on the other hand, is an inflammatory infectious disease that affects the tissues that surround and support the teeth, and it is clinically characterized by a progressive loss of attachment. There is strong evidence about the association between periodontitis and different systemic diseases such as diabetes or cardiovascular diseases, being systemic inflammation and the passage of bacteria from the subgingival biofilm into the bloodstream established as the main mediators of these associations. Epidemiological studies have shown an association between periodontitis and depression, however, the mechanisms by which both comorbidities are related need to be studied through preclinical in vivo studies. Aim: The main objective was to study the influence of oral microbiota and inflammatory mechanisms related to periodontitis in the association between periodontitis and depression. The specific aims were to summarize the known and potential molecular mechanisms (Study #1); to develop a preclinical in vivo model that allows central nervous system inflammation characterization, and periodontal bacteria determination in the brain (Study #2); and to study the permeability of the blood-brain barrier (BBB) and the role of sphingosine-1-phosphate (S1P) pathway in a combined model of periodontitis and depression in rats (Study #3). 18 Material and methods: Study #1: a comprehensive review of scientific literature was conducted on the molecular mechanisms that can potentially mediate the association between periodontitis and depression, including the role of oral microbiota related to periodontal diseases in immunological and inflammatory mechanisms associated to neuropsychiatric diseases, as well as the existing epidemiological evidence between these two diseases. Studies #2 and #3: A preclinical in vivo study was performed in Wistar:Han rats in which periodontitis (P) was induced by oral gavages with Porphyromonas gingivalis and Fusobacterium nucleatum for 12 weeks, and subsequently a depressive-like phenotype was induced using the Chronic Mild Stress (CMS) model. Four groups (n=12 rats/group) were obtained: periodontitis and CMS (P+CMS+); periodontitis without CMS (P+CMS-), CMS without periodontitis (P-CMS+) and control group (P-CMS-). In Study #2, periodontal clinical variables, alveolar bone levels, and depressive-like behavior were registered, and microbial counts and inflammatory mediators in plasma and frontal cortex were determined. In Study #3, expression of protein and mRNA levels, and fluorescence immunohistochemical analyses were performed to characterize BBB permeability, microglia and the S1P pathway. Results: Study #1: Periodontal pathogens have been implicated in the etiology and pathophysiology of neuropsychiatric diseases such as depression and neurodegenerative diseases, especially due to their alteration of the immune system. There are several potential mechanisms that may explain the relationship between periodontitis and depression, such as systemic inflammation, lipopolysaccharide (LPS) levels, bacterial translocation, dysregulation of the hypothalamic-pituitary- adrenal (HPA) axis, and neuroinflammation. Study #2: The P+CMS+ group demonstrated the highest alveolar bone levels, the highest expression of proinflammatory mediators (tumour necrosis factor- 𝛼, interleukin-1𝛽 and nuclear factor kappa-light-chain-enhancer or activated B cells) in the frontal cortex, probably related to LPS transport by APOA1 lipoprotein to the brain, and the detection of F. nucleatum in the brain of two rats. In addition, a dysregulation of the HPA stress axis 19 was detected, reflected by an increase in plasma corticosterone and glucocorticoid receptor in the frontal cortex. Study #3: The combined model of periodontitis and depression (P+CMS+) showed a decrease in the expression of BBB tight junction proteins (zonula occludens and occludin) and an increase in intercellular and vascular cell adhesion molecules (ICAM-1 and VCAM-1) and matrix metalloproteinase 9, suggesting a more severe disruption of the BBB. The enzymes of the S1P pathway were also altered. Conclusions: The association between periodontitis and depression is, at least in part, mediated by the influence of the oral microbiota related to periodontitis (“leaky mouth”) that would induce the activation of inflammatory mechanisms (neuroinflammation). An increase in the permeability of BBB or the S1P pathway have been shown to be connectors between both mechanisms that might explain the association between the two co-morbidities. 20 RESUMEN “Asociación ente periodontitis y depresión: mecanismos moleculares”. Antecedentes: La depresión es una de las enfermedades neuropsiquiátricas más prevalentes, y sus consecuencias a nivel de discapacidad generada son importantes. Sin embargo, diferentes desafíos en su estudio han hecho que su fisiopatología no se haya descrito por completo. En las dos últimas décadas, uno de los focos de atención se ha puesto sobre la teoría inflamatoria de las enfermedades neuropsiquiátricas al encontrarse evidencia de que la inflamación sistémica y la neuroinflamación jugaban un papel importante en la etiopatogenia de estas enfermedades. Sin embargo, es necesario caracterizar de manera más precisa cuáles pueden ser los posibles orígenes de estas rutas inflamatorias. La periodontitis, por su parte, es una enfermedad infecciosa inflamatoria que afecta a los tejidos de soporte del diente y que cursa con una progresiva pérdida de inserción. Existe evidencia fuerte acerca de la asociación entre la periodontitis y distintas enfermedades sistémicas como la diabetes o las enfermedades cardiovasculares, estableciéndose la inflamación sistémica y el paso de bacterias del biofilm subgingival al torrente sanguíneo como los principales mediadores de dichas asociaciones. Estudios epidemiológicos han demostrado la asociación entre periodontitis y depresión, sin embargo, los mecanismos por los que ambas comorbilidades se relacionan necesitan ser estudiados a través de estudios preclínicos in vivo. Objetivo: El objetivo principal fue estudiar la influencia de la microbiota oral y los mecanismos inflamatorios relacionados con la periodontitis en la asociación entre periodontitis y depresión. Los objetivos específicos fueron revisar los mecanismos moleculares conocidos y potenciales (Estudio #1); desarrollar un modelo preclínico in vivo que permitiera caracterizar la inflamación en el sistema nervioso central y la presencia de bacterias periodontales en el cerebro (Estudio #2), y estudiar la permeabilidad de la barreara hematoencefálica (BHE) y el papel de la vía de la 21 esfingosina-1-fosfato (S1P) en un modelo combinado de periodontitis y depresión en ratas (Estudio #3). Material y métodos: Estudio 1: Se realizó una revisión exhaustiva de la literatura científica sobre los mecanismos moleculares que potencialmente pueden mediar la asociación entre periodontitis y depresión, incluyendo el papel de la microbiota oral relacionada con las enfermedades periodontales en mecanismos inmunológicos e inflamatorios relacionados con las enfermedades neuropsiquiátricas, así como de la evidencia epidemiológica existente entre las dos enfermedades. Estudios 2 y 3: Se realizó un estudio preclínico in vivo en ratas Wistar:Han en el que se indujo periodontitis (P) mediante lavados orales con Porphyromonas gingivalis y Fusobacterium nucleatum durante 12 semanas, y posteriormente se indujo un fenotipo depresivo mediante el modelo Chronic Mild Stress (CMS). Se obtuvieron cuatro grupos (n=12 ratas/grupo): periodontitis y CMS (P+CMS+); periodontitis sin CMS (P+CMS-); CMS sin periodontitis (P-CMS+) y control (P-CMS-). En el Estudio 2 se midieron variables clínicas periodontales, niveles de hueso alveolar y comportamiento depresivo y se determinaron recuentos microbianos y mediadores inflamatorios en plasma y corteza frontal. En el Estudio 3 se determinó la expresión a nivel de proteína y de mRNA y se realizaron estudios inmunohistoquímicos de fluorescencia para caracterizar la permeabilidad de la BHE, la microglía y la vía de la S1P. Resultados: Estudio 1: Diferentes patógenos periodontales han sido implicados en la etiología y fisiopatología de enfermedades neuropsiquiátricas (como la depresión) y neurodegenerativas, especialmente por su alteración del sistema inmune. Existen varios mecanismos potenciales que pueden explicar la relación entre periodontitis y depresión, como son la inflamación sistémica, los niveles de lipopolisacárido (LPS) en plasma, la translocación bacteriana, la desregulación del eje hipotalámico- pituitario-adrenal (HPA) y la neuroinflamación. Estudio 2: El grupo P+CMS+ demostró los mayores niveles de pérdida de hueso alveolar, la mayor expresión de 22 mediadores pro-inflamatorios (factor de necrosis tumoral- 𝛼, interleuquina-1𝛽 y factor nuclear kappa B) en corteza frontal, relacionada con un transporte por parte de la lipoproteína APOA1 del LPS hasta el cerebro, y la detección de F. nucleatum en el cerebro de 2 ratas. Además, se detectó una desregulación del eje del estrés HPA reflejado por un incremento de corticosterona en plasma y receptor de glucocorticoides en corteza frontal. Estudio 3: El modelo combinado de periodontitis y depresión (P+CMS+) mostró una disminución en la expresión de proteínas de unión estrecha de la BHE (zonula occludens y ocludina) y un incremento en moléculas de adhesión intercelular y a la pared vascular (ICAM-1 y VCAM-1) y de la metaloproteinasa de la matriz 9, sugiriendo una disrupción más severa de la BHE. Las enzimas de la vía de la S1P se vieron igualmente alteradas. Conclusiones: La combinación de los resultados de los tres estudios demuestra que la asociación entre periodontitis y depresión está, al menos en parte, mediada por la influencia de la microbiota oral relacionada con la periodontitis (“leaky mouth” o “boca permeable”) en los mecanismos inflamatorios (neuroinflamación). Un aumento en la permeabilidad de la BHE o la vía de la S1P se han demostrado como conectores entre ambos mecanismos que explicarían la asociación entre las dos co- morbilidades. 23 24 25 INTRODUCTION 1- Central Nervous System Disorders The nervous system is the responsible for orchestrating the signals that leave from and arrive to the brain and spinal cord, which are the components of the central nervous system (CNS). The peripheral nervous system guides those signals to different parts of the body. From a structural point of view, the CNS is composed of three different cellular types: neurons, glial cells and vascular cells (Ransohoff and Cardona, 2010). They are organized as grey matter, which includes the set of these types of cells; and white matter, which includes mostly axons from neurons. These structures are protected against physical injuries by the skull, the meninges and the cerebrospinal fluid; and from toxins and pathogens by the blood-brain barrier (BBB). Central nervous system physiology can be altered by different disorders, being the most common the following: Traumatic brain injuries: damage to the brain from an external mechanical force that may result in temporary or permanent impairment (Capizzi et al., 2020). Brain tumors: abnormal tissue masses that result from an uncontrollable cell growth. There are two main groups termed primary and metastatic, depending on its primary origin (American Association of Neurological Surgeons). Neurodegenerative diseases: defined as progressive impairments of brain function (Cummings, 2016). Among them, Alzheimer´s disease (AD), Parkinson´s disease and amyotrophic lateral sclerosis are the most common (Checkoway et al., 2011). These diseases share features such as the alteration of proteins with neurotoxic properties (e.g., amyloid 𝛽 protein or microtubule associated protein tau) 26 that lead them to accumulate within the brain tissues provoking early neuronal death (Cummings, 2016). Neuropsychiatric diseases: alterations of higher cognition, emotion regulation or executive function due to specific behavioral or mental patterns. They negatively affect general health and are, especially mood disorders (e.g., major depressive disorder, bipolar disorder), the leading risk factors for suicide. The major effect they provoke on disease burden is disability, as stated by the World Health Organization (WHO) in 2001, who reported that neuropsychiatric disorders were responsible for 43% of all years of healthy life lost due to disability (YLDs) (Hyman, 2008, World Health Organization, 2001). Among them, depressive disorders are highly prevalent and important in terms of caused disability. 2- Depressive Disorders Depressive disorders englobe a series of mood related neuropsychiatric disorders associated with sadness, irritability, or emptiness. The attempt to understand depressive disorders goes back to 5th century before Christ (BC) when Hippocrates used the term “melancholia” to define those sadness and defection states (Hippocrates, 5th Century BC). From that moment, the attempt to study these disorders has been as incessant as challenging. Throughout much of the history, depression has been associated to euphoria describing cyclic forms of mental disorders. However, Karl Leonhard differentiated in 1957 between bipolar depression (maniac and depressive disorders) and unipolar depression (only depressive symptoms) (Leonhard, 1957). This differentiation has been maintained until today´s classifications of neuropsychiatric disorders. 27 2.1. Classification and prevalence Regarding depressive disorders, nowadays, there are two classification systems used as reference by the scientific community: The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) published by the American Psychiatric Association (APA) (American Psychiatry Association, 2013) and the International Classification of Diseases, 11th Revision (ICD-11) published by WHO (World Health Organization, 2019) (Table 1). The main difference between those classification systems is that DSM-5 classified in different chapters depressive disorders and bipolar disorders. However, ICD-11 places together both type of diseases under the “mood disorders”, as well as previous DSM system did (DSM-4). Major depressive disorder (DSM-5) is equivalent to single episode depressive disorder (ICD-11) and they represent the classic conditions of depressive disorders, which are characterized by episodes of 2 or more weeks of alterations in affect, cognition and neurovegetative functions. Sometimes this disease is diagnosed with a single episode, but most of the times this is a recurrent disorder. There is also a chronic presentation of the disorder which is termed dysthymia (DSM-5) or recurrent depressive disorder (ICD-11) which is related to a mood disturbance that lasts for at least 2 years in adults. From now on, when using the term “depression” in the present project, we will be referring to major depressive disorder (DSM-5) or single episode of depressive disorder (ICD-11). It should be noted that even if the WHO classification (ICD-11) still uses the term “episode”, this term doesn´t refer to an isolated state. On the contrary, symptoms must last for a minimum of two weeks for the diagnosis (see below 2.2). 28 Table 1: Differences between the Depressive Disorders classifications proposed by the American Psychiatry Association (DSM-5) and the World Health Organization (ICD-11). In 2019, according to the Global Burden of Disease Study, depressive disorders affected 279.6 million people worldwide. Even if it is the second most prevalent mental disorder, after anxiety disorders (disorders that include behavioral disturbances related to excessive fear or anxiety, which is the anticipation of a future threat), it accounted for the largest proportion of mental disorder disability-adjusted Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) International Classification of Diseases, 11th Revision (ICD-11) “Depressive Disorders” and “Bipolar and Related Disorder” belongs to two different chapters of the DSM-5 “Depressive Disorders” and “Bipolar Disorders” are within the section “Mental, behavioral or neurodevelopmental disorders- Mood disorders”. DEPRESSIVE DISORDERS Disruptive Mood Dysregulation Disorder Major Depressive Disorder Persistent Depressive Disorder (Dysthymia) Premenstrual Dysphoric Disorder Substance/ Medication-Induced Depressive Disorder Depressive Disorder Due to Another Medical Condition Other Specified Depressive Disorder Unspecified Depressive Disorder DEPRESSIVE DISORDERS Single episode Depressive Disorder Recurrent Depressive Disorder Dysthymic Disorder Mixed Depressive and Anxiety Disorder Premenstrual Dysphoric Disorder Other Specified Depressive Disorders Depressive Disorders, Unspecified BIPOLAR AND RELATED DISORDERS Bipolar I Disorder Bipolar II Disorder Cyclothymic Disorder Substance/ Medication-Induced Bipolar and Related Disorder Bipolar and Related Disorder Due to Another Medical Condition Specified Bipolar and Related Disorder Unspecified Bipolar and Related Disorder BIPOLAR AND RELATED DISORDERS Bipolar type I Disorder Bipolar type II Disorder Cyclothymic Disorder Other Specified Bipolar or Related Disorders Bipolar or Related Disorders, Unspecified OTHER DISORDERS Symptomatic and Course Presentations for Mood Episodes in Mood Disorders Substance-induced Mood Disorders Secondary Mood Syndrome Other Specified Mood Disorders Mood Disorders, Unspecified 29 life years (DALYs) (37.3%, 95% uncertainty interval [95% UI] [32.3; 43.0%]), being the sixth leading cause DALYs in people between 25 and 49 years when taking into consideration more than 350 diseases and injuries (Global Burden of Disease 2019 Mental Disorders Collaborators, 2022). These results agree with similar previous studies, that reported estimations of more than 300 million people suffering from depression, which represent an aggregate prevalence of 12.9% (95% confidence interval [95% CI] [11.1; 15.1]) (Lim et al., 2018). However, the COVID-19 pandemic has worsened these data reaching an increase of 27.6% (95% UI [25.1; 30.3] in cases of major depression (COVID-19 Mental Disorders Collaborators, 2021). 2.2. Diagnostic criteria The APA Diagnostic and Statistical Manual of Mental Disorders, together with the classification system of mental disorders, tries to overcome the difficulties in diagnosis of depression and other neuropsychiatric disorders (e.g., no biological objective marker) and gives unified diagnostic criteria for the scientific community. The diagnostic criteria for major depressive disorder are the following (Americal Psychiatry Association, 2013): A- At least five of the following symptoms have been present during the same 2- week period and associated to a change from previous functioning. It is also a requisite that at least one of them is depressed mood (a) or loss of interest or pleasure (b). Symptoms that are clearly attributable to another medical conditions are not considered to the diagnosis. a. Depressed mood most of the day, nearly every day, as indicated by either subjective report (e.g., feels sad, empty, or hopeless) or observation made by others (e.g., appears tearful). 30 b. Marked anhedonia, which is a diminished interest or pleasure in all, or almost all, activities most of the day, nearly every day (as indicated by either subjective account or observation by others). c. Significant weight change (loss when not dieting or gain) (e.g., a one month change of more than 5% of body weight), or change (decrease or increase) in appetite nearly every day. d. Insomnia or hyperemia nearly every day. e. Psychomotor agitation or retardation nearly every day, which is noticeable by others, nor only subjective ideas of restlessness or being slowed down). f. Fatigue or loss of energy nearly every day. g. Feelings of worthlessness or excessive or inappropriate guilt, which may be unrealistic, nearly every day (not merely self-reproval or guilt about being sick). h. Diminished capacity to think or concentrate, or indecisiveness, nearly every day (as indicated by either subjective account or observation by others). i. Recurrent thoughts of death (not just worry of dying), recurrent suicidal ideation with or without a specific plan, or a suicide attempt. B- The symptoms cause clinically significant suffering or deteriorations in social, professional, or other important areas. C- The episode is not attributable to the physiological effects of a substance or to another medical condition. Symptoms that are clearly attributable to another medical conditions are not considered to the diagnosis. These criteria (A-C) represent a major depression disorder. Symptoms that are clearly attributable to another medical conditions are not considered to the diagnosis. However, two other elements should be checked: 31 D- The occurrence of the major depressive episode is not better explained by schizoaffective disorder, schizophrenia, schizophreniform disorder, delusional disorder, or other specified and unspecified schizophrenia spectrum and other psychotic disorders. E- There has never been a maniac episode or a hypomanic episode. 2.3. Etiopathogenesis: inflammatory theory of psychiatric disorders. Understanding of depression pathophysiology is challenging because of different reasons. First, observing pathological alterations in the CNS, more specifically in the brain, is not as easy as for all other organs, as doing it in vivo in patients would require invasive techniques. Therefore, most of the evidence in this area comes from either post-mortem or neuroimaging techniques and preclinical studies. Second, the diagnosis is based on somehow subjective symptom-based approach. Third, its etiology is not completely elucidated, although there is a genetic predisposition, with a degree of heritability of around 30% (Sullivan et al., 2000, Wium-Andersen et al., 2020, Middeldorp et al., 2005, Petersen et al., 2016). Large genome-wide studies have tried to identify genetic risk factors for depression. However, there is no consistent and robust evidence in those studies of genuine genes associated to depression (Wray et al., 2018, Howard et al., 2019, Wu et al., 2020) as happens in other diseases such as AD that allow researchers to generate animal disease models based on genetic susceptibilities. Genetic predispositions seem to interact with environmental risk factors (Figure 1) (Köhler et al., 2018), being stress (e.g., stressful live events) highly implicated in depression genesis (Kendler et al., 1999). 32 Figure 1: Summary of the most relevant environmental risk factors and determinants for depression. Based on Köhler and co-workers, 2018. RR: relative risk; OR: odds ratio; HR: hazard ratio; CI: confidence interval. The Figure was partly generated using Servier Medical Art, provided by Servier, licensed under a Creative Commons Attribution 3.0 unported license. Because of the previously exposed challenges in the study of depression, many advances on the understanding of its pathophysiology have been made based on clinical observations. That is how the role of monoamines in depression was discovered. Iproniazid and imipramine were two drugs initially prescribed for tuberculosis and psychosis respectively, and that resulted “by chance” in potent antidepressant effects. On the contrary way occurred with reserpine, an antihypertensive that produced depression symptoms. These findings lead to the execution of preclinical and clinical studies that aimed to discern the involved drugs´ action mechanisms, and to prove its antidepressant effects in humans. Three monoamines were implicated in the mechanisms by which those drugs were related to depressed symptoms: serotonin, noradrenaline, and dopamine (Krishnan and Nestler, 2008). Iproniazid acted as a monoamine oxidase inhibitor and imipramine Dietary factors Vitamin D deficiency HR= 2.22 (95%CI: 1.42-3.47) Heavy cannabis use OR= 1.43 (95%CI: 1.00-2.04) Family factors Widowhood RR= 5.59 (95%CI: 3.79-8.23) Lifestyle Internet addiction OR= 2.77 (95%CI: 2.04-3.75) Infections Borna disease virus infection OR= 3.25 (95%CI: 1.62-6.54) Medical History Dry eye disease with Sjögren syndrome OR=4.25 (95% CI: 2.67-6.76) Metabolic abnormalities 4 of 5 metabolic risk factors OR=2.06 (95% CI: 1.59-2.68) Low birth weight (<2.5 kg) OR=1.38 (95% CI: 1.16-1.65) Low socioeconomic status OR=1.87 (95% CI: 1.62-2.16) Trauma and disasters Emotional abuse in childhood OR= 2.78 (95% CI: 1.89-4.09) Major Depressive Disorder- Risk factors and determinants Pregnancy & birth- related Drug substances Sociodemographic factors 33 inhibited reuptake of serotonin and noradrenalin. Some of the currently used antidepressants are based on those mechanisms which are focused on mitigate the monoamine deficit in the synaptic cleft (Berton and Nestler, 2006). Those drugs include monoamine reuptake inhibitors (tricyclic drugs, selective serotonin reuptake inhibitors [fluoxetine], selective noradrenaline reuptake inhibitors and serotonin-noradrenaline reuptake inhibitors) and monoamine oxidase inhibitors (such as tranylcypromine) (Krishnan and Nestler, 2008). Later observations related serotonin, dopamine and noradrenaline with emotions (e.g. guilt) (Kanen et al., 2021), anhedonia (Szczypiński and Gola, 2018), and psychomotor defects (Singh, 2020), respectively. Despite this evidence, the monoamine´s theory is not able to explain depression´s pathophysiology alone, mainly because even if monoamine oxidase inhibitors and selective serotonin reuptake inhibitors increase monoamine transmission immediately, their effect in the mood require weeks of treatment. That is the reason why contemporary theories have arisen trying to amplify the description of the neurobiological basis of depression. Neuroplasticity and hippocampal neurogenesis In vivo imaging studies have shown structural and functional changes in prefrontal and limbic regions (which are related to emotion, behavior, or memory) in patients with depression. Among the affected regions are frontal lobe, hippocampus, temporal lobe, thalamus, striatum, and amygdala (Bremner, 2002, Sheline, 2000, Zhang et al., 2018b). Hippocampus is the one that has caught more attention as it is a consistent finding that patients with depression had their hippocampus volume significantly reduced by 5-20% (Sheline et al., 1996, Bremner et al., 2000, Campbell et al., 2004, Binnewies et al., 2022). Preclinical in vivo and clinical studies have tried to explain this shrinkage in depressed patients: 34 - Cell apoptosis, a priori, is the most important candidate for volume reduction. Apoptosis protease activator factor (APAF1) gene has been proposed in some studies as a predisposing risk factor for depression (Harlan et al., 2006). Moreover, antidepressant treatment has shown to reduce apoptosis in the temporal cortex and dentate gyrus (Lucassen et al., 2004). However, human and animal studies have shown no indication of massive cell loss caused by depression, chronic stress exposure or glucocorticoids prolonged treatment (Lucassen et al., 2001, Leverenz et al., 1999), so massive apoptosis can be excluded as the main mechanism responsible for hippocampal volume shrinkage (Czéh and Lucassen, 2007). - A reduction in adult hippocampal neurogenesis has also been proposed to reduce hippocampal volume. In the dentate gyrus, a subregion of the hippocampus, new neurons are generated throughout life being essential for mood, memory and other cognitive functions. A reduction in adult hippocampal neurogenesis has been associated to depression as preclinical in vivo studies have shown the ability of antidepressants to stimulate the creation of new neurons and reverse neurogenesis inhibition (Musaelyan et al., 2020, Malberg et al., 2000, David et al., 2009). Neurotrophic factors positively affect neural stem cells proliferation and differentiation. Especially, brain-derived neurotrophic factor (BDNF) has been extensively studied and has been proposed as having a central role in the neuroplasticity of the brain. Moreover, BDNF is related to synaptic plasticity, responsible for synaptic transmission (Park and Poo, 2013). Polymorphisms on BDNF genes as well as in its receptor tyrosine kinase B (TrkB) gene predispose to depression (Duncan et al., 2009, Avdoshina et al., 2013). Moreover, patients with depression have lower serum levels of BDNF (Karege et al., 2002). Electroconvulsive therapy has tried to treat severe depression as it enhances neuroplasticity and neurogenesis. Even if the mechanisms of action are not 35 completely understood, this treatment has shown changes in the expression of BDNF and alterations in DNA methylation as key mechanisms behind the decrease in depression scores during the electroconvulsive therapy (Schurgers et al., 2022). Other therapies linked to the Trk signaling pathways may play a role in future antidepressant drugs (Yang et al., 2020). Even if these results are promising, the number of new neurons is too small to explain alone the hippocampal volume reduction. Even if neither neural apoptosis nor neurogenesis can explain the hippocampus shrinkage in depression patients by themselves, they will affect the overall hippocampus composition. Average age or characteristics of neurons may have consequences for connectivity and hippocampal function. Which seems clear is that depression is more related to neuroplasticity and cellular resilience than to neurodegeneration. Alterations in synaptic and neural components (e.g., number and function of glial cells) can contribute to hippocampal shrinkage and needs of further investigation (Czéh and Lucassen, 2007). Inflammatory theory of depression During the 1980s-1990s, the first evidence of the influence of inflammation on depression emerged with the observations of peripheral T cell activation and an increase in leukocyte and lymphocyte numbers in depressed patients (Maes et al., 1990, Irwin et al., 1990, Schleifer et al., 1984). Since then, the scientific literature on this subject has grown exponentially. The immune dysregulation and activation of the inflammatory response system can be reflected, first, by the statistically significant increase in the systemic levels of pro- inflammatory cytokines such as tumour necrosis factor (TNF)-𝛼 (weighted mean difference - WMD= 3.97 pg/mL; 95% CI [2.24; 5.71]) or interleukin (IL)-6 (WMD=1.78 pg/mL; 95% CI [1.23; 2.33]) in patients with depression when compared 36 to control patients (Dowlati et al., 2010). Increases of IL-1 has also been observed, even with less consistency (Howren et al., 2009). Those results correlate with the higher levels of both TNF-𝛼 and IL-6 at central nervous system, as showed in cerebrospinal fluid of depressed patients (Enache et al., 2019). Moreover, acute- phase proteins such as C reactive protein (CRP) (Howren et al., 2009); chemokine and adhesion molecules such as human macrophage chemoattractant protein-1 (MCP-1), soluble intracellular adhesion molecule-1 (sICAM-1) and e-selectin are also elevated in patients with depression (Rajagopalan et al., 2001). In this sense, it is interesting emerging evidence about patients failing to respond to antidepressant drugs, who had higher baseline levels of systemic inflammation (CRP or IL-8) (Gasparini et al., 2022). Some trends of thought have shown doubts about the role of inflammation on depression: is it a cause or a consequence? The fact that immunotherapy treatment with cytokines for other non-psychiatric disorders (e.g., cancer or hepatitis C) prompted depressive symptoms showed the causal role of inflammation (Hoyo- Becerra et al., 2014). Moreover, non-steroid anti-inflammatory drugs such as acetylsalicylic acid, ibuprofen, naproxen or celecoxib exert an antidepressant effect (Guo et al., 2009) and potentiates antidepressant effects of fluoxetine (Akhondzadeh et al., 2009). On the contrary, antidepressant drugs have shown an anti- inflammatory potential in preclinical in vivo studies (Zhu et al., 2001). As we have mentioned, the level of systemic inflammation correlates with central inflammation in patients with depression. A possible passage of cytokines from the blood flow to the CNS has been described (Banks et al., 1995, Quan and Banks, 2007). However, this passage may be modest, and other mechanisms seem to orchestrate neuroinflammation. This is the case of microglia, the innate immune cells which activation triggers a signaling cascade of inflammation. They will also produce different mediators that influence synaptic plasticity, neurogenesis (Zhang et al., 2018d) or behavior (Norden et al., 2015). There is evidence of the activation of 37 microglial cells on suicide patients with depression (Steiner et al., 2008), highlighting the neuroinflammation role in this disorder. That relation between the periphery and the CNS in terms on pro- and anti- inflammatory mechanisms has been attributed, at least in part, to stress (García- Bueno et al., 2008). First, because cytokines are key factors of the stress axis. As well as stress does, cytokines can promote corticotropin-releasing factor (CRF) production in the hypothalamus, process that can perpetuate inflammation due to a dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis via glucocorticoid resistance (Silverman and Sternberg, 2012). Second, because stressful events can increase BBB permeability as well as permeability of other barriers in the body due to the opening of epithelial intercellular tight junctions. That event has been proven to occur on the gut (Ponferrada et al., 2007) and due to the huge gut microbial diversity, it was hypothesized that, mediated by stress, gut bacteria (or their endotoxins) may contribute to neuroinflammation via eliciting immune and inflammatory responses. Thus, increased immunoglobulin (Ig) A and IgM responses against gut commensals have been found in plasma of patients with depression and schizophrenia (Maes et al., 2012, Maes et al., 2019). Also interesting was the observation of Gárate and coworkers (2013), who found that after intestinal decontamination with antibiotics in rats, the stress induced inflammatory pathways in the brain were downregulated (Gárate et al., 2013). To summarize the etiopathogenesis of depression, different mechanisms such as monoaminergic neurotransmitter alteration or brain neuroplasticity have been suggested as determinant in the onset and/or progression of depressive disorders. The inflammatory theory of depression has become of high importance in the last two decades, even if there is still a necessity of describing how distant infective/inflammatory foci are able to cause an effect on the CNS. It cannot be forgotten, however, that most of the evidence derives from post-mortem or 38 neuroimaging techniques and preclinical in vivo studies. Even if different animals from non-human primates to zebrafish have been used in the study of depression and other neuropsychiatric disorders, the rodent model is the most extensively used and remains the gold-standard animal model (Gururajan et al., 2019). 2.4. Depression models in rodents Historically, a depression model is accepted for its use when it has face validity, predictive validity, and construct validity (Willner, 1984). Face validity refers to a similar symptomatology between the animal model and the human condition, which is analyzed in preclinical studies with depressive-like behaviors tests (anhedonia, weight loss, diminished pleasure…). Moreover, biological alterations in humans should also appear in animals. Predictive validity means that current antidepressant treatments in humans can dim, and reverse depressive-like behaviors provoked by the model. Finally, construct validity corresponds to the theoretical rationale of the model, which means that the model needs to follow the etiopathogenesis of depression as much as possible (Planchez et al., 2019). Different models have tried to mimic depressive-like behaviors in rodents. These models can be classified in three groups: Early life adversity models: rodents strongly depend on maternal care after birth, so maternal separation is an early life stressor. Different timings for separation have been proven, and they are related to depressive- and anxiety- like behaviors (Marais et al., 2008), with exception to anhedonia, which is not a consistent finding among these animals (Planchez et al., 2019). One of the limitations of these models is related to construct validity: new-born pups development stage is more similar to pre-natal human stage than to early life stage. 39 Biological causality models: there are different neurobiological alterations that animal models of depression have tried to mimic: neuroinflammation [models with lipopolysaccharide (LPS) injection or Bacille-Calmette-Guérin administration], dysregulation of HPA axis (corticosterone administration), neural degeneration (bulbectomy) or genetic polymorphisms (genetic models). Again, the main limitation of these models is related to construct validity, as it is still unclear if these changes are more correlating than causing depression. Adult stress models: depression is a stressor-induced psychopathology, and these models consist in applying unpredictable or/and uncontrollable stressors. These models differ from each other in the duration and intensity of stressors. In learned helplessness model intense stressors are repeated over several hours. Even if a great face validity, the predictive validity of this model is low (Ramaker and Dulawa, 2017) and not all rodents are vulnerable to helplessness. In social defeat model, intense stressors (test rodent is placed in the cage of an aggressive rodent 10 minutes daily) are repeated over days. In Chronic Mild Stress (CMS) model, mild stressors are repeated during weeks. These are unpredictable stressors that have shown depressive-like behaviors as well as depressive-like biochemical and structural alterations. All face, construct and predictive validity has been proven for CMS (Willner, 2017). 40 3- Periodontal diseases 3.1- Classification and prevalence Periodontal diseases encompass a group of infectious and inflammatory diseases that affect the tissues that surround and support the teeth, the periodontium, which is comprised of gingival, alveolar bone, periodontal ligament and cementum. These diseases have been recently revised and classified during the 2017 World Workshop, organized by the European Federation of Periodontology and the American Academy of Periodontology. According to this new classification, there are two main types of periodontal diseases: gingivitis and periodontitis (Caton et al., 2018). Figure 2: Classification of Periodontal Diseases and Conditions (2017). Adapted from Caton et al. (2018). There are two main types of periodontal diseases: gingivitis and periodontitis, which were classified during the 2017 World Workshop. The main difference between gingivitis and periodontitis lies in which parts of the periodontium are affected and its reversibility. While gingivitis is the biofilm- induced inflammatory condition that remains contained within the gingiva and is reversible, periodontitis is characterized by the irreversible loss of periodontal tissue support. Clinically, periodontitis is manifested by an increased probing pocket depth (PPD), the presence of bleeding on probing (BOP) or radiographic bone loss (Papapanou et 41 al., 2018). It is classified in different stages and grades (Figure 3). Stages (Stage I, II, III, or IV) are related to severity and complexity of the disease. Each stage is also defined regarding its extent as localized (≤ 30% of teeth involved), generalized (> 30% of teeth involved) or molar/incisor pattern. Grades (Grade A, B, or C) are related to the estimation of risk of progression and responsiveness to standard treatment, as well as its potential health impact (Papapanou et al., 2018). Figure 3: Classification of Periodontitis based on stages, extent, and grades. Stages define severity and complexity of the case, while grades define risk of progression, anticipated response to treatment, and potential effects on systemic health. CAL, clinical attachment level; Rx: radiographic; PPD, probing pocket depth. In 2019, according to the Global Burden of Disease Study, severe periodontitis [Community Index of Periodontal Treatment Needs Class IV, clinical attachment level (CAL) higher than 6 mm, or PPD higher than 5 mm] affected 1.09 billion people worldwide (95% UI [0.828; 1.36]). It was ranked as the seventh most prevalent 42 disease and caused 7.09 million (95% UI [2.78; 15.5]) YDLs globally (Institute for Health Metrics and Evaluation, 2020). These data have shown an increase in the prevalence of periodontitis when compared to the same study in 2017, when the age- standardized prevalence of severe periodontitis was 9.8% (95% UI [8.2; 11.4]), affecting 796 million people (95% UI [671; 930]) (Bernabe et al., 2020). 3.2. Etiopathogenesis The multifactorial etiology and pathogenesis of periodontitis has been described in different narrative reviews (Kornman, 2008, Hajishengallis et al., 2020). Bacterial accumulation and biofilm organization have been described as the primary initiation factors in periodontitis. Since the 1980s, differences in biofilm composition began to be demonstrated between subgingival locations with periodontitis and the adjacent supragingival microbiota (Moore et al., 1982). In addition, there is a co- association or tendency for some groups of bacteria to be consistently detected together. Thus, Socransky et al. (1998) described five clusters, which were associated with either periodontal health or periodontitis. The cluster that is most associated with periodontitis is the “red complex”, made up of Porphyromonas gingivalis, Treponema denticola and Tannerella forsythia, while for example, the “yellow complex” or the “green complex”, dominated by species of Streptococcus and Captocytophaga respectively, are associated with periodontal health (Socransky et al., 1998). The American Academy of Periodontology, in a consensus report in 1996, also defined groups of pathogens associated with the initiation and progression of periodontitis. The first group, composed of Aggregatibacter actinomycetemcomitans, P. gingivalis and T. forsythia, had strong evidence for the association. The second group, composed of Campylobacter rectus, Fusobacterium nucleatum, Prevotella intermedia, Parvimonas micra and T. denticola, was moderately associated to periodontitis. The third group, which included bacteria such as Eikenella corredens, had initial evidence for the association (AAP, 1996). 43 Next generation sequencing technologies have identified twice the number of species from dental supra- and sub-gingival biofilm samples than previous techniques (Mougeot et al., 2016), and have shown us the complex bacterial communities that colonize the subgingival area. They have also demonstrated some dominant bacterial species in the subgingival biofilm of periodontitis patients (Abusleme et al., 2013, Hong et al., 2015). However, it seems that it is not the acquisition of new bacterial species, but a transformation of the bacterial communities with changes in the abundance of different organisms which is related to the shift from health to periodontitis (Curtis et al., 2020). This transformation is termed dysbiosis. More recently, microbial ecology studies have shown that the presence of P. gingivalis in low proportions (<1%) is sufficient for the development of the disease, causing an immune response related to the establishment of a dysbiosis that results in an inflammatory response (Darveau et al., 2012). For this reason, P. gingivalis has been proposed as a “keystone pathogen”, whose presence would cause an imbalance in the microbiome that is related to chronic inflammatory alterations that are characteristic from periodontitis (Darveau et al., 2012, Hajishengallis et al., 2012). This microbial challenge activates immunoinflammatory mechanisms. Periodontitis lesion is dominated by B cells and plasma cells, which result in a massive production of inflammatory cytokines such as TNF-𝛼 and IL-1 that are involved in the connective tissue matrix destruction and bone loss, which are responsible for clinical signs and symptoms of periodontitis. This system feed backs, as the presence of inflammation in the gingival tissues also has an impact on the ecology of the subgingival biofilm. However, the microbial challenge is not the only that can activate or modify the immunoinflammatory mechanisms. Several behavioral (e.g. smoking or psychosocial factors), systemic (e.g. diabetes) or genetic risk factors can influence the clinical expression of periodontitis (Kornman, 2008). 44 3.3. Interaction between periodontal and systemic diseases Since the 90s, multiple studies have evidenced the impact of periodontitis in systemic/extraoral health under the term “Periodontal Medicine” (Beck et al., 2019). In fact, the association of periodontitis has been studied with, at least, 57 systemic diseases and conditions (Monsarrat et al., 2016). Among them, diabetes mellitus (Graziani et al., 2018, Madianos and Koromantzos, 2018), atherosclerotic vascular disease (AVD) (Sanz et al., 2020, Schenkein et al., 2020) and adverse pregnancy outcomes (Figuero et al., 2020, Sanz and Kornman, 2013) are the ones more strongly associated to periodontitis. Moreover, periodontitis treatment results in cardiometabolic risk improvement with reductions in CRP (0.56 mg/L, 95% CI [- 0.88; -0.25]) or plasma glucose (1.33 mmol/L, 95% CI [-2.31; -0.24]) and preterm deliveries protection (Risk Ratio [RR]=0.77, 95% CI [0.60; 0.98]) (Orlandi et al., 2022). The mechanisms by which periodontitis may impact systemic health are based on the etiopathogenesis of the disease. The dysbiotic alterations that occur in the subgingival biofilm leads to a local non-resolving chronic inflammation. The systemic translocation of some of these pathobionts or inflammatory mediators are the determinants to explain the association between periodontitis and other comorbidities (Genco and Sanz, 2020). Therefore, there are two main mechanisms linking periodontitis and systemic health: (1) oral microbiome and (2) systemic inflammation (Figure 4). 45 Figure 4: Main biological mechanisms beyond the association between periodontitis and some systemic diseases: (A) Oral microbiome - summary of some oral bacterial species that have been found in distant organs; and (B) Systemic inflammation – consequences of chronic low-grade systemic inflammation that may link periodontitis with other comorbidities. The Figure was partly generated using Servier Medical Art, provided by Servier, licensed under a Creative Commons Attribution 3.0 unported license. Oral microbiome as a mechanism linking periodontitis and systemic health Subgingival biofilm microorganisms can get into the circulatory system through the ulcerated epithelium in a periodontitis patient and reach distant organs in a process called bacteremia (Ambrosio et al., 2019, Reyes et al., 2013, Zhang et al., 2013). Transient bacteremia has been described during daily activities as mastication or self-performed oral hygiene, and after professional dental treatments such as periodontal probing, dental prophylaxis, scaling and root planning, surgical periodontal treatments, or dental extractions (Tomás et al., 2012, Horliana et al., 2014). 46 Different studies have demonstrated the presence of periodontal bacteria in distant organs. For example, bacterial DNA from periodontal pathogens (P. gingivalis, A. actinocycetemcomitans, P. intermedia, T. forsythia, E. corrodens, F. nucleatum and C. rectus) was found in atheromatous plaques from endarterectomies from carotid arteries (Figuero et al., 2011, Haraszthy et al., 2000). Patients indicated for aorta endarterectomy due to myocardial infection also demonstrated A. actinomycetemcomitans in 20% of the atherosclerotic plaque samples (Calandrini et al., 2014). Another example is the one related to adverse pregnancy outcomes. F. nucleatum has been detected in the amniotic fluid from pregnant women complicated by preterm birth (Han et al., 2009), in neonatal gastric aspirates (Gonzales-Marin et al., 2011) or fetal membranes (Cahill et al., 2005) sole or in mixed infections. Systemic inflammation as a mechanism linking periodontitis and systemic health As previously discussed, the ulcerated epithelium in the periodontal pocket constitutes a disturbed barrier that allows bacteria, or bacterial products, and inflammatory mediators get into the blood flow. This fact sets aside the localized inflammatory nature of periodontitis. Even if most of the bacteria entering the circulatory system are eliminated within minutes by the immune system, some of them persist; and mediated by leucocytes, endothelial cells and hepatocytes, trigger significant systemic inflammation (Van Dyke and van Winkelhoff, 2013, Li et al., 2000). Local pro-inflammatory mediators (IL-1𝛽, IL-6 or TNF-𝛼) can also gain access into circulation directly. There is evidence of higher levels of systemic inflammatory markers among periodontitis patients (Loos et al., 2000, Slade et al., 2003). The presence of these mediators in the blood induces leukocytosis and acute-phase proteins [CRP, fibrinogen, plasminogen activator inhibitor 1 (PAI-1), complement proteins or lipopolysaccharide binding protein (LBP)] with important systemic 47 effects. For example, periodontitis patients have demonstrated higher levels (1.56 mg/L on average) of high sensitivity CRP (hsCRP) than healthy controls (Paraskevas et al., 2008), which is an important difference taking into account that levels of hsCRP between 1 and 2 mg/L are associated with a moderate risk for AVD and levels higher than 3 mg/L are associated with high risk (Ridker, 2003). In the case of diabetes, inflammation is a contrasted inductor of insulin resistance, key in the diabetes pathogenesis; and it is related to initiation and evolution of cardiorenal complications in diabetic and non-diabetic patients (Shoelson et al., 2006, Colombo et al., 2012). To develop evidence about the relationship between periodontitis and systemic diseases, it is necessary (1) evidence derived from epidemiological studies that shows a positive association between both conditions; (2) preclinical in vivo or in vitro studies that analyze the biological plausibility or the potential biological mechanisms that link both conditions; and (3) evidence derived from intervention studies, in which a preventive or therapeutic measure reduces the risk of developing the systemic condition in patients with periodontitis. None of these points is individually sufficient to affirm the relationship between two conditions. Among the systemic diseases that have been associated to periodontitis, some of them, such as diabetes mellitus or AVD have demonstrated all the three points. However, for others such as the neuropsychiatric disorders the biological plausibility needs to be understood. For this purpose, periodontitis animal models are needed. 3.4. Periodontitis models in rodents Rodents have been extensively used in the studies relating periodontitis with other systemic conditions, even if they are resistant to naturally develop periodontitis (Graves et al., 2008), because of their small size and ease of maintenance (Bryda, 2013). 48 There are three main types of periodontitis induction models in rats: Ligatures model: this model is based on the placement of a thread around the animal molars to facilitate biofilm accumulation. It was firstly described with stainless steel wires (Weiner et al., 1979), but, nowadays, silk is the most used material for this purpose. Alveolar bone destruction has been demonstrated with this model as soon as 7 days after the placement of the ligature (Bezerra et al., 2000), even if longer models (up to 7 weeks) have been described (Macri et al., 2014). Ligatures alone does not initiate clinical signs of inflammation or alveolar bone loss in gnotobiotic rats (Rovin et al., 1966), which highlight the importance of biofilm in the induction of periodontitis. Based on this premise, some authors have used periodontal pathogens such as P. gingivalis to embed the ligatures before placing them (Wang et al., 2017). The most important disadvantage of this model is the traumatic effect that has been attributed to the ligature, ulcerating the sulcular epithelium leading to pathogen invasion (Klausen, 1991). Lipopolysaccharide injection model: this model is based on the injection of LPS, as an important inflammatory stimulus to the innate immune system, in the gingival tissues (palatal gingiva or interdental papilla) surrounding molars with microsyringes usually 3 times a week during the experiment (Graves et al., 2012). Alveolar bone loss has been observed from 7 days since the first injection with P. gingivalis (Leira et al., 2019) or A. actinomycetemccomitans (Nakamura et al., 2008). This model, however, does not follow periodontitis etiological pathway as well as the oral gavage model does. Oral gavages model: this model is based on the oral inoculation of human strains of bacteria that have been associated to periodontitis (P. gingivalis, A. actinomycetemcomitans, or F. nucleatum). These bacteria are given in a viscous solution (2% carboxymethylcellulose) daily for at least 1 week with 109 colony forming 49 units/mL (Graves et al., 2012). Reproducibility and predictability of periodontitis infection is increased with the previous administration of antibiotics. Nowadays is more usual to combine different bacteria, as it has been proven that animals inoculated with the mixed infection had more alveolar bone loss that those inoculated with single infection (Polak et al., 2009). When compared to ligatures model, oral gavage model is not able to induce such a severe periodontitis (de Molon et al., 2016). 4- Association of periodontitis and depression The association between periodontitis and depression has been proven to be bidirectional, as several factors can contribute to it: poor nutrition and oral hygiene (Jain et al., 2009), comorbid substance misuse (e.g. tobacco or alcohol) (Rubin et al., 2020) or limited access to dental care (Almohaimeed et al., 2022). Individuals with depression have shown higher risk of periodontitis (RR=1.19, 95% CI [1.04; 1.36] (Nascimento et al., 2019). However, this PhD thesis is focused on one direction: the role of periodontitis in the pathogenesis of depression. 4.1. Epidemiology Among the neuropsychiatric diseases, major depression is the disorder that has been most extensively studied in its relation to periodontitis (Martínez et al., 2021). There are three systematic reviews with consistent results about their epidemiologic association, even if they have slight differences in the inclusion and exclusion criteria (Araújo et al., 2016, Liu et al., 2018, Zheng et al., 2021). Araújo et al. (2016) and Liu et al. (2018) included the same 7 cross-sectional studies in their meta-analysis founding a non-significant association between periodontitis and depression (odds ratio [OR]=1.03, 95% CI [0.75; 1.41]). Zheng et al. (2021), despite increasing their sample to 17 cross-sectional studies, was also unable to find a significant association 50 (OR=1.08, 95% CI [0.88; 1.32]). However, when case-control studies were included, both Liu et al. (2018) and Zheng et al. (2021) found a significant association between periodontitis and depression with OR=3.72, 95%CI [2.45; 9.52] and OR=1.70, 95% CI [1.01; 2.83], respectively. One global meta-analysis by Liu et al. (2018) that included cross-sectional and case-control studies found a significant association between both comorbidities (OR=1.61, 95% CI [1.16; 2.23]). In the case of Zheng et al. (2021), they also performed a subgroup analysis including only severe periodontitis patients also revealing a significant association between the two conditions (OR=1.43, 95% CI [1.05; 1.93]). There are very few studies describing the association between these comorbidities using periodontitis as the exposure, and even less longitudinal studies. One of the examples is the study by Hsu et al. (2015), who selected 12,708 patients with new periodontitis diagnosis and 50,832 healthy controls. These patients were followed from 5 to 11 year until the diagnosis of depression, and after adjustment for age, sex and comorbidities showed an increased risk of developing depression (Hazard Ratio [HR]= 1.73, 95% CI [1.58; 1.89]). This finding suggests that periodontitis could be a risk factor for depression. However, more cohort studies are needed. 4.2. Biologic Plausibility Most of previous studies analyzing the biologic relationship between periodontitis and depression have been centered in the immunomodulatory role of stress and have used depression as the exposure. Stress increases adrenaline and noradrenaline levels (Boyapati and Wang, 2007, Takada et al., 2004) that activate adrenoceptors in the immune system. Moreover, there is a dysregulation in the HPA via the upregulation of CRF in stressed individuals that leads to a stimulation of the immune response, and in the end, cortisol levels have been positively associated to higher CAL (Hilgert et al., 2006). It has also been stated that stress may influence 51 immune activities directly via neurotransmitters and neuropeptides (Breivik et al., 1996). Many knowledge gaps exist, however, when the association is to be explained in the contrary direction (periodontitis as the exposure). Systemic inflammation as a mechanism linking periodontitis and depression As stated before, in the recent years, the inflammatory theory of the neuropsychiatric diseases has shown a great progress. A higher inflammatory state has been demonstrated both in the periphery (systemic inflammation) and in the CNS of patients with depression (Enache et al., 2019, Dowlati et al., 2010). In the same way, periodontitis patients present a chronic low-grade systemic inflammation (Loos et al., 2000). However, there are unresolved issues in the inflammatory theory of depression. Its study, when combined with other comorbidities such as periodontitis, can at the same time help to shed light in the pathophysiology of depression and contribute to generate knowledge about the biological mechanisms linking both diseases. The main aspect which has not yet been solved in the inflammatory theory of depression is the origin of the inflammation. Inflammatory response can be activated by different stimulus (physical stress, psychological stress, chronic infections…) and most of the times, it is non-specific. Moreover, it is not well- characterized if the immune system activation is a cause or a consequence of depression. Thus, it is needed to deep in the origin of the inflammation in neuropsychiatric diseases with longitudinal studies that allow the temporal course of the immune activation. The infective- inflammatory nature of the periodontitis exposure could help on the understanding of this mechanism. 52 Nowadays, there are five described signaling pathways by which the CNS could detect peripheral stimuli as an increase in pro-inflammatory cytokines or LPS: • Neural pathway through the vagus nerve at the level of the nucleus of the medullary solitary tract in the brain (Breit et al., 2018). • Though the BBB, which under certain circumstances, as stressful events, can increase its permeability (Madrigal et al., 2002). • Signaling through astrocytes, pericytes, perivascular macrophages or endothelial cells in the neurovascular unit. Molecules such as prostaglandins and specific transporters of the BBB have been implicated in this pathway (Diaz-Castro et al., 2021). • Thought brain aeras without BBB (vascular organ of lamina terminalis, area postrema or subfornical organ). • Though the infiltration of activated peripheral immune cells to the brain parenchyma (Zhang et al., 2018a). In fact, in the last years it has been demonstrated in animal models that different stress protocols lead to a hyper-inflammatory state and to an increase in the permeability of the gut mucosa, which might lead to a bacterial (and bacterial products) translocation to the systemic circulation. This activation of the immune system is mediated by the relation between Pathogen Recognition Receptors (PRRs) and Pathogen-Associated Molecular Patterns (PAMPs) or Damage-Associated Molecular Patterns (DAMPs). There are different families of PRRs, being the Toll- like receptors (TLRs), and above all TLR-4, the one that has been traditionally most studied in both periodontitis and neuropsychiatric diseases associated to neuroinflammation. First, because TLR-4 recognizes Gram negative bacteria, which are representative to the periodontal pathogens. Second, because TLR-4 signaling has been associated to stress-related inflammatory processes, and specifically in depressive disorder (Gárate et al., 2011, Cheng et al., 2016). 53 Toll-like receptors are transmembrane glycoproteins with two domains: an extracellular domain, which mediate the PAMPs or DAMPs recognition, and an intracellular domain which takes over the intracellular inflammatory response. To develop the inflammatory response, TLR-4 activates different pathways (Figure 5). The myeloid differentiation primary response 88 (MyD88) dependent pathway will activate the two key pathways in the immune response of TLR-4: the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-𝜅B) and the mitogen activated protein kinases (MAPKs) pathways. The translocation to the nucleus of the ultimate molecules in these pathways are related to the transcription of inflammatory genes such as IL-6, TNF-𝛼 or MCP-1 (Collart et al., 1990, Kawai and Akira, 2007) and to essential cell functions such as cellular survival, differentiation or apoptosis (Tang et al., 2002). There is also a MyD88 independent pathway that also activates NF-𝜅B, even if it is more related to interferon (IFN)-related gene expression (Kawai et al., 2001). 54 Figure 5. Toll-like receptor 4 (TLR-4) signaling. After the recognition lipopolysaccharide by TLR-4 three different pathways can be activated after the activation of consecutive ligands. (1) Nuclear Factor kappa B (NF-𝜅B) pathway- myeloid differentiation primary response 88 (MyD88) dependent; (2) the Mitogen-Activated Protein Kinases (MAPKs)- MyD88 dependent pathway; and (3) the interferon (IFN) – MyD88 independent pathway. This response only occurs in the presence of the different molecules represented in this figure. IL-1: interleukin 1; IL-1R: interleukin 1 receptor; TLR-4: toll-like receptor 4; LBP: lipopolysaccharide binding protein; CD14: cluster of differentiation 14; LPS: lipopolyssacharide; MD-2: myeloid differentiation factor 2; MyD88: myeloid differentiation primary response 88; IRAK: interleukin receptor associated kinase; TRAF6: Tumour necrosis factor receptor associated factor 6; TAK1: transforming growth factor-𝛽 activated kinase 1; TAB1: TAK1 binding protein; TAB2: TAK1 binding protein 2; MAP: mitogen-activated protein; MEK: MAP kinase/kinase; ERK 1/2: extracellular signal-regulated kinase 1/2; JNK: c-jun N terminal kinases; p38: protein 38; AP-1: activator protein 1; CREB: cAMP Response Element-Binding protein; IFN: interferon; IL-6: interleukin-6; TNF-𝛼: tumour necrosis factor alpha; IKK: inhibitor of nuclear factor-kB kinase; IkB: inhibitor of nuclear factor-kB; p50: protein 50 (50 kDa subunit of NF-𝜅B); p65: protein 65 (65 kDa subunit of NF-𝜅B; TRIF: Toll/IL-1-domain-containing adapter-inducing interferon-𝛽; TBK-1: NF- 𝜅B activator associated to TRAF family-binding kinase 1; IFR: interferon regulatory factor. 55 Oral microbiome as a mechanism linking periodontitis and depression As explained before, subgingival biofilm microorganisms can get into the circulatory system through the ulcerated epithelium in periodontitis patients and reach distant organs. Even if the presence of the BBB protects CNS against toxins and pathogens entrance, representative bacteria from the subgingival area related to periodontitis have been found in the brain and cerebrospinal fluid (Table 2). Most of the evidence of periodontal pathogens in the brain is derived from preclinical in vivo and post-mortem human studies, and it is related to the presence of P. gingivalis or its LPS in the presence of AD (Dominy et al., 2019, Hao et al., 2022, Poole et al., 2013). However, when periodontitis has been induced in animal models with oral gavages with periodontopathogens, P. gingivalis was also detected even in the absence of any CNS comorbidity (Ilievski et al., 2018). Other periodontal bacteria such as A. actinomycetemcomitans and T. denticola have been detected in drainages from brain lesions and postmortem human brains, respectively (Rahamat-Langendoen et al., 2011, Riviere et al., 2002). There is only limited evidence about the role or periodontal pathogens such as P. gingivalis in the activation of neuroinflammation via the TLR-4 signaling pathway, and the existing evidence is related to cognitive dysfunction (Zhang et al., 2018c), but not with depression. Considering that most of recognized periodontal pathogens are Gram negative bacteria, a combined model of periodontitis and depression would help to characterize the inflammatory pathway linking both diseases. 56 Table 2: Studies looking for periodontal bacteria in the central nervous system with or without neurogenerative or neuropsychiatric comorbidities. qPCR: quantitative polymerase chain reaction; N/A: not available; FISH: fluorescence in situ hybridization. Author, year Periodontitis Comorbidity Type of sample Microbiological technique Periodontal bacteria Prevalence of periodontal bacteria Preclinical in vivo studies Hao et al. (2022) Oral gavages with P. gingivalis Alzheimer´s Disease Mouse brain tissue FISH P. gingivalis N/A Yan et al. (2022) Ligatures coated with F. nucleatum Alzheimer´s Disease Rat brain tissue qPCR - 0/9 Díaz-de-Zúñiga et al. (2020) P. gingivalis injection - Rat brain tissue Immunofluorescence P. gingivalis N/A Dominy et al. (2019) N/A Alzheimer´s Disease Mouse brain tissue qPCR / Western blot P. gingivalis 8/8 (mouses) Wang et al. (2019) Oral gavages with F. nucleatum AND P. gingivalis - Mouse brain tissue qPCR P. gingivalis N/A Ilievski et al. (2018) Oral gavages with P. gingivalis - Mouse brain tissue qPCR/ Immunofluorescence/ Confocal microscopy P. gingivalis 9/9 (immunofluorescence, confocal microscopy) 5/5 (qPCR) Clinical studies/ Human post-mortem studies Dominy et al. (2019) N/A Alzheimer´s Disease Post-mortem human brain tissue qPCR / Western blot P. gingivalis 3/3 (Alzheimer´s Disease) 5/6 (non-Alzheimer´s Disease) Laugisch et al. (2018) 54.7 % BOP / 26.1% of sites PD > 4 mm Alzheimer´s Disease Cerebrospinal fluid qPCR - 0/20 Poole et al. (2013) N/A Alzheimer´s Disease Post-mortem human brain tissue Immunofluorescence P. gingivalis 4/10 Rahamat-Langendoen et al. (2011) Severe periodontitis - Drainage from brain lesion qPCR A. actinomycetemcomitans 1/1 Riviere et al. (2002) N/A Alzheimer´s Disease Postmortem human brain tissue qPCR T. denticola 5/16 (Alzheimer´s Disease) 2/18 (non-Alzheimer´s Disease) 57 All organisms with a developed CNS have a BBB, which is created by the endothelial cells of the capillaries that are attached to each other by adherens and tight junctions sealing paracellular gaps (Figure 6). This is a highly specialized structure that regulates molecular trafficking and protects the brain against immune challenges. In adherens junctions, cadherin proteins give structural support and are essential for tight junction formation. Tight junctions are formed by more complex proteins, occludin and claudins, that are linked to regulatory proteins such as zonula occludens (ZO)-1, ZO-2, or ZO-3. The maintenance of tight junctions is allowed thanks to multiple intercellular communication between endothelial cells and other CNS cells such as microglia, pericytes, astrocytes, or neurons (Figure 6) (Abbott et al., 2010, Takata et al., 2021). For example, binding of DAMPs to PRRs that occurs in CNS pathologies, triggers the activation of microglia and astrocytes; and activated glial cells act as a source of inflammation, whose derivates (e.g. cytokines or reactive oxygen species) influence BBB integrity (Takata et al., 2021). The disruption of these structural molecules can range from transient mild tight junction opening to chronic barrier breakdown, and has been observed in different pathologies such as neurogenerative and neuropsychiatric diseases (Zlokovic, 2005, Dion-Albert et al., 2022) and conditions such as stress (Welcome and Mastorakis, 2020). Under these circumstances, the stimulus of oral microbiome could reach easily the CNS and elicit neuroinflammation. 58 Figure 6: Blood-brain barrier structure and its association with central nervous system cells. (Abbott et al., 2010). BL1: basal lamina 1; BL2: basal lamina 2. Among the mechanisms intervening in the BBB physiology, sphingosine-1- phosphate (S1P) is a bioactive lipid that regulates endothelial cell barrier function (Burg et al., 2018) and promotes inflammation through immune cell recruitment (Rivera et al., 2008). The S1P metabolism consists of two synthesis sphingosine kinases (Sphk1 and Sphk2) and two sphingosine phosphatases (SGPP-1 and SGPP- 2) and one sphingosine lyase (SGPL-1) responsible for its degradation. Some studies have pointed out a specific involvement of S1P in neuroinflammation (Blaho et al., 2015) and BBB permeability (Yanagida et al., 2017). Thus, S1P can be a key pathway to be studied in the relationship between periodontitis and depression, in which neuroinflammation and BBB permeability could be hypothesized as a linking mechanism. 59 60 61 JUSTIFICATION Major depression is a highly prevalent and serious disease. It affects more than 300 million people worldwide and has important consequences in terms of health and disability. Moreover, due to the unresolved characteristics of its physiopathology, nearly a third of patients do not respond to treatment, and there are many patients suffering from depression experience relapse. Periodontitis is an infective-inflammatory disease which is also highly prevalent, with relevant local and systemic impacts, including the association with different systemic diseases via the impact of its associated microbiota or systemic inflammation. There is epidemiological evidence, mostly derived from observational studies, that associates both conditions. Many of the studies trying to understand the biological background of this association have considered depression as the exposure. However, due to the infective-inflammatory nature of periodontitis, it is of interest to investigate the link between these diseases considering periodontitis as an exposure, above all, with the recent evidence that highlight the importance of inflammation in the pathophysiology of depression. Moreover, the development of animal models combining periodontitis and depression induction would allow to study the temporal course of depression- associated inflammation, to determine more accurately which is the origin of that inflammation in the brain, and to improve the understanding of the impact of periodontitis in neuropsychiatric diseases. 62 63 64 65 HYPOTHESIS AND OBJECTIVES HYPOTHESIS 1. General hypothesis There is an association between periodontitis and depression, where periodontitis, due to its infective-inflammatory nature, would impact the CNS via the oral microbiota related to periodontal diseases and the low-grade systemic inflammation it is related to. 2. Specific hypothesis Study #1: Oral microbiota related to periodontal diseases leads to a microbiological and an immunological link between periodontitis and the CNS. Study #2: Preclinical in vivo models allow the study of the inflammatory-related and oral microbiota-related mechanisms involved in the association between periodontal diseases and psychiatric diseases when a combined model of periodontitis and depression is used. Study #3: Neuroinflammation and BBB dysfunction are key players in the association between periodontitis and depression; and S1P pathway is implicated in this association due to its influence in both mechanisms. 66 67 OBJECTIVES 1. General objective To study the influence of oral microbiota-related to periodontal diseases and inflammatory-related mechanisms in the association between periodontitis and depression. 2. Specific objectives Study #1: To review the known and potential molecular and cellular mechanistic components of the association between oral microbiota related to periodontal diseases and different neuropsychiatric diseases. Study #2: To study the inflammatory-related mechanisms that may link periodontitis and depressive symptoms developing an experimental model to study the influence of periodontitis in psychiatric diseases in rats, that allows to characterize the inflammatory response at a molecular level after the combined exposure to periodontitis and depression, and to analyze de presence of P. gingivalis and F. nucleatum in brain tissues as potential triggers of inflammation. Study #3: To explore the molecular mechanisms behind neuroinflammation and BBB permeability, and to explore the role of S1P pathways and their contribution to these processes in the same experimental model. 68 69 70 MATERIALS AND METHODS. RESULTS 71 The detailed description of the “Materials and Methods” and the “Results” of each study included in the present project have been published as independent scientific articles with the following references: Study #1: Martínez M., Postolache T.T., García-Bueno B., Leza J.C., Figuero E., Lowry C.A., Malan-Müller S. The Role of the Oral Microbiota Related to Periodontal Diseases in Anxiety, Mood and Trauma- and Stress-Related Disorders. Frontiers in Psychiatry. 2022 Jan; 12:814177. doi: 10.3389/fpsyt.2021.814177. Study #2: Martínez M., Martín-Hernández D., Virto L., MacDowell K.S., Montero E., González-Bris A., Marín M.J., Ambrosio N., Herrera D., Leza J.C., Sanz M., García-Bueno B., Figuero E. Periodontal diseases and depression: A pre-clinical in vivo study. Journal of Clinical Periodontology. 2021 Jan; 00:1-25. doi: 10.1111/jcpe.13420. Study #3: Martín-Hernández D., Martínez M., Robledo-Montaña J., Muñoz-López M., Virto L., Ambrosio N., Marín M.J., Montero E., Herrera D., Sanz M., Leza J.C., Figuero E., García-Bueno B. Blood-brain barrier dysfunction and the sphingosine-1- phosphate pathways as mechanisms contributing to neuroinflammation in a pre- clinical experimental in vivo model of periodontitis and depression. Journal of Clinical Periodontology. 2023 Jan; doi: 10.1111/jcpe.13780. 72 73 STUDY #1: “The role of the oral microbiota related to periodontal diseases in anxiety, mood and trauma- and stress- related disorders” The prevalence of anxiety, mood and trauma- and stress-related disorders are on the rise; however, efforts to develop new and effective treatment strategies have had limited success. To identify novel therapeutic targets, a comprehensive understanding of the disease etiology is needed, especially in the context of the holobiont, i.e., the superorganism consisting of a human and its microbiotas. Much emphasis has been placed on the role of the gut microbiota in the development, exacerbation, and persistence of psychiatric disorders, however, data for the oral microbiota are limited. The oral cavity housed the second most diverse microbial community in the body, with over 700 bacterial species that colonize the soft and hard tissues. Periodontal diseases encompass a group of infectious and inflammatory diseases that affect the periodontium. Among them, periodontitis is defined as a chronic, multi-bacterial infection that elicits low-grade systemic inflammation via the release of pro-inflammatory cytokines, as well as local invasion and long-distance translocation of periodontal pathogens. Periodontitis can also induce or exacerbate other chronic systemic inflammatory diseases such as atherosclerosis and diabetes and can lead to adverse pregnancy outcomes. Recently, periodontal pathogens have been implicated in the etiology and pathophysiology dysregulation of neuropsychiatric disorders (such as depression and schizophrenia), especially as dysregulation of the immune system also plays an integral role in the etiology and pathophysiology of these disorders. In this narrative review, epidemiological data of periodontal diseases in individuals with these disorders was presented, followed by a discussion of the microbiological and immunological links between the oral microbiota and the central nervous system. Pre-clinical and clinical findings on the oral microbiota related to periodontal diseases in anxiety, mood and trauma- and stress- related phenotypes were reviewed, followed by a discussion 74 about the bi-directionality of the oral-brain axis. Lastly, attention was given on the oral microbiota associated to periodontal diseases as a target for future therapeutic interventions to alleviate symptoms of these debilitating psychiatric disorders. 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 STUDY #2: “Periodontal diseases and depression: a pre-clinical in vivo study” Aim: To analyse, through a pre-clinical in vivo model, the possible mechanisms linking depression and periodontitis at behavioural, microbiological and molecular levels. Materials and methods: Periodontitis (P) was induced in Wistar:Han rats (oral gav- ages with Porphyromonas gingivalis and Fusobacterium nucleatum) during 12 weeks, followed by a 3-week period of Chronic Mild Stress (CMS) induction. Four groups (n = 12 rats/group) were obtained: periodontitis and CMS (P+CMS+); periodontitis without CMS; CMS without periodontitis; and control. Periodontal clinical variables, alveolar bone levels (ABL), depressive-like behaviour, microbial counts and expression of inflammatory mediators in plasma and brain frontal cortex (FC), were measured. ANOVA tests were applied. Results: The highest values for ABL occurred in the P+CMS+ group, which also presented the highest expression of pro-inflammatory mediators (TNF-α, IL-1β and NF- kB) in frontal cortex, related to the lipoprotein APOA1-mediated transport of bacterial lipopolysaccharide to the brain and the detection of F. nucleatum in the brain parenchyma. A dysregulation of the hypothalamic–pituitary–adrenal stress axis, reflected by the increase in plasma corticosterone and glucocorticoid receptor levels in FC, was also found in this group. Conclusions: Neuroinflammation induced by F. nucleatum (through a leaky mouth) might act as the linking mechanism between periodontal diseases and depression. 98 99 https://pubmed.ncbi.nlm.nih.gov/33432590/ 125 STUDY #3: “Neuroinflammation related to the blood-brain barrier and sphingosine-1- phosphate in a pre-clinical model of periodontal diseases and depression in rats.” Aim: To explore the potential mechanisms of neuroinflammation (microglia, blood- brain barrier [BBB] permeability, and the sphingosine-1-phosphate [S1P] pathways) resulting from the association between periodontitis and depression in rats. Materials and methods: This pre-clinical in vivo experimental study used Wistar rats, in which experimental periodontitis (P) was induced by using oral gavages with Porphyromonas gingivalis and Fusobacterium nucleatum. Then a chronic mild stress (CMS) model was implemented to induce depressive-like behavior, resulting in four groups: P with CMS (P+CMS+), P without CMS (P+CMS-), CMS without P (P-CMS+), and controls (P-CMS-). After harvesting brain samples, Protein/mRNA expression analyses and fluorescence immunohistochemistry were performed in the frontal cortex (FC). Results were analyzed by ANOVA tests. Results: CMS exposure increased the number of microglia (an indicator of neuroinflammation) in the FC. In the combined model (P+CMS+), there was a decrease in the expression of tight junction proteins (zonula occludens-1 [ZO-1], occludin) and an increase in intercellular and vascular cell adhesion molecules (ICAM-1, VCAM-1) and matrix metalloproteinase 9 (MMP9), suggesting a more severe disruption of the BBB. The enzymes and receptors of S1P were also differentially regulated. Conclusions: Microglia, BBB permeability, and S1P pathways could be relevant mechanisms explaining the association between periodontitis and depression. 126 127 https://pubmed.ncbi.nlm.nih.gov/36644813/ 143 144 145 DISCUSSION The present project had the general objective of studying the influence of oral microbiota related to periodontal diseases and inflammatory-related mechanisms in the association between periodontitis and depression. Specifically, a theoretical basis about the association between periodontitis and neuropsychiatric diseases was generated (Study #1), being the key points systemic inflammation and oral microbiome. This review guided the development of a preclinical in vivo model to study the mechanisms linking periodontitis and depression (Studies #2 and #3). It was observed that the combination of periodontitis (P) and depression (CMS) induction resulted in higher values in periodontal outcomes and inflammatory mediators in the brain, together with the presence of F. nucleatum in the brain tissue of two out of nine P+CMS+ rats (Study #2). In order to provide new insights on the possible mechanisms involved in the previously reported neuroinflammation and translocation of oral bacteria to the brain, further analyses demonstrated higher microglial counts, changes in the expression of key mediators involved in the regulation of BBB permeability (e.g., ZO-1) and a S1P signaling modulation in the frontal cortex in rats exposed to both P and CMS (Study #3). 1- Theoretical basis of the association between periodontitis and depression There is epidemiological evidence in favor of the association between periodontitis and depression, which is mainly derived from observational case-control studies (Liu et al., 2018, Zheng et al., 2021). Longitudinal studies are scarce, but there is also evidence derived from cohort studies that showed that patients with periodontitis had 1.73-fold increased risk of developing depression (Hsu et al., 2015) (Study #1). 146 The theoretical basis of the association between periodontitis and depression is reflected in Figure 7 (Study #1), and it is based on the infective/inflammatory nature of periodontitis. Periodontitis is an infectious and inflammatory disease that affects the tissues that surround and support the teeth and is clinically characterized by the presence of periodontal pockets with an ulcerated epithelium, BOP and progressive loss of attachment. Transient bacteremia, defined as the pass of subgingival biofilm microorganisms into the circulatory system has been demonstrated in periodontitis patients (Ambrosio et al., 2019). Bacteria or bacterial products in the bloodstream can directly reach the brain in areas with lack or compromised BBB (Figure 7 [point 1]) or can elicit an inflammatory reaction that activate endothelial cells resulting in neuroinflammation (Figure 7 [points 2-4]). Gingival pro-inflammatory cytokines can as well reach the circulatory system by the same mechanism. The presence of PAMPs such as LPS of periodontal bacteria in the bloodstream can also activate HPA axis and result in a disrupted gut microbiota, which under stressful situations (Ponferrada et al., 2007) could contribute to depressive pathology via the elicit of a systemic immune-inflammatory reaction (Maes et al., 2012) (Figure 7 [points 5-7]). This systemic inflammation could also contribute to periodontal pathology (Figure 7 [point 8]). Thus, Study #1 has also explored the bidirectionality of this association. This theoretical basis needed from pre-clinical models that allow researchers to investigate the temporal course of this association, as animal models allow the researchers to induce pathologies one prior to the other. The understanding of this association required for further research that specifically assessed in a combined 147 model of periodontal diseases and neuropsychiatric disorders the mechanisms linking periodontal status to CNS alterations. Figure 7: Theorical basis of the association between periodontitis and depression (Martínez et al., 2021). This is a schematic representation about the oral-gut-brain axis. Oral microbiota related to periodontal diseases can get the bloodstream and affect systemic inflammation and neuroinflammation [1-4]. The activation of the hypothalamic-pituitary-adrenal axis can also affect gut microbiota, which can also exacerbate systemic inflammation [6-7]. Periodontal bacteria can also affect directly gut microbiota via enteral transmission or hematogenous transmission. CNS, central nervous system; TNF, tumor necrosis factor; IL-1, interleukin-1; LPS, lipopolysaccharide; BBB, blood–brain barrier; HPA, hypothalamic–pituitary– adrenal. Solid arrows indicate direct pathways and dotted arrows indicate indirect pathways. 148 2- Developing an experimental model of periodontitis and depression In order to attain the objectives of this PhD thesis, we developed an experimental model to study the influence of periodontitis in psychiatric diseases in rats, as these animals have been extensively used to evaluate behavioral outcomes, retain translational potential and are less demanding on resources when compared to others (Stahl, 2010). The developed experimental model has consisted of one phase of periodontitis induction with oral gavages method inoculating P. gingivalis ATCC W83 K1 and F. nucleatum DMSZ 20482 four times per week for 12 weeks (Virto et al., 2018), followed by a depressive-like behavior induction based on the CMS protocol, consisting on introducing a series of different stressors daily (two stressors/day) for 21 days (Gárate et al., 2011, Martín-Hernández et al., 2016). Periodontal affectation was demonstrated in this model by increased values of periodontal clinical outcomes. Animals that received CMS demonstrated a depressive-like behavior as they showed a decrease in weight gain or grooming, and a higher time in open arms in the elevated plus maze test for anhedonia and anxiety. Different models have been proposed in the literature to study the relationship between periodontitis and CNS alterations in rats (Table 3). When referring specifically about depression, periodontitis has been suggested always as an outcome in the relationship due to the known immunomodulatory effect of stress and depression (Breivik et al., 1996). However, in our proposed model, periodontitis induction precedes CMS to test our hypothesis that periodontitis, due to its infective- inflammatory nature, would impact the CNS via the oral microbiota and the low- 149 grade systemic inflammation. It should be noted that up to our knowledge this is the first research work that has evaluated the molecular mechanisms involved in the interaction periodontitis-depression in rats using periodontitis as an exposure. In terms of periodontitis induction, the placement of ligatures around the rat molars has been most of the times the method of choice (Breivik et al., 2015, Breivik et al., 2006, Soletti et al., 2009). The amount of alveolar bone destruction with oral gavages is known to be limited when compared with other methods such as ligatures (de Molon et al., 2016). However, ligatures always exert an undesirable high degree of trauma to the periodontium (Klausen, 1991). Moreover, the selection of the oral gavage model with P. gingivalis and F. nucleatum allows for the study of potential mechanisms by which oral microbiota can impact the CNS. In terms of depression induction, methods as maternal deprivation or olfactory bulbectomy have been used to study its relation to periodontitis. However, when compared with CMS, this model has a higher translational potential and has been extensively used in the study of neuroinflammation (Willner, 2017, Gárate et al., 2011). The design of this preclinical in vivo model with four groups (P+CMS-, P+CMS+, P- CMS+ and P-CMS-) have allowed to compare the results from the individual models (P+CMS- and P-CMS+) to a control group (P-CMS-) or to the combined model (P+CMS+). The results in Studies #2 and #3 describe the highest levels of neuroinflammation, the presence of F. nucleatum in brain tissues of 2 rats, and the major effects on occluding or S1P pathway in the combined model (P+CMS+). Thus, this combined model is able to cause changes that cannot be explained by each model separately and can be used for the study of the association between periodontal diseases and neuropsychiatric diseases. 150 Author, year Method of Periodontitis Induction Central Nervous System Disease Method of CNS disease induction Exposure - > Outcome Periodontitis results Central Nervous System results Periodontitis and neurodegenerative diseases Duan et al. (2022) Ligatures coated with Pg 6 weeks AD Intracerebroventr icular injection of streptozin P -> AD Higher ABL in P group. Not quantified P group: Learning and memory function impairment (vs. control group). P + AD group: lower number of neurons, increased tau phosphorylation (vs. AD group). Yan et al. (2022) Ligatures coated with Fn 6 weeks AD Subcutaneous injections with D- galactose and AlCl3 6 weeks P -> AD Higher ABL in P+AD group (≈0,8 mm) (vs. AD and control). Higher ABL in AD group ≈0,6 mm (vs. control). P+AD group: higher number of Aβ1-42 cells in the brain and higher expression of p-Tau181 in the brain Periodontitis and neuropsychiatric diseases Breivik et al. (2015) Ligatures 3 weeks Depression Maternal deprivation D -> P P+D+: ABL 0.90 (0.07) mm P+D-: ABL 0.81 (0.02) mm P+D+: Behavioral alterations in the OFT, lower weight gain, lower corticosterone levels after a LPS exposition, higher glucocorticoid receptor in the hippocampus. Soletti et al. (2009) Ligatures 40 days Depression Neonatal injection of 30 mg/kg clomipramine D -> P P+D+: ABL 0.51-0.60 mm P+D-: ABL 0.64-0.64 mm Behavioral alterations of D rats only in the OFT. Breivik et al. (2006) Ligatures 3 weeks Depression Olfactory bulbectomy (OB) D -> P Rats with OB: higher ABL 1,06 (0,25) mm Rats with OB + P: decreased expression of glucocorticoid receptor in the hippocampus 151 Table 3: Models of periodontitis induction and their results on central nervous system. CNS: central nervous system; Pg: Porhyromonas gingivalis; Fn: Fusobacterium nucleatum; AD: Alzheimer´s Disease; P: periodontitis; ABL: alveolar bone level; 8-OHdG: 8- hydroxyguanosine; OFT: open field test; OB: olfactory bulbectomy; K1: W50 serotype; K2: HG184; K4: ATCC® 49417TM; GPA: glycophorin-A (non-encapsulated strain). Central nervous system changes induced by periodontitis (without SNC disease induction) Kose et al. (2021) Ligatures 5 weeks No No P -> CNS changes Higher ABL measured in histomorphometric and radiomorphometric analysis. Furcation level: 509,81 (72,04) um Buccal level: 1066,62 (203,03) um Distal level: 1137,03 (238,92) um Higher 8-OHdG activity in the P group. Increase in IL-1 β and oxidative membrane damage in the hippocampus. No degenerative or apoptotic changes by P. Hu et al. (2021) Ligatures 8 weeks No No P -> CNS changes Higher ABL in P group. Not quantified. Higher levels of IL-1 β, IL-6, IL-8 and IL-21 in the brain in the P group. Cognitive impairments (memory and learning ability), activated microglia and astrocytes in P group. Díaz- Zúñiga et al. (2020) Pg injection: K1, K2, K4, GPA No No P -> Spatial memory Higher ABL in P groups (K1, K2, K4). Not quantified. Rats infected with K1 or K2 exhibited worse spatial memory (vs. all other groups) K1 and K2 serotypes: higher levels of IL-1b, IL- 6 in the hippocampus (vs. control) No differences in the total number of astrocytes and neurons Varotto et al. (2020) Ligatures 2 or 4 weeks No No P -> Anxiety N/A Anxiety-like behaviors only in the 2 weeks P induction 152 3- Neuroinflammation: the key point of the association The results of this PhD thesis (Studies 2 and 3) have demonstrated that the combination of periodontitis and CMS is related to the highest levels of neuroinflammation, which is proposed as the main mediator in the relationship between periodontitis and depression. Oral microbiota can impact the CNS in two main different ways. First, the increased levels of peripheral LPS can trigger neuroinflammation (Pussinen et al., 2007, Martín-Hernández et al., 2016). However, the results from this PhD thesis, contrary to what might be expected, found a decrease in the plasma levels of LPS and LBP in P+CMS+ compared to controls and P+CMS-. Even if this event requires further investigation, a plausible hypothesis implies a compensatory lipoprotein-mediated transport of free plasma LPS to the CNS (Vargas-Caraveo et al., 2017), as the apolipoprotein APOA1, explored in Study 2, was increased in CMS+ animals. Second, the presence of periodontal bacteria in the brain has been described (Ilievski et al., 2018, Dominy et al., 2019) and can contribute directly to neuroinflammation. In this project, the presence of F. nucleatum was demonstrated in the brain of two rats in the P+CMS+ group (Study 2). All these results introduce the term “leaky mouth” as an analogy of the well-described “leaky gut” in neuropsychiatric diseases. In the case of the gut, bacterial translocation has been reported in patients with depression and schizophrenia (Severance et al., 2012), with increased levels of peripheral specific IgA and IgM against gut bacteria (Maes et al., 2019, Maes et al., 2012). Further studies are required to demonstrate these results for oral bacteria, but it is plausible that in periodontitis patients, due to the widening of the intercellular spaces between the epithelial cells and the rupture of epithelium in the periodontal pockets, a pathway for bacteria to enter the bloodstream is facilitated (Castillo et al., 2011). 153 4- Far beyond inflammatory markers: BBB and microglial alterations Blood-brain barrier is a key structure in protecting the CNS against bacterial colonization (Daneman and Prat, 2015). The presence of periodontal bacteria or bacterial products in the brain set the specific objective in Study 3 of determining the expression of molecules associated to BBB permeability in a combined model of periodontitis and depression. Patients with depression have shown a significant BBB disruption in frontal cortex in postmortem samples (Rajkowska and Stockmeier, 2013). This finding was also corroborated in animal models with a downregulation of BBB tight junction proteins in the hippocampus after CMS (Sun et al., 2016, Taler et al., 2021), and was also demonstrated in the present PhD thesis (Study 3). Moreover, our results showed that periodontitis exposure could contribute to BBB permeability as in addition to ZO-1 downregulation, rats with P+CMS+ showed a decrease in occludin that did not occur in P-CMS+. Further studies are needed to study the impact of oral microbiota on the BBB permeability, as incipient evidence has shown that gingipains from P. gingivalis can contribute to this dysfunction via the decrease in the expression of ZO-1 and occluding (Nonaka et al., 2022). Neuroinflammation and BBB permeability are indeed bidirectional processes. On one hand, BBB dysfunction allows trafficking of immune cells, bacteria (or bacterial products) or inflammatory mediators into brain parenchyma (Takata et al., 2021). In fact, P+CMS+ animals showed the greatest values of inflammatory mediators (IL- 1β, TNF- α and NF-𝜅B) in frontal cortex brain samples (Study 2) and an overexpression of ICAM-1 and VCAM-1 (Study 3), which are cell-adhesion molecules involved in immune trafficking. Different studies have reported an upregulation of all these molecules in the frontal cortex and plasma of depressed patients (Blum et al., 2019, Thomas et al., 2000, Dowlati et al., 2010, Enache et al., 2019). On the other hand, and consistently with above mentioned results, groups 154 exposed to CMS in this work showed higher levels of microglial cells together with some qualitative changes of their morphology (Study 3) that suggest an activated phenotype. This activated phenotype has been associated in the literature BBB dysfunction (Kang et al., 2020), as increasing evidence indicates that microglial activation modulate expression of tight junction proteins (da Fonseca et al., 2014). Figure 8: Blood-brain barrier dysfunction, sphingosine-1-phosphate (S1P) pathway modulation, and microglial activation in rats exposed to a pre-clinical model of periodontitis and depression (P+CMS+). Different color arrows represent the P+CMS+ effects compared to P-CMS- (white), P+CMS- (pink), and P-CMS+(blue). Dashed lines indicate hypothetical consequences of the described findings. The figure was prepared using the Motifolio Illustration Toolkits (https://motifolio.com) (Motifolio, Inc., Ellicott City, MD, USA) and edited with Microsoft PowerPoint 365 (Microsoft Corporation, Redmond, WA, USA). Abbreviations: BBB, blood-brain barrier; S1P, sphingosine-1-phosphate; Sphk1: sphingosine kinase 1; Sphk2, sphingosine kinase 2; SGPP2, sphingosine-1-phosphate phosphatase-2; SGPL1, sphingosine-1-phosphate lyase-1; S1PR1, sphingosine-1-phosphate receptor 1; S1PR3, sphingosine- 1-phosphate receptor 3; RAC1/2/3, Rac family small GTPase 1/2/3; ZO-1, zonula occludens; ICAM- 1, intercellular adhesion molecule-1; VCAM-1, vascular cell adhesion molecule-1; MMP9, matrix metalloproteinase-9; F. nucleatum, Fusobacterium nucleatum. 155 Among the linking mechanisms between neuroinflammation and BBB dysfunction, we have studied matrix metalloproteinase 9 (MMP9) and S1P pathway. Figure 8 illustrates these main findings of Study #3, which may provide new insights to the mechanisms linking both diseases. Metalloproteinase 9 has been classically associated to connective tissue destruction due to periodontitis (Hannas et al., 2007). Indeed, a reduction of MMP levels have been demonstrated in gingival crevicular fluid after periodontal treatment (Gonçalves et al., 2013). Our results, show an upregulation of MMP9 levels in the frontal cortex of periodontitis groups (P+CMS- and P+CMS+) (Study #3), in line with other pre-clinical and clinical studies that have demonstrated higher MMP9 levels in blood after periodontitis induction, leading to brain damage through inflammatory and oxidative stress pathways (Cueno and Ochiai, 2018, Kluknavská et al., 2022). Sphingosine-1-phosphate pathway is also of importance due to the role of S1P in differentiation and migration of CNS cells, immune trafficking, vascular integrity and neuroinflammation (Ghasemi et al., 2016). Its role in periodontitis has not been extensively studied, but it is some recent evidence of increased serum S1P levels in patients with periodontitis, which decrease after non-surgical therapy (steps 1 & 2 of therapy) (Hamdan et al., 2021, Moritz et al., 2021). 5- Strengths and limitations The results of this work are promising, since they have explored for the first time the mechanisms related to the co-morbidity between periodontitis and depression, focusing on periodontitis as an exposure factor. It has resulted in findings that, on one hand, help to explain how both diseases are related, and on the other hand, shed light on how peripheral processes can affect the CNS, specifically, the physiopathology of depression. However, there are also some limitations in this work, being the most important that the results come from a preclinical model, which of course allow for the description 156 of the mechanisms involved in the relationship but forces us to be very cautious when results are extrapolated to what happens in patients. Moreover, the periodontitis model, even if chosen to explore the role or oral microbiota in the development and progression of neuropsychiatric diseases, it was not able to produce severe alveolar bone loss. Future studies on this field should be considered to combine more severe periodontitis models with the introduction of oral bacteria, as this would amplify the systemic effect of periodontitis. 6- Future research On one hand, there are still unresolved questions derived from this combined model that need from further analyses to be clarified. First, it was hypothesized in Study 2 that the decreased plasma levels of LPS and LBP in the P+CMS+ group could be mediated by a compensatory lipoprotein-mediated transport aimed to regulate the free plasma LPS with its negative consequences, and that APOA1 protein can bind and transport LPS to the CNS. Moreover, BBB disruption was analyzed in Study 3 using protein or mRNA expression of molecules involved in BBB permeability, which is an indirect measurement. Both of these findings should be corroborated and studied in depth with alternative methodologies in future studies. On the other hand, this PhD thesis has described some mechanisms involved in the biologic plausibility regarding the association between periodontitis and depression, however, to create strong evidence about this association more research is needed. For example, there is no evidence derived from intervention clinical studies, which will be required in the future to study if periodontal treatment influences depressive symptoms. 157 158 159 CONCLUSIONS Within the limitations of the present project, it can be concluded that the potential association between periodontitis and depression may be mediated by inflammatory mechanisms (neuroinflammation) and the presence of periodontal bacteria in the central nervous system. 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HYPOTHESIS AND OBJECTIVES 5. MATERIALS AND METHODS RESULTS STUDY 1: THE ROLE OF THE ORAL MICROBIOTA RELATED TO PERIODONTAL DISEASES IN ANXIETY, MOOD AND TRAUMA-AND STRESS-RELATED DISORDERS STUDY 2: PERIODONTAL DISEASES AND DEPRESSION: A PRE-CLINICAL IN VIVO STURY STUDY 3: NEUROINFLAMMATION RELATED TO THE BLOOD-BRAIN BARRIER AND SPHINGOSINE-1-PHOSPHATE IN A PRE-CLINICAL MODEL OF PERIODONTAL DISEASES AND DEPRESSION IN RATS 6. DISCUSSION 7. CONCLUSIONS REFERENCES