The gut microbiome: Potential innovations for the understanding and treatment of psychopathology.
Notice bibliographique
Résumé
Biological models for psychiatric disorders, such as anxiety and depression, emphasize the role of neurochemical changes in the development and maintenance of the disorders. The past decade, however, has shown increased evidence for the role of the microbiota-gut-brain axis in psychiatric disorders. Although much of this research is still in its preclinical stages and has largely been based on animal models, the findings in this area have potential implications for the conceptualization and treatment of psychiatric disorders. A number of excellent in-depth systematic and narrative reviews have been published on the topic of the microbiota-gutbrain axis and psychopathology recently (Collins, Surette & Bercik, 2012; De Angelis et al., 2015; Foster & Neufeld, 2013; Montiel-Castro et al., 2013; Wang & Kasper, 2014), many of which have been written by our research group at McMaster University. However, one of the limitations of these reviews is that they are published in basic science journals and tend to provide a very in-depth, detailed, and technical review of the basic science literature as it relates to the microbiota-gut-brain axis with limited focus on clinical implications. Therefore, the goal of the current article is to increase the visibility and accessibility of this research by providing an introduction to the topic with a strong focus on theoretical and clinical implications. Moreover, this article brings together ideas on the topic from a multidisciplinary team, including clinical psychologists, psychiatrists, gastroenterologists, and primary researchers, which highlights an interdisciplinary perspective on the topic with ideas for future research.The Gut MicrobiomeThe human body consists of a number of microbial environments that are predominantly made up of bacteria but also includes archaea, fungi, protists, and viruses. The intestinal or gut microbiome is the largest with approximately 100 trillion bacteria, most of which are located in the distal gut (Gill et al., 2006; Qin et al., 2010). The gut microbiome consists of over 1,000 distinct bacterial species (Qin et al., 2010) and its genetic material outnumbers human DNA by 10-fold. Although a core microbiome is shared by all humans, there is variability and fluctuation in the microbiota throughout the life span. This variability and fluctuation is influenced by factors such as diet, stress, infections, and antibiotic use (Cryan & O'Mahony, 2011; Forsythe, Sudo, Dinan, Taylor, & Bienenstock, 2010; Turnbaugh, Ridaura, Faith, Rey, Knight, & Gordon, 2009; Wu & Hui, 2011). The gut microbiome changes rapidly during the first 2 years of life and is influenced by a number of factors including genetics, method of birth delivery, maternal characteristics, nutrition, infections, use of antibiotics, and stress (Collado et al., 2010; Dominguez-Bello et al., 2010; Harmsen et al., 2000; Palmer et al., 2007; Penders et al., 2006).The Microbiota-Gut-Brain AxisThe microbiota-gut-brain axis is defined by the bidirectional communication between the digestive system and the central nervous system. The microbiota-gut-brain axis involves the central nervous system, the autonomic nervous system, and the enteric nervous system. The enteric nervous system consists of approximately 100 million neurons that line the gastrointestinal tract and is often referred to as the second brain because it can function autonomously (Pocock & Richards, 2006). Early research focused on the role of the gut-brain axis in digestion, metabolism, and immune functioning (Konturek, Konturek, Pawlik, & Brzozowski, 2004; Tache, Vale, Rivier, & Brown, 1980), with a strong focus on the role of the central nervous system in regulating these functions (i.e., a top-down model). More recently, there is growing appreciation for the bidirectional communication between the central nervous and digestive systems. The gut is not only influenced by the brain, but also influences the brain. …
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,004 | 0,006 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».