Award Winner Describes Efforts to Improve Cognition in People With Bipolar Disorder
Notice bibliographique
Résumé
Back to table of contents Previous article Next article Clinical & ResearchFull AccessAward Winner Describes Efforts to Improve Cognition in People With Bipolar DisorderNick ZagorskiNick ZagorskiPublished Online:22 Dec 2023https://doi.org/10.1176/appi.pn.2024.01.1.37AbstractAt the 2023 BBRF Mental Health Research Symposium, Roger McIntyre, M.D., outlined how obesity poses more than physical health risks to people with bipolar disorder or other mood problems.About 30 years ago, Roger McIntyre, M.D., then a newly minted psychiatrist, noticed something about his patients with bipolar disorder that would change the arc of his career: Patients who were overweight were more likely to have cognitive deficits than those who were not overweight.Insulin has shown some neuroprotective effects in the brain, which may explain why obesity and insulin resistance can increase cognitive problems in people with bipolar disorder, said Roger McIntyre, M.D., during his BBRF presentation.Chad David KrausMcIntyre became focused on uncovering the relationship between weight and cognition in patients with bipolar disorder. His efforts have helped psychiatrists to better understand how metabolism and cognition are intertwined and earned McIntyre the 2023 Colvin Prize for Outstanding Achievement in Mood Disorders Research from the Brain & Behavior Research Foundation (BBRF).McIntyre, who is a professor of psychiatry and pharmacology at the University of Toronto, delivered a presentation on some of his work as part of BBRF’s Mental Health Research Symposium in New York. This annual event recognizes the work of exceptional psychiatric researchers (see box).During his presentation, McIntyre noted that the relationship between weight and cognition in patients with bipolar disorder seems to manifest early.BBRF Recognizes Recipients of 2023 Outstanding Achievement PrizesLieber Prize for Outstanding Achievement in Schizophrenia Research: Philip D. Harvey, Ph.D., University of Miami.Maltz Prize for Innovative and Promising Schizophrenia Research: Amy E. Pinkham, Ph.D., The University of Texas at Dallas.Colvin Prize for Outstanding Achievement in Mood Disorders Research: Roger McIntyre, M.D., University of Toronto.Ruane Prize for Outstanding Achievement in Child & Adolescent Psychiatric Research: Katie McLaughlin, Ph.D., University of Oregon.Goldman-Rakic Prize for Outstanding Achievement in Cognitive Neuroscience Research: Elizabeth A. Phelps, Ph.D., Harvard University.He described a study in which he teamed up with a group of researchers in China to examine the cognitive performance of youth who had at least one parent with bipolar disorder but no bipolar diagnosis themselves. (These youth are considered to be high risk for the disorder.) They found that youth with higher body mass .index (BMI) performed worse on attention, working memory, and other cognitive tests. The negative impact of BMI on cognition was even more pronounced in youth who exhibited some mood symptoms.Brain imaging data collected by McIntyre and others also revealed that individuals with bipolar disorder and those with obesity share similar dysfunction in brain activity related to cognition and reward processing. Importantly, in individuals with obesity and bipolar disorder, these shared deficits are additive and lead to even more cognitive problems.Insulin May Be the KeyMcIntyre noted that about 50% of people with bipolar disorder have comorbid diabetes or pre-diabetes.“Insulin has a neuroprotective role in the brain,” he said, adding that insulin resistance has been linked with accumulation of Alzheimer’s-related amyloid proteins. In addition, insulin can also inhibit the enzyme monoamine oxidase—the same enzyme targeted by antidepressants known as monoamine oxidase inhibitors (MAOIs).For a long time, measuring insulin signaling in the brain was challenging. In 2021, McIntyre’s colleague at the University of Toronto, Rodrigo Mansur, M.D., led a study that managed to isolate brain-derived vesicles from the blood of patients with bipolar disorder. The researchers found evidence to suggest that individuals with cognitive problems had insulin resistance that spread to the brain.“So how do we slow this process down?” McIntyre asked. Fortunately, the same approaches that target diabetes and insulin resistance in the rest of the body may improve psychiatric symptoms, he said. A 2012 study by McIntyre suggested that intranasal insulin therapy was associated with executive function improvements in people with bipolar disorder, for example. Another study published in 2022 found metformin could lead some people with bipolar disorder to convert from an insulin-resistant to insulin-sensitive state, and those who converted showed significant improvements in depressive symptoms after six months.McIntyre noted that he’s keeping close watch on the new weight loss drugs called GLP-1 agonists (Ozempic and related medications).“There is evidence that GLP-1 agonists have direct effects on the brain, including an ability to restore dopamine imbalance.”“What if these agents are psychiatric drugs that are masquerading as weight loss drugs?” McIntyre said.He noted that his group in Toronto has just launched a clinical trial testing Ozempic as an adjunct medication for the treatment of cognitive problems in people with major depression. And he’s not alone; he said that organizations in both the private and public sectors are looking at repurposing these diabetes medications.“When I sat with my first bipolar patient, no one was talking about psychiatry and metabolism, but the field has now taken off,” McIntyre said. “I really think this will soon open up a new section on the drop-down menu of therapeutics for people living with depression or bipolar disorder.” ■ResourceMore information on the 2023 BBRF International Mental Health Research Symposium along with videos of all scientific presentations ISSUES NewArchived
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,001 |
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 tête enseignante, 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 ».