التفاصيل البيبلوغرافية
| العنوان: |
Reverse-translational identification of a cerebellar satiation network |
| المؤلفون: |
Aloysius Y. T. Low, Nitsan Goldstein, Jessica R. Gaunt, Kuei-Pin Huang, Norliyana Zainolabidin, Alaric K. K. Yip, Jamie R. E. Carty, Ju Y. Choi, Alekso M. Miller, Helen S. T. Ho, Clara Lenhe |
| المصدر: |
Nature, Nature. 600(7888):269-273 |
| سنة النشر: |
2021 |
| الوصف: |
The brain is the seat of body weight homeostasis. However, our inability to control the increasing prevalence of obesity highlights a need to look beyond canonical feeding pathways to broaden our understanding of body weight control1–3. Here we used a reverse-translational approach to identify and anatomically, molecularly and functionally characterize a neural ensemble that promotes satiation. Unbiased, task-based functional magnetic resonance imaging revealed marked differences in cerebellar responses to food in people with a genetic disorder characterized by insatiable appetite. Transcriptomic analyses in mice revealed molecularly and topographically -distinct neurons in the anterior deep cerebellar nuclei (aDCN) that are activated by feeding or nutrient infusion in the gut. Selective activation of aDCN neurons substantially decreased food intake by reducing meal size without compensatory changes to metabolic rate. We found that aDCN activity terminates food intake by increasing striatal dopamine levels and attenuating the phasic dopamine response to subsequent food consumption. Our study defines a conserved satiation centre that may represent a novel therapeutic target for the management of excessive eating, and underscores the utility of a ‘bedside-to-bench’ approach for the identification of neural circuits that influence behaviour. |
| نوع الوثيقة: |
redif-article |
| اللغة: |
English |
| DOI: |
10.1038/s41586-021-04143 |
| الإتاحة: |
https://ideas.repec.org/a/nat/nature/v600y2021i7888d10.1038_s41586-021-04143-5.html |
| رقم الأكسشن: |
edsrep.a.nat.nature.v600y2021i7888d10.1038.s41586.021.04143.5 |
| قاعدة البيانات: |
RePEc |
