Identification of a Hypothalamic Neural System That Can Reduce Body Weight and Adipose Mass in Diet-Induced Obesity

Abstract

Dynamic hypothalamic circuits balance energy intake with expenditure to protect individuals from obesity. Lasting negative energy balance, however, triggers a compensatory decrease in energy expenditure, hindering progressive weight loss. While we understand some key players underlying energy balance, the detailed neural underpinnings remain unclear. Here I will delineate the functional efferent circuitry from the ventromedial hypothalamic nucleus (VMN) that facilitates weight loss and prevents rebound weight gain. VMN neurons have long been linked to a role in energy balance. Both vesicular communication by VMN steroidogenic factor 1 (SF1) neurons and pituitary adenylate cyclase activating peptide (PACAP) release from VMN neurons are essential for maintaining body weight and activating VMNSf1 neurons curbs diet-induced obesity without altering food intake. However, the exact pathway of this VMN signal is unclear because the VMN does not directly communicate with preganglionic sympathetic neurons, indicating signal transmission through an efferent node. Of the few brain sites they communicate with, VMNSf1 neurons sends the densest projections to the caudal preoptic area (POA) and the anterior bed nucleus of stria terminalis (BNST). Stimulating VMNPACAP axonal fibers in the caudal POA, but not anterior BNST, induced thermogenesis in brown and beige adipose tissues in both sexes of mice. To identify caudal POA populations in body weight regulation, I activated excitatory (glutamatergic) and inhibitory (GABAergic) caudal POA cells in diet-induced obese male mice and found that both glutamatergic and GABAergic caudal POA neurons can reduce diet-induced obesity through separate means. While there is intra-POA communication, my data supports efferent communication with separate downstream circuits by glutamate and GABA caudal POA cells in ameliorating diet-induced obesity. Because the POA and BNST are extremely complex regions with diverse functions, I then employed deep transfer learning to pinpoint obesity and diabetes risk-associated cell subsets in the POA and BNST. Using single nuclei RNA sequencing on >200,000 nuclei from both sexes of mice, I identified 6 specialized sets of caudal POA and BNST neuronal subtypes that increased in obese and glucose-intolerant mice on a high-fat diet. Targeting these newly identified pathways and neuron subtypes could lead to future obesity and diabetes therapeutics.