Max Planck Institute for Metabolism Research

Animals learn about the external world, in part, via interoceptive signals1,2. For example, the nutrient content of food is first estimated in the mouth, in the form of flavor, and then measured again via slower signals from the gut. How these signals from the mouth and gut are integrated to drive learning is unknown. Here we identify a lateralized dopamine pathway that is specialized for learning about the nutrient content of food. We show that dopamine neurons in the ventral tegmental area (VTADA) are necessary for associating nutrients with flavors, and that post-ingestive nutrients trigger DA release selectively in a small region of the anterior basolateral amygdala (BLA) but not canonical DA targets in striatum. Remarkably, this nutrient-triggered DA release occurs preferentially on the left side of the brain in both mice and humans, revealing that the DA system is functionally lateralized. We identify the gut sensors that are responsible for nutrient-triggered DA release; show that they activate BLA-projecting DA neurons defined by expression of cholecystokinin (CCK); and demonstrate that stimulation of DA axon terminals in the anterior BLA drives flavor-nutrient learning but not other aspects of feeding behavior. Two-photon imaging of neurons in the left anterior BLA reveals that they integrate gustatory and post-ingestive cues, and silencing these neurons prevents flavor-nutrient learning. These findings establish a neural basis for how animals learn about the nutrient content of their food. They also reveal unexpectedly that post-ingestive nutrients are differentially represented on the right and left sides of the brain.

Many treatments exist for depression, yet none are universally effective. Multivariable predictive models support personalized treatment selection. To develop a model predicting response to internet-delivered cognitive behavioral therapy (iCBT) and test its treatment specificity against antidepressant medications. The Precision in Psychiatry prognostic study was a 4-week study collecting extensive baseline self-report and cognitive data online to predict early iCBT response, from February 2019 to May 2022. Patients in the iCBT group were recruited via an Irish mental health charity and a UK NHS Talking Therapies clinic. A separate antidepressant group was recruited globally online and via print advertisements. Participants were aged 18 to 70 years, fluent in English, had computer access, started treatment within 2 days of enrollment, and scored at least 10 on the Work and Social Adjustment Scale. Analysis was completed in December 2024. Low-intensity, clinician-guided iCBT with multimedia psychoeducation. Patients receiving antidepressants primarily received selective serotonin-reuptake inhibitors or serotonin-norepinephrine reuptake inhibitors. Machine learning models were trained using the iCBT sample to predict change in depression severity (16-item Quick Inventory of Depressive Symptomatology-Self Report) at week 4. The best model was tested on holdout iCBT and antidepressant data. A separate model was trained on patients receiving iCBT only to assess treatment-specificity. Of 2674 patients screened, 883 completed baseline and final assessments, with 776 patients receiving iCBT (mean [SD] age, 31.8 [11.0] years; 600 [77.5%] female) and 107 patients receiving antidepressant medication (mean [SD] age, 30.1 [10.4] years; 78 [72.9%] female). Both samples had some treatment overlap (24% and 34%, respectively). Elastic net regression with 27 predictors best explained the variance in depression change (R2 = 14%; SD, 0.8%; 95% CI, 13.8%-14.2%). Key predictors included baseline depression, treatment expectation, transdiagnostic symptoms, and, less strongly, cognitive variables. The model performed well on holdout iCBT (R2 = 18.8%; root mean square error [RMSE], 0.88) and antidepressant (R2 = 17.9%; RMSE, 1.10) data. Retraining on 181 patients who received iCBT only increased treatment specificity in predictions (R2 = 19.3%; RMSE, 0.89) vs 71 patients who received antidepressants only (R2 = 10.8%; RMSE, 1.17). This prognostic study in a naturalistic setting found that self-reported data predicted iCBT response better than cognitive data. Model predictions generalized to patients receiving antidepressants, some of whom also received psychotherapy. Training models on single-treatment cohorts may yield more treatment-specific predictions.

This Viewpoint discusses the use of glucagon-like peptide-1 (GLP-1) receptor agonists as a strategy to manage psychotropic-induced weight gain.

Selective functionalization of C­(sp3)–Hbondsremains challenging yet crucial for researchers. A frequently usedapproach by chemists to tackle this challenge involves leveraging1,2-metal migration/insertion, which enables the selective activationand cleavage of a specific C­(sp3)–H bond adjacentto or distant from the directing group. Palladium is among the mostcommonly employed catalysts for C­(sp3)–H functionalizationthrough metal migration/insertion, with Pd­(OAc)2 beingthe predominant palladium complex utilized in these processes. 1,2-Palladiummigration is a key strategy for achieving selective C­(sp3)–H functionalization. After palladium coordinates to a directinggroup, its migration can activate the nearby C­(sp3)–Hbond. With subsequent migrations, more distant C­(sp3)–Hbonds can be targeted and transformed into C­(sp3)–functionalgroups. During the 1,2-insertion of palladium, the migration of palladiumtakes place following the activation of the C­(sp3)–Hbond. This migration step typically involves the palladium insertinginto a double bond, which links the C­(sp3)–H bondto a C­(sp2)–H bond, thereby progressing the reaction.Ultimately, this review highlights that C­(sp3)–Hfunctionalization via 1,2-palladium migration/insertion has the potentialto selectively modify both proximal and remote C–H bonds inorganic molecules, offering a valuable tool for researchers to synthesizea wide range of organic compounds in future studies. This accountencompasses all types of 1,2-palladium migration/insertion and examinestheir impact on C­(sp3)–H functionalization. It providesa detailed analysis of the mechanisms involved and explores how thesemigrations enable the activation of both remote and proximal C­(sp3)–H bonds with the directing group.

Abstract Our understanding of the genetic architecture of obesity has primarily been shaped by observations from adult populations with relatively few studies on childhood obesity. To address this gap, we conduct a longitudinal genetic association study in up to ∼600,000 individuals with objectively measured or recalled childhood adiposity-related traits. We identify 624 common variant signals (only 7% are previously reported) associated with childhood adiposity, of which one third have no concordant association with adult BMI. Signals linked to the leptin-melanocortin pathway (BSX, GNAS,LEPRandPCSK1) and incretin-signalling genes (GIPRandGLP1R) show stronger associations in childhood than in adults, suggesting that childhood provides a more sensitive window for detecting variation in key endocrine and neuropeptide pathways regulating energy balance. This observation is further supported by integrating single-nucleus RNA sequencing data from the human hypothalamus, identifying childhood-specific adiposity-regulating cell populations in the arcuate nucleus and mammillary bodies, indicating distinct neuro-circuits that regulate adiposity only during childhood. Three signals showed parent-of-origin specific associations with childhood BMI, atKLF14(maternal-specific),GNAS(parental-discordant) andZDBF2(paternal-specific). Finally, we complement these common variant analyses with DNA sequence data in 479,615 individuals, identifying rare protein-coding variation inADCY3,CALCR,MC4R,MRAP2,POMCandMYH13,all of which demonstrate stronger adiposity associations in childhood than in adults. Collectively, our findings emphasize the value of expanding research on childhood adiposity alongside studies focused on adult obesity measures.

SummaryObesity, a main driver of cardiovascular morbidity, contributes to endothelial dysfunction and inflammation in adipose tissues. Perivascular adipose tissue (PVAT) surrounds arteries and influences vascular function. In obesity, immune cells, including myeloperoxidase (MPO)-releasing myeloid cells, accumulate in PVAT. In this study, we show MPO levels to correlate with body weight and endothelial function in obese patients (n = 33) and mice. In addition, MPO deficiency reduces immune cell frequency, enhances PVAT beiging via soluble guanylyl cyclase β1 (sGC-β1), and increases oxygen consumption in vivo. Further, nitrotyrosine formation and inflammatory cytokine release are attenuated in obese Mpo−/− mice. Mechanistically, adiponectin (APN) secretion improves endothelial function and reduces arterial stiffness. In vitro, MPO-treated human white adipocytes show lower APN and brown adipocyte marker expression but increased inflammation. Thus, MPO impairs vascular function via PVAT inflammation and suppression of vasoprotective mediators, making it a potential therapeutic target in obesity-related cardiovascular disease.

Orexin signaling in the ventral tegmental area and substantia nigra promotes locomotion and reward processing, but it is not clear whether dopaminergic neurons directly mediate these effects. We show that dopaminergic neurons in these areas mainly express orexin receptor subtype 1 (Ox1R). In contrast, only a minor population in the medial ventral tegmental area express orexin receptor subtype 2 (Ox2R). To analyze the functional role of Ox1R signaling in dopaminergic neurons, we deleted Ox1R specifically in dopamine transporter-expressing neurons of mice and investigated the functional consequences. Deletion of Ox1R increased locomotor activity and exploration during exposure to novel environments or when intracerebroventricularely injected with orexin A. Spontaneous activity in home cages, anxiety, reward processing, and energy metabolism did not change. Positron emission tomography imaging revealed that Ox1R signaling in dopaminergic neurons affected distinct neural circuits depending on the stimulation mode. In line with an increase of neural activity in the lateral paragigantocellular nucleus (LPGi) of Ox1RΔDAT mice, we found that dopaminergic projections innervate the LPGi in regions where the inhibitory dopamine receptor subtype D2 but not the excitatory D1 subtype resides. These data suggest a crucial regulatory role of Ox1R signaling in dopaminergic neurons in novelty-induced locomotion and exploration.

Maternal obesity predisposes offspring to metabolic diseases. Here, we show that non-nutritive sensory components of a high-fat diet (HFD), beyond its hypercaloric, obesogenic effects, are sufficient to alter metabolic health in the offspring. To dissociate the caloric and sensory components of HFD, we fed dams a bacon-flavoured diet, isonutritional to a normal chow diet but enriched with fat-related odours. Offspring exposed to these fat-related odours during development display metabolic inflexibility and increased adiposity when fed HFD in adulthood independently of maternal metabolic health. Developmental exposure to fat-related odours shifts mesolimbic dopaminergic circuits and Agouti-related peptide (AgRP) hunger neurons’ responses to phenocopy those of obese mice, including a desensitization of AgRP neurons to dietary fat. While neither neonatal optogenetic activation of sensory circuits nor passive exposure to fat-related odours is sufficient to alter metabolic responses to HFD, coupling optogenetic stimulation of sensory circuits with caloric intake exacerbates obesity. Collectively, we report that fat-related sensory cues during development act as signals that can prime central responses to food cues and whole-body metabolism regulation.