Endocrine Abstracts

Single-cell and spatial genomics are reshaping hypothalamic biology by resolving molecular diversity at cellular resolution while preserving anatomical context. Our efforts to map the adult human hypothalamus through HYPOMAP integrate single-nucleus RNA sequencing with spatial transcriptomics to generate a reference of cell states, their organisation, and their relevance to the physiology & pharmacology of energy balance. Across ~430,000 nuclei, HYPOMAP delineates 452 transcriptionally defined clusters spanning neuronal and non-neuronal populations and maps their spatial distributions across the human hypothalamus. The results show broad conservation of major cell classes across species alongside notable divergence in neuronal subtypes and drug-relevant receptor programmes, underscoring why translation from rodent models can succeed in principle yet fail in detail. Within systems central to body-weight regulation, the atlas reveals species differences in the cellular and spatial organisation of key endocrine-relevant pathways, including the melanocortin and incretin systems, with direct implications for interpreting pharmacology and refining target biology. By anchoring human genetics to specific cell populations, the data further sharpen where, and in which cell types, BMI heritability is manifested. Common-variant BMI association signals are enriched in defined neuronal populations and nominate putative effector genes, while rare variant burden implicates genes with established links to BMI and highlights additional candidates for investigation. These convergent genetic signals provide a bridge from population studies to candidate circuits and mechanisms. A concrete example is DENND1B-mediated regulation of MC4R trafficking: integrating genetic evidence with cell-resolved expression and spatial localisation supports biological plausibility in the human hypothalamus and illustrates how atlases can move beyond cataloguing to enable hypothesis generation. Together, these results position human spatio-cellular atlases as enabling infrastructure for discovery—connecting anatomy, cell identity, and human genetics to accelerate mechanistic insight and therapeutic translation in endocrinology.