bioRxivNeurosciencePreprint
Human HYPOMAP: A comprehensive spatio-cellular map of the human hypothalamus
John A. TadrossiD, Lukas SteuernageliD, Georgina K.C. DowsettiD, Katherine A. KentistouiD, Sofia Hult LundhiD, Marta PornieceiD, Paul KlemmiD, Kara RainbowiD, Henning HvidiD, Katarzyna Kania, Joseph Polex-WolfiD, Lotte Bjerre KnudseniD, Charles PykeiD, John R. B. PerryiD, Brian LamiD, Jens C. BrüningiD, Giles S.H. YeoiD
Abstract
The hypothalamus is a brain region that plays a key role in coordinating fundamental biological functions. However, our understanding of the underlying cellular components and circuitry, have, until recently, emerged primarily from rodent studies. Here, we combine a single-nucleus sequencing database of 433,369 human hypothalamic cells, with spatial transcriptomics, to present a comprehensive spatio-cellular transcriptional map of the human hypothalamus, the HYPOMAP. Analysing hypothalamic leptin melanocortin pathway neuronal populations that play a role in appetite control, we identify spatially distinct populations of arcuate nucleus POMC and AGRP neurons, and their receptors MC3R and MC4R. Next, we map the cells expressing incretin receptors, targets of the new generation of anti-obesity medications, and uncover transcriptionally distinct GLP1R and GIPR-expressing cellular populations. Finally, out of the 458 hypothalamic cell types in HYPOMAP, we find 182 neuronal clusters are significantly enriched in expression of BMI GWAS genes. This enrichment is driven by 375 effector genes, with rare deleterious variants in 6 of these; MC4R, PCSK1, POMC, CALCR, BSN and CORO1A, the last of which has previously not been linked to obesity; being significantly associated with changes in BMI at the population level. Thus, the HYPOMAP provides a detailed atlas of the human hypothalamus in a spatial context, and serves as an important resource to identify novel druggable targets for treating a wide range of conditions, including reproductive, circadian, and metabolic disorders.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 8
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