Resolution limits on effector composition in VMH leptin-receptor neurons
Year: 2026
Type: preprint
Abstract: Leptin acts directly on ventromedial hypothalamic (VMH) neurons to regulate energy and glucose homeostasis, and the individual neurons that respond to it do so in both directions, with many not responding at all. The prevailing hypothesis has been that these represent discrete functional subpopulations distinguished by their underlying ion conductances (effectors), implying finer genetic markers should resolve each subgroup. How much of that structure such data can see was therefore measured before anything was concluded from them. At the depth these assays reach, a per-cell effector score proved to be largely capture noise. Its component transcripts did not behave as indicators of one underlying quantity in individual cells, though they did across cell clusters. Every composition result is therefore placed at cluster and class resolution and not finer. Within those bounds, reanalyzing deposited single-nucleus and translatome datasets indicates that the composition of these effectors is distributed unevenly beneath the conserved cell classes and not specifically between them. The classes do separate on the axis, but an arbitrary panel of comparable detectability separates them about as well, so what the axis registers at that level is largely general expression difference. However, no within-class structure is detectable in the leptin-receptor population, while it is present and distributed across clusters in two neighboring classes, one of them measured with poorer sampling. The translatome supplies a second constraint: calls about individual channel genes made from single-nucleus data alone do not survive comparison against it, and the effectors that withstand both are not the ones either modality would nominate by itself. That second constraint carries a bound of its own: the translatome was collected from SF1-marked neurons, and because Lepr was not itself enriched in that fraction, the surviving repertoire describes the SF1 population as a whole, not the subset of it that expressed the leptin receptor. At the resolution these data allow, transcriptional identity does not resolve differences in effector composition within this population. The particular configuration the subpopulation account predicts still lies outside what this test can detect, and the step from composition to response sign remains an assumption, not a measurement.
Author: Kaniganti, Tarun
Institution: Columbia University
Language: English
Subfield: Endocrine and Autonomic Systems
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7225466430