Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.06.20.660741

MRI-Based Structural Development of the Human Newborn Hypothalamus

Abstract

BackgroundPreclinical evidence suggests that intrauterine exposures can impact hypothalamic structure at birth and future disease risk, yet early human data are limited. MethodsHypothalamic volumes were measured from 699 T1-weighted MRI scans from 631 newborns (54% female; 27-45 weeks postmenstrual age/PMA) in the Developing Human Connectome Project. Linear mixed-effects models tested associations with prenatal exposures: gestational age (GA) at birth, PMA at scan, sex, maternal body mass index (BMI), and smoking. Findings were partially replicated in the Adolescent Brain and Child Development (ABCD) Study (release 5.1) data (16,934 observations from 11,207 participants). ResultsAbsolute hypothalamus volume increased with PMA (+5.5%/week, t=39.9, p<10-{superscript 1}), but not after adjusting for brain volume (t=1.2, p=0.24). Males showed larger absolute (+3.3%, t=3.2, p=0.002) but smaller relative hypothalamus volume (t=-2.8, p=0.005). Lower GA was linked to larger relative hypothalamus volume (t=-6.5, p<10-), with evidence for sex moderation (t=-2.4, p=0.019). Smoking during pregnancy was associated with smaller hypothalamus volume in newborns (t=-2.05, p=0.04; dose dependence: t=-2.9, p<0.01). Smoking remained associated with reduced hypothalamus volume in adolescents (t=-2.8, p=0.005). ConclusionsThe findings suggest that the hypothalamus is a crucial and underexplored target of perinatal influences for understanding the origins of long-term health and disease. Impact- This study highlights the hypothalamus as a critical and underexplored target for understanding how prenatal exposures in human newborns could influence long-term health and disease. - Gestational age (GA) at birth, postmenstrual age at scan, and smoking during pregnancy are associated with hypothalamic volume in newborns. - The effects of GA on adjusted hypothalamic volume appear to be transient, while the effects of smoking seem to last throughout adolescence. - Our findings suggested sex-specific effects on the associations between volume and age measures across development.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Yen, E., De Asis-Cruz, J., Rasmussen, J. M.. 2025-06-21. MRI-Based Structural Development of the Human Newborn Hypothalamus. https://doi.org/10.1101/2025.06.20.660741

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗