Skip to content
Open access

Systematic Evaluation of Competing Brain Transcriptomic Representations Reveals Reciprocal Patterns Across Heterogeneous Contexts

Jul 2026 · International Journal of Molecular Sciences · Vol 27, pp. 6083 · 0 citations · 63 references
Medicine

TL;DR

Two representations of cross-context brain transcriptomic organization are compared: a transcriptome-wide global-axis model and a low-dimensional reciprocal model, motivating a low-dimensional reciprocal representation as an exploratory framework while emphasizing context dependence, cohort dependence, and heterogeneity.

Abstract

Adaptive and adverse brain states are often assumed to lie on a shared molecular continuum, but this assumption has rarely been evaluated against explicit transcriptomic alternatives. This study aimed to compare two representations of cross-context brain transcriptomic organization: a transcriptome-wide global-axis model and a low-dimensional reciprocal model. We benchmarked these models across a curated cross-study brain cohort spanning exercise, alcohol-related adversity-like contexts, stress, aging, and neurodegeneration, using prespecified intervention-like and adversity-like directional contrast labels rather than assuming homogeneous biological states. We assessed the competing representations using signed-effect correlations, permutation analyses, non-linear fitting, and held-out reconstruction, and we then examined the resulting structure through region-specific human bulk evaluation and exploratory cellular, single-nucleus, spatial, and chromatin projection analyses. These downstream analyses were used to examine localization and biological interpretability and were not treated as independent evaluation of the module 1/module 2 (M1/M2) partition. The combined signed-effect statistics were interpreted as representation-level directional summaries rather than estimates of a homogeneous cross-study biological effect. The global-axis model received limited support: intervention-like and adversity-like signed-effect summaries were only weakly correlated, were not stronger than permutation null expectations, and were not improved by non-linear fitting. Within the selected reciprocal-gene space, a rank-1 latent profile reconstructed held-out genes more accurately than the hard M1/M2 partition, whereas the M1/M2 discretization provided a more interpretable but selection-conditioned directional summary. Human analyses yielded an asymmetric pattern: a significant M1 association was observed only in the hippocampal dataset, whereas M2, the reciprocal index, and the other examined brain regions showed no consistent corresponding effects; leave-one-stratum-out analyses indicated poor cross-stratum reproducibility of the exact gene-level partition. These findings motivate a low-dimensional reciprocal representation as an exploratory framework while emphasizing context dependence, cohort dependence, and heterogeneity.

Read PDF

Similar papers

Open access Aug 2026

Cross-Modal Brain Network Disruptions in Schizophrenia: Insights from Multiplex Modeling and Transcriptomic Associations.

Multiplex network modeling uncovers cross-modal disruptions in brain organization in SCZ and links these alterations to specific molecular pathways and glial-neuronal substrates, providing multiscale insights into the disorder's neurobiology.

Wei Zhao, Hanrui Chen, Hairong Xiao et al. · 0 citations
Open access Aug 2026

Multiscale spatial transcriptomics resolves the cellular and molecular architecture of the human amygdala

A spatial transcriptomic atlas of the human amygdala from nine neurotypical donors provides a foundational resource and framework for accelerating cross-species comparisons and human disease-focused investigations.

Michael S. Totty, Svitlana V. Bach, Madeline R. Valentine et al. · 0 citations
Open access Sep 2026

An Integrated Single-Nucleus Atlas Resolves Cell-Type-Specific Programs and Molecular Subtypes in Alzheimer’s Disease

Interindividual heterogeneity in Alzheimer’s disease (AD) remains poorly understood, as disparate single-cell studies leave it unclear whether findings reflect shared architecture or dataset-specific idiosyncrasies. Here, we present panAD, a transcriptomic atlas of >3 million nuclei from 791 individuals across 13 studi...

Negin Rahimzadeh, S. Morabito, S. Khullar et al. · 0 citations
Review Open access Aug 2026

AI-Guided Systems Neurogenomics in Neurodevelopmental Disorders

A hypothesis-generating load-capacity framework comprising regulatory load, network capacity, developmental buffering and regulatory network instability is proposed, and the Instability Twin is described as a prospective architecture composed of independently testable patient-specific sub-models rather than an existing...

H. Goel, T. Dudding-Byth, B. Kamien · 0 citations
Open access Aug 2026

Coordinated dysregulation of modular gene activity in human neuropathologies

By comparing CoPA projection patterns between normal and pathological human brain samples using differential CoPA, this work identifies gene coexpression modules that are uniformly and reproducibly dysregulated in specific neocortical cell types in Alzheimer’s disease or schizophrenia.

Gugene Kang, M. C. Oldham · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.