Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.09.25.614887

The relationship between brain activation and mitochondrial complex I protein levels during cognitive function in healthy humans: an BCPP-EF PET and functional MRI study of task switching

Shatalina, E.·Whitehurst, T.·Chika Onwordi, E.·Whittington, A.·Mansur, A.·Arumuham, A.·Reis Marques, T.·Gunn, R. N.·Natesan, S.·Nour, M. M.·Rabiner, E. A.·Wall, M. B.·Howes, O. D.
View original source ↗Export metadata ↓

Abstract

Mitochondrial complex I is the largest enzyme complex in the respiratory chain and can be non-invasively measured using [18F]BCPP-EF positron emission tomography (PET). Neurological conditions associated with mitochondria complex I pathology are also associated with altered blood oxygen level dependent (BOLD) response and impairments in cognition. To evaluate the link between mitochondrial complex I, cognition and associated neural activity, 23 cognitively healthy adults underwent a [18F]BCPP-EF PET scan and a functional magnetic resonance imaging (fMRI) scan during which they performed a task switching exercise. We found significant positive associations between [18F]BCPP-EF volume of distribution (VT), which measures mitochondrial complex I levels and the task switching fMRI response (Partial Least Squares (PLS) Canonical Analysis (CA), first component r=0.51, p=0.03). Exploratory Pearsons correlations showed significant positive associations between mitochondrial complex I levels and the fMRI response in regions including the dorsolateral prefrontal cortex (r=0.61, p=0.0019), insula (r=0.46, p=0.0264) parietal-precuneus (r=0.51, p=0.0139) and anterior cingulate cortex (r=0.45, p=0.0293). Mitochondrial complex I levels across task-relevant regions were also predictive of task switching accuracy (PLS-Regression (PLS-R), R2=0.48, RMSE=0.154, p=0.011) and of switch cost (PLS-R, R^2=0.38, RMSE=0.07, p=0.048). Our findings suggest that higher mitochondrial complex I levels may underlie an individuals ability to exhibit a stronger BOLD response during task switching and are predictive of better task switching performance. This provides the first evidence linking the BOLD response with mitochondrial complex I and suggests a possible biological mechanism for aberrant BOLD response in conditions associated with mitochondrial complex I dysfunction, that should be tested in future studies.

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Shatalina, E., Whitehurst, T., Chika Onwordi, E., Whittington, A., Mansur, A., Arumuham, A., Reis Marques, T., Gunn, R. N., Natesan, S., Nour, M. M., Rabiner, E. A., Wall, M. B., Howes, O. D.. 2024-09-27. The relationship between brain activation and mitochondrial complex I protein levels during cognitive function in healthy humans: an BCPP-EF PET and functional MRI study of task switching. https://doi.org/10.1101/2024.09.25.614887

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

KEEP EXPLORING

Related preprints

bioRxiv2026

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↗
bioRxiv2026

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↗
bioRxiv2026

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↗