Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.05.06.652374

Complement biosynthesis in human brain: Insights from single-nucleus transcriptomics of hippocampus.

Abstract

Complement is a key contributor to neuroinflammation, driving pathology in neurodegenerative diseases (NDDs); however, little is known about the source of complement in brain. Effective targeting of complement in NDDs requires understanding of its source; in particular, which brain cells express complement genes, how expression is regulated and how expression changes in disease. To address this knowledge gap, we identified and integrated single-nucleus RNA sequencing (snRNA-seq) datasets from 398,097 nuclei across 48 hippocampal samples from non-demented brains to create a comprehensive transcriptomic atlas of complement gene expression ("complementome") in healthy brain. Expression levels of genes encoding complement components, receptors, and regulators were analysed across different brain cell types and the impact of sex and age on complement gene expression tested. To test impact of disease, we generated a further atlas from datasets comprising 11 non-demented and 12 Alzheimers disease (AD) patient hippocampi to assess changes in complement gene expression in AD. All glial cells in the non-demented hippocampus expressed complement genes. C1Q A/B/C genes were exclusively expressed in microglia, while C3 was highly expressed in microglia and astrocytes. Notably, C3 expression defined a subset of pro-inflammatory microglia. Complement receptor encoding genes (C3AR1, C5AR2, ITGAM, ITGAX, ITGB2, VSIG4) were predominantly expressed in microglia, while neurons expressed a set of brain-specific putative receptors (NPTX 1/2, NPTXR, NRP1). Endothelial cells abundantly expressed key regulators (CD46, CD55, CD59, CFH), while neurons and OPCs expressed a set of putative regulators (CSMD 1/2/3, and SUSD4). Astrocytes abundantly expressed CLU. Cell type-specific gender differences included higher expression of C1Q A/B/C, C1R, C1S in female microglia and higher expression of ITGAM and ITGAX in male microglia. Generally higher complement gene expression was seen in older donors. Compared to controls, AD microglia showed higher expression of C1QB and C3, and AD astrocytes showed higher C1S and C3 expression. Expression of ITGAX was elevated in AD microglia compared to controls, while many AD cell types demonstrated reduced expression of brain-specific putative receptors. Defining the complementome in non-demented hippocampus provides a baseline for exploration of brain complement expression. Complement expression is upregulated in AD, likely contributing to neuroinflammation and highlighting its potential as a therapeutic target. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=183 SRC="FIGDIR/small/652374v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@100fbc1org.highwire.dtl.DTLVardef@1905402org.highwire.dtl.DTLVardef@7b8573org.highwire.dtl.DTLVardef@176424a_HPS_FORMAT_FIGEXP M_FIG C_FIG

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Nguyen, V. D., Bright, M., Zhou, Y., Morgan, B. P., Zelek, W. M.. 2025-05-07. Complement biosynthesis in human brain: Insights from single-nucleus transcriptomics of hippocampus.. https://doi.org/10.1101/2025.05.06.652374

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

KEEP EXPLORING

Related preprints

CoReg, tracking-based motion compensation for in vivo calcium imaging

In vivo calcium imaging enables the observation of neural activity with high spatial and temporal resolution. However, recordings are frequently affected by motion artifacts caused by animal movement, physiological processes, tissue drift, or instability of the imaging setup. These artifacts make signal extraction harder and reduce the consistency of downstream analyses. Current registration methods can correct rigid and non-rigid motion, but often estimate motion from individual frames or image patches and make limited use of temporal information. In addition, activity-driven fluorescence changes can make it difficult to distinguish changes in image appearance from actual motion. Here, we treat motion correction in calcium imaging as a point tracking problem and introduce CoReg, an open-source Python- based software tool with a graphical user interface. We benchmark CoReg against established registration methods using fluorescence imaging datasets from multiple species. CoReg performs competitively with or better than existing approaches across several settings. We further show that its performance is robust to the choice of tracked points, making the method straightforward to apply. CoReg includes implementations of both our method and the evaluated established methods. Our results show that tracking-based registration provides a simple and reliable approach for motion correction in vivo calcium imaging.

neuroscience↗

A shared slowing axis and phenotype-specific rhythms link clinical EEG to FDG-PET dementia phenotypes

Early and accurate identification of neurodegenerative disorders has notable implications for treatment and quality of life. Whereas neuroimaging-based biomarkers can accurately identify neurodegenerative subtypes, EEG represents a low-cost alternative that could expand access to dementia care. Here, we investigated whether six data-driven EEG latent factors, derived by nonnegative tensor decomposition of clinical EEGs, differ systematically across FDG-PET-defined neurodegenerative phenotypes. In 455 patients with EEG and FDG-PET acquired within one year of each other, factor expression was compared across 14 diagnostic classes assigned by StateViewer, a validated artificial intelligence framework for FDG-PET interpretation. To separate disease-general severity from phenotype-specific topography, each factor was also regressed on a subject-level slowing index. Finally, we related the factors to regional FDG uptake and to neuropsychological performance (n = 98) and assessed their potential utility for single-subject classification. Four factors reflecting neurophysiological oscillations (posterior alpha, Rolandic beta, frontotemporal delta-theta and posterior theta-slow alpha) varied significantly across phenotypes, with attenuation of faster and augmentation of slower rhythms most pronounced in dementia with Lewy bodies (DLB), dysexecutive Alzheimer disease (AD) and posterior cortical atrophy, whereas factors dominated by eye-movement and muscle artifact showed no robust phenotypic association. Alpha and beta effects were largely attributable to overall slowing, whereas posterior theta-slow alpha became more phenotype-specific after adjustment (eta-squared 0.082 to 0.147), dissociating the Alzheimer disease spectrum from frontotemporal syndromes. The slowing index tracked with an FDG-PET pattern highly associated with DLB across the cohort, irrespective of assigned phenotype (r = 0.51, P < 0.001). Consistent with a model in which dementia phenotypes reflect altered hippocampal-neocortical oscillatory coupling (stochastic latent oscillatory diffusion), frontotemporal delta-theta tracked a limbocortical axis of metabolic pattern expression, rising with neocortical and falling with limbic-predominant involvement, independent of overall slowing and phenotype. Each factor mapped onto a distinct metabolic topography, with frontotemporal delta-theta resembling Alzheimer-type hypometabolism and posterior theta-slow alpha the medial occipital hypometabolism of DLB. In terms of neuropsychological performance, Rolandic beta was associated with executive functions, and frontotemporal delta-theta with memory, visuospatial and global performance. Using these four factors alone, an exploratory logistic regression classifier separated cognitively unimpaired participants from DLB, posterior cortical atrophy, typical AD, and dysexecutive AD (area under the curve > 0.8) but poorly discriminated frontotemporal dementia phenotypes canonically associated with 4-repeat tau. Thus, data-driven decomposition of clinical EEG separates oscillatory activity from artifact into factors that track metabolic phenotype, regional metabolism and cognition, capturing both overall slowing and phenotype-specific patterns. This work informs the further development of scalable, biology-informed EEG-based phenotyping of neurodegenerative disease.

neuroscience↗

An application of fNIRS for the prediction of hearing thresholds in sleeping infants: a proof of principle

This study applied a two-component-response modelling approach to fNIRS recordings obtained from naturally sleeping infants presented with auditory stimuli at different sound intensities. We investigated whether the relationship between fNIRS response measures and stimulus intensity could be modelled to estimate individual auditory hearing thresholds. In the normal-hearing group, 75% of infants had threshold estimates for the sound /ba/ within the expected normal-hearing range, with an estimated mean equivalent normal loudness (ENL) of 10.72 dB HL (SD 8.64 dB HL). A case study further explored the potential application of this approach in an infant with hearing impairment, highlighting the importance of reliable responses at lower stimulus intensities and appropriate regression model selection. These findings provide preliminary evidence that cortical haemodynamic responses can be quantitatively related to sound intensity for estimating auditory sensitivity.

neuroscience↗