Pathway enrichment analysis of up-regulated DEGs in ESAD with reference to DisGeNET.

Pathway enrichment analysis of up-regulated DEGs in ESAD with reference to DisGeNET.</p

Validation of cortical layer markers by spatial transcriptomic analysis.

(A) Visualization of cortical layers in sample #151707 from the jhpce#HumanPilot10x dataset using spatialLIBD. (B) Visualization of the distribution and counts of cortical layer-specific markers per spot. (C) Boxplots showing the expression levels of various layer-specific markers across different spatial locations defined in (A) to validate their layer specificities. (D) t-SNE and (E) UMAP plots illustrating the differential enrichment of cortical layer-specific markers in different neuronal subclusters in the integrated cohort analyses. (TIF)</p

Impact of predicted CNVs on the transcriptomic signature in subcluster 5 (late senescent neurons).

(A, C) Venn diagram illustrating the degree of similarity of the DEGs identified in subcluster 5 compared to the remaining non-cell cycle gene reexpressing excitatory neurons in the list of genes located in the predicted (A) CNV gain and (C) loss regions. (B, D) Functional overrepresentation analysis of common genes identified in (A) and (C), respectively, with reference to pathways in the Reactome database. The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. (TIF)</p

Characterization of upstream events underlying the transcriptome profile changes in terminally senescent neurons.

(A) In an integrated cohort setting, an SCENIC binary regulon activity matrix showing that all 162 corrected regulons were activated in more than one subcluster. Each column represents neurons in a single cortical layer (or ES or LS neuronal clusters), and each row represents one regulon. The term “regulon” refers to the regulatory network of transcription factors and their target genes. Key regulons (rows) are magnified and colored according to their activities: active (orange) or inactive (blue) in the ES and LS neuronal clusters. (B) The same set of analyses illustrated in (A) was conducted separately for each individual dataset. Manhattan plots illustrating the enriched signaling networks of coinhibited (top panel) or coactivated (bottom panel) TFs. Significantly (p https://zenodo.org/doi/10.5281/zenodo.10604562. (TIF)</p

Identification of cell cycle re-engaging postmitotic excitatory neurons in single-nucleus transcriptomic profiles.

(A) Schematic diagram illustrating the general layout and design of the bioinformatics analyses applied in this study. (B) t-SNE plot of a total of 34,140 nuclei derived from 24 unaffected, age (mean ± SD = 85.59 ± 4.20), and sex-matched (12 males and 12 females) prefrontal cortex samples from Brodmann area 10 [28]. The different cell types used are abbreviated as follows: excitatory neurons (Ex), oligodendrocytes (Oli), inhibitory neurons (In), astrocytes (Ast), microglia (Mic), endothelial cells (En), and oligodendrocyte progenitor cells (Opc). (C) Normalized expression levels of cell type-specific markers in all cell types mentioned above. (D) t-SNE plot of 32,685 postmitotic cell nuclei colored according to cell type (left panel) and subcluster number (right panel). (E) Schematic illustration of the cell cycle phase scoring workflow for each nucleus. (F) Violin plots showing the distribution of the cell cycle phase scores in all postmitotic cell subclusters. The bold highlights indicate the subcluster with the most significant differences above the average gene expression levels in any particular cell cycle phase. P values against other subclusters are shown on the right. (G) Estimation of copy number variants among all excitatory neurons via the InferCNV algorithm. The heatmap on the left shows the CNA regions identified by the HMM, i.e., regions of gain (red) and loss (blue) of expression along each chromosome, at various regions from the p-arm (left side of each box) to the q-arm (right side of each box) in all subclusters. The middle heatmap is an outcome of the Bayesian latent-mixture model implemented to identify the posterior probabilities of alteration status in each cell and whole CNA region. True positive predictions of CNV events were identified only in subcluster 13 (red: gain of copy number; blue: loss of copy number). On the far right are line plots illustrating in detail how gene expression levels on each chromosome are altered in subclusters 13 and 5 compared to a negative control (subcluster 2). The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. CNA, copy number alteration; CNV, copy number variation; HMM, hidden Markov model; t-SNE, t-distributed stochastic neighbor embedding.</p

Application of the bioinformatics analytical pipeline in the Parkinson’s disease (PD)/Lewy-body dementia (LBD) model.

(A) t-SNE plot of dopaminergic neurons extracted from healthy and diseased mid-brain samples; these nuclei were divided into 9 subclusters (0–8). (B) Violin plots showing the distribution of cell cycle phase scores in all dopaminergic neuronal nuclei subclusters. The bold highlights indicate the subcluster with the most significant above-average gene expression levels in any particular cell cycle phase; p values against other subclusters are shown. (C) Single-cell trajectory analysis with the Monocle 2.0 algorithm revealing the evolutionary relationship between 2 subclusters of cell cycle gene-expressing neurons. Locations of subclusters 2 and 5 on this trajectory are labeled, indicating that they are on the same trajectory of fate, with subcluster 2 located at the terminal. (D) Estimation of copy number variants among all the dopaminergic neuronal nuclei extracted via the InferCNV algorithm. True positives of copy number variation events were identified in subcluster 2 (red: gain of copy number. Blue: loss of copy number). (E) Dot plot showing the expression levels of 55 differentially expressed senescence genes defined by Hernandez-Segura and colleagues [47] among all dopaminergic neuronal subclusters. (F) Bar plot representing the numbers of DEGs between groups of nuclei from PD-LBD patients and nondemented samples in all subclusters of dopaminergic neuronal nuclei. (G) Functional enrichment analysis of both up- and down-regulated DEGs in subcluster 5/ES (PD-LBD vs ND) was performed on the Metascape platform. (H) Bar plot showing the disease enrichment analysis of both up- and down-regulated DEGs in the ES cohort (PD-LBD vs ND) with the DisGenNet database. The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. (TIF)</p

Cell cycle gene reexpressing and senescent neurons exhibit compromised two-way communication with glia.

Dot plots illustrating the detailed results of the connectome analysis, which indicate the probabilities of communication between the indicated pairs of ligands and receptors according to the color label. The strength of the interaction, as indicated by the presence of a dot and the color between ligands expressed on glia and cell surface receptors expressed on neurons in various clusters, are shown on the left. Similarly, cell surface receptors expressed on glia and ligands expressed on neurons in various clusters are shown on the right. The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. (TIF)</p

Supporting data for Figs 1F, 1G; 2C–2H; 3A, 3E–3I; 4A–4C, 4F–4J; S2C; S3H; S4D and S4F; S5; S8; S9A–S9F; S10A–S10D; S11A, S11B; S12; S13; S14; S15; S16; S17; S18; S19; S20B, S20E–S20G; S21C; S22C and S22I; S23B; S24B.

Supporting data for Figs 1F, 1G; 2C–2H; 3A, 3E–3I; 4A–4C, 4F–4J; S2C; S3H; S4D and S4F; S5; S8; S9A–S9F; S10A–S10D; S11A, S11B; S12; S13; S14; S15; S16; S17; S18; S19; S20B, S20E–S20G; S21C; S22C and S22I; S23B; S24B.</p

Early senescent neurons in the AD brain exhibit a unique proneuropathological signature.

(A) AD risk gene loci mapped to CNV locations identified in subclusters 3 (ES) and 5 (LS) compared to the negative control subcluster 0. The yellow highlights indicate chromosomal locations of the classic AD risk gene loci where significant changes in the absolute CNV scores were observed compared with those of the control cluster. The red and blue labels indicate the up- and down-regulated AD risk genes, respectively, located within the highlighted locations. (B) Normalized expression levels of highlighted AD risk loci indicated in (A) among ES, LS, and the remaining non-cell cycle re-engaging neurons stratified in different cortical layers. (C) Scatter plot illustrating the correlation between the cell cycle re-engaging neuron ratio and the total number of neurons in each sample with age. (D) UMAP plot of excitatory neuronal and glial nuclei extracted from the Mathys and colleagues dataset [28]. The color code represents different cell types and neurons located at different cortical layers. (E) Heatmaps illustrating the differences in intercell communication strength among different cell types, quantified by corresponding ligand (left) or receptor (right) gene expression levels. The details of this analysis are shown in S1 Data files. (F, G) Dot and box plots illustrating the relationships between the cell number ratios of subclusters of concern and total neuronal nuclei in each sample with (F) a definitive diagnostic status and (G) Cogdx scores. (H) Bar plot representing the numbers of DEGs between groups of nuclei from AD versus ND samples in subclusters ES and LS and those belonging to different cortical layers. (I) Upset plot displaying the intersections among DEGs identified in the LS (AD vs ND), ES (AD vs ND), and LS (general versus non-cell cycling neurons) populations. (J) Functional enrichment analysis of up-regulated DEGs in ES (AD vs ND) was performed on the Metascape platform. (K) Bar plot showing the disease enrichment analysis of up-regulated DEGs in ES(AD vs ND) with reference to the DisGenNet database. The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. AD, Alzheimer’s disease; CNV, copy number variation; ES, early senescent; LS, late senescence.</p