Early Alzheimer's disease pathology in human cortex involves transient cell states

Abstract

Cellular perturbations underlying Alzheimer's disease (AD) are primarily studied in human postmortem samples and model organisms. Here, we generated a single-nucleus atlas from a rare cohort of cortical biopsies from living individuals with varying degrees of AD pathology. We next performed a systematic cross-disease and cross-species integrative analysis to identify a set of cell states that are specific to early AD pathology. These changes-which we refer to as the early cortical amyloid response-were prominent in neurons, wherein we identified a transitional hyperactive state preceding the loss of excitatory neurons, which we confirmed by acute slice physiology on independent biopsy specimens. Microglia overexpressing neuroinflammatory-related processes also expanded as AD pathology increased. Finally, both oligodendrocytes and pyramidal neurons upregulated genes associated with β-amyloid production and processing during this early hyperactive phase. Our integrative analysis provides an organizing framework for targeting circuit dysfunction, neuroinflammation, and amyloid production early in AD pathogenesis.

Keywords: Alzheimer’s disease; amyloid pathology; disease systems biology; human cortex; meta-analysis; microglia disease response; neuronal hyperactivity; single-nucleus RNA sequencing; β-amyloid metabolism.

Figure 1.. A fresh-tissue atlas of cortical states associated with AD pathology

A) Schematic of the frontal cortex brain biopsy sampling workflow. Brodmann areas are color-coded in the second panel. B) CSF Aβ-42 (left), phosphorylated tau (middle) and ratio of the two (right) in association with Aβ and tau burden scores. The “ind. AD” refers to an independent cohort of 36 NPH patients who were clinically diagnosed with AD prior to, or within one year after, CSF collection. Cohen d (d) effect sizes are reported. C) A summary of datasets that are included in the integrative analysis. pm, postmortem. D) Expression of markers of cell classes (top), main neuronal classes (middle), and individual cell types (bottom) across four select human studies. Each row indicates the normalized expression level of each gene across the human postmortem datasets (color-coded on y-axis) and 82 cell types. See also Table S2.

Figure 2.. Identification of early- and late-stage cellular perturbations in AD

A) Volcano plot of a meta-analysis of cell type proportional changes in early- and late-stage AD-related samples. Colors indicate cell class assignment. Dashed lines represent FDR thresholds of 0.05 and 0.1. B) Individual log-odds ratios of six significant cell types in Aβ+ (triangles) and Aβ+Tau+ samples (circles). Whiskers indicate standard errors. C) Number of DE genes in each cell class, stratified by biopsy histopathology. JK: Jack-knife. D) Fold change concordance of DE genes between Aβ+ and Aβ+Tau+ samples. The y-axis shows the average logFC difference between Aβ+Tau+ and Aβ+. The Z-scores on the x-axis are transformations of p-values from a paired t-test analysis. E) Fraction of DE genes in Aβ+ and Aβ+Tau+ biopsies that are similarly up- or down-regulated between the seven major cell classes and their associated subtypes in biopsy samples (based on top 300 protein-coding DE genes at the cell class). The dendrogram illustrates the subdivision of the seven major cell classes to a total of 82 subtypes. See also Figure S2G.

Figure 3.. NDNF-PROX1 inhibitory neuron loss is associated with a hyperactivity signature in L2/3 excitatory neurons.

A) Logistic mixed-effect model regression of NDNF-PROX1 proportion versus cell type transcriptional signature in Aβ+ subjects. The dashed horizontal line represents the FDR threshold of 0.05. B) Associations (by logistic mixed-effect model) between the proportion of each inhibitory neuron type with each ExN type’s transcriptional signature in Aβ+ subjects. The red dots indicate the LINC00507-COL5A2 ExNs. See also Figure S3H. C) Scatter plot comparing the Aβ+ and Aβ+Tau+ logFC in the ExNs (union of top 300 protein-coding DE genes based on jack-knifed p-value). D) Logistic mixed-effect model regression of NDNF-PROX1 proportion versus early-specific up-regulated DE genes (green dots in C) and up-regulated DE genes shared in both Aβ+ and Aβ+Tau+ samples (blue dots in C) for each ExN cell type. E) Logistic mixed-effect model regression of NDNF-PROX1 cell fraction versus expression of neural activity signatures in each ExN type in Aβ+ samples (one-sided). PRG, primary response genes; SRG, secondary response genes. F) Scatter plot showing normalized NDNF-PROX1 fraction (x-axis) and the percent of LINC00507-COL5A2 ExNs with high expression of core immediate early genes (y-axis, Methods) in Aβ+ subjects. A logistic mixed-effect model was used to calculate the p-value. G) GSEA of Reactome pathways on DE results across ExN types. Dots outlined in black denote significant terms (FDR-adjusted p-value < 0.05). H) Concordance of DE genes between different stages of AD pathology within excitatory neuron cell types. The LINC00507+ and RORB+ were selected as upper layer excitatory neurons and FEZF2+, CTGF+, and THEMIS+ populations as lower layer. I) Representation of select ExN DE genes. The outlined dots represent DE genes with jack-knifed FDR-adjusted p-value < 0.01. J) GSEA of human KEGG pathways on WIF1+ homeostatic astrocytes. Outlined dots represent significant terms (FDR-adjusted p-value < 0.1). K) Acute slice physiology experiment on biopsy specimens from an independent cohort of 26 individuals. Boxplots quantifying the number of bursts per second in acute slices treated with NMDA from control subjects (Ctrl, n=10), subjects with low Aβ burden (N = 8), and with high Aβ burden (N=8). Each dot represents mean spike activity of electrodes for each individual. The p-value was computed by a regression analysis with age as a covariate. In all panels with boxplots, Center line, median; box limits, upper and lower quartiles; whiskers, 1.5x interquartile range. See also Figure S4. In (B), (D), and (E), the dashed lines indicate FDR threshold of 0.05.

Figure 4.. Precise molecular definitions of microglial states activated in early and late AD.

A) Pseudobulk expression of select microglia marker genes across human datasets. B) Representation of 13 microglia states. C) Dot plot of p-values from MAGMA enrichment analysis of AD, PD, or ASD genetic risk in the up-regulated DE genes of each cell class. Dashed line represents an FDR threshold of 0.05. D) Dot plot of p-values for a Fisher’s exact test assessing the overlap between microglial DE genes with markers of each of the 13 microglial states. E) Radar plot representation of enriched gene sets in differential markers of the three GPNMB-LPL states. F) Association of proportion of each microglial state with early and late AD pathology, as well as PD and ASD. In meta-analysis columns, black dots represent microglia states with FDR-adjusted p-value < 0.05. Points are scaled by the absolute Z-scores. G) Fraction of markers shared between the biopsy cohort and each other dataset (y-axis), in each microglial state (x-axis). Datasets are stratified by species. Mean values are denoted with a line. H) Statistical comparison of the differences in (G) by Student’s t-test. The dashed line represents an FDR threshold of 0.05.

Figure 5.. Cell-type-specific dysregulation of amyloid formation in the human frontal cortex

A) GSEA trace plot of amyloid-associated gene set across the seven cell classes. The x-axis shows the rank order of the DE genes (signed p-value) in corresponding cell classes; the y-axis is the normalized enrichment scores (NES) from GSEA. The dashed line indicates NES score corresponding to an FDR threshold of 0.05. B) Dot plot of FDR-adjusted p-values of GSEA results of the top 300 upregulated protein-coding genes (sorted by their jack-knifed p-values) from each cell class against an ordered list of DE genes in oligodendrocytes. Dotted red line indicates the FDR threshold of 0.05. C) Gene ontology terms significantly enriched in intersect of DE genes between oligodendrocytes and excitatory neurons from REVIGO. Size of dots denote significance. D) GSEA results of amyloid gene set against cell type level DE genes across increasing levels of Aβ and tau burden. Cell types are grouped based on their major cell class annotations. The dashed line represents the FDR threshold of 0.05. E) Schematic of the amyloid metabolism pathway. See also Table S5. F) Excitatory neuron and oligodendrocyte DE results across increasing levels of Aβ and tau burden for genes found by the leading edge analysis in A. G) GSEA results for the amyloid gene set on Oligo DE genes from postmortem AD, PD, MS, and ASD cohorts.

Figure 6.. Quantitation of Aβ production by human mature oligodendrocytes and excitatory neurons

A) Schematic of experiments performed with iOligos and iExN cultures. B) Two dimensional representation of single-cell expression profiles obtained from iOligo (left) and iExN (right) differentiation protocols. C-D) Expression of key marker genes (C) and Aβ processing genes (D) in iOligo and iExN cultures. E) Immunofluorescence stains of O4 and MBP in iOligo cultures five days after doxycycline addition. F) Normalized Aβ protein abundance for iExNs (top) and iOligos (bottom) across differentiation. G) Fractional abundance of Aβ protein levels relative to median Aβ protein levels in DMSO condition for PSEN inhibitor-treated and BACE inhibitor-treated conditioned media samples for iOligos and iExNs. Error bars indicate one standard deviation above and below the mean. H) Ratio of Aβ-38 to Aβ-40 (left) and Aβ-40 to Aβ-42 (right) species from culture conditioned media. In all panels with boxplots, Center line, median; box limits, upper and lower quartiles; whiskers, 1.5x interquartile range; points, outliers.