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Mathys H, Peng Z, Boix CA, Victor MB, Leary N, Babu S, Abdelhady G, Jiang X, Ng AP, Ghafari K, Kunisky AK, Mantero J, Galani K, Lohia VN, Fortier GE, Lotfi Y, Ivey J, Brown HP, Patel PR, Chakraborty N, Beaudway JI, Imhoff EJ, Keeler CF, McChesney MM, Patel HH, Patel SP, Thai MT, Bennett DA, Kellis M, Tsai LH. Single-cell atlas reveals correlates of high cognitive function, dementia, and resilience to Alzheimer's disease pathology. Cell. 2023 Sep 28;186(20):4365-4385.e27. PubMed.
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University of California, Irvine
The paper by Xiong et al. represents a seminal contribution to our understanding of Alzheimer's disease from a functional genomics perspective, elucidating previously unrecognized aspects of the disease's molecular etiology. One of the most significant advances lies in the comprehensive mapping of the brain regulome, derived from the prefrontal cortexes of 92 individuals. By employing single-cell resolution for epigenomic and transcriptomic landscapes, the authors were able to resolve cell-type-specific regulatory modules and peak-to-gene links, thus overcoming the limitations posed by earlier bulk tissue analyses.
Of paramount interest is the identification of AD risk loci enrichment in microglial enhancers and in specific transcription factors, such as SPI1, ELF2, and RUNX1. This not only helps in understanding the transcriptional regulatory circuitry of AD but also paves the way for targeted therapeutic interventions. Furthermore, the discovery of 9,628 cell-type-specific ATAC-QTL loci, integrated alongside peak-to-gene links, provides an unprecedented depth to the study of AD variant regulatory circuits, thereby presenting avenues for identifying causal links between genetic variants and their regulatory roles in pathogenesis.
The paper is particularly illuminating when discussing the phenomenon of epigenomic erosion and loss of cell identity in late-stage AD. The use of advanced, single-cell technologies allowed the authors to distinguish “de-identified” cells with eroded cellular identities across various major brain cell types in late AD, demonstrating that this is a feature intrinsic to disease progression rather than a technical artifact. Strikingly, this epigenomic erosion was shown to manifest as a global dysregulation of the epigenome, corroborated by integrated erosion scores and changes in three-dimensional genome organization, suggesting a profound loss of cellular function and identity as AD progresses.
In summary, this paper provides a paradigm shift in our understanding of the regulatory genomics of Alzheimer's disease. It addresses critical gaps in knowledge—ranging from cell-type-specific regulatory elements to late-stage epigenomic aberrations—thus offering not just mechanistic insights but also revealing potential targets for therapeutic development. The study elevates our comprehension from isolated genetic loci to a more holistic view, focusing on the interplay between genetic, epigenetic, and transcriptomic landscapes in the context of Alzheimer's disease.
View all comments by Vivek SwarupColumbia University Medical Center
Sun et al. provide a comprehensive assessment of human microglia phenotypes in the aged and Alzheimer’s disease brain. Utilizing the data-rich ROS/MAP cohort the authors established the presence of 12 different microglia transcriptional states, identifying gene sets that are differentially expressed within each microglia subset at different stages of AD, measuring changes in the relative abundance of microglia subsets with AD progression, and establishing relationships between microglia subset abundances and clinicopathological traits, all of which will serve as a great resource for the scientific community.
Importantly, the authors found good correlation between microglia phenotypes and ones described previously that were based on single cell RNA-seq, an approach that has been shown to be better suited to capturing microglial phenotypes than single nucleus approaches (Thrupp et al., 2020). Despite this, while the prior scRNA-seq study (Olah et al., 2020) identified one inflammatory state, the current study was able to identify three. These were governed by the same transcription factors, but had unique gene sets, and likely constituted phenotypes at different stages along a microglial inflammatory activation trajectory. The ability to detect transitioning microglia states was most likely enabled by the much larger sample size, justifying the generation of ever-larger datasets to increase resolving power.
Nevertheless, perhaps the most intriguing finding of this study is the observation that single-nucleus chromatic accessibility does not recapitulate the transcriptionally defined states very well, beyond the ability to discern a homeostatic state from one to two activated states. Studies usually find strong correlation between chromatin accessibility (as assayed by ATAC-Seq) and gene expression, so it is particularly interesting that this is not the case here. These findings will need to be further corroborated using orthogonal approaches (or better technology) to exclude the possibility that the lack of resolution comes from the sparseness of the snATAC-Seq data. Nonetheless, if confirmed, it could suggest, as the authors concluded, that non-resting/activated microglia may maintain a permissive chromatin accessibility architecture that could allow dynamic state transitions to occur in response to changes in the microenvironment, and, indeed, in response to therapeutic targeting. This retained microglial plasticity is the conceptual prerequisite and cornerstone of any future effort to devise therapeutic approaches that target individual microglia subsets to fine-tune the microglial population to maintain or regain tissue homeostasis.
References:
Thrupp N, Sala Frigerio C, Wolfs L, Skene NG, Fattorelli N, Poovathingal S, Fourne Y, Matthews PM, Theys T, Mancuso R, de Strooper B, Fiers M. Single-Nucleus RNA-Seq Is Not Suitable for Detection of Microglial Activation Genes in Humans. Cell Rep. 2020 Sep 29;32(13):108189. PubMed.
Olah M, Menon V, Habib N, Taga MF, Ma Y, Yung CJ, Cimpean M, Khairallah A, Coronas-Samano G, Sankowski R, Grün D, Kroshilina AA, Dionne D, Sarkis RA, Cosgrove GR, Helgager J, Golden JA, Pennell PB, Prinz M, Vonsattel JP, Teich AF, Schneider JA, Bennett DA, Regev A, Elyaman W, Bradshaw EM, De Jager PL. Single cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer's disease. Nat Commun. 2020 Nov 30;11(1):6129. PubMed.
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