Alzheimer’s disease (AD) manifested before age 65 is commonly referred to as early-onset AD (EOAD) (Reitz et al. Neurol Genet. 2020;6:e512). While the majority (> 90%) of EOAD cases are not caused by autosomal-dominant mutations in PSEN1, PSEN2, and APP, they do have a higher heritability (92–100%) than sporadic late-onset AD (LOAD, 70%) (Wingo et al. Arch Neurol. 2012;69:59–64, Fulton-Howard et al. Neurobiol Aging. 2021;99:101.e1–101.e9). Although the endpoint clinicopathological changes, i.e., Aβ plaques, tau tangles, and cognitive decline, are common across EOAD and LOAD, the disease progression is highly heterogeneous (Neff et al. Sci Adv Am Assoc Adv Sci. 2021;7:eabb5398). This heterogeneity, leading to temporally distinct age at onset (AAO) and stages of cognitive decline, may be caused by myriad combinations of distinct disease-associated molecular mechanisms. We and others have used transcriptome profiling in AD patient-derived neuron models of autosomal-dominant EOAD and sporadic LOAD to identify disease endotypes (Caldwell et al. Sci Adv Am Assoc Adv Sci. 2020;6:eaba5933, Mertens et al. Cell Stem Cell. 2021;28:1533–1548.e6, Caldwell et al. Alzheimers Demen. 2022). Further, analyses of large postmortem brain cohorts demonstrate that only one-third of AD patients show hallmark disease endotypes like increased inflammation and decreased synaptic signaling (Neff et al. Sci Adv Am Assoc Adv Sci. 2021;7:eabb5398). Areas of the brain less affected by AD pathology at early disease stages—such as the primary visual cortex—exhibit similar transcriptomic dysregulation as those regions traditionally affected and, therefore, may offer a view into the molecular mechanisms of AD without the associated inflammatory changes and gliosis induced by pathology (Haroutunian et al. Neurobiol Aging. 2009;30:561–73). To this end, we analyzed AD patient samples from the primary visual cortex (19 EOAD, 20 LOAD) using transcriptomic signatures to identify patient clusters and disease endotypes. Interestingly, although the clusters showed distinct combinations and severity of endotypes, each patient cluster contained both EOAD and LOAD cases, suggesting that AAO may not directly correlate with the identity and severity of AD endotypes.
While amyloid‐β (Aβ) plaques are considered a hallmark of Alzheimer's disease, clinical trials focused on targeting gamma secretase, an enzyme involved in aberrant Aβ peptide production, have not led to amelioration of AD symptoms or synaptic dysregulation. Screening strategies based on mechanistic, multi‐omics approaches that go beyond pathological readouts can aid in the evaluation of therapeutics. Using early‐onset Alzheimer's (EOFAD) disease patient lineage PSEN1A246E iPSC‐derived neurons, we performed RNA‐seq to characterize AD‐associated endotypes, which are in turn used as a screening evaluation metric for two gamma secretase drugs, the inhibitor Semagacestat and the modulator BPN‐15606. We demonstrate that drug treatment partially restores the neuronal state while concomitantly inhibiting cell cycle re‐entry and dedifferentiation endotypes to different degrees depending on the mechanism of gamma secretase engagement. Our endotype‐centric screening approach offers a new paradigm by which candidate AD therapeutics can be evaluated for their overall ability to reverse disease endotypes.
Background Mutations in PSEN1, PSEN2, and APP can lead to Alzheimer’s disease (AD) with an early age at onset (AAO) and hallmark progressive cognitive decline. These mutations are highly penetrant. Although mutations in PSEN1 are more common and usually have an earlier AAO, certain mutations in PSEN1 cause a later AAO, similar to PSEN2 and APP mutations. We sought to determine whether common disease endotypes exist across these mutations with a relatively late AAO. Methods We generated hiPSC-derived neurons from patients harboring autosomal-dominant, familial Alzheimer’s disease (FAD) mutations in PSEN1, PSEN2, and APP with a documented age at onset (AAO) around 55 years: PSEN1A79V, PSEN2N141I, and APPV717I. We carried out RNA-seq and ATAC-seq to mechanistically characterize the gene expression and chromatin accessibility changes, respectively. Differential expression analysis, enrichment analysis, TF activity identification, and co-expression module detection were performed for RNA-seq. Differential peak analysis and annotation, TF motif footprinting and differential motif accessibility, and peak functional enrichment were performed for ATAC-seq. This approach allowed us to identify the correlation between gene expression and chromatin accessibility associated with key disease endotypes. Results Using a multiomics approach, we identify and characterize common endotypes in mutations across all three FAD genes: dedifferentiation of a mature neuron to a less differentiated quasi-neuron state, dysregulation of synaptic signaling, repression of mitochondrial function and metabolism, and inflammation. The integrativeanalysis allowed us to ascertain the master transcriptional regulators associated with these endotypes, including REST, ASCL1, and ZIC family members (activation), as well as NRF1 (repression). Conclusions Our findings characterize the common regulatory changes within endotypes across these FAD mutations. However, the severity of dysregulation often differs between PSEN1, PSEN2, and APP mutations both in magnitude and direction. The overarching common link between mutations in FAD genes is the reversion to a less-differentiated neuron state. The transcriptional regulatory mechanisms described within disease endotypes offer potential targets for therapeutic interventions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.