Multi‐Omics‐Based Autophagy‐Related Untypical Subtypes in Patients with Cerebral Amyloid Pathology

Abstract

Recent multi-omics analyses paved the way for a comprehensive understanding of pathological processes. However, only few studies have explored Alzheimer's disease (AD) despite the possibility of biological subtypes within these patients. For this study, unsupervised classification of four datasets (genetics, miRNA transcriptomics, proteomics, and blood-based biomarkers) using Multi-Omics Factor Analysis+ (MOFA+), along with systems-biological approaches following various downstream analyses are performed. New subgroups within 170 patients with cerebral amyloid pathology (A𝜷+) are revealed and the features of them are identified based on the top-rated targets constructing multi-omics factors of both whole (M-TPAD) and immune-focused models (M-IPAD). The authors explored the characteristics of subtypes and possible key-drivers for AD pathogenesis. Further in-depth studies showed that these subtypes are associated with longitudinal brain changes and autophagy pathways are main contributors. The significance of autophagy or clustering tendency is validated in peripheral blood mononuclear cells (PBMCs; n = 120 including 30 A𝜷-and 90 A𝜷+), induced pluripotent stem cell-derived human brain organoids/microglia (n = 12 including 5 A𝜷-, 5 A𝜷+, and CRISPR-Cas9 apolipoprotein isogenic lines), and human brain transcriptome (n = 78). Collectively, this study provides a strategy for precision medicine therapy and drug development for AD using integrative multi-omics analysis and network modelling.

Innovations advancing our understanding of microglia in Alzheimer's disease: From in vitro to in vivo models

“…Human pluripotent stem cell (hPSC) models have offered an avenue to study microglial function in AD in a human living system. AD patient‐derived microglia have been utilized for study in mono‐cultures (Cosker et al, 2021; Konttinen et al, 2019; Monzón‐Sandoval et al, 2022; Piers et al, 2020; Wißfeld et al, 2021; Xu et al, 2019), tri‐cultures with astrocytes and neurons (Bassil et al, 2021; Grubman et al, 2020; Guttikonda et al, 2021; Park et al, 2018; Reich et al, 2021) and 3D cultures with organoids (Brownjohn et al, 2018; Cakir et al, 2022; Lin et al, 2018; Park et al, 2022). The use of 2D and 3D co‐cultures and organoids allows for increased ramification and motility and the expression of disease‐associated genes, which better resemble native microglia, compared to mono‐cultures (Grubman et al, 2020; Haenseler et al, 2017; Popova et al, 2021; Reich et al, 2021).…”

“…Human pluripotent stem cell (hPSC) models have offered an avenue to study microglial function in AD in a human living system, in 2D mono‐cultures (Cosker et al, 2021; Konttinen et al, 2019; Monzón‐Sandoval et al, 2022; Piers et al, 2020; Wißfeld et al, 2021; Xu et al, 2019), co‐cultures (Bassil et al, 2021; Grubman et al, 2020; Guttikonda et al, 2021; Park et al, 2018; Reich et al, 2021) or in 3D, within brain organoids (Brownjohn et al, 2018; Cakir et al, 2022; Lin et al, 2018; Park et al, 2022). To conserve age‐associated factors, the transdifferentiation of peripheral blood mononuclear cells (PBMCs) or monocytes from patients can be used to rapidly generate microglia within 2 weeks (Banerjee et al, 2021; Quek, Cuní‐López, Stewart, Lim, et al, 2022; Ryan et al, 2017; as reviewed by Sargeant & Fourrier, 2023).…”

Association of B cell profile and receptor repertoire with the progression of Alzheimer’s disease

“…Induced pluripotent stem cell (iPSC)-derived microglial cell culture, IgG treatment, and imaging iPSC-derived microglia were generated according to the protocol described in our previous study (Park et al, 2022). Monomeric Ab 1-42 (1 mM; Bachem Holding, Bubendorf, Switzerland) was used for 4 days to mimic mild Ab (acute model) conditions.…”

The promise of multi-omics approaches to discover biological alterations with clinical relevance in Alzheimer’s disease

“…On the other hand, blood (or systemic)-derived multi-omics data are better suited to identify biomarkers for individual diagnosis, prognosis and monitoring. For example, using readily accessible blood-derived genomics, transcriptomics and proteomics data from patients with cerebral amyloid pathology, Park et al (2022) have identified possible molecular drivers of AD heterogeneity or AD subtypes. This suggests that specific clinical manifestations of AD could be associated with distinct biological alterations.…”