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.

The deposition of beta-amyloid (Aβ) in the brain precedes the onset of symptoms such as cognitive impairment in Alzheimer’s disease (AD); therefore, the early detection of Aβ accumulation is crucial. We previously reported the applicability of the QPLEXTM Alz plus assay kit for the prescreening of Aβ accumulation. Here, we tested the specific application of the kit in a large cohort of cognitively normal (CN) individuals of varying ages for the early detection of Aβ accumulation. We included a total of 221 CN participants with or without brain Aβ. The QPLEXTM biomarkers were characterized based on age groups (1st–3rd tertile) and across various brain regions with cerebral amyloid deposition. The 3rd tertile group (>65 years) was found to be the most suitable age group for the application of our assay kit. Receiver operating characteristic curve analysis showed that the area under the curve (AUC, discrimination power) was 0.878 with 69.7% sensitivity and 98.4% specificity in the 3rd tertile group. Additionally, specific correlations between biomarkers and cerebral amyloid deposition in four different brain regions revealed an overall correlation with general amyloid deposition, consistent with previous findings. Furthermore, the combinational panel with plasma Aβ1–42 levels maximized the discrimination efficiency and achieved an AUC of 0.921 with 95.7% sensitivity and 67.3% specificity. Thus, we suggest that the QPLEXTM Alz plus assay is useful for prescreening brain Aβ levels in CN individuals, especially those aged >65 years, to prevent disease progression via the early detection of disease initiation.