Using blood transcriptome analysis for Alzheimer's disease diagnosis and patient stratification.

INTRODUCTION: Blood protein biomarkers demonstrate potential for Alzheimer's disease (AD) diagnosis. Limited studies examine the molecular changes in AD blood cells. METHODS: Bulk RNA-sequencing of blood cells was performed on AD patients of Chinese descent (n = 214 and 26 in the discovery and validation cohorts, respectively) with normal controls (n = 208 and 38 in the discovery and validation cohorts, respectively). Weighted gene co-expression network analysis (WGCNA) and deconvolution analysis identified AD-associated gene modules and blood cell types. Regression and unsupervised clustering analysis identified AD-associated genes, gene modules, cell types, and established AD classification models. RESULTS: WGCNA on differentially expressed genes revealed 15 gene modules, with 6 accurately classifying AD (areas under the receiver operating characteristics curve [auROCs] > 0.90). These modules stratified AD patients into subgroups with distinct disease states. Cell-type deconvolution analysis identified specific blood cell types potentially associated with AD pathogenesis. DISCUSSION: This study highlights the potential of blood transcriptome for AD diagnosis, patient stratification, and mechanistic studies. HIGHLIGHTS: We comprehensively analyze the blood transcriptomes of a well-characterized Alzheimer's disease cohort to identify genes, gene modules, pathways, and specific blood cells associated with the disease. Blood transcriptome analysis accurately classifies and stratifies patients with Alzheimer's disease, with some gene modules achieving classification accuracy comparable to that of the plasma ATN biomarkers. Immune-associated pathways and immune cells, such as neutrophils, have potential roles in the pathogenesis and progression of Alzheimer's disease.

A blood-based multi-pathway biomarker assay for early detection and staging of Alzheimer's disease across ethnic groups.

INTRODUCTION: Existing blood-based biomarkers for Alzheimer's disease (AD) mainly focus on its pathological features. However, studies on blood-based biomarkers associated with other biological processes for a comprehensive evaluation of AD status are limited. METHODS: We developed a blood-based, multiplex biomarker assay for AD that measures the levels of 21 proteins involved in multiple biological pathways. We evaluated the assay's performance for classifying AD and indicating AD-related endophenotypes in three independent cohorts from Chinese or European-descent populations. RESULTS: The 21-protein assay accurately classified AD (area under the receiver operating characteristic curve [AUC] = 0.9407 to 0.9867) and mild cognitive impairment (MCI; AUC = 0.8434 to 0.8945) while also indicating brain amyloid pathology. Moreover, the assay simultaneously evaluated the changes of five biological processes in individuals and revealed the ethnic-specific dysregulations of biological processes upon AD progression. DISCUSSION: This study demonstrated the utility of a blood-based, multi-pathway biomarker assay for early screening and staging of AD, providing insights for patient stratification and precision medicine. HIGHLIGHTS: The authors developed a blood-based biomarker assay for Alzheimer's disease. The 21-protein assay classifies AD/MCI and indicates brain amyloid pathology. The 21-protein assay can simultaneously assess activities of five biological processes. Ethnic-specific dysregulations of biological processes in AD were revealed.