Identification of the molecular subgroups in Alzheimer's disease by transcriptomic data

He Li; Meiqi Wei; Tianyuan Ye; Yiduan Liu; Dongmei Qi; Xiaorui Cheng

doi:10.3389/fneur.2022.901179

Identification of the molecular subgroups in Alzheimer's disease by transcriptomic data

Front Neurol. 2022 Sep 20:13:901179. doi: 10.3389/fneur.2022.901179. eCollection 2022.

Authors

He Li¹, Meiqi Wei², Tianyuan Ye¹, Yiduan Liu³, Dongmei Qi⁴, Xiaorui Cheng¹

Affiliations

¹ Innovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, China.
² Institute of Chinese Medical Literature and Culture, Shandong University of Traditional Chinese Medicine, Jinan, China.
³ School of Rehabilitation Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
⁴ Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, China.

Abstract

Background: Alzheimer's disease (AD) is a heterogeneous pathological disease with genetic background accompanied by aging. This inconsistency is present among molecular subtypes, which has led to diagnostic ambiguity and failure in drug development. We precisely distinguished patients of AD at the transcriptome level.

Methods: We collected 1,240 AD brain tissue samples collected from the GEO dataset. Consensus clustering was used to identify molecular subtypes, and the clinical characteristics were focused on. To reveal transcriptome differences among subgroups, we certificated specific upregulated genes and annotated the biological function. According to RANK METRIC SCORE in GSEA, TOP10 was defined as the hub gene. In addition, the systematic correlation between the hub gene and "A/T/N" was analyzed. Finally, we used external data sets to verify the diagnostic value of hub genes.

Results: We identified three molecular subtypes of AD from 743 AD samples, among which subtypes I and III had high-risk factors, and subtype II had protective factors. All three subgroups had higher neuritis plaque density, and subgroups I and III had higher clinical dementia scores and neurofibrillary tangles than subgroup II. Our results confirmed a positive association between neurofibrillary tangles and dementia, but not neuritis plaques. Subgroup I genes clustered in viral infection, hypoxia injury, and angiogenesis. Subgroup II showed heterogeneity in synaptic pathology, and we found several essential beneficial synaptic proteins. Due to presenilin one amplification, Subgroup III was a risk subgroup suspected of familial AD, involving abnormal neurogenic signals, glial cell differentiation, and proliferation. Among the three subgroups, the highest combined diagnostic value of the hub genes were 0.95, 0.92, and 0.83, respectively, indicating that the hub genes had sound typing and diagnostic ability.

Conclusion: The transcriptome classification of AD cases played out the pathological heterogeneity of different subgroups. It throws daylight on the personalized diagnosis and treatment of AD.

Keywords: Alzheimer's disease; diagnosis; heterogeneity; molecular subtype; transcriptomics.