Abstract #4371

Transcriptional expression patterns of morphometric inverse divergence networks in Alzheimer’s disease

Yongsheng Wu¹, Junyu Qu¹, Hao Zhang², Jianhong Yang², Rui Zhu¹, Guihua Xu¹, Wenwen Xu¹, Jiaxiang Xin³, and Dawei Wang^1,4,5

¹Department of Radiology, Qilu Hospital of Shandong University, Qilu Medical Imaging Institute of Shandong University, Jinan, China, ²School of Control Science and Engineering, Shandong University, Jinan, China, ³MR Research Collaboration, Siemens Healthineers Ltd., Shanghai, China, ⁴Magnetic Field-free Medicine & Functional Imaging, Research Institute of Shandong University, Jinan, China, ⁵Magnetic Field-free Medicine & Functional Imaging (MF), Shandong Key Laboratory, Jinan, China

Synopsis

Keywords: Alzheimer's Disease, Analysis/Processing, morphometric inverse divergence network

Motivation: The alterations in morphometric inverse divergence (MIND) networks in Alzheimer's disease (AD) and their association with gene expression remain unclear, necessitating further investigation.

Goal(s): To investigate structural alterations in AD through MIND networks and examine their association with gene transcriptional patterns.

Approach: We analyzed structural MRI data from 192 patients with AD and 294 healthy individuals, constructing MIND networks and correlating structural changes with gene expression profiles.

Results: We identified notable MIND alterations in AD-related regions, with these changes linked to cognitive decline, tau pathology, and specific gene expression patterns involved in synaptic signaling.

Impact: This study reveals that MIND networks capture structural alterations in AD, linking these changes to cognitive decline, tau pathology, and gene expression. These findings offer a novel framework for understanding AD pathology and may guide future therapeutic interventions.

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