Mapping the Genetic-Imaging-Clinical Pathway with Applications to Alzheimer's Disease

TL;DR

This paper introduces a novel two-step method to map the genetic, imaging, and clinical pathways in Alzheimer's disease, revealing specific hippocampal regions linked to disease severity using high-dimensional data analysis.

Contribution

It develops a new approach to associate high-dimensional hippocampal surface data with cognitive scores, accounting for genetic and clinical covariates in AD progression.

Findings

Radial hippocampal distance negatively correlates with disease severity.

Associations are stronger in CA1 and subiculum regions.

The method effectively integrates genetic, imaging, and clinical data.

Abstract

Alzheimer's disease is a progressive form of dementia that results in problems with memory, thinking, and behavior. It often starts with abnormal aggregation and deposition of beta amyloid and tau, followed by neuronal damage such as atrophy of the hippocampi, leading to Alzheimer's Disease (AD). The aim of this paper is to map the genetic-imaging-clinical pathway for AD in order to delineate the genetically regulated brain changes that drive disease progression based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We develop a novel two-step approach to delineate the association between high-dimensional 2D hippocampal surface exposures and the Alzheimer's Disease Assessment Scale (ADAS) cognitive score, while taking into account the ultra-high dimensional clinical and genetic covariates at baseline. Analysis results suggest that the radial distance of each pixel of both hippocampi is negatively associated with the severity of behavioral deficits conditional on observed clinical and genetic covariates. These associations are stronger in Cornu Ammonis region 1 (CA1) and subiculum subregions compared to Cornu Ammonis region 2 (CA2) and Cornu Ammonis region 3 (CA3) subregions.