» Articles » PMID: 31174557

Neuroimaging Biomarkers for Alzheimer's Disease

Overview
Publisher Biomed Central
Date 2019 Jun 9
PMID 31174557
Citations 97
Authors
Affiliations
Soon will be listed here.
Abstract

Currently, over five million Americans suffer with Alzheimer's disease (AD). In the absence of a cure, this number could increase to 13.8 million by 2050. A critical goal of biomedical research is to establish indicators of AD during the preclinical stage (i.e. biomarkers) allowing for early diagnosis and intervention. Numerous advances have been made in developing biomarkers for AD using neuroimaging approaches. These approaches offer tremendous versatility in terms of targeting distinct age-related and pathophysiological mechanisms such as structural decline (e.g. volumetry, cortical thinning), functional decline (e.g. fMRI activity, network correlations), connectivity decline (e.g. diffusion anisotropy), and pathological aggregates (e.g. amyloid and tau PET). In this review, we survey the state of the literature on neuroimaging approaches to developing novel biomarkers for the amnestic form of AD, with an emphasis on combining approaches into multimodal biomarkers. We also discuss emerging methods including imaging epigenetics, neuroinflammation, and synaptic integrity using PET tracers. Finally, we review the complementary information that neuroimaging biomarkers provide, which highlights the potential utility of composite biomarkers as suitable outcome measures for proof-of-concept clinical trials with experimental therapeutics.

Citing Articles

Association between BrainAGE and Alzheimer's disease biomarkers.

Abughofah Y, Deardorff R, Vosmeier A, Hottle S, Dage J, Dempsey D Alzheimers Dement (Amst). 2025; 17(1):e70094.

PMID: 40018325 PMC: 11865712. DOI: 10.1002/dad2.70094.


Altered brain functional network connectivity and topology in type 2 diabetes mellitus.

Ni W, Liu W, Li M, Wei S, Xu X, Huang S Front Neurosci. 2025; 19:1472010.

PMID: 39935840 PMC: 11811103. DOI: 10.3389/fnins.2025.1472010.


Current Status and Future Perspective of Seoul National University Hospital-Dementia Brain Bank with Concordance of Clinical and Neuropathological Diagnosis.

Lee K, Kim S, Shim Y, Kim E, Yoo S, Won J Exp Neurobiol. 2025; 33(6):295-311.

PMID: 39806943 PMC: 11738475. DOI: 10.5607/en24027.


Blood-derived APLP1 extracellular vesicles are potential biomarkers for the early diagnosis of brain diseases.

Choi Y, Park J, Jo A, Lim C, Park J, Hwang J Sci Adv. 2025; 11(1):eado6894.

PMID: 39742488 PMC: 11691634. DOI: 10.1126/sciadv.ado6894.


Neuroimaging techniques, gene therapy, and gut microbiota: frontier advances and integrated applications in Alzheimer's Disease research.

Wang H, Shi C, Jiang L, Liu X, Tang R, Tang M Front Aging Neurosci. 2024; 16:1485657.

PMID: 39691161 PMC: 11649678. DOI: 10.3389/fnagi.2024.1485657.


References
1.
Lenglet C, Campbell J, Descoteaux M, Haro G, Savadjiev P, Wassermann D . Mathematical methods for diffusion MRI processing. Neuroimage. 2008; 45(1 Suppl):S111-22. PMC: 2678879. DOI: 10.1016/j.neuroimage.2008.10.054. View

2.
Cho H, Choi J, Hwang M, Kim Y, Lee H, Lee H . In vivo cortical spreading pattern of tau and amyloid in the Alzheimer disease spectrum. Ann Neurol. 2016; 80(2):247-58. DOI: 10.1002/ana.24711. View

3.
Rasmussen T, Schliemann T, Sorensen J, Zimmer J, West M . Memory impaired aged rats: no loss of principal hippocampal and subicular neurons. Neurobiol Aging. 1996; 17(1):143-7. DOI: 10.1016/0197-4580(95)02032-2. View

4.
Petrella J, Sheldon F, Prince S, Calhoun V, Doraiswamy P . Default mode network connectivity in stable vs progressive mild cognitive impairment. Neurology. 2011; 76(6):511-7. PMC: 3053179. DOI: 10.1212/WNL.0b013e31820af94e. View

5.
Gaffan D . Scene-specific memory for objects: a model of episodic memory impairment in monkeys with fornix transection. J Cogn Neurosci. 2013; 6(4):305-20. DOI: 10.1162/jocn.1994.6.4.305. View