» Articles » PMID: 23302773

Clinical, Imaging, and Pathological Heterogeneity of the Alzheimer's Disease Syndrome

Overview
Date 2013 Jan 11
PMID 23302773
Citations 156
Authors
Affiliations
Soon will be listed here.
Abstract

With increasing knowledge of clinical in vivo biomarkers and the pathological intricacies of Alzheimer's disease (AD), nosology is evolving. Harmonized consensus criteria that emphasize prototypic illness continue to develop to achieve diagnostic clarity for treatment decisions and clinical trials. However, it is clear that AD is clinically heterogeneous in presentation and progression, demonstrating variable topographic distributions of atrophy and hypometabolism/hypoperfusion. AD furthermore often keeps company with other conditions that may further nuance clinical expression, such as synucleinopathy exacerbating executive and visuospatial dysfunction and vascular pathologies (particularly small vessel disease that is increasingly ubiquitous with human aging) accentuating frontal-dysexecutive symptomatology. That some of these atypical clinical patterns recur may imply the existence of distinct AD variants. For example, focal temporal lobe dysfunction is associated with a pure amnestic syndrome, very slow decline, with atrophy and neurofibrillary tangles limited largely to the medial temporal region including the entorhinal cortex. Left parietal atrophy and/or hypometabolism/hypoperfusion are associated with language symptoms, younger age of onset, and faster rate of decline - a potential 'language variant' of AD. Conversely, the same pattern but predominantly affecting the right parietal lobe is associated with a similar syndrome but with visuospatial symptoms replacing impaired language function. Finally, the extremely rare frontal variant is associated with executive dysfunction out of keeping with degree of memory decline and may have prominent behavioural symptoms. Genotypic differences may underlie some of these subtypes; for example, absence of apolipoprotein E e4 is often associated with atypicality in younger onset AD. Understanding the mechanisms behind this variability merits further investigation, informed by recent advances in imaging techniques, biomarker assays, and quantitative pathological methods, in conjunction with standardized clinical, functional, neuropsychological and neurobehavioral evaluations. Such an understanding is needed to facilitate 'personalized AD medicine', and eventually allow for clinical trials targeting specific AD subtypes. Although the focus legitimately remains on prototypic illness, continuing efforts to develop disease-modifying therapies should not exclude the rarer AD subtypes and common comorbid presentations, as is currently often the case. Only by treating them as well can we address the full burden of this devastating dementia syndrome.

Citing Articles

The study on cuproptosis in Alzheimer's disease based on the cuproptosis key gene .

Chen G, Xi E, Gu X, Wang H, Tang Q Front Aging Neurosci. 2025; 16:1480332.

PMID: 39759399 PMC: 11696982. DOI: 10.3389/fnagi.2024.1480332.


Mixture Disease Progression Model to Predict and Cluster the Long-Term Trajectory of Cognitive Decline in Alzheimer's Disease.

Hanazawa R, Sato H, Hirakawa A Ther Innov Regul Sci. 2024; 59(2):264-277.

PMID: 39671047 DOI: 10.1007/s43441-024-00708-4.


Adaptive Subtype and Stage Inference for Alzheimer's Disease.

Wang X, Shi Y Med Image Comput Comput Assist Interv. 2024; 15003():46-55.

PMID: 39664696 PMC: 11632966. DOI: 10.1007/978-3-031-72384-1_5.


Prediction, prognosis and monitoring of neurodegeneration at biobank-scale via machine learning and imaging.

Dadu A, Ta M, Tustison N, Daneshmand A, Marek K, Singleton A medRxiv. 2024; .

PMID: 39574848 PMC: 11581077. DOI: 10.1101/2024.10.27.24316215.


Examining heterogeneity in dementia using data-driven unsupervised clustering of cognitive profiles.

Kumar S, Oh I, Schindler S, Ghoshal N, Abrams Z, Payne P PLoS One. 2024; 19(11):e0313425.

PMID: 39541270 PMC: 11563363. DOI: 10.1371/journal.pone.0313425.


References
1.
Marra C, Villa G, Quaranta D, Valenza A, Vita M, Gainotti G . Probable Alzheimer's disease patients presenting as "focal temporal lobe dysfunction" show a slow rate of cognitive decline. J Int Neuropsychol Soc. 2011; 18(1):144-50. DOI: 10.1017/S1355617711001287. View

2.
DeCarli C, Murphy D, Tranh M, Grady C, Haxby J, Gillette J . The effect of white matter hyperintensity volume on brain structure, cognitive performance, and cerebral metabolism of glucose in 51 healthy adults. Neurology. 1995; 45(11):2077-84. DOI: 10.1212/wnl.45.11.2077. View

3.
Poggesi A, Pantoni L, Inzitari D, Fazekas F, Ferro J, OBrien J . 2001-2011: A Decade of the LADIS (Leukoaraiosis And DISability) Study: What Have We Learned about White Matter Changes and Small-Vessel Disease?. Cerebrovasc Dis. 2012; 32(6):577-588. DOI: 10.1159/000334498. View

4.
Fisher N, Rourke B, Bieliauskas L, Giordani B, Berent S, Foster N . Neuropsychological subgroups of patients with Alzheimer's disease. J Clin Exp Neuropsychol. 1996; 18(3):349-70. DOI: 10.1080/01688639608408993. View

5.
Habek M, Hajnsek S, Zarkovic K, Chudy D, Mubrin Z . Frontal variant of Alzheimer's disease: clinico-CSF-pathological correlation. Can J Neurol Sci. 2010; 37(1):118-20. View