Detecting Non-cognitive Features of Prodromal Neurodegenerative Diseases

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Author(s): Seifan A., Ganzer C. A., Ryon K., Lin M., Mahmudur R., Henriquez A., Shih C., Jacobs R. A., Greenwald M., R. S. Isaacson.

Journal Name: Current Aging Science

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Abstract:

Background/Aims: Prodromal Neurodegenerative Disease (ND) due to Alzheimer’s disease, Parkinson’s disease, and Frontotemporal Lobar Degeneration presents with neurological, psychiatric and medical symptomatology prior to the onset of cognitive changes. Currently, recognition of clinical syndromes during prodromal ND stages is clinically challenging. Fragmentation in care across medical specialties for people with neurological or psychiatric symptoms challenge our ability to recognize clear-cut syndromes because different doctors are paying attention to different aspects of the patient’s case. , patients with prodromal ND are Better identification of specific syndrome not only cognitive, but also emotional and medical symptomatology can aid in diagnosing ND at earlier stages, even prior to cognitive changes. Phenotypic heterogeneity in neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and Frontotemporal Lobar Degeneration is a main reason why diagnosing prodromal ND remains clinically challenging. Since disease-modifying interventions are most effective during prodromal stages, our objective was to introduce a new method for detecting prodromal ND using non-cognitive features.

Methods: 165 patients completed baseline neuropsychological testing and gave subjective measures of non-cognitive symptoms. A principal component analysis (PCA) was performed on the sample to identify the symptoms that clustered together. Symptom clusters were compared with the symptoms present in subjects with four diagnostic groupings. These are prodromal AD, PD/LBD, and Cognitively Normal.

Results: A total of twelve distinct symptom clusters were identified. Symptom clusters were/were not present across all stages of AD and were/were not present across all stages of PD/LBD, regardless of pathology.

Conclusions: Our findings suggest that non-cognitive features can be reliably measured by selfreport in busy clinical settings and such measurement can be useful in distinguishing patients with different etiologies of ND. Better characterization of unique, prodromal, non-cognitive ND trajectories could improve public health efforts to increase access to prodromal ND detection during the most modifiable disease stages.

Keywords: Non-cognitive, neurodegenerative, Alzheimer’s disease, self-report, mild cognitive impairment, dementia.

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Article Details

(E-pub Ahead of Print)
DOI: 10.2174/1874609812666190204094233
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