Blood plasma profiles of neuropsychiatric symptoms in older people. (20th December 2022)

• Record Type: Journal Article
• Authors: Rabl, Miriam; Clark, Christopher; Dayon, Loic; Bowman, Gene L.; Popp, Julius
• Is Part Of: Alzheimer's & dementia. Volume 18(2022)Supplement 5
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-20
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.063376
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Neuropsychiatric symptoms (NPS) in older people worsen the patients' and caregivers' quality of life and are associated with cognitive decline. A better understanding of the biology underlying NPS may lead to novel ways for early detection and more targeted treatment. This study tested the hypothesis that NPS are associated with altered protein levels in blood plasma and these proteins improve prediction of NPS in a memory clinic setting. Additionally, we explored the association of the protein patterns with persistent NPS and cognitive decline. Method: We performed a cross‐sectional and longitudinal study in older people with and without cognitive impairment. NPS were recorded through the Neuropsychiatric Inventory Questionnaire (NPI‐Q) while cognition was assessed through a comprehensive neuropsychological test battery collected at baseline and follow‐up visits. Shotgun proteomic analysis based on liquid chromatography‐mass spectrometry identifying 420 proteins were conducted in blood plasma samples of all participants. Multivariate linear regression and correlation analysis were used. Result: Eighty‐five subjects with a mean age of 70 (± 7.4) years, 65% female and 54% with mild cognitive impairment or mild dementia were divided into groups with (NPI‐Q score > 0) and without NPS. We found 15 plasma proteins with altered baseline levels in participants with NPS. The model which best predicted the occurrence of NPS at baseline contained clinical data (age, sex, education years, cognitive impairment) and additionally the 15 altered proteins. Comparing this model with a reference model containing just the clinical data, the prediction of NPS significantly improved (from receiver operating characteristic area under the curve (AUC) 0.72 to AUC 0.89, p = 0.001) with a specificity of 87 % and a sensitivity of 72% (Fig. 1). Preliminary results indicate that five out of the 15 proteins were associated with persisting NPS and six with cognitive decline at follow‐up (mean: 3.4 ± 1.3 years). Conclusion: Using a proteomic approach, we identified a panel of blood proteins associated with NPS in older people. These findings showed the potential of this approach to identify protein biomarkers of pathological changes underlying NPS and to detect novel treatment targets to reduce NPS and related cognitive decline.