Neuropsychiatric symptoms in cognitive decline and Alzheimer's disease: biomarker discovery using plasma proteomics.

BACKGROUND AND OBJECTIVES: Neuropsychiatric symptoms (NPS) are common in older people with cognitive impairment and Alzheimer's disease (AD). No biomarkers to detect the related pathology or predict the clinical evolution of NPS are available yet. This study aimed to identify plasma proteins that may serve as biomarkers for NPS and NPS-related clinical disease progression. METHODS: A panel of 190 plasma proteins was quantified using Luminex xMAP in the Alzheimer's Disease Neuroimaging Initiative cohort. NPS and cognitive performance were assessed at baseline and after 1 and 2 years. Logistic regression, receiver operating characteristic analysis and cross-validation were used to address the relations of interest. RESULTS: A total of 507 participants with mild cognitive impairment (n=396) or mild AD dementia (n=111) were considered. Selected plasma proteins improved the prediction of NPS (area under the curve (AUC) from 0.61 to 0.76, p<0.001) and future NPS (AUC from 0.63 to 0.80, p<0.001) when added to a reference model. Distinct protein panels were identified for single symptoms. Among the selected proteins, ANGT, CCL1 and IL3 were associated with NPS at all three time points while CCL1, serum glutamic oxaloacetic transaminase and complement factor H were also associated with cognitive decline. The associations were independent of the presence of cerebral AD pathology as assessed using cerebrospinal fluid biomarkers. CONCLUSIONS: Plasma proteins are associated with NPS and improve prediction of future NPS.

Blood plasma protein profiles of neuropsychiatric symptoms and related cognitive decline in older people.

Neuropsychiatric symptoms (NPS) severely affect patients and their caregivers, and are associated with worse long-term outcomes. This study tested the hypothesis that altered protein levels in blood plasma could serve as biomarkers of NPS; and that altered protein levels are associated with persisting NPS and cognitive decline over time. We performed a cross-sectional and longitudinal study in older subjects with cognitive impairment and cognitively unimpaired in a memory clinic setting. NPS were recorded through the Neuropsychiatric Inventory Questionnaire (NPI-Q) while cognitive and functional impairment was assessed using the clinical dementia rating sum of boxes (CDR-SoB) score at baseline and follow-up visits. Shotgun proteomic analysis based on liquid chromatography-mass spectrometry was conducted in blood plasma samples, identifying 420 proteins. The presence of Alzheimer's Disease (AD) pathology was determined by cerebrospinal fluid biomarkers. Eighty-five subjects with a mean age of 70 (±7.4) years, 62% female and 54% with mild cognitive impairment or mild dementia were included. We found 15 plasma proteins with altered baseline levels in participants with NPS (NPI-Q score > 0). Adding those 15 proteins to a reference model based on clinical data (age, CDR-SoB) significantly improved the prediction of NPS (from receiver operating characteristic area under the curve [AUC] 0.75 to AUC 0.91, p = 0.004) with a specificity of 89% and a sensitivity of 74%. The identified proteins additionally predicted both persisting NPS and cognitive decline at follow-up visits. The observed associations were independent of the presence of AD pathology. Using proteomics, we identified a panel of specific blood proteins associated with current and future NPS, and related cognitive decline in older people. These findings show the potential of untargeted proteomics to identify blood-based biomarkers of pathological alterations relevant for NPS and related clinical disease progression.

Plasma neurofilament light, glial fibrillary acid protein, and phosphorylated tau 181 as biomarkers for neuropsychiatric symptoms and related clinical disease progression.

BACKGROUND: Neuropsychiatric symptoms (NPS) are common in older people, may occur early in the development of dementia disorders, and have been associated with faster cognitive decline. Here, our objectives were to investigate whether plasma levels of neurofilament light chain (NfL), glial fibrillary acid protein (GFAP), and tau phosphorylated at threonine 181 (pTau181) are associated with current NPS and predict future NPS in non-demented older people. Furthermore, we tested whether the presence of NPS combined with plasma biomarkers are useful to predict Alzheimer's disease (AD) pathology and cognitive decline. METHODS: One hundred and fifty-one participants with normal cognition (n = 76) or mild cognitive impairment (n = 75) were examined in a longitudinal brain aging study at the Memory Centers, University Hospital of Lausanne, Switzerland. Plasma levels of NfL, GFAP, and pTau181 along with CSF biomarkers of AD pathology were measured at baseline. NPS were assessed through the Neuropsychiatric Inventory Questionnaire (NPI-Q), along with the cognitive and functional performance at baseline and follow-up (mean: 20 months). Different regression and ROC analyses were used to address the associations of interest. RESULTS: None of the three plasma biomarker was associated with NPS at baseline. Higher GFAP levels were associated with the presence of NPS at follow-up (OR = 2.8, p = .002) and both, higher NfL and higher GFAP with an increase in the NPI-Q severity score over time (ß = 0.25, p = .034 and ß = 0.30, p = .013, respectively). Adding NPS and the plasma biomarkers to a reference model improved the prediction of future NPS (AUC 0.72 to 0.88, p = .002) and AD pathology (AUC 0.78 to 0.87, p = .010), but not of cognitive decline (AUC 0.79 to 0.85, p = .081). CONCLUSION: Plasma NfL and GFAP are both associated with future NPS and NPS severity change. Considering the presence of NPS along with blood-based AD-biomarkers may improve the prediction of clinical progression of NPS over time and inform clinical decision-making in non-demented older people.

Plasma neurofilament light, glial fibrillary acid protein, and phosphorylated tau 181 as biomarkers for neuropsychiatric symptoms and related clinical disease progression.

BACKGROUND: Neuropsychiatric symptoms (NPS) are common in older people, may occur early in the development of dementia disorders, and have been associated with faster cognitive decline. Here, our objectives were to investigate whether plasma levels of neurofilament light chain (NfL), glial fibrillary acid protein (GFAP), and tau phosphorylated at threonine 181 (pTau181) are associated with current NPS and predict future NPS in non-demented older people. Furthermore, we tested whether the presence of NPS combined with plasma biomarkers are useful to predict Alzheimer's disease (AD) pathology and cognitive decline. METHODS: One hundred and fifty-one participants with normal cognition (n=76) or mild cognitive impairment (n=75) were examined in a longitudinal brain aging study at the Memory Centers, University Hospital of Lausanne, Switzerland. Plasma levels of NfL, GFAP, and pTau181 along with CSF biomarkers of AD pathology were measured at baseline. NPS were assessed through the Neuropsychiatric Inventory Questionnaire (NPI-Q), along with the cognitive and functional performance at baseline and follow-up (mean: 20 months). Linear regression and ROC analyses were used to address the associations of interest. RESULTS: Higher GFAP levels were associated with NPS at baseline (ß=0.23, p=.008). Higher NfL and GFAP levels were associated with the presence of NPS at follow-up (ß=0.29, p=.007 and ß=0.28, p=.007, respectively) and with an increase in the NPI-Q severity score over time (ß=0.23, p=.035 and ß=0.27, p=.011, respectively). Adding NPS and the plasma biomarkers to a reference model improved the prediction of future NPS (AUC 0.73 to 0.84, p=.007) and AD pathology (AUC 0.79 to 0.86, p=.006), but not of cognitive decline (AUC 0.79 to 0.84, p=.068). CONCLUSION: Plasma GFAP is associated with NPS while NfL and GFAP are both associated with future NPS and NPS severity. Considering the presence of NPS along with blood-based AD-biomarkers may improve diagnosis and prediction of clinical progression of NPS and inform clinical decision-making in non-demented older people.

The promise of multi-omics approaches to discover biological alterations with clinical relevance in Alzheimer's disease.

Beyond the core features of Alzheimer's disease (AD) pathology, i.e. amyloid pathology, tau-related neurodegeneration and microglia response, multiple other molecular alterations and pathway dysregulations have been observed in AD. Their inter-individual variations, complex interactions and relevance for clinical manifestation and disease progression remain poorly understood, however. Heterogeneity at both pathophysiological and clinical levels complicates diagnosis, prognosis, treatment and drug design and testing. High-throughput "omics" comprise unbiased and untargeted data-driven methods which allow the exploration of a wide spectrum of disease-related changes at different endophenotype levels without focussing a priori on specific molecular pathways or molecules. Crucially, new methodological and statistical advances now allow for the integrative analysis of data resulting from multiple and different omics methods. These multi-omics approaches offer the unique advantage of providing a more comprehensive characterisation of the AD endophenotype and to capture molecular signatures and interactions spanning various biological levels. These new insights can then help decipher disease mechanisms more deeply. In this review, we describe the different multi-omics tools and approaches currently available and how they have been applied in AD research so far. We discuss how multi-omics can be used to explore molecular alterations related to core features of the AD pathologies and how they interact with comorbid pathological alterations. We further discuss whether the identified pathophysiological changes are relevant for the clinical manifestation of AD, in terms of both cognitive impairment and neuropsychiatric symptoms, and for clinical disease progression over time. Finally, we address the opportunities for multi-omics approaches to help discover novel biomarkers for diagnosis and monitoring of relevant pathophysiological processes, along with personalised intervention strategies in AD.

Persisting neuropsychiatric symptoms, Alzheimer's disease, and cerebrospinal fluid cortisol and dehydroepiandrosterone sulfate.

INTRODUCTION: Neuropsychiatric symptoms are important treatment targets in the management of dementia and can be present at very early clinical stages of neurodegenerative diseases. Increased cortisol has been reported in Alzheimer's disease (AD) and has been associated with faster cognitive decline. Elevated cortisol output has been observed in relation to perceived stress, depression, and anxiety. Dehydroepiandrosterone sulfate (DHEAS) has known anti-glucocorticoid effects and may counter the effects of cortisol. OBJECTIVES: We aimed to examine whether CSF cortisol and DHEAS levels were associated with (1) neuropsychiatric symptoms at baseline, (2) changes in neuropsychiatric symptoms over 3 years, and (3) whether these associations were related to or independent of AD pathology. METHODS: One hundred and eighteen participants on a prospective study in a memory clinic setting, including patients with cognitive impairment (n = 78), i.e., mild cognitive impairment or mild dementia, and volunteers with normal cognition (n = 40), were included. Neuropsychiatric symptoms were assessed using the Neuropsychiatric Inventory Questionnaire (NPI-Q). CSF cortisol and DHEAS, as well as CSF AD biomarkers, were obtained at baseline. Neuropsychiatric symptoms were re-assessed at follow-up visits 18 and 36 months from baseline. We constructed linear regression models to examine the links between baseline neuropsychiatric symptoms, the presence of AD pathology as indicated by CSF biomarkers, and CSF cortisol and DHEAS. We used repeated-measures mixed ANCOVA models to examine the associations between the neuropsychiatric symptoms' changes over time, baseline CSF cortisol and DHEAS, and AD pathology. RESULTS: Higher CSF cortisol was associated with higher NPI-Q severity scores at baseline after controlling for covariates including AD pathology status (B = 0.085 [0.027; 0.144], p = 0.027; r = 0.277). In particular, higher CSF cortisol was associated with higher baseline scores of depression/dysphoria, anxiety, and apathy/indifference. Elevated CSF cortisol was also associated with more marked increase in NPI-Q scores over time regardless of AD status (p = 0.036, η2 = 0.207), but this association was no longer significant after controlling for BMI and the use of psychotropic medications. CSF DHEAS was associated neither with NPI-Q scores at baseline nor with their change over time. Cortisol did not mediate the association between baseline NPI-Q and changes in clinical dementia rating sum of boxes over 36 months. CONCLUSION: Higher CSF cortisol may reflect or contribute to more severe neuropsychiatric symptoms at baseline, as well as more pronounced worsening over 3 years, independently of the presence of AD pathology. Our findings also suggest that interventions targeting the HPA axis may be helpful to treat neuropsychiatric symptoms in patients with dementia.