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 DNA methylomic signatures associated with CSF biomarkers of Alzheimer's disease in the EMIF-AD study.

INTRODUCTION: We investigated blood DNA methylation patterns associated with 15 well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) pathophysiology, neuroinflammation, and neurodegeneration. METHODS: We assessed DNA methylation in 885 blood samples from the European Medical Information Framework for Alzheimer's Disease (EMIF-AD) study using the EPIC array. RESULTS: We identified Bonferroni-significant differential methylation associated with CSF YKL-40 (five loci) and neurofilament light chain (NfL; seven loci) levels, with two of the loci associated with CSF YKL-40 levels correlating with plasma YKL-40 levels. A co-localization analysis showed shared genetic variants underlying YKL-40 DNA methylation and CSF protein levels, with evidence that DNA methylation mediates the association between genotype and protein levels. Weighted gene correlation network analysis identified two modules of co-methylated loci correlated with several amyloid measures and enriched in pathways associated with lipoproteins and development. DISCUSSION: We conducted the most comprehensive epigenome-wide association study (EWAS) of AD-relevant CSF biomarkers to date. Future work should explore the relationship between YKL-40 genotype, DNA methylation, and protein levels in the brain. HIGHLIGHTS: Blood DNA methylation was assessed in the EMIF-AD MBD study. Epigenome-wide association studies (EWASs) were performed for 15 Alzheimer's disease (AD)-relevant cerebrospinal fluid (CSF) biomarker measures. Five Bonferroni-significant loci were associated with YKL-40 levels and seven with neurofilament light chain (NfL). DNA methylation in YKL-40 co-localized with previously reported genetic variation. DNA methylation potentially mediates the effect of single-nucleotide polymorphisms (SNPs) in YKL-40 on CSF protein levels.

Blood-based multivariate methylation risk score for cognitive impairment and dementia.

INTRODUCTION: The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection. METHODS: In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts. RESULTS: We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P = 2.0 × 10-3). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia = 2.59). DISCUSSION: Our work shows the potential of employing blood-derived DNA methylation data in the assessment of dementia risk. HIGHLIGHTS: We used whole blood DNA methylation as a surrogate for 14 dementia risk factors. Created a multivariate methylation risk score for predicting cognitive impairment. Emphasized the role of machine learning and omics data in predicting dementia. The score predicts cognitive impairment development at the population level.

Synaptic protein CSF levels relate to memory scores in individuals without dementia.

INTRODUCTION: We investigated how cerebrospinal fluid levels of synaptic proteins associate with memory function in normal cognition (CN) and mild cognitive impairment (MCI), and investigated the effect of amyloid positivity on these associations. METHODS: We included 242 CN (105(43%) abnormal amyloid), and 278 MCI individuals (183(66%) abnormal amyloid) from EMIF-AD MBD and ADNI. For 181 (EMIF-AD MBD) and 36 (ADNI) proteins with a synaptic annotation in SynGO, associations with word learning recall were analysed with linear models. RESULTS: Subsets of synaptic proteins showed lower levels with worse recall in preclinical AD (EMIF-AD MBD: 7, ADNI: 5 proteins, none overlapping), prodromal AD (EMIF-AD MBD only, 27 proteins) and non-AD MCI (EMIF-AD MBD: 1, ADNI: 7 proteins). The majority of these associations were specific to these groups. DISCUSSION: Synaptic disturbance-related memory impairment occurred very early in AD, indicating it may be relevant to develop therapies targeting the synapse early in the disease.

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.

Involvement of the choroid plexus in Alzheimer's disease pathophysiology: findings from mouse and human proteomic studies.

BACKGROUND: Structural and functional changes of the choroid plexus (ChP) have been reported in Alzheimer's disease (AD). Nonetheless, the role of the ChP in the pathogenesis of AD remains largely unknown. We aim to unravel the relation between ChP functioning and core AD pathogenesis using a unique proteomic approach in mice and humans. METHODS: We used an APP knock-in mouse model, APPNL-G-F, exhibiting amyloid pathology, to study the association between AD brain pathology and protein changes in mouse ChP tissue and CSF using liquid chromatography mass spectrometry. Mouse proteomes were investigated at the age of 7 weeks (n = 5) and 40 weeks (n = 5). Results were compared with previously published human AD CSF proteomic data (n = 496) to identify key proteins and pathways associated with ChP changes in AD. RESULTS: ChP tissue proteome was dysregulated in APPNL-G-F mice relative to wild-type mice at both 7 and 40 weeks. At both ages, ChP tissue proteomic changes were associated with epithelial cells, mitochondria, protein modification, extracellular matrix and lipids. Nonetheless, some ChP tissue proteomic changes were different across the disease trajectory; pathways related to lysosomal function, endocytosis, protein formation, actin and complement were uniquely dysregulated at 7 weeks, while pathways associated with nervous system, immune system, protein degradation and vascular system were uniquely dysregulated at 40 weeks. CSF proteomics in both mice and humans showed similar ChP-related dysregulated pathways. CONCLUSIONS: Together, our findings support the hypothesis of ChP dysfunction in AD. These ChP changes were related to amyloid pathology. Therefore, the ChP could become a novel promising therapeutic target for AD.

CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease.

INTRODUCTION: We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics. METHODS: Individuals without dementia were classified as A+ (CSF amyloid beta [Aß]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance. RESULTS: Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress. DISCUSSION: Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology. HIGHLIGHTS: In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau.

Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. METHOD: Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. RESULTS: Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. CONCLUSIONS: This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways.

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.

Association between Serum Phytosterols and Lipid Levels in a Population-Based Study.

The association between phytosterols and lipid levels remains poorly assessed at a population level. We assessed the associations between serum levels of six phytosterols (campesterol, campestanol, stigmasterol, sitosterol, sitostanol and brassicasterol) and of lipids [total, low-density lipoprotein (LDL)- and high-density lipoprotein (HDL)-cholesterol, triglycerides, apolipopoprotein A-IV and lipoprotein Lp(a)] in two cross-sectional surveys of a population-based, prospective study. Data from 910 participants (59.1% women, 70.4 ± 4.7 years) for the first survey (2009-2012) and from 721 participants (60.2% women, 75.1 ± 4.7 years) for the second survey (2014-2017) were used. After multivariable adjustment, all phytosterols were positively associated with total cholesterol: slope and (95% confidence interval) 1.594 (1.273-1.915); 0.073 (0.058-0.088); 0.060 (0.044-0.076); 2.333 (1.836-2.830); 0.049 (0.033-0.064) and 0.022 (0.017-0.028) for campesterol, campestanol, stigmasterol, sitosterol, sitostanol and brassicasterol, respectively, in the first survey, and 1.257 (0.965-1.548); 0.066 (0.052-0.079); 0.049 (0.034-0.063); 1.834 (1.382-2.285); 0.043 (0.029-0.057) and 0.018 (0.012-0.023) in the second survey, all p < 0.05. Similar positive associations were found between all phytosterols and LDL cholesterol. Positive associations were found between campesterol and sitosterol and HDL-cholesterol: slope and (95% CI) 0.269 (0.134-0.405) and 0.393 (0.184-0.602) for campesterol and sitosterol, respectively, in the first survey, and 1.301 (0.999-1.604) and 0.588 (0.327-0.849) in the second survey, all p < 0.05. No associations were found between phytosterols and triglyceride or lipoprotein Lp(a) levels, while a positive association between campesterol and apolipoprotein A-IV levels was found: 2.138 (0.454-3.822). Upon normal dietary intakes, serum phytosterol levels were positively associated with total and LDL cholesterol levels, while no consistent association with other lipid markers was found.

Cholesterol-metabolism, plant sterols, and long-term cognitive decline in older people - Effects of sex and APOEe4.

Neurodegenerative, vascular, and dementia diseases are linked to dysregulations in cholesterol metabolism. Dietary plant sterols, or phytosterols, may interfere to neurodegeneration and cognitive decline, and have cholesterol-lowering, anti-inflammatory, and antioxidant qualities. Here, we investigated the potential associations between circulating cholesterol precursors and metabolites, triglycerides, and phytosterols with cognitive decline in older people by performing multivariate analysis on 246 participants engaged in a population-based prospective study. In our analysis we considered the potential effect of sex and APOEe4. We reveal particular dysregulations of diet-derived phytosterols and endogenous cholesterol synthesis and metabolism, and their variations over time linked to cognitive decline in the general population. These results are significant to the development of interventions to avoid cognitive decline in older adults and suggest that levels of circulating sterols should be taken into account when evaluating risk.

Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning.

BACKGROUND: Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (ß-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences. METHODS: We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects. RESULTS: Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers. CONCLUSIONS: These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine.

Plant sterols and cholesterol metabolism are associated with five-year cognitive decline in the elderly population.

Dysregulations in cholesterol metabolism are associated with neurodegenerative and vascular pathologies, and dementia. Diet-derived plant sterols (phytosterols) have cholesterol-lowering, anti-inflammatory, and antioxidant properties and may interfere with neurodegeneration and cognitive decline. Here we performed multivariate analysis in 720 individuals enrolled in a population-based prospective study to determine whether circulating cholesterol precursors and metabolites, triglycerides, and phytosterols, are associated with cognitive impairment and decline in the older population. We report specific dysregulations of endogenous cholesterol synthesis and metabolism, and diet-derived phytosterols, and their changes over time associated with cognitive impairment, and decline in the general population. These findings suggest circulating sterols levels could be considered in risk evaluation and are relevant for the development of strategies to prevent cognitive decline in older people.

Obstructive sleep apnoea and 5-year cognitive decline in the elderly.

BACKGROUND: The relationship between obstructive sleep apnoea (OSA) and cognitive decline remains controversial, especially in the elderly population. We used data from the HypnoLaus study to assess associations between OSA and longitudinal cognitive changes in a sample of community-dwelling elderly individuals. METHODS: We studied associations between polysomnographic OSA parameters (of breathing/hypoxaemia and sleep fragmentation) and cognitive changes over a 5-year period, after adjustment for potential confounders. The primary outcome was the annual change in cognitive scores. The moderating effects of age, sex and apolipoprotein E4 (ApoE4) status were also examined. RESULTS: 358 elderly individuals without dementia were included (mean±sd age 71.0±4.2 years; 42.5% males). A lower mean peripheral oxygen saturation (S pO2 ) during sleep was associated with a steeper decline in Mini-Mental State Examination (B= -0.12, p=0.004), Stroop test condition 1 (B=0.53, p=0.002) and Free and Cued Selective Reminding Test delayed free recall (B= -0.05, p=0.008). A longer time spent asleep with S pO2 <90% was associated with a steeper decline in Stroop test condition 1 (B=0.47, p=0.006). Moderation analysis showed that apnoea-hypopnoea index and oxygen desaturation index were associated with a steeper decline in global cognitive function, processing speed and executive function only in older participants, men and ApoE4 carriers. CONCLUSIONS: Our results provide evidence of the contribution of OSA and nocturnal hypoxaemia to cognitive decline in the elderly population.

Multiomics profiling of human plasma and cerebrospinal fluid reveals ATN-derived networks and highlights causal links in Alzheimer's disease.

INTRODUCTION: This study employed an integrative system and causal inference approach to explore molecular signatures in blood and CSF, the amyloid/tau/neurodegeneration [AT(N)] framework, mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD), and genetic risk for AD. METHODS: Using the European Medical Information Framework (EMIF)-AD cohort, we measured 696 proteins in cerebrospinal fluid (n = 371), 4001 proteins in plasma (n = 972), 611 metabolites in plasma (n = 696), and genotyped whole-blood (7,778,465 autosomal single nucleotide epolymorphisms, n = 936). We investigated associations: molecular modules to AT(N), module hubs with AD Polygenic Risk scores and APOE4 genotypes, molecular hubs to MCI conversion and probed for causality with AD using Mendelian randomization (MR). RESULTS: AT(N) framework associated with protein and lipid hubs. In plasma, Proprotein Convertase Subtilisin/Kexin Type 7 showed evidence for causal associations with AD. AD was causally associated with Reticulocalbin 2 and sphingomyelins, an association driven by the APOE isoform. DISCUSSION: This study reveals multi-omics networks associated with AT(N) and causal AD molecular candidates.

Whole-exome rare-variant analysis of Alzheimer's disease and related biomarker traits.

INTRODUCTION: Despite increasing evidence of a role of rare genetic variation in the risk of Alzheimer's disease (AD), limited attention has been paid to its contribution to AD-related biomarker traits indicative of AD-relevant pathophysiological processes. METHODS: We performed whole-exome gene-based rare-variant association studies (RVASs) of 17 AD-related traits on whole-exome sequencing (WES) data generated in the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study (n = 450) and whole-genome sequencing (WGS) data from ADNI (n = 808). RESULTS: Mutation screening revealed a novel probably pathogenic mutation (PSEN1 p.Leu232Phe). Gene-based RVAS revealed the exome-wide significant contribution of rare coding variation in RBKS and OR7A10 to cognitive performance and protection against left hippocampal atrophy, respectively. DISCUSSION: The identification of these novel gene-trait associations offers new perspectives into the role of rare coding variation in the distinct pathophysiological processes culminating in AD, which may lead to identification of novel therapeutic and diagnostic targets.

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.

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.

Predicting AT(N) pathologies in Alzheimer's disease from blood-based proteomic data using neural networks.

Background and objective: Blood-based biomarkers represent a promising approach to help identify early Alzheimer's disease (AD). Previous research has applied traditional machine learning (ML) to analyze plasma omics data and search for potential biomarkers, but the most modern ML methods based on deep learning has however been scarcely explored. In the current study, we aim to harness the power of state-of-the-art deep learning neural networks (NNs) to identify plasma proteins that predict amyloid, tau, and neurodegeneration (AT[N]) pathologies in AD. Methods: We measured 3,635 proteins using SOMAscan in 881 participants from the European Medical Information Framework for AD Multimodal Biomarker Discovery study (EMIF-AD MBD). Participants underwent measurements of brain amyloid ß (Aß) burden, phosphorylated tau (p-tau) burden, and total tau (t-tau) burden to determine their AT(N) statuses. We ranked proteins by their association with Aß, p-tau, t-tau, and AT(N), and fed the top 100 proteins along with age and apolipoprotein E (APOE) status into NN classifiers as input features to predict these four outcomes relevant to AD. We compared NN performance of using proteins, age, and APOE genotype with performance of using age and APOE status alone to identify protein panels that optimally improved the prediction over these main risk factors. Proteins that improved the prediction for each outcome were aggregated and nominated for pathway enrichment and protein-protein interaction enrichment analysis. Results: Age and APOE alone predicted Aß, p-tau, t-tau, and AT(N) burden with area under the curve (AUC) scores of 0.748, 0.662, 0.710, and 0.795. The addition of proteins significantly improved AUCs to 0.782, 0.674, 0.734, and 0.831, respectively. The identified proteins were enriched in five clusters of AD-associated pathways including human immunodeficiency virus 1 infection, p53 signaling pathway, and phosphoinositide-3-kinase-protein kinase B/Akt signaling pathway. Conclusion: Combined with age and APOE genotype, the proteins identified have the potential to serve as blood-based biomarkers for AD and await validation in future studies. While the NNs did not achieve better scores than the support vector machine model used in our previous study, their performances were likely limited by small sample size.

[Biomarkers for the diagnosis of cognitive impairment - Recommendations from the Swiss Memory Clinics]. / Biomarqueurs des pathologies neurodégénératives dans le diagnostic des troubles cognitifs - Revue et recommandations de Swiss Memory Clinics.

Established cerebrospinal fluid (CSF) biomarkers allow for earlier and more accurate etiological diagnosis of cognitive impairment. Information and counselling are needed both before and after biomarker-supported diagnosis. The procedures for diagnostic lumbar punctures and pre-analytical sample handling should follow published consensus recommendations. The results must be interpreted in the context of the other available history information and assessments. Blood-based biomarkers and other non-invasive markers are expected to become available for clinical practice soon. Consequently, a broader usage of biomarkers is expected and may accelerate the development of individually tailored prevention and treatment approaches. This article provides the recommendations of the Swiss Memory Clinics for the use of biomarkers in clinical practice.

Les marqueurs du liquide céphalorachidien établis permettent un diagnostic des troubles cognitifs plus précoce et précis. Il est nécessaire de conseiller les patients avant et après un examen des biomarqueurs. Les procédures de la ponction lombaire et de traitement préanalytique des échantillons doivent suivre des recommandations publiées. L'interprétation des résultats prendra en compte les antécédents médicaux et les autres résultats d'examen disponibles. Des marqueurs sanguins pourraient être disponibles dans un avenir proche. Cela pourrait conduire à une utilisation plus large des biomarqueurs et accélérer le développement d'approches personnalisées de prévention et de traitement. Cet article présente les recommandations de Swiss Memory Clinics concernant l'utilisation des biomarqueurs en pratique clinique.