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.

Cerebral blood flow, amyloid burden, and cognition in cognitively normal individuals.

PURPOSE: The role of cerebral blood flow (CBF) in the early stages of Alzheimer's disease is complex and largely unknown. We investigated cross-sectional and longitudinal associations between CBF, amyloid burden, and cognition, in cognitively normal individuals with subjective cognitive decline (SCD). METHODS: We included 187 cognitively normal individuals with SCD from the SCIENCe project (65 ± 8 years, 39% F, MMSE 29 ± 1). Each underwent a dynamic (0-70 min) [18F]florbetapir PET and T1-weighted MRI scan, enabling calculation of mean binding potential (BPND; specific amyloid binding) and R1 (measure of relative (r)CBF). Eighty-three individuals underwent a second [18F]florbetapir PET (2.6 ± 0.7 years). Participants annually underwent neuropsychological assessment (follow-up time 3.8 ± 3.1 years; number of observations n = 774). RESULTS: A low baseline R1 was associated with steeper decline on tests addressing memory, attention, and global cognition (range betas 0.01 to 0.27, p < 0.05). High BPND was associated with steeper decline on tests covering all domains (range betas - 0.004 to - 0.70, p < 0.05). When both predictors were simultaneously added to the model, associations remained essentially unchanged. Additionally, we found longitudinal associations between R1 and BPND. High baseline BPND predicted decline over time in R1 (all regions, range betasBP×time - 0.09 to - 0.14, p < 0.05). Vice versa, low baseline R1 predicted increase in BPND in frontal, temporal, and composite ROIs over time (range betasR1×time - 0.03 to - 0.08, p < 0.05). CONCLUSION: Our results suggest that amyloid accumulation and decrease in rCBF are two parallel disease processes without a fixed order, both providing unique predictive information for cognitive decline and each process enhancing the other longitudinally.

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.

Cerebrospinal fluid proteomic profiling of individuals with mild cognitive impairment and suspected non-Alzheimer's disease pathophysiology.

BACKGROUND: Suspected non-Alzheimer's disease pathophysiology (SNAP) is a biomarker concept that encompasses individuals with neuronal injury but without amyloidosis. We aim to investigate the pathophysiology of SNAP, defined as abnormal tau without amyloidosis, in individuals with mild cognitive impairment (MCI) by cerebrospinal fluid (CSF) proteomics. METHODS: Individuals were classified based on CSF amyloid beta (Aß)1-42 (A) and phosphorylated tau (T), as cognitively normal A-T- (CN), MCI A-T+ (MCI-SNAP), and MCI A+T+ (MCI-AD). Proteomics analyses, Gene Ontology (GO), brain cell expression, and gene expression analyses in brain regions of interest were performed. RESULTS: A total of 96 proteins were decreased in MCI-SNAP compared to CN and MCI-AD. These proteins were enriched for extracellular matrix (ECM), hemostasis, immune system, protein processing/degradation, lipids, and synapse. Fifty-one percent were enriched for expression in the choroid plexus. CONCLUSION: The pathophysiology of MCI-SNAP (A-T+) is distinct from that of MCI-AD. Our findings highlight the need for a different treatment in MCI-SNAP compared to MCI-AD.

Are Apathy and Depressive Symptoms Related to Vascular White Matter Hyperintensities in Severe Late Life Depression?

OBJECTIVE: Apathy symptoms are defined as a lack of interest and motivation. Patients with late-life depression (LLD) also suffer from lack of interest and motivation and previous studies have linked apathy to vascular white matter hyperintensities (WMH) of the brain in depressed and nondepressed patients. The aim of this study was to investigate the relationship between apathy symptoms, depressive symptoms, and WMH in LLD. We hypothesize that late-onset depression (LOD; first episode of depression after 55 years of age) is associated with WMH and apathy symptoms. METHODS: Apathy scores were collected for 87 inpatients diagnosed with LLD. Eighty patients underwent brain magnetic resonance imaging. Associations between depressive and apathy symptoms and WMH were analyzed using linear regression. RESULTS: All 3 subdomains of the 10-item Montgomery-Åsberg Depression Rating Scale correlated significantly with the apathy scale score (all P < .05). In the total sample, apathy nor depressive symptoms were related to specific WMH. In LOD only, periventricular WMH were associated with depression severity (ß = 5.21, P = .04), while WMH in the left infratentorial region were associated with apathy symptoms (ß coefficient = 5.89, P = .03). CONCLUSION: Apathy and depressive symptoms are highly overlapping in the current cohort of older patients with severe LLD, leading to the hypothesis that apathy symptoms are part of depressive symptoms in the symptom profile of older patients with severe LLD. Neither apathy nor depressive symptoms were related to WMH, suggesting that radiological markers of cerebrovascular disease, such as WMH, may not be useful in predicting these symptoms in severe LLD.

Replication study of plasma proteins relating to Alzheimer's pathology.

INTRODUCTION: This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis. METHODS: Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively. RESULTS: Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis. DISCUSSION: Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.

Discovery and validation of plasma proteomic biomarkers relating to brain amyloid burden by SOMAscan assay.

INTRODUCTION: Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins. METHODS: 4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid. RESULTS: A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization. DISCUSSION: The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition.

Early-Onset Dementia: Frequency, Diagnostic Procedures, and Quality Indicators in Three European Tertiary Referral Centers.

BACKGROUND: Early-onset dementia (EOD) is a rare condition, with an often atypical clinical presentation, and it may therefore be challenging to diagnose. Specialized memory clinics vary in the type of patients seen, diagnostic procedures applied, and the pharmacological treatment given. The aim of this study was to investigate quality-of-care indicators in subjects with EOD from 3 tertiary memory clinics in 3 European countries. METHODS: We included 1325 newly diagnosed EOD patients, ages 65 years or younger, between January 1, 2007 and December 31, 2013, from the Danish Dementia Registry (Rigshospitalet, Copenhagen), the Swedish Dementia Registry ("SveDem", Karolinska University Hospital, Stockholm), and the Amsterdam Dementia Cohort (VU University Medical Center). RESULTS: The frequency of EOD among all dementia patients was significantly lower in Copenhagen (410, 20%) and Stockholm (284, 21%) compared with Amsterdam (631, 48%). Not all quality indicator targets were met, such as the time to diagnosis, the mini-mental state examination score available, and the prescription of cholinesterase inhibitors. Cerebrospinal fluid sampling, registered in 2 sites, was performed in over 80% of the subjects. CONCLUSIONS: In tertiary referral centers in Copenhagen, Stockholm, and Amsterdam, quality indicators were not always met for patients with EOD. Results partly reflect differences in referral pattern, the application of diagnostic criteria, and local best practices. Standardized international procedures for patients with EOD may reduce this variability.

Genetic, vascular and amyloid components of cerebral blood flow in a preclinical population.

Aging-related cognitive decline can be accelerated by a combination of genetic factors, cardiovascular and cerebrovascular dysfunction, and amyloid-ß burden. Whereas cerebral blood flow (CBF) has been studied as a potential early biomarker of cognitive decline, its normal variability in healthy elderly is less known. In this study, we investigated the contribution of genetic, vascular, and amyloid-ß components of CBF in a cognitively unimpaired (CU) population of monozygotic older twins. We included 134 participants who underwent arterial spin labeling (ASL) MRI and [18F]flutemetamol amyloid-PET imaging at baseline and after a four-year follow-up. Generalized estimating equations were used to investigate the associations of amyloid burden and white matter hyperintensities with CBF. We showed that, in CU individuals, CBF: 1) has a genetic component, as within-pair similarities in CBF values were moderate and significant (ICC > 0.40); 2) is negatively associated with cerebrovascular damage; and 3) is positively associated with the interaction between cardiovascular risk scores and early amyloid-ß burden, which may reflect a vascular compensatory response of CBF to early amyloid-ß accumulation. These findings encourage future studies to account for multiple interactions with CBF in disease trajectory analyses.

Sex-Specific Metabolic Pathways Were Associated with Alzheimer's Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort.

BACKGROUND: physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives. METHODS: We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites' discriminatory performance in AD. RESULTS: In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046). CONCLUSIONS: metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.

Assessing Amyloid Pathology in Cognitively Normal Subjects Using 18F-Flutemetamol PET: Comparing Visual Reads and Quantitative Methods.

Our objective was to determine the optimal approach for assessing amyloid disease in a cognitively normal elderly population. Methods: Dynamic 18F-flutemetamol PET scans were acquired using a coffee-break protocol (a 0- to 30-min scan and a 90- to 110-min scan) on 190 cognitively normal elderly individuals (mean age, 70.4 y; 60% female). Parametric images were generated from SUV ratio (SUVr) and nondisplaceable binding potential (BPND) methods, with cerebellar gray matter as a reference region, and were visually assessed by 3 trained readers. Interreader agreement was calculated using κ-statistics, and semiquantitative values were obtained. Global cutoffs were calculated for both SUVr and BPND using a receiver-operating-characteristic analysis and the Youden index. Visual assessment was related to semiquantitative classifications. Results: Interreader agreement in visual assessment was moderate for SUVr (κ = 0.57) and good for BPND images (κ = 0.77). There was discordance between readers for 35 cases (18%) using SUVr and for 15 cases (8%) using BPND, with 9 overlapping cases. For the total cohort, the mean (±SD) SUVr and BPND were 1.33 (±0.21) and 0.16 (±0.12), respectively. Most of the 35 cases (91%) for which SUVr image assessment was discordant between readers were classified as negative based on semiquantitative measurements. Conclusion: The use of parametric BPND images for visual assessment of 18F-flutemetamol in a population with low amyloid burden improves interreader agreement. Implementing semiquantification in addition to visual assessment of SUVr images can reduce false-positive classification in this population.

A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort.

INTRODUCTION: Machine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer Disease (AD). Here we set out to test the performance of metabolites in blood to categorize AD when compared to CSF biomarkers. METHODS: This study analyzed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n = 883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV). RESULTS: On the test data, DL produced the AUC of 0.85 (0.80-0.89), XGBoost produced 0.88 (0.86-0.89) and RF produced 0.85 (0.83-0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively. DISCUSSION: This study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders.

Disease trajectories in behavioural variant frontotemporal dementia, primary psychiatric and other neurodegenerative disorders presenting with behavioural change.

Behavioural variant frontotemporal dementia (bvFTD) is characterized by behavioural and social cognitive disturbances, while various psychiatric and neurodegenerative disorders may have similar clinical symptoms. Since neurodegenerative disorders are eventually progressive, whereas primary psychiatric disorders are not, this study aimed to investigate whether the change in clinical symptoms over time differed between groups and which biomarkers predicted rate of decline. Disease trajectories (median follow-up = 3 years) of frontal and stereotyped behaviour, general and frontal cognitive functioning, and social cognition were examined in bvFTD (n = 34), other neurodegenerative (n = 28) and primary psychiatric disorders (n = 43), all presenting with late-onset frontal lobe syndrome (45-75 years), using linear mixed models. To gain more insight in underlying pathological processes driving disease progression, we studied the association of baseline cerebrospinal fluid (CSF) (neurofilament light (NfL) and YKL-40 levels, phosphotau181 to total tau ratio) and neuroimaging markers with disease trajectories. Frontal behavioural symptoms (e.g., disinhibition, apathy) worsened over time in bvFTD, whereas they improved in psychiatric disorders and remained stable in other neurodegenerative disorders. General and frontal cognitive decline was observed in bvFTD and other neurodegenerative disorders, but not in psychiatric disorders. None of the groups showed change in stereotypy and social cognition. For all diagnostic groups, higher CSF NfL levels were associated with faster frontal cognitive decline. A modest association was observed between caudate volume and stereotyped behaviour. Tracking frontal behavioural symptoms and cognition has potential to distinguish bvFTD from other disorders. CSF NfL levels seem to be associated with decline in frontal cognitive functioning.

Gray matter network disruptions and amyloid beta in cognitively normal adults.

Gray matter networks are disrupted in Alzheimer's disease (AD). It is unclear when these disruptions start during the development of AD. Amyloid beta 1-42 (Aß42) is among the earliest changes in AD. We studied, in cognitively healthy adults, the relationship between Aß42 levels in cerebrospinal fluid (CSF) and single-subject cortical gray matter network measures. Single-subject gray matter networks were extracted from structural magnetic resonance imaging scans in a sample of cognitively healthy adults (N = 185; age range 39-79, mini-mental state examination >25, N = 12 showed abnormal Aß42 < 550 pg/mL). Degree, clustering coefficient, and path length were computed at whole brain level and for 90 anatomical areas. Associations between continuous Aß42 CSF levels and single-subject cortical gray matter network measures were tested. Smoothing splines were used to determine whether a linear or nonlinear relationship gave a better fit to the data. Lower Aß42 CSF levels were linearly associated at whole brain level with lower connectivity density, and nonlinearly with lower clustering values and higher path length values, which is indicative of a less-efficient network organization. These relationships were specific to medial temporal areas, precuneus, and the middle frontal gyrus (all p < 0.05). These results suggest that mostly within the normal spectrum of amyloid, lower Aß42 levels can be related to gray matter networks disruptions.