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 [Aβ]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

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 [Aβ]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

Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology

Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown. We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes. We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677). We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ 4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts. Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo

Deleterious ABCA7 mutations and transcript rescue mechanisms in early onset Alzheimer’s disease

Abstract: Premature termination codon (PTC) mutations in the ATP-Binding Cassette, Sub-Family A, Member 7 gene (ABCA7) have recently been identified as intermediate-to-high penetrant risk factor for late-onset Alzheimer's disease (LOAD). High variability, however, is observed in downstream ABCA7 mRNA and protein expression, disease penetrance, and onset age, indicative of unknown modifying factors. Here, we investigated the prevalence and disease penetrance of ABCA7 PTC mutations in a large early onset AD (EOAD)-control cohort, and examined the effect on transcript level with comprehensive third-generation long-read sequencing. We characterized the ABCA7 coding sequence with next-generation sequencing in 928 EOAD patients and 980 matched control individuals. With MetaSKAT rare variant association analysis, we observed a fivefold enrichment (p = 0.0004) of PTC mutations in EOAD patients (3%) versus controls (0.6%). Ten novel PTC mutations were only observed in patients, and PTC mutation carriers in general had an increased familial AD load. In addition, we observed nominal risk reducing trends for three common coding variants. Seven PTC mutations were further analyzed using targeted long-read cDNA sequencing on an Oxford Nanopore MinION platform. PTC-containing transcripts for each investigated PTC mutation were observed at varying proportion (5-41% of the total read count), implying incomplete nonsense-mediated mRNA decay (NMD). Furthermore, we distinguished and phased several previously unknown alternative splicing events (up to 30% of transcripts). In conjunction with PTC mutations, several of these novel ABCA7 isoforms have the potential to rescue deleterious PTC effects. In conclusion, ABCA7 PTC mutations play a substantial role in EOAD, warranting genetic screening of ABCA7 in genetically unexplained patients. Long-read cDNA sequencing revealed both varying degrees of NMD and transcript-modifying events, which may influence ABCA7 dosage, disease severity, and may create opportunities for therapeutic interventions in AD

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

INTRODUCTION: Machine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer’s Disease (AD). Here we set out to test the performance of metabolites in blood to categorise AD when compared to CSF biomarkers. METHODS: This study analysed 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

Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Funder: Funder: Fundación bancaria ‘La Caixa’ Number: LCF/PR/PR16/51110003 Funder: Grifols SA Number: LCF/PR/PR16/51110003 Funder: European Union/EFPIA Innovative Medicines Initiative Joint Number: 115975 Funder: JPco-fuND FP-829-029 Number: 733051061Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease

Multiancestry analysis of the HLA locus in Alzheimer’s and Parkinson’s diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues

Exploring Cognitive Frailty: Prevalence and Associations with Other Frailty Domains in Older People with Different Degrees of Cognitive Impairment

BACKGROUND: Cognitive frailty has long been defined as the co-occurrence of mild cognitive deficits and physical frailty. However, recently, a new approach to cognitive frailty has been proposed: cognitive frailty as a distinct construct. Nonetheless, the relationship between this relatively new construct of cognitive frailty and other frailty domains is unclear. OBJECTIVES: The aims of this study were to explore the prevalence of cognitive frailty in groups with different degrees of cognitive impairment, as well as to explore the associations between frailty domains, and if this varies with level of objective cognitive impairment. METHOD: Cross-sectional, secondary data from 3 research projects among community-dwelling people aged ≥60 years, with different degrees of objective cognitive impairment, were used: (1) a randomly selected sample (n = 353); (2) a sample at an increased risk of frailty (n = 95); and (3) a sample of memory clinic patients who scored 0.5 on the Clinical Dementia Rating scale - according to the "original" definition of cognitive frailty (n = 47). Multidimensional frailty was assessed with the Comprehensive Frailty Assessment Instrument - Plus and general cognitive functioning with the Montreal Cognitive Assessment. Descriptive statistics and linear regression were used to determine the prevalence of cognitive frailty and to explore the relationship between cognitive frailty and the other types of frailty in each sample. RESULTS: The prevalence of cognitive frailty increased along with the degree of objective cognitive impairment in the 3 samples (range 35.1-80.9%), while its co-occurrence with (one of) the other types of frailty was most frequent in the frail and community samples. Regarding its relationship with the other domains, cognitive frailty was positively associated with psychological frailty's subdomain mood disorder symptoms in all 3 samples (p ≤ 0.01), while there was no significant association with environmental frailty and social loneliness. The associations between cognitive frailty and the other types of frailty differed between the samples. CONCLUSION: Psychological and cognitive frailty are strongly associated, irrespective of the objective degree of cognitive impairment. In addition, it is shown that cognitive frailty can occur independently from the other frailty domains, including physical frailty, and therefore it can be seen as a distinct concept.status: publishe