The clinical importance of suspected non-Alzheimer disease pathophysiology.

The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) - a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP.

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.

Local patterns of genetic sharing challenge the boundaries between neuropsychiatric and insulin resistance-related conditions.

The co-occurrence of insulin resistance (IR)-related metabolic conditions with neuropsychiatric disorders is a complex public health challenge. Evidence of the genetic links between these phenotypes is emerging, but little is currently known about the genomic regions and biological functions that are involved. To address this, we performed Local Analysis of [co]Variant Association (LAVA) using large-scale (N=9,725-933,970) genome-wide association studies (GWASs) results for three IR-related conditions (type 2 diabetes mellitus, obesity, and metabolic syndrome) and nine neuropsychiatric disorders. Subsequently, positional and expression quantitative trait locus (eQTL)-based gene mapping and downstream functional genomic analyses were performed on the significant loci. Patterns of negative and positive local genetic correlations (|rg|=0.21-1, pFDR<0.05) were identified at 109 unique genomic regions across all phenotype pairs. Local correlations emerged even in the absence of global genetic correlations between IR-related conditions and Alzheimer's disease, bipolar disorder, and Tourette's syndrome. Genes mapped to the correlated regions showed enrichment in biological pathways integral to immune-inflammatory function, vesicle trafficking, insulin signalling, oxygen transport, and lipid metabolism. Colocalisation analyses further prioritised 10 genetically correlated regions for likely harbouring shared causal variants, displaying high deleterious or regulatory potential. These variants were found within or in close proximity to genes, such as SLC39A8 and HLA-DRB1, that can be targeted by supplements and already known drugs, including omega-3/6 fatty acids, immunomodulatory, antihypertensive, and cholesterol-lowering drugs. Overall, our findings underscore the complex genetic landscape of IR-neuropsychiatric multimorbidity, advocating for an integrated disease model and offering novel insights for research and treatment strategies in this domain.

The association of glucose metabolism measures and diabetes status with Alzheimer's disease biomarkers of amyloid and tau: A systematic review and meta-analysis.

Conflicting evidence exists on the relationship between diabetes mellitus (DM) and Alzheimer's disease (AD) biomarkers. Therefore, we conducted a random-effects meta-analysis to evaluate the correlation of glucose metabolism measures (glycated hemoglobin, fasting blood glucose, insulin resistance indices) and DM status with AD biomarkers of amyloid-ß and tau measured by positron emission tomography or cerebrospinal fluid. We selected 37 studies from PubMed and Embase, including 11,694 individuals. More impaired glucose metabolism and DM status were associated with higher tau biomarkers (r=0.11[0.03-0.18], p=0.008; I2=68%), but were not associated with amyloid-ß biomarkers (r=-0.06[-0.13-0.01], p=0.08; I2=81%). Meta-regression revealed that glucose metabolism and DM were specifically associated with tau biomarkers in population settings (p=0.001). Furthermore, more impaired glucose metabolism and DM status were associated with lower amyloid-ß biomarkers in memory clinic settings (p=0.004), and in studies with a higher prevalence of dementia (p<0.001) or lower cognitive scores (p=0.04). These findings indicate that DM is associated with biomarkers of tau but not with amyloid-ß. This knowledge is valuable for improving dementia and DM diagnostics and treatment.

Contributions of Vascular Burden and Amyloid Abnormality to Cognitive Decline in Memory Clinic Patients.

Background: Alzheimer's disease pathology and vascular burden are highly prevalent and often co-occur in elderly. It remains unclear how both relate to cognitive decline. Objective: To investigate whether amyloid abnormality and vascular burden synergistically contribute to cognitive decline in a memory clinic population. Methods: We included 227 patients from Maastricht and Aachen memory clinics. Amyloid abnormality (A+) was defined by CSF Aß42 using data-driven cut-offs. Vascular burden (V+) was defined as having moderate to severe white matter hyperintensities, or any microbleeds, macrohemorrhage or infarcts on MRI. Longitudinal change in global cognition, memory, processing speed, executive functioning, and verbal fluency was analysed across the A-V-, A-V+, A+V-, A+V+ groups by linear mixed models. Additionally, individual MRI measures, vascular risk and vascular disease were used as V definitions. Results: At baseline, the A+V+ group scored worse on global cognition and verbal fluency compared to all other groups, and showed worse memory compared to A-V+ and A-V- groups. Over time (mean 2.7+ - 1.5 years), A+V+ and A+V- groups showed faster global cognition decline than A-V+ and A-V- groups. Only the A+V- group showed decline on memory and verbal fluency. The A-V+ group did not differ from the A-V- group. Individual MRI vascular measures only indicated an independent association of microbleeds with executive functioning decline. Findings were similar using other V definitions. Conclusions: Our study demonstrates that amyloid abnormality predicts cognitive decline independent from vascular burden in a memory clinic population. Vascular burden shows a minor contribution to cognitive decline in these patients. This has important prognostic implications.

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.

The link between cognition and somatic conditions related to insulin resistance in the UK Biobank study cohort: a systematic review.

Clinical and genomic studies have shown an overlap between neuropsychiatric disorders and insulin resistance (IR)-related somatic conditions, including obesity, type 2 diabetes, and cardiovascular diseases. Impaired cognition is often observed among neuropsychiatric disorders, where multiple cognitive domains may be affected. In this review, we aimed to summarise previous evidence on the relationship between IR-related diseases/traits and cognitive performance in the large UK Biobank study cohort. Electronic searches were conducted on PubMed, Scopus, and Web of Science until April 2022. Eighteen articles met the inclusion criteria and were qualitatively reviewed. Overall, there is substantial evidence for an association between IR-related cardio-metabolic diseases/traits and worse performance on various cognitive domains, which is largely independent of possible confoundings. The most consistent findings referred to IR-related associations with poorer verbal and numerical reasoning ability, as well as slower processing speed. The observed associations might be mediated by alterations in immune-inflammation, brain integrity/connectivity, and/or comorbid somatic or psychiatric diseases/traits. Our findings provide impetus for further research into the underlying neurobiology and possible new therapeutic targets.

Temporally ordered associations between type 2 diabetes and brain disorders - a Danish register-based cohort study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is linked with several neurodegenerative and psychiatric disorders, either as a comorbid condition or as a risk factor. We aimed to expand the evidence by examining associations with a broad range of brain disorders (psychiatric and neurological disorders, excluding late-onset neurodegenerative disorders), while also accounting for the temporal order of T2DM and these brain disorders. METHODS: In a population-based cohort-study of 1,883,198 Danish citizens, born 1955-1984 and followed until end of 2016, we estimated associations between T2DM and 16 brain disorders first diagnosed between childhood and mid-adulthood. We calculated odds ratios (OR) and hazard ratios (HR) with 95% confidence intervals (CI) in temporally ordered analyses (brain disorder diagnosis after T2DM and vice versa), adjusted for sex, age, follow-up, birth year, and parental factors. RESULTS: A total of 67,660 (3.6%) of the study population were identified as T2DM cases after age 30 and by a mean age of 45 years (SD of 8 years). T2DM was associated with most psychiatric disorders. Strongest associations were seen with other (i.e. non-anorectic) eating disorders (OR [95% CI]: 2.64 [2.36-2.94]) and schizophrenia spectrum disorder (2.73 [2.63-2.84]). Among neurological disorders especially inflammatory brain diseases (1.73 [1.57-1.91]) and epilepsy (1.67 [1.60-1.75]) were associated with T2DM. Most associations remained in both directions in the temporally ordered analyses. For most psychiatric disorders, associations were strongest in females. CONCLUSIONS: T2DM was associated with several psychiatric and neurological disorders, and most associations were consistently found for both temporal order of disorders. This suggests a shared etiology of T2DM and those brain disorders. This study can form the starting point for studies directed at further elucidating potential causal links between disorders and shared biological mechanisms.

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.

Effects of age, amyloid, sex, and APOE ε4 on the CSF proteome in normal cognition.

Introduction: It is important to understand which biological processes change with aging, and how such changes are associated with increased Alzheimer's disease (AD) risk. We studied how cerebrospinal fluid (CSF) proteomics changed with age and tested if associations depended on amyloid status, sex, and apolipoprotein E Ɛ4 genotype. Methods: We included 277 cognitively intact individuals aged 46 to 89 years from Alzheimer's Disease Neuroimaging Initiative, European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery, and Metabolic Syndrome in Men. In total, 1149 proteins were measured with liquid chromatography mass spectrometry with multiple reaction monitoring/Rules-Based Medicine, tandem mass tag mass spectrometry, and SOMAscan. We tested associations between age and protein levels in linear models and tested enrichment for Reactome pathways. Results: Levels of 252 proteins increased with age independently of amyloid status. These proteins were associated with immune and signaling processes. Levels of 21 proteins decreased with older age exclusively in amyloid abnormal participants and these were enriched for extracellular matrix organization. Discussion: We found amyloid-independent and -dependent CSF proteome changes with older age, perhaps representing physiological aging and early AD pathology.

Genome-Wide Association Study of Alzheimer's Disease Brain Imaging Biomarkers and Neuropsychological Phenotypes in the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Dataset.

Alzheimer's disease (AD) is the most frequent neurodegenerative disease with an increasing prevalence in industrialized, aging populations. AD susceptibility has an established genetic basis which has been the focus of a large number of genome-wide association studies (GWAS) published over the last decade. Most of these GWAS used dichotomized clinical diagnostic status, i.e., case vs. control classification, as outcome phenotypes, without the use of biomarkers. An alternative and potentially more powerful study design is afforded by using quantitative AD-related phenotypes as GWAS outcome traits, an analysis paradigm that we followed in this work. Specifically, we utilized genotype and phenotype data from n = 931 individuals collected under the auspices of the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study to perform a total of 19 separate GWAS analyses. As outcomes we used five magnetic resonance imaging (MRI) traits and seven cognitive performance traits. For the latter, longitudinal data from at least two timepoints were available in addition to cross-sectional assessments at baseline. Our GWAS analyses revealed several genome-wide significant associations for the neuropsychological performance measures, in particular those assayed longitudinally. Among the most noteworthy signals were associations in or near EHBP1 (EH domain binding protein 1; on chromosome 2p15) and CEP112 (centrosomal protein 112; 17q24.1) with delayed recall as well as SMOC2 (SPARC related modular calcium binding 2; 6p27) with immediate recall in a memory performance test. On the X chromosome, which is often excluded in other GWAS, we identified a genome-wide significant signal near IL1RAPL1 (interleukin 1 receptor accessory protein like 1; Xp21.3). While polygenic score (PGS) analyses showed the expected strong associations with SNPs highlighted in relevant previous GWAS on hippocampal volume and cognitive function, they did not show noteworthy associations with recent AD risk GWAS findings. In summary, our study highlights the power of using quantitative endophenotypes as outcome traits in AD-related GWAS analyses and nominates several new loci not previously implicated in cognitive decline.

The Role of Vascular Risk Factors in Biomarker-Based AT(N) Groups: A German-Dutch Memory Clinic Study.

BACKGROUND: The relation between vascular risk factors (VRFs) and Alzheimer's disease (AD) is important due to possible pathophysiological association. OBJECTIVE: To assess the prevalence of VRFs in biomarker-based AT(N) groups and the associations between VRFs, AD cerebrospinal fluid (CSF) biomarkers, brain magnetic resonance imaging (MRI), and cognition in clinical context. METHODS: We included patients from two memory clinics in University Hospital Aachen (Germany) and Maastricht University Medical Centre (The Netherlands). Subjects were older than 45 years and had available data on demographics, VRFs, CSF AD biomarkers, and MRI. We categorized individuals in normal AD biomarkers, non-AD change, and AD-continuum groups based on amyloid (A), tau (T), and neurodegeneration (N) status in CSF and MRI. Regression models were corrected for age, sex, and site. RESULTS: We included 838 participants (mean age 68.7, 53.2% male, mean MMSE 24.9). The most common VRFs were smoking (60.9%), hypertension (54.6%), and dyslipidemia (37.8%). Alcohol abuse and smoking were most frequent in the non-AD-change group, and coronary heart disease and carotid artery stenosis in the AD continuum group. Higher rates of depression were found in the normal AD biomarkers group. Parietal atrophy and cortical microbleeds were specific for the AD continuum group. Carotid artery stenosis was associated with pathological Aß42 and T-tau values, and diabetes and alcohol abuse were associated with worse medial temporal atrophy and atrial fibrillation, with worse cognition. CONCLUSION: VRFs are common in memory clinic patients, showing differences across the AT(N) biomarker groups. This is important for prevention and individualized treatment of dementia.

Cerebrospinal fluid tau levels are associated with abnormal neuronal plasticity markers in Alzheimer's disease.

BACKGROUND: Increased total tau (t-tau) in cerebrospinal fluid (CSF) is a key characteristic of Alzheimer's disease (AD) and is considered to result from neurodegeneration. T-tau levels, however, can be increased in very early disease stages, when neurodegeneration is limited, and can be normal in advanced disease stages. This suggests that t-tau levels may be driven by other mechanisms as well. Because tau pathophysiology is emerging as treatment target for AD, we aimed to clarify molecular processes associated with CSF t-tau levels. METHODS: We performed a proteomic, genomic, and imaging study in 1380 individuals with AD, in the preclinical, prodromal, and mild dementia stage, and 380 controls from the Alzheimer's Disease Neuroimaging Initiative and EMIF-AD Multimodality Biomarker Discovery study. RESULTS: We found that, relative to controls, AD individuals with increased t-tau had increased CSF concentrations of over 400 proteins enriched for neuronal plasticity processes. In contrast, AD individuals with normal t-tau had decreased levels of these plasticity proteins and showed increased concentrations of proteins indicative of blood-brain barrier and blood-CSF barrier dysfunction, relative to controls. The distinct proteomic profiles were already present in the preclinical AD stage and persisted in prodromal and dementia stages implying that they reflect disease traits rather than disease states. Dysregulated plasticity proteins were associated with SUZ12 and REST signaling, suggesting aberrant gene repression. GWAS analyses contrasting AD individuals with and without increased t-tau highlighted several genes involved in the regulation of gene expression. Targeted analyses of SNP rs9877502 in GMNC, associated with t-tau levels previously, correlated in individuals with AD with CSF concentrations of 591 plasticity associated proteins. The number of APOE-e4 alleles, however, was not associated with the concentration of plasticity related proteins. CONCLUSIONS: CSF t-tau levels in AD are associated with altered levels of proteins involved in neuronal plasticity and blood-brain and blood-CSF barrier dysfunction. Future trials may need to stratify on CSF t-tau status, as AD individuals with increased t-tau and normal t-tau are likely to respond differently to treatment, given their opposite CSF proteomic profiles.

Insulinopathies of the brain? Genetic overlap between somatic insulin-related and neuropsychiatric disorders.

The prevalence of somatic insulinopathies, like metabolic syndrome (MetS), obesity, and type 2 diabetes mellitus (T2DM), is higher in Alzheimer's disease (AD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD). Dysregulation of insulin signalling has been implicated in these neuropsychiatric disorders, and shared genetic factors might partly underlie this observed multimorbidity. We investigated the genetic overlap between AD, ASD, and OCD with MetS, obesity, and T2DM by estimating pairwise global genetic correlations using the summary statistics of the largest available genome-wide association studies for these phenotypes. Having tested these hypotheses, other potential brain "insulinopathies" were also explored by estimating the genetic relationship of six additional neuropsychiatric disorders with nine insulin-related diseases/traits. Stratified covariance analyses were then performed to investigate the contribution of insulin-related gene sets. Significant negative genetic correlations were found between OCD and MetS (rg = -0.315, p = 3.9 × 10-8), OCD and obesity (rg = -0.379, p = 3.4 × 10-5), and OCD and T2DM (rg = -0.172, p = 3 × 10-4). Significant genetic correlations with insulin-related phenotypes were also found for anorexia nervosa (AN), attention-deficit/hyperactivity disorder (ADHD), major depressive disorder, and schizophrenia (p < 6.17 × 10-4). Stratified analyses showed negative genetic covariances between AD, ASD, OCD, ADHD, AN, bipolar disorder, schizophrenia and somatic insulinopathies through gene sets related to insulin signalling and insulin receptor recycling, and positive genetic covariances between AN and T2DM, as well as ADHD and MetS through gene sets related to insulin processing/secretion (p < 2.06 × 10-4). Overall, our findings suggest the existence of two clusters of neuropsychiatric disorders, in which the genetics of insulin-related diseases/traits may exert divergent pleiotropic effects. These results represent a starting point for a new research line on "insulinopathies" of the brain.

Rare variants in IFFO1, DTNB, NLRC3 and SLC22A10 associate with Alzheimer's disease CSF profile of neuronal injury and inflammation.

Alzheimer's disease (AD) biomarkers represent several neurodegenerative processes, such as synaptic dysfunction, neuronal inflammation and injury, as well as amyloid pathology. We performed an exome-wide rare variant analysis of six AD biomarkers (ß-amyloid, total/phosphorylated tau, NfL, YKL-40, and Neurogranin) to discover genes associated with these markers. Genetic and biomarker information was available for 480 participants from two studies: EMIF-AD and ADNI. We applied a principal component (PC) analysis to derive biomarkers combinations, which represent statistically independent biological processes. We then tested whether rare variants in 9576 protein-coding genes associate with these PCs using a Meta-SKAT test. We also tested whether the PCs are intermediary to gene effects on AD symptoms with a SMUT test. One PC loaded on NfL and YKL-40, indicators of neuronal injury and inflammation. Four genes were associated with this PC: IFFO1, DTNB, NLRC3, and SLC22A10. Mediation tests suggest, that these genes also affect dementia symptoms via inflammation/injury. We also observed an association between a PC loading on Neurogranin, a marker for synaptic functioning, with GABBR2 and CASZ1, but no mediation effects. The results suggest that rare variants in IFFO1, DTNB, NLRC3, and SLC22A10 heighten susceptibility to neuronal injury and inflammation, potentially by altering cytoskeleton structure and immune activity disinhibition, resulting in an elevated dementia risk. GABBR2 and CASZ1 were associated with synaptic functioning, but mediation analyses suggest that the effect of these two genes on synaptic functioning is not consequential for AD development.

Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum.

IMPORTANCE: One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design. OBJECTIVE: To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria. EXPOSURES: Alzheimer disease biomarkers detected on PET or in CSF. MAIN OUTCOMES AND MEASURES: Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations. RESULTS: Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18). CONCLUSIONS AND RELEVANCE: This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.

Characteristics of subjective cognitive decline associated with amyloid positivity.

INTRODUCTION: The evidence for characteristics of persons with subjective cognitive decline (SCD) associated with amyloid positivity is limited. METHODS: In 1640 persons with SCD from 20 Amyloid Biomarker Study cohort, we investigated the associations of SCD-specific characteristics (informant confirmation, domain-specific complaints, concerns, feelings of worse performance) demographics, setting, apolipoprotein E gene (APOE) ε4 carriership, and neuropsychiatric symptoms with amyloid positivity. RESULTS: Between cohorts, amyloid positivity in 70-year-olds varied from 10% to 76%. Only older age, clinical setting, and APOE ε4 carriership showed univariate associations with increased amyloid positivity. After adjusting for these, lower education was also associated with increased amyloid positivity. Only within a research setting, informant-confirmed complaints, memory complaints, attention/concentration complaints, and no depressive symptoms were associated with increased amyloid positivity. Feelings of worse performance were associated with less amyloid positivity at younger ages and more at older ages. DISCUSSION: Next to age, setting, and APOE ε4 carriership, SCD-specific characteristics may facilitate the identification of amyloid-positive individuals.

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.