Predictor Of Alzheimer Research Articles

Amyloid-β and Phosphorylated Tau are the Key Biomarkers and Predictors of Alzheimer's Disease.

Alzheimer's disease (AD) is a age-related neurodegenerative disease and is a major public health concern both in Texas, US and Worldwide. This neurodegenerative disease is mainly characterized by amyloid-beta (Aβ) and phosphorylated Tau (p-Tau) accumulation in the brains of patients with AD and increasing evidence suggests that these are key biomarkers in AD. Both Aβ and p-tau can be detected through various imaging techniques (such as positron emission tomography, PET) and cerebrospinal fluid (CSF) analysis. The presence of these biomarkers in individuals, who are asymptomatic or have mild cognitive impairment can indicate an increased risk of developing AD in the future. Furthermore, the combination of Aβ and p-tau biomarkers is often used for more accurate diagnosis and prediction of AD progression. Along with AD being a neurodegenerative disease, it is associated with other chronic conditions such as cardiovascular disease, obesity, depression, and diabetes because studies have shown that these comorbid conditions make people more vulnerable to AD. In the first part of this review, we discuss that biofluid-based biomarkers such as Aβ, p-Tau in cerebrospinal fluid (CSF) and Aβ & p-Tau in plasma could be used as an alternative sensitive technique to diagnose AD. In the second part, we discuss the underlying molecular mechanisms of chronic conditions linked with AD and how they affect the patients in clinical care.

Comparing Symmetric Dimethylarginine and Amyloid-β42 as Predictors of Alzheimer's Disease Development.

Physicians may soon be able to diagnose Alzheimer's disease (AD) in its early stages using fluid biomarkers like amyloid. However, it is acknowledged that additional biomarkers need to be characterized which would facilitate earlier monitoring of AD pathogenesis. To determine if a potential novel inflammation biomarker for AD, symmetric dimethylarginine, has utility as a baseline serum biomarker for discriminating prodromal AD from cognitively unimpaired controls in comparison to cerebrospinal fluid amyloid-β42 (Aβ42). Data including demographics, magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography scans, Mini-Mental State Examination and Functional Activities Questionnaire scores, and biomarker concentrations were obtained from the Alzheimer's Disease Neuroimaging Initiative for a total of 146 prodromal AD participants and 108 cognitively unimpaired controls. Aβ42 (p = 0.65) and symmetric dimethylarginine (p = 0.45) were unable to predict age-matched cognitively unimpaired controls and prodromal AD participants. Aβ42 was negatively associated with regional brain atrophy and hypometabolism as well as cognitive and functional decline in cognitively unimpaired control participants (p < 0.05) that generally decreased in time. There were no significant associations between Aβ42 and symmetric dimethylarginine with imaging or neurocognitive biomarkers in prodromal AD patients. Correlations were smaller between Aβ42 and neuropathological biomarkers over time and were absent in prodromal AD participants, suggesting a plateau effect dependent on age and disease stage. Evidence supporting symmetric dimethylarginine as a novel biomarker for AD as a single measurement was not found.

Risk of Mild Behavioral Impairment: the role of gender and APOE allele carrier status

AbstractBackgroundGender differences in dementia and dementia‐related neuropsychiatric symptoms are well described. Similarly, the Apolipoprotein E (APOE) ε4 allele is a well‐known predictor of Alzheimer’s disease. However, their impact on the clinical manifestation of Mild Behavioral Impairment (MBI) remains unclear. Using data from the Australian population‐based PATH Through Life Study we explored the associations between gender and APOE ε4 carrier status with MBI. We hypothesized that MBI likelihood would be greater in males and ε4 carriers.Method1316 dementia‐free participants (48% female; aged 72‐79) were included. Gender was self‐reported (female/male). Participants were classified as APOE ε4+ if they carried at least one ε4 allele (APOE ε4/ε4, ε2/ε4, ε3/ε4). MBI was approximated using a previously published transformation algorithm, which utilizes items from the Neuropsychiatric Inventory assessed at a single study visit. Binomial logistic regression was used to examine the role of gender and APOE ε4 carrier status, and their interaction, on predicting MBI status, while controlling for self‐reported years of education.ResultOf the 1316 participants, 339 (25.8%) were APOE ε4+ and 445 (34%) had MBI symptoms. A higher proportion of APOE ε4+ carriers (χ2 (1) = 5.99, p = .014) and men (χ2 (1) = 4.59, p = .032) were in the MBI group compared to the non‐MBI group. Binomial logistic regression showed APOE ε4 carrier status (OR = 1.58, 95% CI: 1.063‐2.344) and male gender (OR = 1.45, 95% CI: 1.093‐1.925) were associated with a greater likelihood of MBI. Male gender was also associated with a 2‐fold greater likelihood of having symptoms of the Decreased Motivation (OR = 2.08, 95% CI: 1.13‐3.86) and Impulse Dyscontrol (OR = 2.16, 95% CI: 1.54‐3.03) domains. No interaction effects were found between gender and APOE ε4 carrier status for MBI or any of its domains.ConclusionThe current study found that in dementia‐free older adults both male gender and APOE ε4+ status increased the risk of having MBI. However, no cumulative/interaction effect between gender and APOE ε4 carrier status was found, suggesting that being both male and APOE ε4+ does not further increase the risk of MBI. These results provide novel and valuable insight into the connection between gender, APOE ε4 carrier status and MBI.

Predictive factors for Alzheimer's disease progression: a comprehensive retrospective analysis of 3,553 cases with 211 months follow-up.

There is conflicting data regarding the predictors of Alzheimer's Disease (AD), the most common form of dementia. The main objective of the study is to evaluate potential predictors of AD progression using a comprehensive follow-up dataset that includes functional/cognitive assessments, clinical and neuropsychiatric evaluations, and neuroimaging biomarkers such as hippocampal atrophy or white matter intensities (WMIs). A total of 161 AD cases were recruited from a dementia database consisting of individuals who consulted the Dementia Outpatient Clinic of the Neurology Department at Mersin University Medical Faculty between 2000 and 2022, under the supervision of the same senior author have at least 3 full evaluation follow-up visit including functional, clinical, biochemical, neuropsychological, and radiological screening. Data were exported and analyzed by experts accordingly. Mean follow-up duration of study sample was 71.66 ± 41.98, min 15 to max 211 months. The results showed a fast and slow progressive subgroup of our AD cases with a high sensitivity (Entropy = 0.836), with a close relationship with several cofactors and the level of disability upon admittance. Hippocampal atrophy and WMIs grading via Fazekas were found to be underestimated predictors of AD progression, and functional capacity upon admittance was also among the main stakeholders. The study highlights the importance of evaluating multiple potential predictors for AD progression, including functional capacity upon admittance, hippocampal atrophy, and WMIs grading via Fazekas. Our findings provide insight into the complexity of AD progression and may contribute to the development of effective strategies for managing and treating AD.

Baseline Differences in Driving Frequency as a Predictor of Cognitive Decline and Alzheimer's Disease.

To extend prior research by examining daily driving frequency as a predictor of cognitive decline and later diagnosis of Alzheimer's disease. 1,426 older adults completed batteries of questionnaires and neuropsychological tests at baseline and yearly follow-ups (M = 6.8, SD = 4.9). Linear mixed effects models were estimated to examine whether daily driving frequency at baseline was predictive of cognitive decline while accounting for IADLs, mobility, depression, and demographics. Cox regression was used to examine driving frequency as a predictor of Alzheimer's disease diagnosis. Less daily driving frequency was associated with greater decline in all cognitive domains over time except for working memory. Although driving frequency was associated with these changes in cognition, it did not uniquely predict the development of Alzheimer's disease when accounting for other factors (eg, other IADLs). Our findings extend prior research linking driving cessation to greater levels of cognitive decline. Future work might benefit from examining the utility of driving habits (especially changes in driving) as measures of everyday functioning in older adult evaluations.

Characteristics and Predictors of Alzheimer's Disease Resilience Phenotype.

Alzheimer's disease (AD) is characterized by cognitive impairment in the presence of cerebral amyloid plaques and neurofibrillary tangles. Less is known about the characteristics and predictors of resilience to cognitive impairment in the presence of neuropathological evidence of AD, the focus of this study. Of 3170 adults age ≥65 years in the National Alzheimer's Coordinating Center (NACC) brain autopsy cohort, 1373 had evidence of CERAD level moderate to frequent neuritic plaque density and Braak stage V-VI neurofibrillary tangles. Resilience was defined by CDR-SOB and CDR-Global scores of 0-2.5 and 0-0.5, respectively, and non-resilience, CDR-SOB and CDR-Global scores >2.5 and >0.5, respectively. Multivariable logistic regression models were used to examine the independent associations of patient characteristics with resilience. There were 62 participants (4.8%) with resilience. Those with resilience were older (mean age, 88.3 vs. 82.4 years), more likely to be women (61.3% vs. 47.3%) and had a lower prevalence of the APOE-e4 carrier (41.9% vs. 56.2%). They also had a higher prevalence of hypertension, heart failure, atrial fibrillation, diuretic use, beta-blocker use, and APOE-e2 carrier status. Greater age at death, diuretic use, and APOE-e2 were the only characteristics independently associated with higher odds of the AD resilience phenotype (adjusted OR, 1.09; 95% CI, 1.05-1.13; p < 0.01; 2.00 (1.04-3.87), p = 0.04, 2.71 (1.31-5.64), p < 0.01, respectively). The phenotype of resilience to cognitive impairment is uncommon in older adults who have neuropathological evidence of AD.

Utility of Environmental Complexity as a Predictor of Alzheimer’s Disease Diagnosis: A Big-Data Machine Learning Approach

BackgroundRural-urban differences and spatial navigation deficits have received much attention in Alzheimer’s Disease research. While individual environmental and neighborhood factors have been independently investigated, their integrative, multifactorial effects on Alzheimer’s diagnosis have not. Here we explore this “environmental complexity” for predictive power in classifying Alzheimer’s from cognitively-normal status.MethodsWe utilized data from the National Alzheimer’s Coordinating Center (NACC) uniform data set containing annual visits since 2005 and selected individuals with multiple visits and who remained in their zipcode (N = 22,553). We georeferenced each subject with 3-digit zipcodes of their residences since entering the program. We calculated environmental complexity measures using geospatial tools from street networks and landmarks for spatial navigation in subjects’ zipcode zones. Zipcode zones were grouped into two cognitive classes (Cognitively-Normal and Alzheimer’s-inclined) based on the ratios of AD and dementia subjects to all subjects in an individual zipcode zone. We randomly selected 80% of the data to train a neural network classifier model on environmental complexity measures to predict the cognitive class for each zone, controlling for salient demographic variables. The remaining 20% served as the test set for performance evaluation.ResultsOur proposed model reached excellent classification ability on the testing data: 83.87% accuracy, 95.23% precision, 83.33% recall, and 0.8889 F1-score (F1-score=1 for perfect prediction). The most salient features of “Alzheimer’s-inclined” zipcode zones included longer street-length average, higher circuity, and slightly fewer points of interest. Most “cognitively-normal” zipcode zones appeared in or near urban areas with high environmental complexity measures.ConclusionEnvironmental complexity, reflected in frequency and density of street networks and landmarks features, predicted with high precision the cognitive status of 3-digit zipcode zones based on the etiologic diagnoses and observed cognitive impairment of NACC subjects residing in these zones. The zipcode zones vary widely in size (1.6 km2 to 35,241 km2), and large zipcode zones suffer high spatial heterogeneity. Other proven AD risk factors, such as PM2.5, disperse across zones, and so do individual’s activities, leading to spatial uncertainty. Nevertheless, the model classifies diagnosis well, establishing the need for prospective experiments to quantify effects of environmental complexity on Alzheimer’s development.

Predictors of Alzheimer’s disease risk in women with bilateral oophorectomy from the UK Biobank

AbstractBackgroundTwo‐thirds of individuals with Alzheimer’s disease (AD) are women and at age 45, the lifetime risk for AD is twice as high in women compared to men (Alzheimer’s Association, 2019). Early life events affecting 17β‐estradiol (E2) may be a mechanism behind this sex difference. Bilateral oophorectomy (BO) predicts cognitive decline, and neurodegeneration, and increased risk of AD in later life—adverse outcomes that are mitigated with E2 therapy (Gervais et al., 2020; Kantarci et al., 2018; Rocca et al., 2007; Zeydan et al., 2019). Our aim was to investigate compounding risk factors for AD in women with BO using UK Biobank data.MethodWe studied women aged 60 or older who had BO prior to age 49 with an AD diagnosis (n = 53) and without an AD diagnosis (n = 5418) from the UK Biobank (Sudlow et al. 2015). Data were analyzed using Firth’s bias‐reduced logistic regression in R 3.6.1 (R Core Team, 2019).ResultParticipants were on average 63.7 years old and 43.4 years old at BO. Women with BO who developed AD: (a) were significantly older, (b) had fewer years of education, (c) had an earlier age at BO, (d) less frequently used any form of hormone therapy (HT), and (e) were more frequently apolipoprotein E4 (APOE4) carriers. As age increased, AD risk increased by 25%; it deceased by 10% with greater years of education. Women with BO and an APOE4 allele were 5.2 times as likely to develop AD than those without an APOE4 allele. Finally, ever using any form of HT decreased AD risk by 54%.ConclusionThis research fills a gap in understanding predictors of AD in a high‐risk group of women with early E2 loss. The heightened AD risk for women with BO and APOE4 is of note, as prior work suggests women with APOE4 may benefit less from HT (MacLusky, 2004). Further, the reduction in AD risk with any HT provides added support for HT in mitigating cognitive decline. Although details on HT formulation were unavailable, the specific use of E2‐based therapy may further decrease AD risk (Sherwin &amp; Henry, 2008).

Association of APOE-Independent Alzheimer Disease Polygenic Risk Score With Brain Amyloid Deposition in Asymptomatic Older Adults.

Background and ObjectivesBrain amyloid deposition, a major risk factor for Alzheimer disease (AD), is currently estimated by measuring CSF or plasma amyloid peptide levels or by PET imaging. Assessing genetic risks relating to amyloid deposition before any accumulation has occurred would allow for earlier intervention in persons at increased risk for developing AD. Previous work linking amyloid burden and genetic risk relied almost exclusively on APOE, a major AD genetic risk factor. Here, we ask whether a polygenic risk score (PRS) that incorporates an optimized list of common variants linked to AD and excludes APOE is associated with brain amyloid load in cognitively unimpaired older adults.MethodsWe included 291 asymptomatic older participants from the INveStIGation of AlzHeimer's PredicTors (INSIGHT pre-AD) cohort who underwent amyloid imaging, including 83 amyloid-positive (+) participants. We used an Alzheimer's (A) PRS composed of 33 AD risk variants excluding APOE and selected the 17 variants that showed the strongest association with amyloid positivity to define an optimized (oA) PRS. Participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study (228 participants, 90 amyloid [+]) were tested as a validation cohort. Finally, 2,300 patients with AD and 6,994 controls from the European Alzheimer's Disease Initiative (EADI) were evaluated.ResultsA-PRS was not significantly associated with amyloid burden in the INSIGHT or ADNI cohorts with or without correction for the APOE genotype. However, oA-PRS was significantly associated with amyloid status independently of APOE adjustment (INSIGHT odds ratio [OR]: 5.26 [1.71–16.88]; ADNI OR: 3.38 [1.02–11.63]). Of interest, oA-PRS accurately discriminated amyloid (+) and (−) APOE ε4 carriers (INSIGHT OR: 181.6 [7.53–10,674.6]; ADNI OR: 44.94 [3.03–1,277]). A-PRS and oA-PRS showed a significant association with disease status in the EADI cohort (OR: 1.68 [1.53–1.85] and 2.06 [1.73–2.45], respectively). Genes assigned to oA-PRS variants were enriched in ontologies related to β-amyloid metabolism and deposition.DiscussionPRSs relying on AD genetic risk factors excluding APOE may improve risk prediction for brain amyloid, allowing stratification of cognitively unimpaired individuals at risk of AD independent of their APOE status.

316 Frontal-cerebellar EEG source localization and functional connectivity as predictors of Alzheimer’s disease-related cognitive decline

OBJECTIVES/GOALS: Novel EEG source localization and functional connectivity will assess frontal and cerebellar activity as predictors of subsequent memory and executive functioning (EF) decline in healthy, asymptomatic older adults who carry the Apolipoprotein-E ε4 allele (ε4+), which conveys up to 12x increased risk for Alzheimers disease (AD). METHODS/STUDY POPULATION: Healthy, cognitively intact ε4+ older adults (n = 23; ages 65-89) completed neuropsychological testing (focus on memory and EF) and EEG at Time 1, returning an average of one year later for neuropsychological retesting. EEG data during successful stop-signal inhibitory control trials will be used for advanced source localization and functional connectivity, with a focus on frontal and cerebellar regions of interest (ROIs). Source analyses will focus on the N200 time window (~200-350ms) to assess conflict processing and P300 (~300-550ms) for performance evaluation. Connectivity analyses are frequency-based, and will focus on theta band connectivity to assess conflict processing and delta to assess performance evaluation. RESULTS/ANTICIPATED RESULTS: Using hierarchical linear regression models, the magnitude of source activation within ROIs and connectivity metrics between ROIs will be used to predict residualized change in memory and executive function metrics between Time 1 and Time 2. We anticipate that 1) greater, compensatory activation in frontal ROIs during the N200 window, and 2) less cerebellar activation during P300, will predict memory and executive decline over the retest interval. Decline will also be predicted by 3) greater inter-hemispheric frontal connectivity in the theta band (conflict processing) and 4) less frontal-cerebellar delta connectivity (performance evaluation). DISCUSSION/SIGNIFICANCE: At most, ~50% of ε4 carriers will develop AD. Thus, identifying which carriers will decline is crucial to enabling successful, early intervention. Cerebellar dysfunction and impaired connectivity may be among the earliest indicators of incipient AD. Cutting-edge cerebellar EEG may enable an accessible option for early discernment of AD risk.

Neurofilament light as a biomarker of axonal degeneration in patients with mild cognitive impairment and Alzheimer's disease.

Cerebrospinal fluid neurofilament light and plasma neurofilament light concentrations are elevated in patients with mild cognitive impairment and Alzheimer's disease. We investigated the clinical relevance of increased neurofilament light concentrations in mild cognitive impairment and Alzheimer's disease patients. In this study, 244 subjects were divided into cognitively normal control (n = 67), stable mild cognitive impairment (n = 52), progressive mild cognitive impairment (n = 68), and Alzheimer's disease (n = 57). Linear regression examined the relationships between neurofilament light levels in cerebrospinal fluid or plasma and the diagnostic group. The relationships between neurofilament light and other biomarkers were assessed by Spearman correlation. Linear mixed-effects models were used to test cerebrospinal fluid and plasma neurofilament light as predictors of Alzheimer's disease characteristics, including cognition, cortical glucose metabolism, and brain structure. Cerebrospinal fluid and plasma neurofilament light levels were significantly elevated in Alzheimer's disease. Still, the correlations between neurofilament light and other cerebrospinal fluid biomarkers within the diagnostic groups were often not statistically significant. In addition, the diagnostic accuracy of cerebrospinal fluid and plasma neurofilament light for progressive mild cognitive impairment and Alzheimer's disease was almost the same as that of cerebrospinal fluid total tau (T-tau). It is phosphorylated tau (P-tau) and high cerebrospinal fluid. Neurofilament light predicted conversion from mild cognitive impairment to Alzheimer's disease. A high neurofilament light is related to poor cognition, low cerebral metabolism, hippocampal atrophy, and ventricular enlargement caused by Alzheimer's disease. Our work further identifies cerebrospinal fluid neurofilament light and plasma neurofilament light as biomarkers of axonal degeneration in patients with mild cognitive impairment and Alzheimer's disease.

Increased β-site APP cleaving enzyme 1-mediated insulin receptor cleavage in type 2 diabetes mellitus with cognitive impairment.

Patients with type 2 diabetes mellitus (T2DM) are at a high risk of cognitive impairment, with insulin resistance playing a pivotal role. β-site amyloid precursor protein cleaving enzyme 1 (BACE1) is considered a predictor of Alzheimer's disease. However, the potential roles of BACE1 in insulin resistance and the risk of cognitive impairment in T2DM remain unclear. We measured plasma BACE1 levels, BACE1 cleavage activities for Swedish mutant amyloid precursor protein (APPsw) and insulin receptor β subunit (INSR-β), and soluble INSR (sINSR) levels in a clinical cohort study. T2DM patients with or without cognitive impairment exhibited elevated plasma BACE1 levels and BACE1 enzymatic activities for APPsw and INSR-β, and sINSR levels. Moreover, the glycemic status correlated with elevated BACE1 levels and BACE1-mediated INSR cleavage, which was associated with insulin resistance. The elevated BACE1 levels in T2DM may contribute to increasing the cognitive impairment risk through both amyloidogenesis and insulin resistance.

Development of an ultrasensitive multiplex assay for simultaneous detection of Aβ1‐42, Aβ1‐40, GFAP and NF‐L in blood

AbstractBackgroundPrevious work (1) has described plasma amyloid, GFAP and NF‐L as predictors of Alzheimer’s pathology. Here we build on the Amyblood 1‐42/1‐40 Simoa assay (1,2) where GFAP and NF‐L, as indicators of astrogliosis and neurodegeneration, further added to the prediction for Aβ PET imaging or diagnosis. We report a Simoa multiplex assay that simultaneously measures Aβ1‐42, Aβ1‐40, GFAP and NF‐L in blood.MethodsA 4‐plex immunoassay was designed using Simoa technology. A monoclonal capture antibody specific for each analyte was attached to one of four different fluorescent dye‐encoded beads. Antibodies against Aβ1‐42 and Aβ1‐40 were from ADx (clones 21F12 and 2G3 as capture; 3D6 as detector), NF‐L and GFAP antibodies were as supplied in Quanterix commercial kits. The assay was further evaluated for its analytical performance, including analyte detectability in commercially‐sourced human plasma (n=20) and CSF (n=10) from healthy controls, and for discrimination between AD patient and control plasma (each n=10) from the Alzheimer Center Amsterdam.ResultsAssay calibration ranges were 0.041‐30pg/mL (Aβ1‐42), 0.016‐12pg/mL (Aβ1‐40), 6.86‐5000pg/mL (GFAP), and 0.686‐500pg/mL (NF‐L). Lower Limits of detection were 0.148pg/mL (Aβ1‐42), 0.084pg/mL (Aβ1‐40), 1.66pg/mL (GFAP), 0.157pg/mL (NF‐light). Limits of quantification for assay prototype were 0.381pg/mL (Aβ1‐42), 0.125pg/mL (Aβ1‐40), 4.99pg/mL (GFAP), 0.493pg/mL (NF‐light). In parallelism studies, mean recovery of serially diluted endogenous plasma and CSF (each n=4) was within 80‐120%. Grand mean recovery of expected spike concentration was within 70‐130% (n=4). The assay has 100% detectability for all four analytes in both plasma and CSF samples. NF‐L and GFAP concentrations increased in AD samples (respectively p&lt;0.05 and 0.01) while the Aβ 42/40 ratio decreased (p&lt;0.05) in AD samples versus healthy donors.ConclusionsThis multiplex Simoa assay accurately and specifically measure four biomarkers simultaneously in plasma and CSF, providing a new tool to quantify Aβ1‐42, Aβ1‐40, GFAP and NF‐L. Ongoing studies using a larger cohort of clinical samples will determine the potential clinical utility of this assay.

Cognitive Functions as Predictors of Alzheimer's Disease Biomarker Status in the European Prevention of Alzheimer's Dementia Cohort.

Alterations in Alzheimer's disease (AD) biomarkers have been observed decades before the onset of dementia. Cognitive dysfunction, while central to the clinical diagnosis of AD, has long been considered as a late-stage phenomenon. This assumption is currently challenged and signals on some cognitive tests are now being observed within the preclinical stage. As part of the European Prevention of Alzheimer's Dementia (EPAD) project, a battery of cognitive tests has been proposed (the EPAD Neuropsychological Examination, ENE) which is designed to detect cognitive changes in persons without clinical signs of AD but who are at high risk. Analysis of results from the 361 participants with complete measures and without dementia recruited into the EPAD Longitudinal Cohort Study showed that the majority have elevated biomarker levels, with significant associations between an episodic verbal memory task and tau, while amyloid-β (Aβ) was associated with a central executive task. These preliminary findings suggest that profiles of cognitive performance may be specific to a given biomarker, with a primarily hippocampal task being associated with higher levels of tau and a frontal executive task being associated with higher levels of Aβ. While previous research has focused on the relationship between cognition and levels of Aβ, our findings suggest that p-tau may potentially be a more significant correlate.

In vivo staging of regional amyloid deposition predicts functional conversion in the preclinical and prodromal phases of Alzheimer's disease

We tested the usefulness of a regional amyloid staging based on amyloid sensitive positron emission tomography to predict conversion to cognitive impairment and dementia in preclinical and prodromal Alzheimer's disease (AD). We analyzed 884 cases, including normal controls, and people with subjective cognitive decline or mild cognitive impairment (MCI), from the Alzheimer's Disease Neuroimaging Initiative with a maximum follow-up of 6 years and 318 cases with subjective memory complaints with a maximum follow-up time of three years from the INveStIGation of AlzHeimer's PredicTors cohort (INSIGHT-preAD study). Cox regression showed a significant association of regional amyloid stages with time to conversion from a cognitively normal to an MCI, and from an MCI to a dementia status. The most advanced amyloid stages identified very-high-risk groups of conversion. All results were robustly replicated across the independent samples. These findings indicate the usefulness of regional amyloid staging for identifying preclinical and prodromal AD cases at very high risk of conversion for future amyloid targeted trials.

Plasma tau correlates with basal forebrain atrophy rates in people at risk for Alzheimer disease.

To investigate whether baseline concentrations of plasma total tau (t-tau) and neurofilament light (NfL) chain proteins are associated with annual percent change (APC) of the basal forebrain cholinergic system (BFCS) in cognitively intact older adults at risk for Alzheimer disease (AD). This was a large-scale study of 276 cognitively intact older adults from the monocentric INSIGHT-preAD (Investigation of Alzheimer's Predictors in Subjective Memory Complainers) cohort. Participants underwent baseline assessment of plasma t-tau and NfL concentrations as well as baseline and 24-month follow-up MRI scans. Linear models with and without influential observations (calculated using the Cook distance) were carried out to investigate the effect of plasma NfL and t-tau concentrations, and their interaction effect with β-amyloid status and APOE genotype, on the APC of the whole BFCS and its anterior (Ch1/2) and posterior (Ch4) subdivisions separately. Higher plasma t-tau concentrations at baseline were associated with higher BFCS rate of atrophy (model without influencers: n = 251, F value = 4.6815; p value = 0.031). Subregional analyses showed similar results for both the APC of the Ch1/2 (model without influencers: n = 256, F value = 3.9535, p corrected = 0.047) and Ch4 BFCS sectors (model without influencers: n = 253, F value = 4.9090, p corrected = 0.047). Baseline NfL, β-amyloid load, and APOE ε4 carrier status did not affect APC of the BFCS. Increased concentrations of baseline plasma t-tau may predict in vivo structural BFCS atrophy progression in older adults at risk for AD, independently of β-amyloid status and APOE genotype.

Multi-omics signature of brain amyloid deposition in asymptomatic individuals at-risk for Alzheimer's disease: The INSIGHT-preAD study.

BackgroundOne of the biggest challenge in Alzheimer's disease (AD) is to identify pathways and markers of disease prediction easily accessible, for prevention and treatment. Here we analysed blood samples from the INveStIGation of AlzHeimer's predicTors (INSIGHT-preAD) cohort of elderly asymptomatic individuals with and without brain amyloid load.MethodsWe performed blood RNAseq, and plasma metabolomics and lipidomics using liquid chromatography-mass spectrometry on 48 individuals amyloid positive and 48 amyloid negative (SUVr cut-off of 0·7918). The three data sets were analysed separately using differential gene expression based on negative binomial distribution, non-parametric (Wilcoxon) and parametric (correlation-adjusted Student't) tests. Data integration was conducted using sparse partial least squares-discriminant and principal component analyses. Bootstrap-selected top-ten features from the three data sets were tested for their discriminant power using Receiver Operating Characteristic curve. Longitudinal metabolomic analysis was carried out on a subset of 22 subjects.FindingsUnivariate analyses identified three medium chain fatty acids, 4-nitrophenol and a set of 64 transcripts enriched for inflammation and fatty acid metabolism differentially quantified in amyloid positive and negative subjects. Importantly, the amounts of the three medium chain fatty acids were correlated over time in a subset of 22 subjects (p < 0·05). Multi-omics integrative analyses showed that metabolites efficiently discriminated between subjects according to their amyloid status while lipids did not and transcripts showed trends. Finally, the ten top metabolites and transcripts represented the most discriminant omics features with 99·4% chance prediction for amyloid positivity.InterpretationThis study suggests a potential blood omics signature for prediction of amyloid positivity in asymptomatic at-risk subjects, allowing for a less invasive, more accessible, and less expensive risk assessment of AD as compared to PET studies or lumbar puncture.FundInstitut Hospitalo-Universitaire and Institut du Cerveau et de la Moelle Epiniere (IHU-A-ICM), French Ministry of Research, Fondation Alzheimer, Pfizer, and Avid.

LATENT CLASS ANALYSIS IDENTIFIES FUNCTIONAL DECLINE WITH AMSTERDAM IADL IN PRE-CLINICAL ALZHEIMER’S DISEASE

Introduction: Trials in Alzheimer's disease (AD) now include participants at the earliest stages to prevent further decline. However, the lack of tools sensitive to subtle functional changes in early-stage AD hinders the development of new therapies as it is difficult to prove their clinical relevance. Methods: We assessed functional changes over three years in 289 elderly memory complainers from the Investigation of Alzheimer's Predictors in subjective memory complainers cohort using the Am-sterdam Instrumental-Activities-of-Daily-Living questionnaire (A-IADL-Q). Results: No overall functional decline related to AD imaging markers was evidenced. However, five distinct classes of A-IADL-Q trajectories were identified. The largest class (212 [73.4%]) had stable A-IADL-Q scores over 3 years. A second group (23 [8.0%]) showed a persistent functional decline, higher amyloid load (P 5 .0005), and lower education (P 5 .0392). Discussion: The A-IADL-Q identified a subtle functional decline in asymptomatic at-risk AD individuals. This could have important implications in the field of early intervention in AD.

SEXUAL DIMORPHISM IN PLASMA BETA-SECRETASE 1 CONCENTRATIONS IN COGNITIVELY NORMAL INDIVIDUALS AT RISK FOR AD: CROSS-SECTIONAL AND LONGITUDINAL STUDIES

The development of effective disease-modifying treatments for early Alzheimer's disease (AD) and targeting β-site amyloid precursor protein cleaving enzyme 1 (BACE1)-targeted requires biomarker-drug co-development strategies, including the validation and qualification of accessible and non-invasive biological markers for different contexts of use. Cross-sectional and longitudinal studies demonstrated that plasma and cerebrospinal fluid (CSF) concentrations of BACE1 closely correlate with each other. We conducted both cross-sectional and longitudinal explorative studies in a cohort of individuals with subjective memory complaint (SMC), a condition at risk for AD, to investigate whether key biological factors such as sex, APOE ε4allele, and age affect plasma BACE1 concentrations. SMC individuals were recruited from the “INveStIGation of AlzHeimer's PredicTors in Subjective Memory Complainers” (INSIGHT-preAD) study, a university-based cohort which is part of the Alzheimer Precision Medicine Initiative (APMI) and its Cohort Program (APMI-CP). In the cross-sectional analysis, we found that baseline plasma BACE1 concentrations were highly significantly increased in females compared to males (p<0.001). Women showed a highly significantly increased plasma BACE1 concentrations compared to men, at all the three investigated time intervals (p<0.001). No difference regarding the longitudinal trajectories of plasma BACE1 concentrations was found between women and men. There was no significant effect of age and APOE ε4carrier status neither on overall BACE1 concentrations nor on BACE1 concentrations evolution. There was a highly significant decrease in plasma BACE1 concentrations in the whole sample of SMC individuals over time (p<0.001). We did not find any significant impact of two-way interactions between age and sex, age and APOE ε4 allele, sex and APOE ε4 allele on BACE1 plasma concentrations either at baseline or longitudinally. Thus, we demonstrate that the impact of a sexual-dimorphism on plasma BACE1 concentrations is irrespective of age and time. Evidence of the potential impact of a sexual dimorphism on the concentration and activity of BACE1 may be a relevant missing design component contributing to the failure of negative clinical BACE1 inhibitor therapy trial outcomes. Our results indicate that the impact of a sexual dimorphism on plasma BACE1 should be considered in further biomarker validation and qualification studies and in clinical BACE1 trials.

Low-Density Lipoprotein Particle Size Subfractions and Cerebral Amyloidosis.

Cerebral beta-amyloidosis (CA) is a condition in which amyloid-β (Aβ) proteins are deposited in the cerebral cortex and is a predictor of Alzheimer's disease (AD). The Aging Brain Study (ABS) investigated risk factors for CA in persons with diabetes and dyslipidemia. In the ABS, we identified that greater levels of LDL cholesterol and lower levels of HDL cholesterol were associated with increased CA. LDL particles comprise multiple species of varying size, density, and protein composition. For example, within a lipoprotein profile characteristic for persons with obesity and diabetic dyslipidemia, larger LDL particles have a greater ApoE to ApoB ratio, enhancing their binding affinity to LDL receptors. The goal of this study was to identify LDL particles that associate with CA in ABS. LDL particle size fractions were measured by ion mobility in plasma samples of 58 participants (40 women and 18 men). CA was assessed using Pittsburgh Compound B index-Positron Emission Tomography (PiB-PET) imaging. Among the LDL subfractions, greater plasma levels of large LDL particles were significantly associated with greater cerebral amyloidosis and lower hippocampal volumes independent of LDL cholesterol or triglyceride levels. Since Aβ is cleared by the LDL receptor family, such as lipoprotein-like receptor 1 (LRP1), one potential mechanism for our findings is competition between ApoE enriched larger LDL particles and brain-derived Aβ on hepatic Aβ clearance and degradation. We conclude that assessing larger LDL particles in persons with atherogenic dyslipidemia may provide a mechanistic biomarker for the extent of CA.