Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

The extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of 'sporadic' late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease. We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer's Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset. Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants. These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD) differ in many respects. Here, we address the issue of possible differences in fibrillar amyloid pathology as measured by positron emission tomography (PET), which remains unresolved due to the lack of large-scale comparative studies. Three hundred ninety-nine cognitively impaired participants younger than 65 years of age from the multicenter Longitudinal Early-onset Alzheimer's Disease Study (LEADS) and 450 cognitively impaired participants older than 65 years from the Alzheimer's Disease Neuroimaging Initiative (ADNI) underwent clinical assessment, brain magnetic resonance imaging (MRI), and amyloid PET and were included in this study. We compared amyloid PET outcomes (positivity rate based on visual read and quantified tracer uptake expressed as Centiloids [CLs]) between the 2 cohorts and studied their association with age, sex, APOE genotype, and cognition. The amyloid positivity rate was higher in LEADS (78%, 95% confidence interval [CI] = 74-82) than in ADNI (71%, 95% CI = 67-75, p = 0.02). Lower Mini-Mental State Examination (MMSE) and APOE4 genotype increased the odds of amyloid positivity in both cohorts. Visually positive scans had higher CLs in LEADS (EOAD, mean = 95.3 ± 26.1) than in ADNI (LOAD, mean = 80.9 ± 36.8, p < 0.0001), predominantly in parietal cortex/precuneus, superior temporal, and frontal cortices. In amyloid-positive patients, (1) CLs were higher in female patients in both cohorts; (2) APOE4 carriership was associated with lower CLs in EOAD, which was not observed in LOAD; and (3) correlations between CLs and MMSE scores were significantly stronger in EOAD than in LOAD. Differences in the burden of amyloid pathology may contribute to differences in clinical and anatomic patterns in sporadic EOAD and LOAD, and have implications for optimizing therapeutic strategies in each group. ANN NEUROL 2025;98:236-248.

Young-onset and late-onset Alzheimer's disease has different clinical presentations with late-onset presenting most often with memory deficits while young-onset often presents with a non-amnestic syndrome. However, it is unknown whether there are differences in presentation and progression of neuropsychiatric symptoms in young- versus late-onset Alzheimer's disease. We aimed to investigate differences in the prevalence and severity of neuropsychiatric symptoms in patients with young- and late-onset Alzheimer's disease longitudinally with and without accounting for the effect of medication usage. Sex differences were also considered in these patient groups. We included 126 young-onset and 505 late-onset Alzheimer's disease patients from National Alzheimer's Coordinating Center-Uniform Data Set (NACC-UDS) and Alzheimer's Disease Neuroimaging Initiative (ADNI). We investigated the prevalence and severity of neuropsychiatric symptoms using the Neuropsychiatric Inventory-Questionnaire over 4 visits with 1-year intervals, using a linear mixed-effects model. The prevalence of depression was significantly higher in young-onset than late-onset Alzheimer's disease over a 4-year interval when antidepressant usage was included in our analyses. Our findings suggest that neuropsychiatric symptom profiles of young- and late-onset Alzheimer's disease differ cross-sectionally but also display significant differences in progression.

Genome Sequencing Set to Hunt for Alzheimer's Clues

SREBF2 POLYMORPHISMS AND EXPRESSION LEVELS CORRELATE WITH ALZHEIMER’S DISEASE NEUROPATHOLOGY

The Dominantly Inherited Alzheimer Network (DIAN) initially was funded by the National Institute on Aging (NIA) in 2008 and thus was able to adopt and incorporate the protocols developed by the Alzheimer's Disease Neuroimaging Initiative (ADNI) that had been established by the NIA in 2004. The use of ADNI protocols for DIAN neuroimaging studies and assays of biological fluids for Alzheimer disease (AD) biomarkers permitted examination of the hypothesis that autosomal dominant AD (ADAD), studied by DIAN, and "sporadic" late-onset AD (LOAD), studied by ADNI, shared the same pathobiological construct. In a collaborative effort, the longitudinal DIAN and ADNI databases were compared and the findings supported the conclusion that ADAD and LOAD share a similar pathophysiology. The importance of the DIAN study thus is amplified by its relevance to LOAD, as characterized by the "parent" ADNI program.

INTRODUCTIONThe genetic basis of sporadic early‐onset Alzheimer's disease (EOAD) remains largely unknown, prompting evaluation of late‐onset Alzheimer's disease (LOAD) polygenic risk in EOAD.METHODSA LOAD polygenic score (PGS) was calculated in the Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) and Alzheimer's Disease Neuroimaging Initiative (ADNI) study and tested for associations with AD risk, cognitive performance, and imaging and fluid biomarkers.RESULTSThough PGS was elevated in LOAD and EOAD, it was not a significant predictor of EOAD adjusting for APOE ε4 carrier status and was not associated with age of EOAD onset (p = 0.106) or with cognitive performance (p = 0.417). In LEADS, greater LOAD PGS was associated with differences in neuroimaging and fluid biomarkers, including elevated synaptosomal‐associated protein 25 (SNAP‐25) (p = 2.3 × 10−5).DISCUSSIONWhile LOAD polygenic risk contributed minimally to EOAD onset and cognitive dysfunction, PGS association with fluid biomarkers in LEADS suggests a role for LOAD polygenic risk in EOAD pathophysiology.HighlightsLOAD PGSs were elevated in both LOAD and EOAD compared to controls; however, LOAD PGS did not significantly predict EOAD risk, age at onset, or cognitive performance independent of APOE ε4 in the LEADS.Higher LOAD PGS was associated with lower amyloid PET Centiloids (less brain amyloid deposition) as well as lower CSF biomarker Aβ42 in LEADS (proxy marker suggesting higher brain amyloid deposition) in LEADS; these contradictory findings support the need for larger studies to further investigate whether LOAD PGS is associated with increased amyloid deposition in EOAD.Higher LOAD PGS was also associated with higher levels of CSF synaptosomal‐associated protein 25 (SNAP‐25), a key component of the SNARE complex, suggesting that LOAD genetic factors may contribute to dysregulation of synaptic transmission and/or pathological protein aggregation in EOAD.

Most of the genetic etiology for early-onset Alzheimer's disease (EOAD) is currently unexplained. One hypothesis is that EOAD cases may have similar genetic etiology to late-onset AD (LOAD), but with more LOAD risk SNPs than typical LOAD patients, reflected by higher polygenic scores (PGS) and earlier age of onset (AoO). We will compare the predictive value of a LOAD PGS for EOAD and LOAD in the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). A PGS developed by Desikan et al., 2017 was applied to GWAS data for white non-Hispanic harmonized LEADS (N=487) and ADNI (N=672) participants. Binary logistic regression models were tested to identify predictors of EOAD and LOAD. In the combined cohort, this model was also run covarying for APOE4 carrier status. Cox regression was used to assess differences in ADNI and LEADS AoO for tertile-binned PGS. Within LEADS EOAD participants, five cognitive domains were assessed for correlation with PGS. The AD PGS predicted case/control status in the combined cohort (X2(4)=226.365, p<0.001), in the ADNI-only cohort (X2(4)=149.695, p=<0.001), and in the LEADS-only cohort (X2(3)=30.323, p<0.001). In each model, higher PGS was associated with increased odds of EOAD and/or LOAD. Covarying for APOE4, PGS remained significant in the combined cohort (X2(5)=250.904, p<0.001) and in the ADNI cohort (X2(5)=176.307, p<0.001) but not in the LEADS-only cohort (X2(3)=31.974, p=0<0.001; final model did not include PGS) (Table 1). Hazard survival analysis indicated a significant difference in PGS groups in the combined and ADNI cohorts' AoO but not in the LEADS cohort. In the EOAD group, PGS was significantly correlated with cognitive score for visuospatial performance (F=4.473 p=0.013). Language performance was also correlated with PGS in EOAD (F=3.387 p=0.036). These results suggest that LOAD genetic risk, aside from APOE4, is not a strong driver of EOAD age of onset; however, these variants may mediate some aspects of cognitive dysfunction in EOAD patients.

INTRODUCTIONWe evaluated the long‐term effects of daily 40 Hz (gamma frequency) audiovisual stimulation on cognition and biomarkers in five patients with mild Alzheimer's disease (AD).METHODSOver 2 years, patients received 1‐h daily stimulation. Electroencephalography (EEG) was used to assess neural entrainment; magnetic resonance imaging (MRI) measured brain volumes; actigraphy monitored activity patterns; neuropsychological tests evaluated cognition; and S‐PLEX assay measured plasma pTau217.RESULTSNo adverse events occurred over the study period. Three female patients with late‐onset AD (LOAD) retained strong EEG entrainment and showed less decline in Mini‐Mental State Examination (MMSE), Clinical Dementia Rating (CDR), and Functional Assessment Scale (FAS) scores compared to matched controls from National Alzheimer's Coordinating Center (NACC), Alzheimer's Disease Neuroimaging Initiative (ADNI), and Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS). Plasma samples were available for only two of five participants – both with LOAD – and both showed pTau217 reductions of 47% and 19%.DISCUSSIONThese findings suggest that long‐term 40 Hz audiovisual stimulation is safe, feasible, and may offer cognitive and biomarker benefits in some individuals with mild AD, supporting further investigation.CLINICAL TRIAL REGISTRATION INFORMATIONClinicalTrials.gov (NCT04055376).HighlightsFive mild Alzheimer's disease (AD) patients safely used daily 40 Hz audiovisual stimulation for 2 years.Late‐onset AD (LOAD) patients showed increased 40 Hz electroencephalography (EEG) power and improved cognitive scores.National Alzheimer's Coordinating Center (NACC) data enhanced early‐phase analysis and support precision medicine in AD studies.Plasma pTau217 declined in 2 LOAD patients after 2 years of daily use.This small pilot is the first to link long‐term 40 Hz therapy to AD biomarker change.

The interassay variability and inconsistency of plasma β-amyloid (Aβ) measurements among centers are major factors precluding the interpretation of results and a substantial obstacle in the meta-analysis across studies of this biomarker. The goal of this investigation was to address these problems by improving the performance of the bioanalytical method. We used the Luminex immunoassay platform with a multiplex microsphere-based reagent kit from Innogenetics. A robotic pipetting system was used to perform crucial steps of the procedure. The performance of this method was evaluated using two kit control samples and two quality control plasma samples from volunteer donors, and by retesting previously assayed patient samples in each run. This setup was applied to process 2454 patient plasma samples from the Alzheimer's Disease Neuroimaging Initiative study biofluid repository. We have additionally evaluated the correlations between our results and cerebrospinal fluid (CSF) biomarker data using mixed-effects modeling. The average precision values of the kit controls were 8.3% for Aβ(1-40) and 4.0% for Aβ(1-42), whereas the values for the plasma quality controls were 6.4% for Aβ(1-40) and 4.8% for Aβ(1-42). From the test-retest evaluation, the average precision was 7.2% for Aβ(1-40) and 4.5% for Aβ(1-42). The range of final plasma results for Alzheimer's Disease Neuroimaging Initiative patients was 13 to 372 pg/mL (median: 164 pg/mL) for Aβ(1-40) and 3.5 to 103 pg/mL (median: 39.3 pg/mL) for Aβ(1-42). We found that sample collection parameters (blood volume and time to freeze) have a small, but significant, influence on the result. No significant difference was found between plasma Aβ levels for patients with Alzheimer's disease and healthy control subjects. We have determined multiple significant correlations of plasma Aβ(1-42) levels with CSF biomarkers. The relatively strongest, although modest, correlation was found between plasma Aβ(1-42) levels and CSF p-tau(181)/Aβ(1-42) ratio in patients with mild cognitive impairment. Plasma Aβ(1-40) correlations with CSF biomarkers were weaker and diminished completely when we used longitudinal data. No significant correlations were found for the plasma Aβ(1-42)/Aβ(1-40) ratio. The precision of our robotized method represents a substantial improvement over results reported in the literature. Multiple significant correlations between plasma and CSF biomarkers were found. Although these correlations are not strong enough to support the use of plasma Aβ measurement as a diagnostic screening test, plasma Aβ(1-42) levels are well suited for use as a pharmacodynamic marker.

Striatal changes in the pathogenesis of Alzheimer's disease (AD) is not fully understood yet. We compared structural and functional image differences in the striatum between patients with early onset AD (EOAD) and late onset AD (LOAD) to investigate whether EOAD harbors autosomal dominant AD like imaging findings. The clinical, neuropsychological and neuroimaging biomarkers of 77 probable AD patients and 107 elderly subjects with normal cognition (NC) from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-2 dataset were analyzed. Enrolled each subject completed a 3-Tesla MRI, baseline 18F-FDG-PET, and baseline 18F-AV-45 (Florbetapir) amyloid PET studies. AD patients were divided into two groups based on the onset age of clinical symptoms (EOAD <65 yrs; LOAD ≥65 yrs). A standardized uptake value ratio of the striatum and subcortical structures was obtained from both amyloid and FDG-PET scans. Structural MR imaging analysis was conducted using a parametric boundary description protocol, SPHARM-PDM. Of the 77 AD patients, 18 were EOAD and 59 were LOAD. Except for age of symptom onset, there were no statistically significant differences between the groups in demographics and detailed neuropsychological test results. 18F-AV-45 amyloid PET showed marked β-amyloid accumulation in the bilateral caudate nucleus and left pallidum in the EOAD group. Intriguingly, the caudate nucleus and putamen showed maintained glucose metabolism in the EOAD group compared to the LOAD group. Our image findings in the striatum of EOAD patients suggest that sporadic EOAD may share some pathophysiological changes noted in autosomal dominant AD.

Alzheimer's disease: The influence of age on clinical heterogeneity through the human brain connectome