Preclinical Alzheimer's Disease Biomarkers Research Articles

Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer’s disease neuropathology

Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aβ) profiles, and to predicted progression to Alzheimer's disease (AD). Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42-85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n=291), resilient in both (n=260) or advanced in one/resilient in the other (n=163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task). Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits. The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life. The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute.

Testing bidirectional relationships between functional brain networks and preclinical Alzheimer disease biomarkers

AbstractBackgroundResting‐state functional connectivity (RSFC) provides estimates of brain networks using fMRI. There are conflicting reports regarding the effects of amyloid‐β (Aβ) and tau on RSFC networks in cognitively normal participants. These inconsistencies might be explained by a recently‐proposed theoretical model that Aβ and tau have an interactive effect on RSFC, marked first by hyper‐connectivity in association with Aβ, then by hypo‐connectivity in association with tau. Although there is preliminary support for this model, independent validations and further characterizations of the effects of Aβ and tau on RSFC are needed.MethodWe analyzed RSFC, Aβ PET, and tau PET data from the Knight Alzheimer Disease Research Center (ADRC). All participants were cognitively normal (Clinical Dementia Rating®: 0). RSFC was collected on two scanners in partly‐overlapping samples (PETMR N: 190, TRIO N: 149). RSFC data were processed with framewise censoring and global signal regression. RSFC networks were defined using 298 regions of interest. Aβ was measured with PET PiB and AV‐45 tracers, which were harmonized using a Centiloid conversion. Tau was measured with a PET AV‐1451 tracer and was summarized in pre‐defined regions. Main effect and interaction relationships between Aβ, tau PET, and RSFC were tested with linear regression models, controlling for age, sex, education, and head motion as covariates, with a false discovery rate correction.ResultWe did not observe a bidirectional interaction effect in any of the hypothesized networks (default mode [DMN], salience [SAL], frontoparietal [FPN]). Aβ was positively associated with RSFC, independent of tau, in the DMN and SAL, while tau was negatively associated with RSFC, independent of Aβ, in the SAL only. Exploratory analyses of FC within and between all networks did not identify clear patterns of interactive biomarker effects, nor consistent patterns of main effect relationships within any of the other networks.ConclusionThese results do not support an interactive model of RSFC in preclinical AD. Inconsistencies with previous interactions may be driven by sample‐specific or methodological differences, or the low reliability of FC and brain‐behavior relationships. Prominent biomarker relationships in the DMN and SAL are consistent with regional overlap with Aβ deposition in early AD.

Testing bidirectional relationships between functional brain networks and preclinical Alzheimer disease biomarkers

AbstractBackgroundResting‐state functional connectivity (RSFC) provides estimates of brain networks using fMRI. There are conflicting reports regarding the effects of amyloid‐ß (Aß) and tau on RSFC networks in cognitively normal participants. These inconsistencies might be explained by a recently‐proposed theoretical model that Aß and tau have an interactive effect on RSFC, marked first by hyper‐connectivity in association with Aß, then by hypo‐connectivity in association with tau. Although there is preliminary support for this model, independent validations and further characterizations of the effects of Aß and tau on RSFC are needed.MethodWe analyzed RSFC, Aß PET, and tau PET data from the Knight Alzheimer Disease Research Center (ADRC). All participants were cognitively normal (Clinical Dementia Rating®: 0). RSFC was collected on two scanners in partly‐overlapping samples (PETMR N: 190, TRIO N: 149). RSFC data were processed with framewise censoring and global signal regression. RSFC networks were defined using 298 regions of interest. Aß was measured with PET PiB and AV‐45 tracers, which were harmonized using a Centiloid conversion. Tau was measured with a PET AV‐1451 tracer and was summarized in pre‐defined regions. Main effect and interaction relationships between Aß, tau PET, and RSFC were tested with linear regression models, controlling for age, sex, education, and head motion as covariates, with a false discovery rate correction.ResultWe did not observe a bidirectional interaction effect in any of the hypothesized networks (default mode [DMN], salience [SAL], frontoparietal [FPN]). Aß was positively associated with RSFC, independent of tau, in the DMN and SAL, while tau was negatively associated with RSFC, independent of Aß, in the SAL only. Exploratory analyses of FC within and between all networks did not identify clear patterns of interactive biomarker effects, nor consistent patterns of main effect relationships within any of the other networks.ConclusionThese results do not support an interactive model of RSFC in preclinical AD. Inconsistencies with previous interactions may be driven by sample‐specific or methodological differences, or the low reliability of FC and brain‐behavior relationships. Prominent biomarker relationships in the DMN and SAL are consistent with regional overlap with Aß deposition in early AD.

Proteomic clusters underlie heterogeneity in preclinical Alzheimer's disease progression.

Heterogeneity in progression to Alzheimer's disease (AD) poses challenges for both clinical prognosis and clinical trial implementation. Multiple AD-related subtypes have previously been identified, suggesting differences in receptivity to drug interventions. We identified early differences in preclinical AD biomarkers, assessed patterns for developing preclinical AD across the amyloid-tau-(neurodegeneration) [AT(N)] framework, and considered potential sources of difference by analysing the CSF proteome. Participants (n = 10) enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center completed four or more lumbar punctures. These individuals were cognitively normal at baseline. Cerebrospinal fluid measures of amyloid-β (Aβ)42, phosphorylated tau (pTau181), and neurofilament light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including PET amyloid and tau, and structural MRI, were repeatedly obtained when available. Individuals were staged according to the amyloid-tau-(neurodegeneration) framework. Growth mixture modelling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and Aβ42. Two groups (AD Biomarker Positive and Intermediate AD Biomarker) showed distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were re-classified using only proteomic profiles (AUCAD Biomarker Positive versus AD Biomarker Negative = 0.857, AUCAD Biomarker Positive versus Intermediate AD Biomarkers = 0.525, AUCIntermediate AD Biomarkers versus AD Biomarker Negative = 0.952). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified some individuals who became amyloid positive before the age of 50 years. A second group, Intermediate AD Biomarkers, developed elevated CSF ptau181 significantly before becoming amyloid positive. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing versus other agents) in clinical trials. CSF proteome analysis highlighted additional non-AT(N) biomarkers for potential therapies, including blood-brain barrier-, vascular-, immune-, and neuroinflammatory-related targets.

Adverse driving behaviors increase over time as a function of preclinical Alzheimer's disease biomarkers.

We investigated the relationship between preclinical Alzheimer's disease (AD) biomarkers and adverse driving behaviors in a longitudinal analysis of naturalistic driving data. Naturalistic driving data collected using in-vehicle dataloggers from 137 community-dwelling older adults (65+) were used to model driving behavior over time. Cerebrospinal fluid (CSF) biomarkers were used to identify individuals with preclinical AD. Additionally, hippocampal volume and cognitive biomarkers for AD were investigated in exploratory analyses. CSF biomarkers predicted the longitudinal trajectory of the incidence of adverse driving behavior. Abnormal amyloid beta (Aβ42 /Aβ40 ) ratio was associated with an increase in adverse driving behaviors over time compared to ratios in the normal/lower range. Preclinical AD is associated with increased adverse driving behavior over time that cannot be explained by cognitive changes. Driving behavior as a functional, neurobehavioral marker may serve as an early detection for decline in preclinical AD. Screening may also help prolong safe driving as older drivers age.

NCOG-15. A PILOT STUDY ON RETINAL FEATURES AND COGNITIVE FUNCTION IN PATIENTS WITH LOW GRADE GLIOMAS

Abstract BACKGROUND Retinal structure and vascular changes are used as biomarkers for preclinical Alzheimer disease. We conducted a cohort study to evaluate the feasibility of obtaining these data in patients with low-grade gliomas (LGGs) who completed chemoradiation therapy with and without self or family reported cognitive concerns. METHODS Optical coherence tomography (OCT) and angiography (OCTA, OptoVue, Inc.) images were obtained from 6 LGG patients and 2 healthy controls using 4.5 x 4.5 mm peripapillary and 6x6 mm macular scan patterns. We measured OCTA parameters including radial peripapillary capillary density for the peri-optic disc region, whole macular density, and foveal avascular zone (FAZ). RESULTS We analyzed two eyes of two control subjects, an LGG patient with normal cognition, and 5 LGG patients with cognitive impairment (mean age 45 years, range of 3 months to 10 years after chemoradiation). Both controls had normal eye exams. Average retinal nerve fiber layer thickness was thinner in patients with and without cognitive dysfunction (104 um and 106 um, respectively) than controls (123 um). A similar pattern was seen in macula thickness (283 um and 290 um vs. 325 um). The average peripapillary vessel densities were lower in patients with and without cognitive dysfunction (47.7% and 48.3%, respectively) than controls (51.9%). The whole macular vessel densities were similar in three groups (46.7 %, 48.0%, and 48.0 %). Average FAZs were larger in patients with cognitive dysfunction (0.254 mm2) than the patient with normal cognition (0.204 mm2) and controls (0.226 mm2). CONCLUSIONS Retinal architecture and microvascular changes measured by OCT/OCTA is feasible in LGG patients after chemoradiation. A larger prospective study is needed to investigate the role of OCT/OCTA in detecting peripapillary and perifoveal changes in brain tumor patients with treatment-associated cognitive dysfunction.

Preclinical Alzheimer's disease biomarkers accurately predict cognitive and neuropathological outcomes.

Alzheimer's disease biomarkers are widely accepted as surrogate markers of underlying neuropathological changes. However, few studies have evaluated whether preclinical Alzheimer's disease biomarkers predict Alzheimer's neuropathology at autopsy. We sought to determine whether amyloid PET imaging or CSF biomarkers accurately predict cognitive outcomes and Alzheimer's disease neuropathological findings. This study included 720 participants, 42-91 years of age, who were enrolled in longitudinal studies of memory and aging in the Washington University Knight Alzheimer Disease Research Center and were cognitively normal at baseline, underwent amyloid PET imaging and/or CSF collection within 1 year of baseline clinical assessment, and had subsequent clinical follow-up. Cognitive status was assessed longitudinally by Clinical Dementia Rating®. Biomarker status was assessed using predefined cut-offs for amyloid PET imaging or CSF p-tau181/amyloid-β42. Subsequently, 57 participants died and underwent neuropathologic examination. Alzheimer's disease neuropathological changes were assessed using standard criteria. We assessed the predictive value of Alzheimer's disease biomarker status on progression to cognitive impairment and for presence of Alzheimer's disease neuropathological changes. Among cognitively normal participants with positive biomarkers, 34.4% developed cognitive impairment (Clinical Dementia Rating > 0) as compared to 8.4% of those with negative biomarkers. Cox proportional hazards modelling indicated that preclinical Alzheimer's disease biomarker status, APOE ɛ4 carrier status, polygenic risk score and centred age influenced risk of developing cognitive impairment. Among autopsied participants, 90.9% of biomarker-positive participants and 8.6% of biomarker-negative participants had Alzheimer's disease neuropathological changes. Sensitivity was 87.0%, specificity 94.1%, positive predictive value 90.9% and negative predictive value 91.4% for detection of Alzheimer's disease neuropathological changes by preclinical biomarkers. Single CSF and amyloid PET baseline biomarkers were also predictive of Alzheimer's disease neuropathological changes, as well as Thal phase and Braak stage of pathology at autopsy. Biomarker-negative participants who developed cognitive impairment were more likely to exhibit non-Alzheimer's disease pathology at autopsy. The detection of preclinical Alzheimer's disease biomarkers is strongly predictive of future cognitive impairment and accurately predicts presence of Alzheimer's disease neuropathology at autopsy.

Current advances in digital cognitive assessment for preclinical Alzheimer's disease.

There is a pressing need to capture and track subtle cognitive change at the preclinical stage of Alzheimer's disease (AD) rapidly, cost‐effectively, and with high sensitivity. Concurrently, the landscape of digital cognitive assessment is rapidly evolving as technology advances, older adult tech‐adoption increases, and external events (i.e., COVID‐19) necessitate remote digital assessment. Here, we provide a snapshot review of the current state of digital cognitive assessment for preclinical AD including different device platforms/assessment approaches, levels of validation, and implementation challenges. We focus on articles, grants, and recent conference proceedings specifically querying the relationship between digital cognitive assessments and established biomarkers for preclinical AD (e.g., amyloid beta and tau) in clinically normal (CN) individuals. Several digital assessments were identified across platforms (e.g., digital pens, smartphones). Digital assessments varied by intended setting (e.g., remote vs. in‐clinic), level of supervision (e.g., self vs. supervised), and device origin (personal vs. study‐provided). At least 11 publications characterize digital cognitive assessment against AD biomarkers among CN. First available data demonstrate promising validity of this approach against both conventional assessment methods (moderate to large effect sizes) and relevant biomarkers (predominantly weak to moderate effect sizes). We discuss levels of validation and issues relating to usability, data quality, data protection, and attrition. While still in its infancy, digital cognitive assessment, especially when administered remotely, will undoubtedly play a major future role in screening for and tracking preclinical AD.

Genetic Alzheimer’s Disease Risk Affects the Neural Mechanisms of Pattern Separation in Hippocampal Subfields

The hippocampal subfields perform distinct operations during acquisition, differentiation, and recollection of episodic memories, and deficits in pattern separation are among the first symptoms of Alzheimer's disease (AD). We investigated how hippocampal subfields contribute to pattern separation and how this is affected by Apolipoprotein-E (APOE), the strongest AD genetic risk factor. Using ultra-high-field (7T) functional magnetic resonance imaging (fMRI), APOE-ε3-ε3 carriers predominantly recruited cornu ammonis 3 (CA3) during a spatial mnemonic discrimination task, whereas APOE-ε3-ε4 and APOE-ε3-ε2 carriers engaged CA3 and dentate gyrus (DG) to the same degree. Specifically, APOE-ε3-ε4 carriers showed reduced pattern separation in CA3, whereas APOE-ε3-ε2 carriers exhibited increased effects in DG and pattern separation-related functional connectivity between DG and CA3. Collectively, these results demonstrate that AD genetic risk alters hemodynamic responses in young pre-symptomatic individuals, paving the way for development of biomarkers for preclinical AD.

Editors' note: Odor identification as a biomarker of preclinical AD in older adults at risk

In their study “Odor identification as a biomarker of preclinical AD in older adults at risk,” Lafaille-Magnan et al. found that decrease in odor identification (OI) was associated with increasing CSF biomarker evidence of Alzheimer disease (AD) pathology and that the association between OI deficits and cognition in older adults at increased risk of AD was driven by the presence of AD-related CSF biomarkers rather than the effects of age or other confounders. Commenting on the study, Drs. Bohnen and Muller suggest that OI deficits may herald the presence of not only AD but also Lewy body pathologies. Lafaille-Magnan et al. agree but argue that the association of odor identification with presymptomatic AD may be particularly useful owing to the paucity of other inexpensive and noninvasive robust biomarker measures in AD. In their study “Odor identification as a biomarker of preclinical AD in older adults at risk,” Lafaille-Magnan et al. found that decrease in odor identification (OI) was associated with increasing CSF biomarker evidence of Alzheimer disease (AD) pathology and that the association between OI deficits and cognition in older adults at increased risk of AD was driven by the presence of AD-related CSF biomarkers rather than the effects of age or other confounders. Commenting on the study, Drs. Bohnen and Muller suggest that OI deficits may herald the presence of not only AD but also Lewy body pathologies. Lafaille-Magnan et al. agree but argue that the association of odor identification with presymptomatic AD may be particularly useful owing to the paucity of other inexpensive and noninvasive robust biomarker measures in AD.

Reader response: Odor identification as a biomarker of preclinical AD in older adults at risk.

Lafaille-Magnan et al.1 reported that the association between odor identification deficits and cognition in older adults at increased risk of Alzheimer disease (AD) was driven by the presence of AD-related CSF biomarkers rather than the effects of age or other confounders. In addition, the findings were best explained by CSF tau rather than β-amyloid levels. These findings agree with postmortem observations that neurofibrillary tangles in the mesiotemporal lobe robustly predict olfactory deficits in the elderly.2 Dementia with Lewy bodies (DLB) is the second most common type of dementia; odor identification deficits in this hypodopaminergic disorder tend be more severe than in AD.3 However, tau pathology in DLB is substantially less severe compared to AD, including the mesiotemporal lobe.4

Forecasting the prevalence of preclinical and clinical Alzheimer's disease in the United States

IntroductionWe forecast the prevalence of preclinical and clinical Alzheimer's disease (AD) and evaluated potential impacts of primary and secondary preventions in the United States. MethodsWe used a multistate model incorporating biomarkers for preclinical AD with US population projections. ResultsApproximately 6.08 million Americans had either clinical AD or mild cognitive impairment due to AD in 2017 and that will grow to 15.0 million by 2060. In 2017, 46.7 million Americans had preclinical AD (amyloidosis, neurodegeneration, or both), although many may not progress to clinical disease during their lifetimes. Primary and secondary preventions have differential impact on future disease burden. DiscussionBecause large numbers of persons are living with preclinical AD, our results underscore the need for secondary preventions for persons with existing AD brain pathology who are likely to develop clinical disease during their lifetimes as well as primary preventions for persons without preclinical disease.

Moderate-severe obstructive sleep apnea and the risk for preclinical Alzheimer's disease biomarkers changes

Moderate-severe obstructive sleep apnea and the risk for preclinical Alzheimer's disease biomarkers changes

High-Throughput Metabolomics for Discovering Potential Metabolite Biomarkers and Metabolic Mechanism from the APPswe/PS1dE9 Transgenic Model of Alzheimer’s Disease

Alzheimer's disease (AD), a neurodegenerative disorder, is the major form of dementia. As AD is an irreversible disease, it is necessary to focus on earlier intervention. However, the potential biomarkers of preclinical AD are still not clear. In this study, urinary metabolomics based on ultra-high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry was performed for delineating the metabolic changes and potential early biomarkers in APPswe/PS1dE9 (APP/PS1) transgenic mice. A total of 24 differentially regulated metabolites were identified when comparing transgenic mice to wild-type mice using multivariate statistical analysis. Among them, 10 metabolites were significantly upregulated and 14 metabolites were downregulated. On the basis of these potential biomarkers, metabolic pathway analysis found that pentose and glucuronate interconversions, glyoxylate and dicarboxylate metabolism, starch and sucrose metabolism, the citrate cycle, tryptophan metabolism, and arginine and proline metabolism were disturbed in APP/PS1 mice. Our study revealed that levels of endogenous metabolites in the urine of APP/PS1 mice changed prior to the emergence of learning and cognitive impairment, which may be associated with abnormal nitric oxide production pathways and metabolic disorders of monoaminergic neurotransmitters. In conclusion, this study showed that metabolomics provides an early indicator of disease occurrence for AD.

Cerebrospinal Fluid and Blood Biomarkers in Alzheimer's Disease

To cope with an aging society, development of disease-modifying drugs for Alzheimer's disease (AD) is essential. Currently, only symptomatic treatments that suppress clinical manifestations are available. Amyloid-β₄₂ (Aβ₄₂) is an AD-related pathogenic molecule that triggers development of AD pathology; thus, decreasing Aβ₄₂ in the brain is a promising candidate for AD therapy. Numerous pharmaceutical companies have developed therapeutic drugs against Aβ₄₂, such as β-secretase inhibitors, γ-secretase inhibitors, and anti-Aβ monoclonal antibodies, but in clinical trials for patients with mild to moderate AD, these drugs did not meet the expected endpoints. These results suggest that earlier administration of these drugs to individuals who have not yet developed cognitive decline, but have AD pathological changes in the brain or high risk of developing these changes, may be beneficial. To enable such early treatment, preclinical AD biomarkers are required. In this review, we comment on current AD biomarkers in cerebrospinal fluid and in blood. We also explain CSF/blood APL1β, which is a candidate surrogate marker for Aβ₄₂ in the brain.

Preclinical AD and Biomarker; from J-ADNI to AMED Preclinical Study

Alzheimer's disease (AD) is most prevalent cause of dementia and no cure has been discovered. Although the framework of AD clinical trials is being established utilizing results of large-scale observational studies such as the AD Neuroimaging Initiative (ADNI) and the Japanese-ADNI (J-ADNI), the development of disease-modifying therapy for Alzheimer's disease (AD) has not yet been achieved. Preclinical AD was recently defined as a new disease stage in which AD is asymptomatic but biomarkers suggest the presence of amyloid pathology. Preclinical AD has been focused as promising therapeutic time window and establishment of reliable biomarkers for preclinical AD is an urgent task. The Japanese Agency for Medical Research and Development (AMED) preclinical study is a nationwide multicenter observational study carried out by public research funding from AMED as a successor to the J-ADNI study. The goal of this study is to establish a biomarker that can quantitatively evaluate the disease progression of preclinical AD and mild cognitive impairment (MCI) or predict the progression to MCI and dementia in the future. To achieve this goal, the following assessments will be conducted over time for three years: clinical evaluations; cognitive tests; genetic testing; body fluid biomarker tests; and imaging biomarker studies such as MRI, FDG-PET, and amyloid PET. The obtained data will eventually be released to the public database.

Odor identification as a biomarker of preclinical AD in older adults at risk.

Objective:To assess odor identification (OI) as an indicator of presymptomatic Alzheimer disease (AD) pathogenesis in cognitively normal aging individuals at increased risk of AD dementia.Methods:In 274 members of the PREVENT-AD cohort of healthy aging persons with a parental or multiple-sibling history of AD dementia, we assessed the cross-sectional association of OI with potential indicators of presymptomatic AD. Some 101 participants donated CSF, thus enabling assessment of AD pathology with the biomarkers total tau (t-tau), phospho-tau (P181-tau), and their ratios with β-amyloid (Aβ1-42). Adjusted analyses considered age, cognition, APOE ε4 status, education, and sex as covariates. We measured OI using the University of Pennsylvania Smell Identification Test and cognitive performance using the Repeatable Battery for Assessment of Neuropsychological Status. Standard kits provided assays of the AD biomarkers. Analyses used robust-fit linear regression models.Results:Reduced OI was associated with lower cognitive score and older age, as well as increased ratios of CSF t-tau and P181-tau to Aβ1-42 (all p < 0.02). However, the observed associations of OI with age and cognition were unapparent in adjusted models that restricted observations to CSF donors and included AD biomarkers. OI showed little association with CSF Aβ1-42 alone except in APOE ε4 carriers having lowest-quartile Aβ1-42 levels.Conclusions:These findings from healthy high-risk older individuals suggest that OI reflects degree of preclinical AD pathology, while its relationships with age and cognition result from the association of these latter variables with such pathology. Diminished OI may be a practical and affordable biomarker of AD pathology.

The Utility of Cerebral Blood Flow as a Biomarker of Preclinical Alzheimer's Disease.

There is accumulating evidence suggesting that changes in brain perfusion are present long before the clinical symptoms of Alzheimer's disease (AD), perhaps even before amyloid-β accumulation or brain atrophy. This evidence, consistent with the vascular hypothesis of AD, implicates cerebral blood flow (CBF) in the pathogenesis of AD and suggests its utility as a biomarker of preclinical AD. The extended preclinical phase of AD holds particular significance for disease modification, as treatment would likely be most effective in this early asymptomatic stage of disease. This highlights the importance of identifying reliable and accurate biomarkers of AD that can differentiate normal aging from preclinical AD prior to clinical symptom manifestation. Cerebral perfusion, as measured by arterial spin labeling magnetic resonance imaging (ASL-MRI), has been shown to distinguish between normal controls and adults with AD. In addition to demonstrating diagnostic utility, CBF has shown usefulness as a tool for identifying those who are at risk for AD and for predicting subtle cognitive decline and conversion to mild cognitive impairment and AD. Taken together, this evidence not only implicates CBF as a useful biomarker for tracking disease severity and progression, but also suggests that ASL-measured CBF may be useful for identifying candidates for future AD treatment trials, especially in the preclinical, asymptomatic phases of the disease.

Biomarkers for preclinical Alzheimer's disease.

Currently, there is a pressing need to shift the focus to accurate detection of the earliest phase of increasingly preclinical Alzheimer's disease (AD). Meanwhile, the growing recognition that the pathophysiological process of AD begins many years prior to clinically obvious symptoms and the concept of a presymptomatic or preclinical stage of AD are becoming more widely accepted. Advances in clinical identification of new measurements will be critical not only in the discovery of sensitive, specific, and reliable biomarkers of preclinical AD but also in the development of tests that will aid in the early detection and differential diagnosis of dementia and in monitoring disease progression. The goal of this review is to provide an overview of biomarkers for preclinical AD, with emphasis on neuroimaging and neurochemical biomarkers. We conclude with a discussion of emergent directions for AD biomarker research.

Clearing the amyloid in Alzheimer's: progress towards earlier diagnosis and effective treatments - an update for clinicians.

A beta (Aβ or β-amyloid) is a key molecule in Alzheimer's disease (AD) pathogenesis. According to the 'amyloid hypothesis', the gradual accumulation of Aβ triggers events which results in neuronal loss in regions of the brain involved with memory and learning. Diverse agents have been developed to reduce brain Aβ accumulation or to enhance its clearance. Some have progressed to human trials, however all have failed to improve cognition in patients. This has led researchers to question whether Aβ is really the problem. However, the trials have been targeting end stages of AD, by which stage extensive irreversible neuronal damage has already occurred. Intervention is required preclinically, therefore preclinical AD biomarkers are needed. In this regard, amyloid imaging and cerebrospinal fluid biomarkers are leading the way, with plasma biomarkers and eye tests also being investigated. This review covers the current state of knowledge of Aβ as an early diagnostic biomarker and as a therapeutic target in AD.