Biomarkers for Alzheimer's disease therapeutic trials

Fluid biomarkers in the context of amyloid-targeting disease-modifying treatments in Alzheimer's disease

Clinical management and therapeutics development for Alzheimer's disease (AD) have entered a new era, with recent approvals of monoclonal antibody therapies targeting the underlying pathophysiology of the disease and modifying its trajectory. Imaging and fluid biomarkers are becoming increasingly important in the clinical development of AD therapeutics. This review focuses on the evidence of fluid biomarkers from recent amyloid-β-targeting clinical trials, summarizing biomarker data across 12 trials. It further proposes a simple framework to put biomarker guidance in the context of amyloid-pathway-targeted disease modification, delineates factors that impact biomarker data in clinical trials, and highlights knowledge gaps and future directions. Increased knowledge and data on biomarkers in the context of disease progression and disease modification will help to better design future AD trials and guide the clinical management of patients on AD-modifying therapies, bringing us closer to the implementation of precision medicine in AD.

Baseline serum glutamate: Implications for diagnosis and prediction in mild cognitive impairment and Alzheimer's disease of the Alzheimer's Disease Neuroimaging Initiative

PURPOSE

Numerous studies have highlighted a close link between metabolic imbalances and Alzheimer's Disease (AD). The advancement of metabolomics has recently enabled the exploration of characteristic metabolic changes associated with AD. Studies indicate that serum glutamate (Glu) levels may correlate with mild cognitive impairment (MCI) and AD. This study aims to further elucidate the characteristics of baseline serum Glu levels in MCI and AD.

METHODS

This study included 783 participants from the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1) cohort, categorized into cognitively normal (CN, n = 224), stable MCI (sMCI, n = 181), progressive MCI (pMCI, n = 193), and AD (n = 185). The study aimed to analyze the diagnostic value of baseline serum Glu, to explore its predictive capability for the progression from CN to MCI or AD, and from MCI to AD, and to analyze the relationship between serum Glu and cerebrospinal fluid (CSF) biomarkers and cognitive functions in different diagnostic groups.

RESULTS

Compared to the CN and sMCI groups, the pMCI group showed significantly lower levels of serum Glu, and the AD group also had lower Glu levels compared to the sMCI group. However, serum Glu did not show significant diagnostic value for MCI and AD. Lower levels of serum Glu could predict the progression from MCI to AD.

CONCLUSION

Serum Glu levels can predict the progression from MCI to AD, suggesting that it could provide new insights into the pathophysiological mechanisms of AD. However, serum Glu may not be an ideal peripheral biomarker for AD.

Evaluating the effect of rapamycin treatment in Alzheimer's disease and aging using in vivo imaging: the ERAP phase IIa clinical study protocol

BACKGROUND

Rapamycin is an inhibitor of the mechanistic target of rapamycin (mTOR) protein kinase, and preclinical data demonstrate that it is a promising candidate for a general gero- and neuroprotective treatment in humans. Results from mouse models of Alzheimer's disease have shown beneficial effects of rapamycin, including preventing or reversing cognitive deficits, reducing amyloid oligomers and tauopathies and normalizing synaptic plasticity and cerebral glucose uptake. The "Evaluating Rapamycin Treatment in Alzheimer's Disease using Positron Emission Tomography" (ERAP) trial aims to test if these results translate to humans through evaluating the change in cerebral glucose uptake following six months of rapamycin treatment in participants with early-stage Alzheimer's disease.

METHODS

ERAP is a six-month-long, single-arm, open-label, phase IIa biomarker-driven study evaluating if the drug rapamycin can be repurposed to treat Alzheimer's disease. Fifteen patients will be included and treated with a weekly dose of 7 mg rapamycin for six months. The primary endpoint will be change in cerebral glucose uptake, measured using [18F]FDG positron emission tomography. Secondary endpoints include changes in cognitive measures, markers in cerebrospinal fluid as well as cerebral blood flow measured using magnetic resonance imaging. As exploratory outcomes, the study will assess change in multiple age-related pathological processes, such as periodontal inflammation, retinal degeneration, bone mineral density loss, atherosclerosis and decreased cardiac function.

DISCUSSION

The ERAP study is a clinical trial using in vivo imaging biomarkers to assess the repurposing of rapamycin for the treatment of Alzheimer's disease. If successful, the study would provide a strong rationale for large-scale evaluation of mTOR-inhibitors as a potential disease-modifying treatment in Alzheimer's disease.

TRIAL REGISTRATION

ClinicalTrials.gov ID NCT06022068, date of registration 2023-08-30.

Characterizing age- and sex-related differences in brain structure among middle-aged and older Hispanic/Latino adults in the study of Latinos- investigation of neurocognitive aging magnetic resonance imaging (SOL-INCA MRI)

Hispanic/Latino adults are a growing segment of the older U.S. population yet are underrepresented in brain aging research. We aimed to characterize brain aging among diverse Hispanic/Latino individuals. Hispanic/Latino individuals (unweighted n = 2273 ages 35-85 years; 56% female) from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) population-based study underwent magnetic resonance imaging (MRI) as part of the SOL- Investigation of Neurocognitive Aging MRI (SOL-INCA-MRI) ancillary study (2018-2022). We performed linear regressions to calculate age associations with brain volumes for each outcome (total (global) brain, hippocampal, lateral ventricle, total white matter hyperintensity (WMH), individual cortical lobar, and total cortical gray matter) and tested modification by sex. Older age was associated with smaller gray matter volumes and larger lateral ventricle and WMH volumes. Age-related differences in global brain volumes and gray matter volumes in specific regions (i.e., the hippocampus and temporal and occipital lobes) were less pronounced among women. Our findings warrant further investigation into sex-specific mechanisms of brain aging using longitudinal studies.

Early cognitive comorbidities before disease onset: A common symptom towards prevention of related brain diseases?

Brain diseases are very heterogeneous; however they also display multiple common risk factors and comorbidities. With a paucity of disease-modifying therapies, prevention became a health priority. Towards prevention, one strategy is to focus on similar symptoms of brain diseases occurring before disease onset. Cognitive deficits are a promising candidate as they occur across brain diseases before disease onset. Based on recent research, this review highlights the similarity of brain diseases and discusses how early cognitive deficits can be exploited to tackle disease prevention. After briefly introducing common risk factors, I review common comorbidities across brain diseases, with a focus on cognitive deficits before disease onset, reporting both experimental and clinical findings. Next, I describe network abnormalities associated with early cognitive deficits and discuss how these abnormalities can be targeted to prevent disease onset. A scenario on brain disease etiology with the idea that early cognitive deficits may constitute a common symptom of brain diseases is proposed.

Clinical utility of cerebrospinal fluid biomarkers measured by LUMIPULSE® system

OBJECTIVES

Cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are well-established in research settings, but their use in routine clinical practice remains a largely unexploited potential. Here, we examined the relationship between CSF biomarkers, measured by a fully automated immunoassay platform, and brain β-amyloid (Aβ) deposition status confirmed by amyloid positron emission tomography (PET).

METHODS

One hundred ninety-nine CSF samples from clinically diagnosed AD patients enrolled in a clinical study and who underwent amyloid PET were used for the measurement of CSF biomarkers Aβ 1-40 (Aβ40), Aβ 1-42 (Aβ42), total tau (t-Tau), and phosphorylated tau-181 (p-Tau181) using the LUMIPULSE system. These biomarkers and their combinations were compared to amyloid PET classification (negative or positive) using visual read assessments. Several combinations were also analyzed with a multivariable logistic regression model.

RESULTS

Aβ42, t-Tau, and p-Tau181, and the ratios of Aβ42 with other biomarkers had a good diagnostic agreement with amyloid PET imaging. The multivariable logistic regression analysis showed that amyloid PET status was associated with Aβ40 and Aβ42, but other factors, such as MMSE, sex, t-Tau, and p-Tau181, did not significantly add information to the model.

CONCLUSIONS

CSF biomarkers measured with the LUMIPULSE system showed good agreement with amyloid PET imaging. The ratio of Aβ42 with the other analyzed biomarkers showed a higher correlation with amyloid PET than Aβ42 alone, suggesting that the combinations of biomarkers could be useful in the diagnostic assessment in clinical research and potentially in routine clinical practice.

Functional MRI and ApoE4 genotype for predicting cognitive decline in amyloid-positive individuals

Background:

In light of advancements in machine learning techniques, many studies have implemented machine learning approaches combined with data measures to predict and classify Alzheimer’s disease. Studies that predicted cognitive status with longitudinal follow-up of amyloid-positive individuals remain scarce, however.

Objective:

We developed models based on voxel-wise functional connectivity (FC) density mapping and the presence of the ApoE4 genotype to predict whether amyloid-positive individuals would experience cognitive decline after 1 year.

Methods:

We divided 122 participants into cognitive decline and stable cognition groups based on the participants’ change rates in Mini-Mental State Examination scores. In addition, we included 68 participants from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database as an external validation data set. Subsequently, we developed two classification models: the first model included 99 voxels, and the second model included 99 voxels and the ApoE4 genotype as features to train the models by Wide Neural Network algorithm with fivefold cross-validation and to predict the classes in the hold-out test and ADNI data sets.

Results:

The results revealed that both models demonstrated high accuracy in classifying the two groups in the hold-out test data set. The model for FC demonstrated good performance, with a mean F1-score of 0.86. The model for FC combined with the ApoE4 genotype achieved superior performance, with a mean F1-score of 0.90. In the ADNI data set, the two models demonstrated stable performances, with mean F1-scores of 0.77 in the first and second models.

Conclusion:

Our findings suggest that the proposed models exhibited promising accuracy for predicting cognitive status after 1 year in amyloid-positive individuals. Notably, the combination of FC and the ApoE4 genotype increased prediction accuracy. These findings can assist clinicians in predicting changes in cognitive status in individuals with a high risk of Alzheimer’s disease and can assist future studies in developing precise treatment and prevention strategies.

Anti-Inflammatory Agents: An Approach to Prevent Cognitive Decline in Alzheimer's Disease

Systemic inflammation is an organism's response to an assault by the non-self. However, that inflammation may predispose humans to illnesses targeted to organs, including Alzheimer's disease (AD). Lesions in AD have pro-inflammatory cytokines and activated microglial/monocyte/macrophage cells. Up to this point, clinical trials using anti-amyloid monoclonal antibodies have not shown success. Maybe it is time to look elsewhere by combating inflammation. Neuroinflammation with CNS cellular activation and excessive expression of immune cytokines is suspected as the "principal culprit" in the higher risk for sporadic AD. Microglia, the resident immune cell of the CNS, perivascular myeloid cells, and activated macrophages produce IL-1, IL-6 at higher levels in patients with AD. Anti-inflammatory measures that target cellular/cytokine-mediated damage provide a rational therapeutic strategy. We propose a clinical trial using oral type 1 IFNs to act as such an agent; one that decreases IL-1 and IL-6 secretion by activating lamina propria lymphocytes in the gut associated lymphoid tissue with subsequent migration to the brain undergoing inflammatory responses. A clinical trial would be double-blind, parallel 1-year clinical trial randomized 1 : 1 oral active type 1 IFN versus best medical therapy to determine whether ingested type I IFN would decrease the rate of cognitive decline in mild cognitive impairment or mild AD. Using cognitive psychometrics, imaging, and fluid biomarkers (MxA for effective type I IFN activity beyond the gut), we can determine if oral type I IFN can prevent cognitive decline in AD.

Treatment with TNF-α inhibitors versus methotrexate and the association with dementia and Alzheimer's disease

INTRODUCTION

Peripheral inhibition of tumor necrosis factor (TNF)-α, outside of the central nervous system, may result in clinical improvement of Alzheimer's disease (AD) outcomes. TNF-α inhibitors (TNFIs) are effective treatments for various autoimmune conditions and may be effective for preventing and/or treating AD. The objective of this study was to compare the risk of dementia and AD in patients initiating methotrexate versus those initiating TNFIs.

METHODS

Insurance claims data from databases of commercially insured and Medicare-eligible patients were used to estimate the risk of dementia and AD within patients with rheumatoid arthritis (RA) initiating a TNFI versus initiation of methotrexate. A sensitivity analysis included all patients without the RA diagnosis requirement. The at-risk period spanned from the index date until a diagnosis of the outcome, loss-to-follow-up, or receipt of the comparator drug. Patients were matched 1-to-1 using propensity scores. A Cox proportional hazards model was used to estimate the hazard ratio (HR). Negative controls were used to calibrate the results.

RESULTS

A total of 11,092 new TNFI patients and 44,023 new methotrexate patients were identified, and 8925 from each group were matched. The outcome of dementia occurred in 1.4% of patients in both groups. The calibrated results from the Cox regression found no difference between the two groups (commercially insured database: calibrated HR = 0.69, 95% confidence interval = 0.45 to 1.05; Medicare-only database: 1.14, 0.66 to 1.96). Results were similar in all sensitivity analyses: outcome of AD and including patients without RA.

DISCUSSION

No significant difference for the risk of dementia or AD was seen between patients initiating a TNFI versus methotrexate. Although this study cannot conclude whether use of TNFIs is protective against dementia and AD compared with receiving no treatment, there was no evidence that it is more protective than the active comparator methotrexate.

Plasma Neurofilament Light and Future Declines in Cognition and Function in Alzheimer's Disease in the FIT-AD Trial

Background:

Utilities of blood-based biomarkers in Alzheimer’s disease (AD) clinical trials remain unknown.

Objective:

To evaluate the ability of plasma neurofilament light chain (NfL) to predict future declines in cognition and activities of daily living (ADL) outcomes in 26 older adults with mild-to-moderate AD dementia from the FIT-AD Trial.

Methods:

Plasma NfL was measured at baseline and 3 and 6 months. Cognition and ADL were assessed using the AD Assessment Scale-Cognition (ADAS-Cog) and AD Uniform Dataset Instruments and Disability Assessment for Dementia (DAD), respectively, at baseline, 3, 6, 9, and 12 months. Linear mixed effects models were used to examine the associations between baseline or change in plasma NfL and changes in outcomes.

Results:

Higher baseline plasma NfL was associated with greater rate of decline in ADAS-Cog from baseline to 6 months (standardized estimate of 0.00462, p = 0.02853) and in ADL from baseline to 12 months (standardized estimate of –0.00284, p = 0.03338). Greater increase in plasma NfL in short term from baseline to 3 months was associated with greater rate of decline in memory and ADL from 3 to 6 months (standardized estimate of –0.04638 [0.003], p = 0.01635; standardized estimate of –0.03818, p = 0.0435) and greater rate of decline in ADL from 3 to 12 month (standardized estimate of –0.01492, p = 0.01082).

Conclusion:

This study demonstrated that plasma NfL might have the potential to predict cognitive and function decline up to 12 months. However, future studies with bigger sample sizes need to confirm the findings.

Structurally constrained effective brain connectivity

The relationship between structure and function is of interest in many research fields involving the study of complex biological processes. In neuroscience in particular, the fusion of structural and functional data can help to understand the underlying principles of the operational networks in the brain. To address this issue, this paper proposes a constrained autoregressive model leading to a representation of effective connectivity that can be used to better understand how the structure modulates the function. Or simply, it can be used to find novel biomarkers characterizing groups of subjects. In practice, an initial structural connectivity representation is re-weighted to explain the functional co-activations. This is obtained by minimizing the reconstruction error of an autoregressive model constrained by the structural connectivity prior. The model has been designed to also include indirect connections, allowing to split direct and indirect components in the functional connectivity, and it can be used with raw and deconvoluted BOLD signal. The derived representation of dependencies was compared to the well known dynamic causal model, giving results closer to known ground-truth. Further evaluation of the proposed effective network was performed on two typical tasks. In a first experiment the direct functional dependencies were tested on a community detection problem, where the brain was partitioned using the effective networks across multiple subjects. In a second experiment the model was validated in a case-control task, which aimed at differentiating healthy subjects from individuals with autism spectrum disorder. Results showed that using effective connectivity leads to clusters better describing the functional interactions in the community detection task, while maintaining the original structural organization, and obtaining a better discrimination in the case-control classification task.

Distance disintegration delineates the brain connectivity failure of Alzheimer's disease

Alzheimer's disease (AD) is associated with brain network dysfunction. Network-based investigations of brain connectivity have mainly focused on alterations in the strength of connectivity; however, the network breakdown in AD spectrum is a complex scenario in which multiple pathways of connectivity are affected. To integrate connectivity changes that occur under AD-related conditions, here we developed a novel metric that computes the connectivity distance between cortical regions at the voxel level (or nodes). We studied 114 individuals with mild cognitive impairment, 24 with AD, and 27 healthy controls. Results showed that areas of the default mode network, salience network, and frontoparietal network display a remarkable network separation, or greater connectivity distances, from the rest of the brain. Furthermore, this greater connectivity distance was associated with lower global cognition. Overall, the investigation of AD-related changes in paths and distances of connectivity provides a novel framework for characterizing subjects with cognitive impairment; a framework that integrates the overall network topology changes of the brain and avoids biases toward unreferenced connectivity effects.

Dielectric Constant and Conductivity of Blood Plasma: Possible Novel Biomarkers for Alzheimer's Disease

Alzheimer's disease is a complex debilitating neurodegenerative disease for which there is no cure. The lack of reliable biomarkers for Alzheimer's disease has made the evaluation of the efficacy of new treatments difficult and reliant on only clinical symptoms. In an aged population where cognitive function may be deteriorating for other reasons, the dependence on clinical symptoms is also unreliable. However, it is well established that infusion of β-amyloid into the dorsal hippocampus of rats leads to cognitive impairment in a rat model of Alzheimer's disease. Moreover, the blood plasma of β-amyloid-lesioned rats exhibits a distinct variation of the dielectric constant and conductivity when compared to that of normal rats in a time-dependent manner. These two electric parameters of blood plasma may therefore act as potential biomarkers for dementia due to Alzheimer's disease. This review is aimed at highlighting evidences that support blood plasma electrical properties, e.g., dielectric constant and conductivity as possible novel biomarkers for the early development and progression of dementia due to Alzheimer's disease.

Revealing a Novel Landscape of the Association Between Blood Lipid Levels and Alzheimer's Disease: A Meta-Analysis of a Case-Control Study

Objectives: Blood lipid profiles have been ambiguously reported as biomarkers of AD in recent years. This study was conducted to evaluate the correlation between blood lipid levels and AD in later-life and to explore the effectiveness and reliability of blood lipid profiles as biomarkers of AD. Methods: Database searching was conducted using PubMed, the Cochrane Library, EMBASE, and Medline. This study was designed following the Meta-analysis of Observational Studies in Epidemiology (MOOSE) criteria. Review Manager 5.3 (RevMan 5.3) software was adopted to perform meta-analysis evaluating the standard mean difference (SMD) with its 95% confidence intervals (CI). Results: A total of 5,286 participants were enrolled from 27 case-control studies in this meta-analysis. The pooled results demonstrated that total cholesterol (TC) level was significantly associated with AD in late-life (SMD = 0.17, 95% CI: [0.01, 0.32], P = 0.03), especially in the subgroup under 70 years old (SMD: 0.45, 95% CI: [0.11, 0.79], P = 0.01) and the subgroup of Western population (SMD: 0.29, 95% CI: [0.04, 0.53], P = 0.02). In the subgroup under 70 years old, the high-density lipoprotein cholesterol (HDL-C) level (SMD = -0.50, 95% CI: [-0.76, -0.25], P = 0.0001) and the low-density lipoprotein cholesterol (LDL-C) level (SMD = 0.59, 95% CI: [0.02, 1.16], P = 0.04) in the AD group were significantly lower and higher than in the control group, respectively. In the subgroup with a sample size larger than 100 subjects, the LDL-C level was significantly higher in AD patients than in the control elderly group (SMD = 0.31, 95% CI: [0.05, 0.56], P = 0.02). There was no significant association between triglyceride (TG) levels and AD in later-life (SMD = -0.00, 95% CI: [-0.12, 0.12], P = 1.00). Conclusion: TC can be a new predictive biomarker of AD or cognitive decline in later-life. Increased TC levels are found to be associated with an elevated risk of AD. Decreased HDL-C levels and increased LDL-C levels may relate to an elevated risk of AD in subjects aged 60-70. Further comprehensive researches will be necessary in the future.

Clinical validation of the Lumipulse G cerebrospinal fluid assays for routine diagnosis of Alzheimer's disease

BACKGROUND

Ongoing efforts within the Alzheimer's disease (AD) field have focused on improving the intra- and inter-laboratory variability for cerebrospinal fluid (CSF) biomarkers. Fully automated assays offer the possibility to eliminate sample manipulation steps and are expected to contribute to this improvement. Recently, fully automated chemiluminescence enzyme immunoassays for the quantification of all four AD biomarkers in CSF became available. The aims of this study were to (i) evaluate the analytical performance of the Lumipulse G β-Amyloid 1-42 (restandardized to Certified Reference Materials), β-Amyloid 1-40, total Tau, and pTau 181 assays on the fully automated LUMIPULSE G600II; (ii) compare CSF biomarker results of the Lumipulse G assays with the established manual ELISA assays (INNOTEST®) from the same company (Fujirebio); and (iii) establish cut-off values and the clinical performance of the Lumipulse G assays for AD diagnosis.

METHODS

Intra- and inter-assay variation was assessed in CSF samples with low, medium, and high concentrations of each parameter. Method comparison and clinical evaluation were performed on 40 neurological controls (NC) and 80 patients with a diagnosis of probable AD supported by a follow-up ≥ 3 years and/or positive amyloid PET imaging. A small validation cohort of 10 NC and 20 AD patients was also included to validate the cut-off values obtained on the training cohort.

RESULTS

The maximal observed intra-assay and inter-assay coefficients of variation (CVs) were 3.25% and 5.50%, respectively. Method comparisons revealed correlation coefficients ranging from 0.89 (for Aβ40) to 0.98 (for t-Tau), with those for Aβ42 (0.93) and p-Tau (0.94) in-between. ROC curve analysis showed area under the curve values consistently above 0.85 for individual biomarkers other than Aβ40, and with the Aβ42/40, Aβ42/t-Tau, and Aβ42/p-Tau ratios outperforming Aβ42. Validation of the cut-off values in the independent cohort showed a sensitivity ranging from 75 to 95% and a specificity of 100%. The overall percentage of agreement between Lumipulse and INNOTEST was very high (> 87.5%).

CONCLUSIONS

The Lumipulse G assays show a very good analytical performance that makes them well-suited for CSF clinical routine measurements. The good clinical concordance between the Lumipulse G and INNOTEST assays facilitates the implementation of the new method in routine practice.

Method comparison study of the Elecsys® β-Amyloid (1-42) CSF assay versus comparator assays and LC-MS/MS

BACKGROUND

Alzheimer's disease (AD) biomarkers, such as cerebrospinal fluid (CSF) amyloid-β (1-42; Aβ42), can provide high diagnostic accuracy. Several immunoassays are available for Aβ42 quantitation, but standardisation across assays remains an issue. We compared the Elecsys® β-Amyloid (1-42) CSF assay with three assays and two liquid chromatography tandem mass spectrometry (LC-MS/MS) methods.

METHODS

Three method comparison studies evaluated the correlation between the Elecsys® β-Amyloid (1-42) CSF assay versus: INNOTEST® β-AMYLOID(1-42) (860 samples) and the Roche Diagnostics-developed LC-MS/MS method (250 samples); INNO-BIA AlzBio3 and the University of Pennsylvania (UPenn)-developed LC-MS/MS method (250 samples); and ADx-EUROIMMUN Beta-Amyloid (1-42) enzyme-linked immunosorbent assay (ELISA) (49 samples).

RESULTS

High correlation was demonstrated between Elecsys® β-Amyloid (1-42) CSF and comparator assays: INNOTEST® β-AMYLOID(1-42) (Spearman's ρ, 0.954); INNO-BIA AlzBio3 (Spearman's ρ, 0.864); ADx-EUROIMMUN Beta-Amyloid (1-42) ELISA (Pearson's r, 0.925). Elecsys® assay and LC-MS/MS measurements were highly correlated: Pearson's r, 0.949 (Roche Diagnostics-developed method) and 0.943 (UPenn-developed method).

CONCLUSION

Findings from this multicentre evaluation further support use of the Elecsys® β-Amyloid (1-42) CSF assay to aid AD diagnosis. CSF-based certified reference materials should improve agreement across assays and mass spectrometry-based methods, which is essential to establish a global uniform CSF Aβ42 cut-off to detect amyloid pathology.

Oscillatory hyperactivity and hyperconnectivity in young APOE-ɛ4 carriers and hypoconnectivity in Alzheimer's disease

We studied resting-state oscillatory connectivity using magnetoencephalography in healthy young humans (N = 183) genotyped for APOE-ɛ4, the greatest genetic risk for Alzheimer's disease (AD). Connectivity across frequencies, but most prevalent in alpha/beta, was increased in APOE-ɛ4 in a set of mostly right-hemisphere connections, including lateral parietal and precuneus regions of the Default Mode Network. Similar regions also demonstrated hyperactivity, but only in gamma (40-160 Hz). In a separate study of AD patients, hypoconnectivity was seen in an extended bilateral network that partially overlapped with the hyperconnected regions seen in young APOE-ɛ4 carriers. Using machine-learning, AD patients could be distinguished from elderly controls with reasonable sensitivity and specificity, while young APOE-e4 carriers could also be distinguished from their controls with above chance performance. These results support theories of initial hyperconnectivity driving eventual profound disconnection in AD and suggest that this is present decades before the onset of AD symptomology.

Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic

Biomarker discovery and development for clinical research, diagnostics and therapy monitoring in clinical trials have advanced rapidly in key areas of medicine - most notably, oncology and cardiovascular diseases - allowing rapid early detection and supporting the evolution of biomarker-guided, precision-medicine-based targeted therapies. In Alzheimer disease (AD), breakthroughs in biomarker identification and validation include cerebrospinal fluid and PET markers of amyloid-β and tau proteins, which are highly accurate in detecting the presence of AD-associated pathophysiological and neuropathological changes. However, the high cost, insufficient accessibility and/or invasiveness of these assays limit their use as viable first-line tools for detecting patterns of pathophysiology. Therefore, a multistage, tiered approach is needed, prioritizing development of an initial screen to exclude from these tests the high numbers of people with cognitive deficits who do not demonstrate evidence of underlying AD pathophysiology. This Review summarizes the efforts of an international working group that aimed to survey the current landscape of blood-based AD biomarkers and outlines operational steps for an effective academic-industry co-development pathway from identification and assay development to validation for clinical use.

Increased expression of TREM2 in peripheral cells from mild cognitive impairment patients who progress into Alzheimer's disease

BACKGROUND AND PURPOSE

Neuroinflammation plays a role in the aetiopathogenesis of Alzheimer's disease (AD). Triggering receptor expressed on myeloid cells 2 (TREM2), a cell surface receptor of the immunoglobulin superfamily, seems to have protective anti-inflammatory activity in AD.

METHODS

Triggering receptor expressed on myeloid cells 2 expression was analysed in peripheral blood mononuclear cells from healthy subjects (CT) and from patients with either AD or mild cognitive impairment (MCI). MCI patients were re-evaluated at a 2-year follow-up to investigate their progression to AD (MCI-AD) or lack thereof (MCI-MCI).

RESULTS

Triggering receptor expressed on myeloid cells 2 gene expression was higher in AD than CT patients, but was highest in MCI. At recruitment TREM2 levels were higher in MCI-AD than in MCI-MCI, and in MCI-AD were higher initially than at follow-up. TREM2 displayed a moderate degree of sensitivity and specificity for identifying MCI-AD in all MCI patients. Our data showed higher TREM2 levels in allele ε4 of apolipoprotein E (ApoE ε4) carriers than non-carriers in MCI and particularly in MCI-AD.

CONCLUSIONS

These data seem to confirm the protective role of TREM2 in the pre-clinical stage of AD. Upregulation of TREM2 in MCI-AD could be a mechanism to counteract the activation of neuroinflammatory processes. It is possible that TREM2 and ApoE ε4 interact synergistically in the pre-clinical stage of AD. Therefore, TREM2 may be useful as an early peripheral biomarker for the development of AD.

Cerebrospinal fluid biomarkers measured by Elecsys assays compared to amyloid imaging

INTRODUCTION

Levels of amyloid β peptide 42 (Aβ42), total tau, and phosphorylated tau-181 are well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease, but variability in manual plate-based assays has limited their use. We examined the relationship between CSF biomarkers, as measured by a novel automated immunoassay platform, and amyloid positron emission tomography.

METHODS

CSF samples from 200 individuals underwent separate analysis for Aβ42, total tau, and phosphorylated tau-181 with automated Roche Elecsys assays. Aβ40 was measured with a commercial plate-based assay. Positron emission tomography with Pittsburgh Compound B was performed less than 1 year from CSF collection.

RESULTS

Ratios of CSF biomarkers (total tau/Aβ42, phosphorylated tau-181/Aβ42, and Aβ42/Aβ40) best discriminated Pittsburgh Compound B-positive from Pittsburgh Compound B-negative individuals.

DISCUSSION

CSF biomarkers and amyloid positron emission tomography reflect different aspects of Alzheimer's disease brain pathology, and therefore, less-than-perfect correspondence is expected. Automated assays are likely to increase the utility of CSF biomarkers.

Upward drift in cerebrospinal fluid amyloid β 42 assay values for more than 10 years

INTRODUCTION

The best-established cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease are levels of amyloid β 42 (Aβ42), total tau (tau), and phosphorylated tau 181 (ptau). We examined whether a widely used commercial immunoassay for CSF Aβ42, tau, and ptau provided stable measurements for more than ∼10 years.

METHODS

INNOTEST assay values for CSF Aβ42, tau, and ptau from Washington University in St. Louis and VU Medical Center, Amsterdam, were evaluated.

RESULTS

Aβ42 values as measured by the INNOTEST assay drifted upward by approximately 3% per year over the past decade. Tau values remained relatively stable, whereas results for ptau were mixed.

DISCUSSION

Assay drift may reduce statistical power or even confound analyses. The drift in INNOTEST Aβ42 values may reduce diagnostic accuracy for Alzheimer's disease in the clinic. We recommend methods to account for assay drift in existing data sets and to reduce assay drift in future studies.

EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects

We studied whether electroencephalography (EEG)-derived measures of brain oscillatory activity are related to clinical progression in nondemented, amyloid positive subjects. We included 205 nondemented amyloid positive subjects (63 subjective cognitive decline [SCD]; 142 mild cognitive impairment [MCI]) with a baseline resting-state EEG data and ≥1-year follow-up. Peak frequency and relative power of 4 frequency bands were calculated. Relationships between normalized EEG measures and time to clinical progression (conversion from SCD to MCI/dementia or from MCI to dementia) were analyzed using Cox proportional hazard models. One hundred eight (53%) subjects clinically progressed after 2.1 (IQR 1.3-3.0) years. In the total sample, none of the EEG spectral measures were significant predictors. Stratified for baseline diagnosis, we found that in SCD patients higher delta and theta power (HR [95% CI] = 1.7 [1.0-2.7] resp. 2.3 [1.2-4.4]), and lower alpha power and peak frequency (HR [95% CI] = 0.5 [0.3-1.0] resp. 0.6 [0.4-1.0]) were associated with clinical progression over time. In amyloid positive subjects with normal cognition, slowing of oscillatory brain activity is related to clinical progression.

Diabesity and Brain Energy Metabolism: The Case of Alzheimer's Disease

It is widely accepted that high calorie diets and a sedentary lifestyle sturdily influence the incidence and outcome of type 2 diabetes and obesity, which can occur simultaneously, a situation called diabesity. Tightly linked with metabolic and energy regulation, a close association between diabetes and Alzheimer's disease (AD) has been proposed. Among the common pathogenic mechanisms that underpin both conditions, insulin resistance, brain glucose hypometabolism, and metabolic dyshomeostasis appear to have a pivotal role. This century is an unprecedented diabetogenic period in human history, so therapeutic strategies and/or approaches to control and/or revert this evolving epidemic is of utmost importance. This chapter will make a brief contextualization about the impact that diabetes and obesity can exert in brain structure and function alongside with a brief survey about the role of insulin in normal brain function, exploring its roles in cognition and brain glucose metabolism. Later, attention will be given to the intricate relation of diabesity, insulin resistance, and AD. Finally, both pharmacological and lifestyle interventions will also be reviewed as strategies aimed at fighting diabesity and/or AD-related metabolic effects.

Fluselenamyl: A Novel Benzoselenazole Derivative for PET Detection of Amyloid Plaques (Aβ) in Alzheimer's Disease

Fluselenamyl (5), a novel planar benzoselenazole shows traits desirable of enabling noninvasive imaging of Aβ pathophysiology in vivo; labeling of both diffuse (an earlier manifestation of neuritic plaques) and fibrillar plaques in Alzheimer's disease (AD) brain sections, and remarkable specificity for mapping Aβ compared with biomarker proteins of other neurodegenerative diseases. Employing AD homogenates, [¹⁸F]-9, a PET tracer demonstrates superior (2-10 fold higher) binding affinity than approved FDA tracers, while also indicating binding to high affinity site on Aβ plaques. Pharmacokinetic studies indicate high initial influx of [¹⁸F]-9 in normal mice brains accompanied by rapid clearance in the absence of targeted plaques. Following incubation in human serum, [¹⁸F]-9 indicates presence of parental compound up to 3h thus indicating its stability. Furthermore, in vitro autoradiography studies of [¹⁸F]-9 with AD brain tissue sections and ex vivo autoradiography studies in transgenic mouse brain sections show cortical Aβ binding, and a fair correlation with Aβ immunostaining. Finally, multiphoton- and microPET/CT imaging indicate its ability to penetrate brain and label parenchymal plaques in transgenic mice. Following further validation of its performance in other AD rodent models and nonhuman primates, Fluselenamyl could offer a platform technology for monitoring earliest stages of Aβ pathophysiology in vivo.

Evaluating the clinical relevance of a cognitive composite outcome measure: An analysis of 1414 participants from the 5-year GuidAge Alzheimer's prevention trial

INTRODUCTION

Composite cognitive scores have been developed as primary outcome measures for preclinical/prevention trials for Alzheimer's disease (AD), mainly using observational data and with little consideration of clinical relevance.

METHODS

Secondary analysis of placebo group data from a 5-year AD prevention trial. The composite score was the average of the following z scores: MMSE orientation items, Free and Cued Selective Reminding Test, Category Fluency, Trail Making Test-part B.

RESULTS

Composite score change from baseline differed significantly by age, APOE genotype, and CDR progression and AD dementia status. A 1 point decrease in baseline score was highly predictive of 5-year AD dementia risk (HR = 3.51, 95% CI, 2.62-4.71, P < .001). The 1 year minimum clinically important difference was estimated at -0.3 points and predicted AD dementia.

DISCUSSION

We explored the clinical relevance of a composite score in a prevention trial setting. This type of analysis facilitates the interpretation of composite scores and informs power calculations.

Preclinical Alzheimer's disease: Definition, natural history, and diagnostic criteria

During the past decade, a conceptual shift occurred in the field of Alzheimer's disease (AD) considering the disease as a continuum. Thanks to evolving biomarker research and substantial discoveries, it is now possible to identify the disease even at the preclinical stage before the occurrence of the first clinical symptoms. This preclinical stage of AD has become a major research focus as the field postulates that early intervention may offer the best chance of therapeutic success. To date, very little evidence is established on this "silent" stage of the disease. A clarification is needed about the definitions and lexicon, the limits, the natural history, the markers of progression, and the ethical consequence of detecting the disease at this asymptomatic stage. This article is aimed at addressing all the different issues by providing for each of them an updated review of the literature and evidence, with practical recommendations.

Amyloid-β-Secondary Structure Distribution in Cerebrospinal Fluid and Blood Measured by an Immuno-Infrared-Sensor: A Biomarker Candidate for Alzheimer's Disease

The misfolding of the Amyloid-beta (Aβ) peptide into β-sheet enriched conformations was proposed as an early event in Alzheimer's Disease (AD). Here, the Aβ peptide secondary structure distribution in cerebrospinal fluid (CSF) and blood plasma of 141 patients was measured with an immuno-infrared-sensor. The sensor detected the amide I band, which reflects the overall secondary structure distribution of all Aβ peptides extracted from the body fluid. We observed a significant downshift of the amide I band frequency of Aβ peptides in Dementia Alzheimer type (DAT) patients, which indicated an overall shift to β-sheet. The secondary structure distribution of all Aβ peptides provides a better marker for DAT detection than a single Aβ misfold or the concentration of a specific oligomer. The discrimination between DAT and disease control patients according to the amide I frequency was in excellent agreement with the clinical diagnosis (accuracy 90% for CSF and 84% for blood). The amide I band maximum above or below the decisive marker frequency appears as a novel spectral biomarker candidate of AD. Additionally, a preliminary proof-of-concept study indicated an amide I band shift below the marker band already in patients with mild cognitive impairment due to AD. The presented immuno-IR-sensor method represents a promising, simple, robust, and label-free diagnostic tool for CSF and blood analysis.

Revolutionizing Alzheimer's disease and clinical trials through biomarkers

The Alzheimer's Association's Research Roundtable met in May 2014 to explore recent progress in developing biomarkers to improve understanding of disease pathogenesis and expedite drug development. Although existing biomarkers have proved extremely useful for enrichment of subjects in clinical trials, there is a clear need to develop novel biomarkers that are minimally invasive and that more broadly characterize underlying pathogenic mechanisms, including neurodegeneration, neuroinflammation, and synaptic dysfunction. These may include blood-based assays and new neuropsychological testing protocols, as well as novel ligands for positron emission tomography imaging, and advanced magnetic resonance imaging methodologies. In addition, there is a need for biomarkers that can serve as theragnostic markers of response to treatment. Standardization remains a challenge, although international consortia have made substantial progress in this area and provide lessons for future standardization efforts.

Prevention of sporadic Alzheimer's disease: lessons learned from clinical trials and future directions

Interventions that have even quite modest effects at the individual level could drastically reduce the future burden of dementia associated with Alzheimer's disease at the population level. In the past three decades, both pharmacological and lifestyle interventions have been studied for the prevention of cognitive decline or dementia in randomised controlled trials of individuals mostly aged older than 50-55 years with or without risk factors for Alzheimer's disease. Several trials testing the effects of physical activity, cognitive training, or antihypertensive interventions showed some evidence of efficacy on a primary cognitive endpoint. However, most of these trials had short follow-up periods, and further evidence is needed to confirm effectiveness and establish the optimum design or dose of interventions and ideal target populations. Important innovations in ongoing trials include the development of multidomain interventions, and the use of biomarker or genetic inclusion criteria. Challenges include the use of adaptive trial designs, the development of standardised, sensitive outcome measures, and the need for interventions that can be implemented in resource-poor settings.

Prevention studies in Alzheimer's disease: progress towards the development of new therapeutics

Alzheimer's disease (AD) is the most common form of dementia and is a major cause of disability and dependency amongst older people. AD drugs approved so far are symptomatic treatments and are not thought to affect the underlying disease process. Trials conducted with agents aiming to slow or stop disease progression in patients with AD have all failed, perhaps because they were tested too late in the disease process. Therefore, there has been a move towards prevention of AD. This paper presents an overview of trials testing pharmacological interventions for sporadic AD prevention. Those tested to date were initially developed for the treatment of AD or for the treatment of other conditions, rather than being specifically developed for AD prevention. Associated issues, such as evidence of 'proof-of-concept,' doses and safety, are discussed. A major shift has taken place in the methodology of AD prevention trials since the results of the first trials were published in the 1990s. New directions that are currently being considered in ongoing or future prevention trials are discussed, in terms of endpoints, target populations, and study design. The use of AD-specific drugs to prevent AD in high-risk individuals is currently limited by a lack of validated predictive and surrogate markers. Population approaches, such as lifestyle changes, are an alternative strategy that could be of public health interest, but may provide only limited benefits for individuals. The best chance of preventing AD may come from a combination of individual and population prevention approaches.

Diffusion imaging changes in grey matter in Alzheimer's disease: a potential marker of early neurodegeneration

Alzheimer's disease (AD) is recognized to have a long presymptomatic period, during which there is progressive accumulation of molecular pathology, followed by inexorable neuronal damage. The ability to identify presymptomatic individuals with evidence of neurodegenerative change, to stage their disease, and to track progressive changes will be important for early diagnosis and for prevention trials. Despite recent advances, particularly in magnetic resonance imaging, our ability to identify early neurodegenerative changes reliably is limited. The development of diffusion-weighted magnetic resonance imaging, which is sensitive to microstructural changes not visible with conventional volumetric techniques, has led to a number of diffusion imaging studies in AD; these have largely focused on white matter changes. However, in AD cerebral grey matter is affected very early, with pathological studies suggesting that grey matter changes predate those in white matter. In this article we review the growing number of studies that assess grey matter diffusivity changes in AD. Although use of the technique is still at a relatively early stage, results so far have been promising. Initial studies identified changes in diffusion measures in the hippocampi of patients with mild cognitive impairment, which predated macroscopic volume loss, with positive predictive value for progression to AD dementia. More recent studies have identified abnormalities in multiple neocortical areas (particularly the posterior cingulate) at various stages of disease progression. Studies of patients who carry genetic mutations predisposing to autosomal dominant familial AD have shown cortical and subcortical grey matter diffusivity changes several years before the expected onset of the first clinical symptoms. The technique is not without potential methodological difficulties, especially relating to partial volume effects, although recent advances appear to be reducing such issues. Going forward, further utilization of grey matter diffusion measurements in AD may improve our understanding with regards to the timing and nature of the earliest presymptomatic neurodegenerative changes. This imaging technique may also be useful in comparing and contrasting subtle variations in different disease subgroups, and as a sensitive outcome measure for presymptomatic clinical trials in AD and other neurodegenerative diseases.

Synthesis, characterization, and preclinical validation of a PET radiopharmaceutical for interrogating Aβ (β-amyloid) plaques in Alzheimer's disease

Background

PET radiopharmaceuticals capable of imaging β-amyloid (Aβ) plaque burden in the brain could offer highly valuable diagnostic tools for clinical studies of Alzheimer’s disease. To further supplement existing armamentarium of FDA-approved agents as well as those under development, and to correlate multiphoton-imaging data reported earlier, herein, we describe preclinical validation of a PET tracer.

Methods

A novel PET radiopharmaceutical (¹⁸F-7B) was synthesized and characterized. To assess its affinity for Aβ, binding assays with Aβ_1-42 fibrils, Alzheimer’s disease (AD) homogenates, and autoradiography studies and their IHC correlations were performed. For assessing its overall pharmacokinetic profiles in general and its ability to cross the blood-brain barrier (BBB) in particular, biodistribution studies in normal mice were performed. Finally, for evaluating potential for ¹⁸F-7B to serve as a targeted Aβ probe, the microPET/CT imaging was performed in age-matched amyloid precursor protein/presenilin-1 (APP/PS1) mice and wild-type (WT) counterparts.

Results

The radiotracer ¹⁸F-7B shows saturable binding to autopsy-confirmed AD homogenates (K_d = 17.7 nM) and Aβ_1-42 fibrils (K_d = 61 nM). Preliminary autoradiography studies show binding of ¹⁸F-7B to cortical Aβ plaques in autopsy-confirmed AD tissue sections, inhibition of that binding by unlabeled counterpart 7A-indicating specificity, and a good correlation of tracer binding with Aβ immunostaining. The agent indicates high initial penetration into brains (7.23 ± 0.47%ID/g; 5 min) of normal mice, thus indicating a 5-min/120-min brain uptake clearance ratio of 4.7, a benchmark value (>4) consistent with the ability of agents to traverse the BBB to enable PET brain imaging. Additionally, ¹⁸F-7B demonstrates the presence of parental species in human serum. Preliminary microPET/CT imaging demonstrates significantly higher retention of ¹⁸F-7B in brains of transgenic mice compared with their WT counterparts, consistent with expected binding of the radiotracer to Aβ plaques, present in APP/PS1 mice, compared with their age-matched WT counterparts lacking those Aβ aggregates.

Conclusions

These data offer a platform scaffold conducive to further optimization for developing new PET tracers to study Aβ pathophysiology in vitro and in vivo.

Molecular imaging biomarkers for dementia with Lewy bodies: an update

BACKGROUND

Dementia with Lewy body (DLB) is considered to be the second most common form of neurodegenerative disorders after Alzheimer's disease (AD), affecting as many as 100,000 people in the UK and up to 1.3 million in the USA. However, nearly half of patients with DLB remain undiagnosed thus depriving many of them from an early and adequate treatment of their distressing symptoms. Accurate and early diagnosis of DLB is important for both patients and their caregivers, since the neuropsychiatric symptoms require specific management.

METHODS

In the current study, we review the most recent developments in the field of molecular nuclear imaging to diagnose DLB.

RESULTS

The review addresses, the neurotransmitter based (dopaminergic, cholinergic, and glutamatergic) nuclear imaging techniques, role of the autonomic dysfunction and its visualization in DLB with myocardial sympathetic imaging and vesicular catecholamine uptake, as well as the use of amyloid polypeptides and glial markers as molecular imaging probes in the clinical diagnosis of DLB.

CONCLUSIONS

Most of the above nuclear imaging methods are restricted to highly specialized clinical centers, and thus not applicable to a large number of patients requiring dementia (e.g. DLB) diagnosis in routine clinical setting. Validating them against more readily accessible peripheral biomarkers, e.g. CSF and blood biomarkers linked to the DLB process, may facilitate their use in wider clinical settings.

Biomarkers in the diagnosis and management of Alzheimer's disease

Traditionally Alzheimer's disease (AD) has been diagnosed and its course followed based on clinical observations and cognitive testing, and confirmed postmortem by demonstrating amyloid plaques and neurofibrillary tangles in the brain. But the growing recognition that the disease process is ongoing, damaging the brain long before clinical findings appear, has intensified a search for biomarkers that might allow its very early diagnosis and the objective assessment of its responses to putative treatments. At present at least eight biochemical measurements or scanning procedures are used as biomarkers, usually in panels, by neurologists and others. The biochemical measurements are principally of amyloid proteins and their A-beta precursors, or of tau proteins. Brain atrophy can be assessed by means of structural magnetic resonance imaging (sMRI), and decreased blood flow and metabolism can be estimated by functional magnetic resonance imaging (fMRI). [18F]fluorodeoxyglucose-positron emission tomography (FDG-PET) is used to measure the brain's energy utilization and to infer synaptic number. Impaired connectivity between brain regions is indicated by diffusion tensor imaging (DTI), while magnetic resonance spectroscopy (MRS) provides metabolic markers of diminished cell number. Additional proposed biomarkers utilize electroencephalography (EEG) and magnetoencephalography (MEG) for quantifying impairments in connectivity. Genetic analyses illustrate the heterogeneity of disease processes that can cause cognitive impairment syndromes. Recent observations awaiting confirmation suggest that levels of some plasma phospholipids can also be biomarkers of AD and that reductions in these levels can enable the accurate prediction that a cognitively normal individual will go on to develop MCI or AD within 2 years.

Eyes-closed task-free electroencephalography in clinical trials for Alzheimer's disease: an emerging method based upon brain dynamics

Electroencephalography (EEG) is a longstanding technique to measure electrical brain activity and thereby an indirect measure of synaptic activity. Synaptic dysfunction accompanies Alzheimer’s disease (AD) and EEG can be regarded as a potentially useful biomarker in this disease. Lately, emerging analysis techniques of time series have become available for EEG, such as functional connectivity and network analysis, which have increased the possibilities for use in AD clinical trials. In this review, we report the EEG changes in the course of AD, including slowing of the EEG oscillations, decreased functional connectivity in the higher-frequency bands, and decline in optimal functional network organization. We discuss the use of EEG in clinical trials and provide directions for future research.

In vivo SPECT imaging of amyloid-β deposition with radioiodinated imidazo[1,2-a]pyridine derivative DRM106 in a mouse model of Alzheimer's disease

Noninvasive determination of amyloid-β peptide (Aβ) deposition has important significance for early diagnosis and medical intervention for Alzheimer's disease (AD). In the present study, we investigated the availability of radiolabeled DRM106 ((123/125)I-DRM106 [6-iodo-2-[4-(1H-3-pyrazolyl)phenyl]imidazo[1,2-a]pyridine]), a compound with sufficient affinity for the synthesis of human Aβ fibrils and satisfactory metabolic stability, as a SPECT ligand in living brains.

METHOD

The sensitivity of (125)I-DRM106 for detecting Aβ deposition was compared with that of (125)I-IMPY (2-(4'-dimethylaminophenyl)-6-iodo-imidazo[1,2-a]pyridine), a well-known amyloid SPECT ligand, by ex vivo autoradiographic analyses in 18-mo-old amyloid precursor protein transgenic mice. To verify the sensitivity and quantitation of radiolabeled DRM106 for in vivo imaging, we compared the detectability of Aβ plaques with (123)I-DRM106 and a well-known amyloid PET agent, (11)C-labeled Pittsburgh compound B ((11)C-PiB), in 29-mo-old transgenic mice and age-matched nontransgenic littermates. Additionally, we compared the binding characteristics of (125)I-DRM106 with those of (11)C-PiB and (11)C-PBB3, which selectively bind to Aβ plaques and preferentially to tau aggregates, respectively, in postmortem AD brain sections.

RESULTS

Ex vivo autoradiographic analysis showed that measurement with (125)I-DRM106 has a higher sensitivity for detecting Aβ accumulation than with (125)I-IMPY in transgenic mice. SPECT imaging with (123)I-DRM106 also successfully detected Aβ deposition in living aged transgenic mice and showed strong correlation (R = 0.95, P < 0.01) in quantitative analysis for Aβ plaque detection by PET imaging with (11)C-PiB, implying that sensitivity and quantitation of SPECT imaging with (123)I-DRM106 are almost as good as (11)C-PiB PET for the detectability of Aβ deposition. Further, the addition of nonradiolabeled DRM106 fully blocked the binding of (125)I-DRM106 and (11)C-PiB, but not (11)C-PBB3, to AD brain sections, and (125)I-DRM106 showed a lower binding ratio of the diffuse plaque-rich lateral temporal cortex to the dense-cored/neuritic plaque-rich hippocampal CA1 area, compared with (11)C-PiB.

CONCLUSION

All of these data demonstrated the high potential of (123)I-DRM106 for amyloid imaging in preclinical and clinical application, and it might more preferentially detect dense-cored/neuritic amyloid deposition, which is expected to be closely associated with neuropathologic changes of AD.

Advances in MRI biomarkers for the diagnosis of Alzheimer's disease

With the prevalence of Alzheimer's disease (AD) predicted to increase substantially over the coming decades, the development of effective biomarkers for the early detection of the disease is paramount. In this short review, the main neuroimaging techniques which have shown potential as biomarkers for AD are introduced, with a focus on MRI. Structural MRI measures of the hippocampus and medial temporal lobe are still the most clinically validated biomarkers for AD, but newer techniques such as functional MRI and diffusion tensor imaging offer great scope in tracking changes in the brain, particularly in functional and structural connectivity, which may precede gray matter atrophy. These new advances in neuroimaging methods require further development and crucially, standardization; however, before they are used as biomarkers to aid in the diagnosis of AD.

Attempted and successful compensation in preclinical and early manifest neurodegeneration - a review of task FMRI studies

Several models of neural compensation in healthy aging have been suggested to explain brain activity that aids to sustain cognitive function. Applying recently suggested criteria of "attempted" and "successful" compensation, we reviewed existing literature on compensatory mechanisms in preclinical Huntington's disease (HD) and amnestic mild cognitive impairment (aMCI). Both disorders constitute early stages of neurodegeneration ideal for examining compensatory mechanisms and developing targeted interventions. We strived to clarify whether compensation criteria derived from healthy aging populations can be applied to early neurodegeneration. To concentrate on the close coupling of cognitive performance and brain activity, we exclusively addressed task fMRI studies. First, we found evidence for parallels in compensatory mechanisms between healthy aging and neurodegenerative disease. Several studies fulfilled criteria of attempted compensation, while reports of successful compensation were largely absent, which made it difficult to conclude on. Second, comparing working memory studies in preclinical HD and aMCI, we identified similar compensatory patterns across neurodegenerative disorders in lateral and medial prefrontal cortex. Such patterns included an inverted U-shaped relationship of neurodegeneration and compensatory activity spanning from preclinical to manifest disease. Due to the lack of studies systematically targeting all criteria of compensation, we propose an exemplary study design, including the manipulation of compensating brain areas by brain stimulation. Furthermore, we delineate the benefits of targeted interventions by non-invasive brain stimulation, as well as of unspecific interventions such as physical activity or cognitive training. Unambiguously detecting compensation in early neurodegenerative disease will help tailor interventions aiming at sustained overall functioning and delayed clinical disease onset.

Neural correlates of cognitive intervention in persons at risk of developing Alzheimer's disease

Cognitive training is an emergent approach that has begun to receive increased attention in recent years as a non-pharmacological, cost-effective intervention for Alzheimer’s disease (AD). There has been increasing behavioral evidence regarding training-related improvement in cognitive performance in early stages of AD. Although these studies provide important insight about the efficacy of cognitive training, neuroimaging studies are crucial to pinpoint changes in brain structure and function associated with training and to examine their overlap with pathology in AD. In this study, we reviewed the existing neuroimaging studies on cognitive training in persons at risk of developing AD to provide an overview of the overlap between neural networks rehabilitated by the current training methods and those affected in AD. The data suggest a consistent training-related increase in brain activity in medial temporal, prefrontal, and posterior default mode networks, as well as increase in gray matter structure in frontoparietal and entorhinal regions. This pattern differs from the observed pattern in healthy older adults that shows a combination of increased and decreased activity in response to training. Detailed investigation of the data suggests that training in persons at risk of developing AD mainly improves compensatory mechanisms and partly restores the affected functions. While current neuroimaging studies are quite helpful in identifying the mechanisms underlying cognitive training, the data calls for future multi-modal neuroimaging studies with focus on multi-domain cognitive training, network level connectivity, and individual differences in response to training.

Sleep deficits in mild cognitive impairment are related to increased levels of plasma amyloid-β and cortical thinning

Evidence suggests that amyloid-beta (Aβ) depositions parallel sleep deficits in Alzheimer's disease (AD). However, it remains unknown whether impaired sleep and changes in plasma Aβ levels are related in amnestic mild cognitive impairment (aMCI) subjects, and whether both markers are further associated with cortical thinning in canonical AD regions. To jointly address this issue, we investigated relationships between changes in physiological sleep and plasma Aβ concentrations in 21 healthy old (HO) adults and 21 aMCI subjects, and further assessed whether these two factors were associated with cortical loss in each group. aMCI, but not HO subjects, showed significant relationships between disrupted slow-wave sleep (SWS) and increased plasma levels of Aβ42. We also found that shortened rapid-eye movement (REM) sleep in aMCI correlated with thinning of the posterior cingulate, precuneus, and postcentral gyrus; whereas higher levels of Aβ40 and Aβ42 accounted for grey matter (GM) loss of posterior cingulate and entorhinal cortex, respectively. These results support preliminary relationships between Aβ burden and altered sleep physiology observed in animal models of AD amyloidosis, and provide precise cortical correlates of these changes in older adults with aMCI. Taken together, these findings open new research avenues on the combined role of sleep, peripheral Aβ levels and cortical integrity in tracking the progression from normal aging to early neurodegeneration.

Mild cognitive impairment. Part 2: Biological markers for diagnosis and prediction of dementia in Alzheimer's disease

OBJECTIVE

To present a critical review of publications reporting on the rationale and clinical implications of the use of biomarkers for the early diagnosis of Alzheimer's disease (AD).

METHODS

We conducted a systematic search of the PubMed and Web of Science electronic databases, limited to articles published in English between 1999 and 2012, and based on the following terms: mild cognitive impairment, Alzheimer's disease OR dementia, biomarkers. We retrieved 1,130 articles, of which 175 were reviews. Overall, 955 original articles were eligible.

RESULTS

The following points were considered relevant for the present review: a) rationale for biomarkers research in AD and mild cognitive impairment (MCI); b) usefulness of distinct biomarkers for the diagnosis and prediction of AD; c) the role of multimodality biomarkers for the diagnosis and prediction of AD; d) the role of biomarkers in clinical trials of patients with AD and MCI; and e) current limitations to the widespread use of biomarkers in research and clinical settings.

CONCLUSION

Different biomarkers are useful for the early diagnosis and prediction of AD in at-risk subjects. Nonetheless, important methodological limitations need to be overcome for widespread use of biomarkers in research and clinical settings.

Impaired cortical oscillatory coupling in mild cognitive impairment: anatomical substrate and ApoE4 effects

Our current knowledge about the anatomical substrate of impaired resting-state cortical oscillatory coupling in mild cognitive impairment is still rudimentary. Here, we show that both resting-state oscillatory coupling and its anatomical correlates clearly distinguish healthy older (HO) adults from individuals with amnestic mild cognitive impairment (aMCI). aMCI showed failures in neural-phase coupling of resting-state electroencephalographic alpha activity mostly evident between fronto-temporal and parietal regions. As oligomers of amyloid-beta (Aβ) are linked to synaptic dysfunction in Alzheimer's disease (AD), we further investigated whether plasma concentrations of these oligomers (Aβ40 and Aβ42) accounted for impaired patterns of oscillatory coupling in aMCI. Results revealed that decreased plasma Aβ42 was associated with augmented coupling of parieto-temporal regions in HO subjects, but no relationship was found in aMCI. Oscillatory coupling of frontal regions was also significantly reduced in aMCI carriers of the ε4 allele of the Apolipoprotein E (ApoE) compared to ε4 noncarriers, although neither neuroanatomical nor plasma Aβ changes accounted for this difference. However, the abnormal pattern of oscillatory coupling in aMCI was negatively related to volume of the angular gyrus, and positively related to volume of the precuneus and the splenium of the corpus callosum. Previous evidence suggests that all these regions are neuropathological targets of AD. The current study takes that scenario one step further, suggesting that this anatomical damage could be responsible for disrupted cortical oscillatory coupling in aMCI. Together, these data shed light on how the MCI status modifies anatomo-functional relationships underlying coordination of large-scale cortical systems in the resting-state.