Biological markers for therapeutic trials in Alzheimer's disease. Proceedings of the biological markers working group; NIA initiative on neuroimaging in Alzheimer's disease

Controversial Past, Splendid Present, Unpredictable Future: A Brief Review of Alzheimer Disease History

Background: The concept of Alzheimer disease (AD)-since its histological discovery by Alzheimer to the present day-has undergone substantial modifications. Methods: We conducted a classical narrative review of this field with a bibliography selection (giving preference to Medline best match). Results: The following subjects are reviewed and discussed: Alzheimer's discovery, Kraepelin's creation of a new disease that was a rare condition until the 1970's, the growing interest and investment in AD as a major killer in a society with a large elderly population in the second half of the 20th century, the consolidation of the AD clinicopathological model, and the modern AD nosology based on the dominant amyloid hypothesis among many others. In the 21st century, the development of AD biomarkers has supported a novel biological definition of AD, although the proposed therapies have failed to cure this disease. The incidence of dementia/AD has shown a decrease in affluent countries (possibly due to control of risk factors), and mixed dementia has been established as the most frequent etiology in the oldest old. Conclusions: The current concept of AD lacks unanimity. Many hypotheses attempt to explain its complex physiopathology entwined with aging, and the dominant amyloid cascade has yielded poor therapeutic results. The reduction in the incidence of dementia/AD appears promising but it should be confirmed in the future. A reevaluation of the AD concept is also necessary.

Blood-based biomarkers for Alzheimer's disease: Current state and future use in a transformed global healthcare landscape

Timely detection of the pathophysiological changes and cognitive impairment caused by Alzheimer's disease (AD) is increasingly pressing because of the advent of biomarker-guided targeted therapies that may be most effective when provided early in the disease. Currently, diagnosis and management of early AD are largely guided by clinical symptoms. FDA-approved neuroimaging and cerebrospinal fluid biomarkers can aid detection and diagnosis, but the clinical implementation of these testing modalities is limited because of availability, cost, and perceived invasiveness. Blood-based biomarkers (BBBMs) may enable earlier and faster diagnoses as well as aid in risk assessment, early detection, prognosis, and management. Herein, we review data on BBBMs that are closest to clinical implementation, particularly those based on measures of amyloid-β peptides and phosphorylated tau species. We discuss key parameters and considerations for the development and potential deployment of these BBBMs under different contexts of use and highlight challenges at the methodological, clinical, and regulatory levels.

Alzheimer's disease amyloid-β pathology in the lens of the eye

Neuropathological hallmarks of Alzheimer's disease (AD) include pathogenic accumulation of amyloid-β (Aβ) peptides and age-dependent formation of amyloid plaques in the brain. AD-associated Aβ neuropathology begins decades before onset of cognitive symptoms and slowly progresses over the course of the disease. We previously reported discovery of Aβ deposition, β-amyloidopathy, and co-localizing supranuclear cataracts (SNC) in lenses from people with AD, but not other neurodegenerative disorders or normal aging. We confirmed AD-associated Aβ molecular pathology in the lens by immunohistopathology, amyloid histochemistry, immunoblot analysis, epitope mapping, immunogold electron microscopy, quantitative immunoassays, and tryptic digest mass spectrometry peptide sequencing. Ultrastructural analysis revealed that AD-associated Aβ deposits in AD lenses localize as electron-dense microaggregates in the cytoplasm of supranuclear (deep cortex) fiber cells. These Aβ microaggregates also contain αB-crystallin and scatter light, thus linking Aβ pathology and SNC phenotype expression in the lenses of people with AD. Subsequent research identified Aβ lens pathology as the molecular origin of the distinctive cataracts associated with Down syndrome (DS, trisomy 21), a chromosomal disorder invariantly associated with early-onset Aβ accumulation and Aβ amyloidopathy in the brain. Investigation of 1249 participants in the Framingham Eye Study found that AD-associated quantitative traits in brain and lens are co-heritable. Moreover, AD-associated lens traits preceded MRI brain traits and cognitive deficits by a decade or more and predicted future AD. A genome-wide association study of bivariate outcomes in the same subjects identified a new AD risk factor locus in the CTNND2 gene encoding δ-catenin, a protein that modulates Aβ production in brain and lens. Here we report identification of AD-related human Aβ (hAβ) lens pathology and age-dependent SNC phenotype expression in the Tg2576 transgenic mouse model of AD. Tg2576 mice express Swedish mutant human amyloid precursor protein (APP-Swe), accumulate hAβ peptides and amyloid pathology in the brain, and exhibit cognitive deficits that slowly progress with increasing age. We found that Tg2576 trangenic (Tg⁺) mice, but not non-transgenic (Tg^-) control mice, also express human APP, accumulate hAβ peptides, and develop hAβ molecular and ultrastructural pathologies in the lens. Tg2576 Tg⁺ mice exhibit age-dependent Aβ supranuclear lens opacification that recapitulates lens pathology and SNC phenotype expression in human AD. In addition, we detected hAβ in conditioned medium from lens explant cultures prepared from Tg⁺ mice, but not Tg^- control mice, a finding consistent with constitutive hAβ generation in the lens. In vitro studies showed that hAβ promoted mouse lens protein aggregation detected by quasi-elastic light scattering (QLS) spectroscopy. These results support mechanistic (genotype-phenotype) linkage between Aβ pathology and AD-related phenotypes in lens and brain. Collectively, our findings identify Aβ pathology as the shared molecular etiology of two age-dependent AD-related cataracts associated with two human diseases (AD, DS) and homologous murine cataracts in the Tg2576 transgenic mouse model of AD. These results represent the first evidence of AD-related Aβ pathology outside the brain and point to lens Aβ as an optically-accessible AD biomarker for early detection and longitudinal monitoring of this devastating neurodegenerative disease.

Primitive detection of Alzheimer’s disease using neuroimaging: A progression model for Alzheimer’s disease: Their applications, benefits, and drawbacks

Alzheimer’s disease (A.D.) is the most widespread type of Dementia, and it is not a curable neurodegenerative disease that affects millions of older people. Researchers were able to use their understanding of Alzheimer’s disease risk variables to develop enrichment processes for longitudinal imaging studies. Using this method, they reduced their sample size and study time. This paper describes the primitive detective of Alzheimer’s diseases using Neuroimaging techniques. Several preprocessing methods were used to ensure that the dataset was ready for subsequent feature extraction and categorization. The noise was reduced by converting and averaging many scan frames from real to DCT space. Both sides of the averaged image were filtered and combined into a single shot after being converted to real space. InceptionV3 and DenseNet201 are two pre-trained models used in the suggested model. The PCA approach was used to select the traits, and the resulting explained variance ratio was 0.99The Simons Foundation Autism Research Initiative (SFARI)—Simon’s Simplex Collection (SSC)—and UCI machine learning datasets showed that our method is faster and more successful at identifying complete long-risk patterns when compared to existing methods.

A Comparison of Cerebrospinal Fluid Beta-Amyloid and Tau in Idiopathic Normal Pressure Hydrocephalus and Neurodegenerative Dementias

Purpose

Idiopathic normal pressure hydrocephalus (iNPH) is the leading reversible cause of cognitive impairment and gait disturbance that has similar clinical manifestations and accompanies to major neurodegenerative disorders in older adults. We aimed to investigate whether cerebrospinal fluid (CSF) biomarker for Alzheimer’s disease (AD) may be useful in the differential diagnosis of iNPH.

Patients and Methods

Amyloid-beta (Aß) 42 and 40, total tau (t-tau), phosphorylated tau (p-tau) were measured via ELISA in 192 consecutive CSF samples of patients with iNPH (n=80), AD (n=48), frontotemporal dementia (FTD) (n=34), Lewy body diseases (LBDs) (n=30) consisting of Parkinson’s disease dementia and dementia with Lewy bodies.

Results

The mean age of the study population was 75.6±7.7 years, and 54.2% were female. CSF Aβ₄₂ levels were significantly higher, and p-tau and t-tau levels were lower in iNPH patients than in those with AD and LBDs patients. Additionally, iNPH patients had significantly higher levels of t-tau than those with FTD. Age and sex-adjusted multi-nominal regression analysis revealed that the odds of having AD relative to iNPH decreased by 37% when the Aβ₄₂ level increased by one standard deviation (SD), and the odds of having LBDs relative to iNPH decreased by 47%. The odds of having LBDs relative to iNPH increased 76% when the p-tau level increased 1SD. It is 2.5 times more likely for a patient to have LBD relative to NPH and 2.1 times more likely to have AD relative to iNPH when the t-tau value increased 1SD.

Conclusion

Our results suggest that levels of CSF Aβ₄₂, p-tau, and t-tau, in particularly decreased t-tau, are of potential value in differentiating iNPH from LBDs and also confirm previous studies reporting t-tau level is lower and Aβ₄₂ level is higher in iNPH than in AD.

Shared genetic influences on resting‐state functional networks of the brain

The amplitude of activation in brain resting state networks (RSNs), measured with resting‐state functional magnetic resonance imaging, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome‐wide association studies (GWASs) explored the genetic underpinnings of individual variation in RSN activity. Yet univariate genomic analyses do not describe the pleiotropic nature of RSNs. In this study, we used a novel multivariate method called genomic structural equation modeling to model latent factors that capture the shared genomic influence on RSNs and to identify single nucleotide polymorphisms (SNPs) and genes driving this pleiotropy. Using summary statistics from GWAS of 21 RSNs reported in UK Biobank (N = 31,688), the genomic latent factor analysis was first conducted in a discovery sample (N = 21,081), and then tested in an independent sample from the same cohort (N = 10,607). In the discovery sample, we show that the genetic organization of RSNs can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. Eleven of the 17 factor loadings were replicated in the independent sample. With the multivariate GWAS, we found and replicated nine independent SNPs associated with the joint architecture of RSNs. Further, by combining the discovery and replication samples, we discovered additional SNP and gene associations with the two factors of RSN amplitude. We conclude that modeling the genetic effects on brain function in a multivariate way is a powerful approach to learn more about the biological mechanisms involved in brain function.

Comparison of Diagnostic Performances Between Cerebrospinal Fluid Biomarkers and Amyloid PET in a Clinical Setting

The diagnostic performances of cerebrospinal fluid (CSF) biomarkers and amyloid positron emission tomography (PET) were compared by examining the association and concordance or discordance between CSF Aβ1-42 and amyloid PET, after determining our own cut-off values for CSF Alzheimer's disease (AD) biomarkers. Furthermore, we evaluated the ability of CSF biomarkers and amyloid PET to predict clinical progression. CSF Aβ1-42, t-tau, and p-tau levels were analyzed in 203 individuals [27 normal controls, 38 mild cognitive impairment (MCI), 62 AD dementia, and 76 patients with other neurodegenerative diseases] consecutively recruited from two dementia clinics. We used both visual and standardized uptake value ratio (SUVR)-based amyloid PET assessments for analyses. The association of CSF biomarkers with amyloid PET SUVR, hippocampal atrophy, and cognitive function were investigated by linear regression analysis, and the risk of conversion from MCI to AD dementia was assessed using a Cox proportional hazards model. CSF p-tau/Aβ1-42 and t-tau/Aβ1-42 exhibited the best diagnostic accuracies among the CSF AD biomarkers examined. Correlations were observed between CSF biomarkers and global SUVR, hippocampal volume, and cognitive function. Overall concordance and discordance between CSF Aβ1-42 and amyloid PET was 77% and 23%, respectively. Baseline positive CSF Aβ1-42 for MCI demonstrated a 5.6-fold greater conversion risk than negative CSF Aβ1-42 .  However, amyloid PET findings failed to exhibit significant prognostic value. Therefore, despite presence of a significant correlation between the CSF Aβ1-42 level and SUVR of amyloid PET, and a relevant concordance between CSF Aβ1-42 and amyloid PET, baseline CSF Aβ1-42 better predicted AD conversion.

Cerebrospinal Fluid Biomarkers of Alzheimer's Disease: Current Evidence and Future Perspectives

Alzheimer's disease is a progressive, clinically heterogeneous, and particularly complex neurodegenerative disease characterized by a decline in cognition. Over the last two decades, there has been significant growth in the investigation of cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease. This review presents current evidence from many clinical neurochemical studies, with findings that attest to the efficacy of existing core CSF biomarkers such as total tau, phosphorylated tau, and amyloid-β (Aβ42), which diagnose Alzheimer's disease in the early and dementia stages of the disorder. The heterogeneity of the pathophysiology of the late-onset disease warrants the growth of the Alzheimer's disease CSF biomarker toolbox; more biomarkers showing other aspects of the disease mechanism are needed. This review focuses on new biomarkers that track Alzheimer's disease pathology, such as those that assess neuronal injury (VILIP-1 and neurofilament light), neuroinflammation (sTREM2, YKL-40, osteopontin, GFAP, progranulin, and MCP-1), synaptic dysfunction (SNAP-25 and GAP-43), vascular dysregulation (hFABP), as well as CSF α-synuclein levels and TDP-43 pathology. Some of these biomarkers are promising candidates as they are specific and predict future rates of cognitive decline. Findings from the combinations of subclasses of new Alzheimer's disease biomarkers that improve their diagnostic efficacy in detecting associated pathological changes are also presented.

Latent Class and Transition Analysis of Alzheimer's Disease Data

This study uses independent latent class analysis (LCA) and latent transition analysis (LTA) to explore accurate diagnosis and disease status change of a big Alzheimer's disease Neuroimaging Initiative (ADNI) data of 2,132 individuals over a 3-year period. The data includes clinical and neural measures of controls (CN), individuals with subjective memory complains (SMC), early-onset mild cognitive impairment (EMCI), late-onset mild cognitive impairment (LMCI), and Alzheimer's disease (AD). LCA at each time point yielded 3 classes: Class 1 is mostly composed of individuals from CN, SMC, and EMCI groups; Class 2 represents individuals from LMCI and AD groups with improved scores on memory, clinical, and neural measures; in contrast, Class 3 represents LMCI and from AD individuals with deteriorated scores on memory, clinical, and neural measures. However, 63 individuals from Class 1 were diagnosed as AD patients. This could be misdiagnosis, as their conditional probability of belonging to Class 1 (0.65) was higher than that of Class 2 (0.27) and Class 3 (0.08). LTA results showed that individuals had a higher probability of staying in the same class over time with probability >0.90 for Class 1 and 3 and probability >0.85 for Class 2. Individuals from Class 2, however, transitioned to Class 1 from time 2 to time 3 with a probability of 0.10. Other transition probabilities were not significant. Lastly, further analysis showed that individuals in Class 2 who moved to Class 1 have different memory, clinical, and neural measures to other individuals in the same class. We acknowledge that the proposed framework is sophisticated and time-consuming. However, given the severe neurodegenerative nature of AD, we argue that clinicians should prioritize an accurate diagnosis. Our findings show that LCA can provide a more accurate prediction for classifying and identifying the progression of AD compared to traditional clinical cut-off measures on neuropsychological assessments.

The effect of insomnia on development of Alzheimer's disease

Alzheimer's disease (AD) is the most common type of dementia and a neurodegenerative disorder characterized by memory deficits especially forgetting recent information, recall ability impairment, and loss of time tracking, problem-solving, language, and recognition difficulties. AD is also a globally important health issue but despite all scientific efforts, the treatment of AD is still a challenge. Sleep has important roles in learning and memory consolidation. Studies have shown that sleep deprivation (SD) and insomnia are associated with the pathogenesis of Alzheimer's disease and may have an impact on the symptoms and development. Thus, sleep disorders have decisive effects on AD; this association deserves more attention in research, diagnostics, and treatment, and knowing this relation also can help to prevent AD through screening and proper management of sleep disorders. This study aimed to show the potential role of SD and insomnia in the pathogenesis and progression of AD.

A randomized, controlled clinical trial of plasma exchange with albumin replacement for Alzheimer's disease: Primary results of the AMBAR Study

Introduction

This phase 2b/3 trial examined the effects of plasma exchange (PE) in patients with mild‐to‐moderate Alzheimer's disease (AD).

Methods

Three hundred forty‐seven patients (496 screened) were randomized (1:1:1:1) into three PE treatment arms with different doses of albumin and intravenous immunoglobulin replacement (6‐week period of weekly conventional PE followed by a 12‐month period of monthly low‐volume PE), and placebo (sham).

Results

PE‐treated patients performed significantly better than placebo for the co‐primary endpoints: change from baseline of Alzheimer's Disease Cooperative Study–Activities of Daily Living (ADCS‐ADL; P = .03; 52% less decline) with a trend for Alzheimer's Disease Assessment Scale–Cognitive Subscale (ADAS‐Cog; P = .06; 66% less decline) scores at month 14. Moderate‐AD patients (baseline Mini‐Mental State Examination [MMSE] 18‐21) scored better on ADCS‐ADL (P = .002) and ADAS‐Cog (P = .05), 61% less decline both. There were no changes in mild‐AD patients (MMSE 22‐26). PE‐treated patients scored better on the Clinical Dementia Rating Sum of Boxes (CDR‐sb) (P = .002; 71% less decline) and Alzheimer's Disease Cooperative Study‐Clinical Global Impression of Change (ADCS‐CGIC) (P < .0001; 100% less decline) scales.

Discussion

This trial suggests that PE with albumin replacement could slow cognitive and functional decline in AD, although further studies are warranted.

A proof of concept machine learning analysis using multimodal neuroimaging and neurocognitive measures as predictive biomarker in bipolar disorder

BACKGROUND

Concomitant use of complementary, multimodal imaging measures and neurocognitive measures is reported to have higher accuracy as a biomarker in Alzheimer's dementia. However, such an approach has not been examined to differentiate healthy individuals from Bipolar disorder. In this study, we examined the utility of support vector machine (SVM) technique to differentiate bipolar disorder patients and healthy using structural, functional and diffusion tensor images of brain and neurocognitive measures.

METHODS

30 patients with Bipolar disorder-I and 30 age, sex matched individuals participated in the study. Structural MRI, resting state functional MRI and diffusion tensor images were obtained using a 1.5 T scanner. All participants were administered neuropsychological tests to measure executive functions. SVM, a supervised machine learning technique was applied to differentiate patients and healthy individuals with k-fold cross validation over 10 trials.

RESULTS

The composite marker consisting of both neuroimaging and neuropsychological measures, had an accuracy of 87.60 %, sensitivity of 82.3 % and specificity of 92.7 %. The performance of composite marker was better compared to that of individual markers on classificatory.

CONCLUSIONS

We were able to achieve a high accuracy for machine learning technique in distinguishing BD from HV using a combination of multimodal neuroimaging and neurocognitive measures. Findings of this proof of concept study, if replicated in larger samples, could have potential clinical applications.

Cognitive reserve predicts future executive function decline in older adults with Alzheimer's disease pathology but not age-associated pathology

Cognitive reserve has been described as offering protection against Alzheimer's disease (AD) and other neurodegenerative conditions, but also against age-associated brain changes. Using data from the Alzheimer's Disease Neuroimaging Initiative, we defined cognitive reserve using the residual reserve index: episodic memory performance residualized for 3T MRI-derived brain volumes and demographics. We examined whether cognitive reserve predicted executive function (EF) decline equally across 2 groups of older adults-AD biomarker-positive (n = 468) and -negative (n = 402)-defined by the tau-to-amyloid ratio in cerebrospinal fluid. A significant interaction between the residual reserve index and biomarker group revealed that the effect of cognitive reserve on EF decline was dependent on pathology status. In the biomarker-positive group, higher cognitive reserve predicted EF decline over five years. However, cognitive reserve did not predict EF decline in the biomarker-negative group. These results suggest a certain level of AD pathology may be needed before cognitive reserve exerts its protective effects on future cognition; however, further research that tracks cognitive reserve longitudinally is needed.

Examination of retinal vascular trajectory in schizophrenia and bipolar disorder

AIM

Evidence suggests microvascular dysfunction (wider retinal venules and narrower arterioles) in schizophrenia (SCZ) and bipolar disorder (BD). The vascular development is synchronous with neuronal development in the retina and brain. The retinal vessel trajectory is related to retinal nerve fiber layer thinning and cerebrovascular abnormalities in SCZ and BD and has not yet been examined. Hence, in this study we examined the retinal vascular trajectory in SCZ and BD in comparison with healthy volunteers (HV).

METHODS

Retinal images were acquired from 100 HV, SCZ patients, and BD patients, respectively, with a non-mydriatic fundus camera. Images were quantified to obtain the retinal arterial and venous trajectories using a validated, semiautomated algorithm. Analysis of covariance and regression analyses were conducted to examine group differences. A supervised machine-learning ensemble of bagged-trees method was used for automated classification of trajectory values.

RESULTS

There was a significant difference among groups in both the retinal venous trajectory (HV: 0.17 ± 0.08; SCZ: 0.25 ± 0.17; BD: 0.27 ± 0.20; P < 0.001) and the arterial trajectory (HV: 0.34 ± 0.15; SCZ: 0.29 ± 0.10; BD: 0.29 ± 0.11; P = 0.003) even after adjusting for age and sex (P < 0.001). On post-hoc analysis, the SCZ and BD groups differed from the HV on retinal venous and arterial trajectories, but there was no difference between SCZ and BD patients. The machine learning showed an accuracy of 86% and 73% for classifying HV versus SCZ and BD, respectively.

CONCLUSION

Smaller trajectories of retinal arteries indicate wider and flatter curves in SCZ and BD. Considering the relation between retinal/cerebral vasculatures and retinal nerve fiber layer thinness, the retinal vascular trajectory is a potential marker for SCZ and BD. As a relatively affordable investigation, retinal fundus photography should be further explored in SCZ and BD as a potential screening measure.

Biomarker-guided clustering of Alzheimer's disease clinical syndromes

Alzheimer's disease (AD) neuropathology is extremely heterogeneous, and the evolution from preclinical to mild cognitive impairment until dementia is driven by interacting genetic/biological mechanisms not fully captured by current clinical/research criteria. We characterized the heterogeneous "construct" of AD through a cerebrospinal fluid biomarker-guided stratification approach. We analyzed 5 validated pathophysiological cerebrospinal fluid biomarkers (Aβ_1-42, t-tau, p-tau₁₈₁, NFL, YKL-40) in 113 participants (healthy controls [N = 20], subjective memory complainers [N = 36], mild cognitive impairment [N = 20], and AD dementia [N = 37], age: 66.7 ± 10.4, 70.4 ± 7.7, 71.7 ± 8.4, 76.2 ± 3.5 years [mean ± SD], respectively) using Density-Based Spatial Clustering of Applications with Noise, which does not require a priori determination of the number of clusters. We found 5 distinct clusters (sizes: N = 38, 16, 24, 14, and 21) whose composition was independent of phenotypical groups. Two clusters showed biomarker profiles linked to neurodegenerative processes not associated with classical AD-related pathophysiology. One cluster was characterized by the neuroinflammation biomarker YKL-40. Combining nonlinear data aggregation with informative biomarkers can generate novel patient strata which are representative of cellular/molecular pathophysiology and may aid in predicting disease evolution and mechanistic drug response.

Inflammation and cerebral small vessel disease: A systematic review

Inflammation is increasingly implicated as a risk factor for dementia, stroke, and small vessel disease (SVD). However, the underlying mechanisms and causative pathways remain unclear. We systematically reviewed the existing literature on the associations between markers of inflammation and SVD (i.e., white matter hyperintensities (WMH), lacunes, enlarged perivascular spaces (EPVS), cerebral microbleeds (CMB)) in cohorts of older people with good health, cerebrovascular disease, or cognitive impairment. Based on distinctions made in the literature, markers of inflammation were classified as systemic inflammation (e.g. C-reactive protein, interleukin-6, fibrinogen) or vascular inflammation/endothelial dysfunction (e.g. homocysteine, von Willebrand factor, Lp-PLA2). Evidence from 82 articles revealed relatively robust associations between SVD and markers of vascular inflammation, especially amongst stroke patients, suggesting that alterations to the endothelium and blood-brain barrier may be a driving force behind SVD. Conversely, cross-sectional findings on systemic inflammation were mixed, although longitudinal investigations demonstrated that elevated levels of systemic inflammatory markers at baseline predicted subsequent SVD severity and progression. Importantly, regional analysis revealed that systemic and vascular inflammation were differentially related to two distinct forms of SVD. Specifically, markers of vascular inflammation tended to be associated with SVD in areas typical of hypertensive arteriopathy (e.g., basal ganglia), while systemic inflammation appeared to be involved in CAA-related vascular damage (e.g., centrum semiovale). Nonetheless, there is insufficient data to establish whether inflammation is causal of, or secondary to, SVD. Findings have important implications on interventions, suggesting the potential utility of treatments targeting the brain endothelium and blood brain barrier to combat SVD and associated neurodegenerative diseases.

Blood amyloid levels and risk of dementia in the Ginkgo Evaluation of Memory Study (GEMS): A longitudinal analysis

INTRODUCTION

Both high or low plasma amyloid levels have been associated with risk of dementia in nondemented subjects.

METHODS

We examined baseline plasma β-amyloid (Aβ) levels in relationship to incident dementia during a period of 8.5 years in 2840 subjects age >75 years; 2381 were cognitively normal (CN) and 450 mild cognitive impairment.

RESULTS

Increased plasma Aβ1-40 and Aβ1-42 levels were associated with gender (women), age, low education, creatinine levels, history of stroke, and hypertension. CN participants who developed dementia had lower levels of Aβ1-42 and Aβ1-42/Aβ1-40 ratio compared with those who did not. Aβ levels did not predict dementia in mild cognitive impairment participants.

DISCUSSION

There was an inverse association between Aβ1-42 and Aβ1-42/Aβ1-40 ratio to risk of dementia in CN participants. Cerebral and cardiovascular disease and renal function are important determinants of increased Aβ levels and must be considered in evaluations of relationship of plasma Aβ and subsequent risk of dementia.

A Nanoplasmonic Biosensor for Ultrasensitive Detection of Alzheimer's Disease Biomarker Using a Chaotropic Agent

Blood-based diagnosis (hemodiagnosis) of Alzheimer's disease (AD) is emerging as a promising alternative to cerebrospinal-fluid-based methods because blood contains various kinds of AD biomarkers, including amyloid beta 1-40, 1-42, and τ (tau) protein. However, with current technology, the accuracy of the blood-plasma-based methods is relatively low compared to the traditional methods because the concentration of AD biomarkers in blood plasma is incredibly low, and diverse interference is present in blood plasma, which hinders precise detection. Here, we suggest a nanoplasmonic biosensor using gold nanorods with a chaotropic agent for precise ultrasensitive detecting of Alzheimer's disease biomarkers in human plasma. This nanoplasmonic biosensor is based on the localized surface plasmon resonance (LSPR), which is extremely sensitive to the point where it can respond to an insignificant change of the refractive index around the gold nanoparticles. Also, using guanidine hydrochloride as a chaotropic agent, we can overcome the obstacles of blood-based AD diagnostics. In more detail, this agent interrupts the network between water molecules and weakens the hydrophobic interactions between proteins, remarkably improving detection capabilities to target τ protein. By reducing the overlapping ranges between protein levels in an age-matched control and AD patients' plasma, this system can accurately diagnose AD patients. This platform also can analyze disease from mild cognitive impairment using standardized blood biomarker tau protein, which is related to Alzheimer's disease. As a result, our platform can be applied to clinical trials, and thus it has excellent potential in the medical field.

Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3

Brain imaging with diffusion-weighted MRI (dMRI) is sensitive to microstructural white matter (WM) changes associated with brain aging and neurodegeneration. In its third phase, the Alzheimer's Disease Neuroimaging Initiative (ADNI3) is collecting data across multiple sites and scanners using different dMRI acquisition protocols, to better understand disease effects. It is vital to understand when data can be pooled across scanners, and how the choice of dMRI protocol affects the sensitivity of extracted measures to differences in clinical impairment. Here, we analyzed ADNI3 data from 317 participants (mean age: 75.4 ± 7.9 years; 143 men/174 women), who were each scanned at one of 47 sites with one of six dMRI protocols using scanners from three different manufacturers. We computed four standard diffusion tensor imaging (DTI) indices including fractional anisotropy (FA^DTI) and mean, radial, and axial diffusivity, and one FA index based on the tensor distribution function (FA^TDF), in 24 bilaterally averaged WM regions of interest. We found that protocol differences significantly affected dMRI indices, in particular FA^DTI. We ranked the diffusion indices for their strength of association with four clinical assessments. In addition to diagnosis, we evaluated cognitive impairment as indexed by three commonly used screening tools for detecting dementia and AD: the AD Assessment Scale (ADAS-cog), the Mini-Mental State Examination (MMSE), and the Clinical Dementia Rating scale sum-of-boxes (CDR-sob). Using a nested random-effects regression model to account for protocol and site, we found that across all dMRI indices and clinical measures, the hippocampal-cingulum and fornix (crus)/stria terminalis regions most consistently showed strong associations with clinical impairment. Overall, the greatest effect sizes were detected in the hippocampal-cingulum (CGH) and uncinate fasciculus (UNC) for associations between axial or mean diffusivity and CDR-sob. FA^TDF detected robust widespread associations with clinical measures, while FA^DTI was the weakest of the five indices for detecting associations. Ultimately, we were able to successfully pool dMRI data from multiple acquisition protocols from ADNI3 and detect consistent and robust associations with clinical impairment and age.

Current state of Alzheimer's fluid biomarkers

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with a complex and heterogeneous pathophysiology. The number of people living with AD is predicted to increase; however, there are no disease-modifying therapies currently available and none have been successful in late-stage clinical trials. Fluid biomarkers measured in cerebrospinal fluid (CSF) or blood hold promise for enabling more effective drug development and establishing a more personalized medicine approach for AD diagnosis and treatment. Biomarkers used in drug development programmes should be qualified for a specific context of use (COU). These COUs include, but are not limited to, subject/patient selection, assessment of disease state and/or prognosis, assessment of mechanism of action, dose optimization, drug response monitoring, efficacy maximization, and toxicity/adverse reactions identification and minimization. The core AD CSF biomarkers Aβ42, t-tau, and p-tau are recognized by research guidelines for their diagnostic utility and are being considered for qualification for subject selection in clinical trials. However, there is a need to better understand their potential for other COUs, as well as identify additional fluid biomarkers reflecting other aspects of AD pathophysiology. Several novel fluid biomarkers have been proposed, but their role in AD pathology and their use as AD biomarkers have yet to be validated. In this review, we summarize some of the pathological mechanisms implicated in the sporadic AD and highlight the data for several established and novel fluid biomarkers (including BACE1, TREM2, YKL-40, IP-10, neurogranin, SNAP-25, synaptotagmin, α-synuclein, TDP-43, ferritin, VILIP-1, and NF-L) associated with each mechanism. We discuss the potential COUs for each biomarker.

Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry

In the 12 years since the publication of the first Consensus Paper of the WFSBP on biomarkers of neurodegenerative dementias, enormous advancement has taken place in the field, and the Task Force takes now the opportunity to extend and update the original paper. New concepts of Alzheimer's disease (AD) and the conceptual interactions between AD and dementia due to AD were developed, resulting in two sets for diagnostic/research criteria. Procedures for pre-analytical sample handling, biobanking, analyses and post-analytical interpretation of the results were intensively studied and optimised. A global quality control project was introduced to evaluate and monitor the inter-centre variability in measurements with the goal of harmonisation of results. Contexts of use and how to approach candidate biomarkers in biological specimens other than cerebrospinal fluid (CSF), e.g. blood, were precisely defined. Important development was achieved in neuroimaging techniques, including studies comparing amyloid-β positron emission tomography results to fluid-based modalities. Similarly, development in research laboratory technologies, such as ultra-sensitive methods, raises our hopes to further improve analytical and diagnostic accuracy of classic and novel candidate biomarkers. Synergistically, advancement in clinical trials of anti-dementia therapies energises and motivates the efforts to find and optimise the most reliable early diagnostic modalities. Finally, the first studies were published addressing the potential of cost-effectiveness of the biomarkers-based diagnosis of neurodegenerative disorders.

Estimation of the volume under the receiver-operating characteristic surface adjusting for non-ignorable verification bias

The receiver-operating characteristic surface is frequently used for presenting the accuracy of a diagnostic test for three-category classification problems. One common problem that can complicate the estimation of the volume under receiver-operating characteristic surface is that not all subjects receive the verification of the true disease status. Estimation based only on data from subjects with verified disease status may be biased, which is referred to as verification bias. In this article, we propose new verification bias correction methods to estimate the volume under receiver-operating characteristic surface for a continuous diagnostic test. We assume the verification process is missing not at random, which means the missingness might be related to unobserved clinical characteristics. Three classes of estimators are proposed, namely, inverse probability weighted, imputation-based, and doubly robust estimators. A jackknife estimator of variance is derived for all the proposed volume under receiver-operating characteristic surface estimators. The finite sample properties of the new estimators are examined via simulation studies. We illustrate our methods with data collected from Alzheimer's disease research.

Alzheimer's disease biomarker-guided diagnostic workflow using the added value of six combined cerebrospinal fluid candidates: Aβ1-42, total-tau, phosphorylated-tau, NFL, neurogranin, and YKL-40

INTRODUCTION

The diagnostic and classificatory performances of all combinations of three core (amyloid β peptide [i.e., Aβ_1-42], total tau [t-tau], and phosphorylated tau) and three novel (neurofilament light chain protein, neurogranin, and YKL-40) cerebrospinal fluid biomarkers of neurodegeneration were compared among individuals with mild cognitive impairment (n = 41), Alzheimer's disease dementia (ADD; n = 35), frontotemporal dementia (FTD; n = 9), and cognitively healthy controls (HC; n = 21), using 10-fold cross-validation.

METHODS

The combinations ranking in the top 10 according to diagnostic accuracy in differentiating between distinct diagnostic categories were identified.

RESULTS

The single biomarkers or biomarker combinations generating the best area under the receiver operating characteristics (AUROCs) were the following: the combination [amyloid β peptide + phosphorylated tau + neurofilament light chain] for distinguishing between ADD patients and HC (AUROC = 0.86), t-tau for distinguishing between ADD and FTD patients (AUROC = 0.82), and t-tau for distinguishing between FTD patients and HC (AUROC = 0.78).

CONCLUSIONS

Novel and established cerebrospinal fluid markers perform with at least fair accuracy in the discrimination between ADD and FTD. The classification of mild cognitive impairment individuals was poor.

Serum haptoglobin in Chinese patients with Alzheimer's disease and mild cognitive impairment: A case-control study

BACKGROUND

Serum level of Haptoglobin (Hp) maybe associated with Alzheimer's disease (AD) and mild cognitive impairment (MCI).

OBJECTIVE

To investigate associations between serum Hp and AD, as well as between Hp and MCI.

METHODS

Serum levels of Hp were measured and analyzed for 51 patients with AD, 139 patients with MCI and their healthy controls matched with sex and age. All study subjects were from a survey among residents aged 60 years and over in a community located in the southwest suburb of Shanghai.

RESULTS

Serum levels of Hp were observed significantly higher in AD and MCI cases than controls (both p < 0.0001). A significant positive correlation was found between Hp and Activities of Daily Living (ADL) score (r_s = 0.430, p = 0.007), as well as between Hp and Clinical Dementia Rating (CDR) score (r_s = 0.359, p = 0.027) in all AD patients. According to the receiver operating characteristic (ROC) curve analysis, the optimal cut-off point for Hp was found to be 67.50 μg/ml (sensitivity, 0.902; specificity, 0.745) in AD patients, and 44.76 μg/ml (sensitivity, 0.986; specificity, 0.403) in MCI patients.

CONCLUSION

Elevated serum levels of Hp were observed in AD and MCI patients than controls. In addition, Hp may correlate with the severity of AD.

Fluid and imaging biomarkers for Alzheimer's disease: Where we stand and where to head to

There is increasing evidence that a number of potentially informative biomarkers for Alzheimer disease (AD) can improve the accuracy of diagnosing this form of dementia, especially when used as a panel of diagnostic assays and interpreted in the context of neuroimaging and clinical data. Moreover, by combining the power of CSF biomarkers with neuroimaging techniques to visualize Aβ deposits (or neurodegenerative lesions), it might be possible to better identify individuals at greatest risk for developing MCI and converting to AD. The objective of this article was to review recent progress in selected imaging and chemical biomarkers for prediction, early diagnosis and progression of AD. We present our view point of a scenario that places CSF and imaging markers on the verge of general utility based on accuracy levels that already match (or even surpass) current clinical precision.

Surface Assay for Specific Detection of Soluble Amyloid Oligomers Utilizing Pronucleon Peptides Instead of Antibodies

Immunoassays such as enzyme-linked immunosorbent assays (ELISAs) are widely used for diagnostics; however, antibodies as detection reagents may be insufficiently selective and have other shortcomings. We present a novel non-antibody-based detection method based on binding target molecules to peptides (used as recognition molecules): a surface assay for A-β oligomers employing a peptide comprising amino acid residues of the human β-amyloid protein (Pronucleon peptide) as the capture agent. For the sake of convenience, we term this the "Pronucleon peptide-linked immunosorbent assay", or PLISA. Pronucleon peptides are amino acid sequences matched to target amyloids of interest, in particular soluble Aβ-1-42 amyloid protein oligomers, which are widely considered as an early biomarker for Alzheimer's disease in body fluids. The Pronucleon peptide in a PLISA is immobilized on the surface and substitutes for the capture antibody used in an ELISA for binding the Aβ-1-42 oligomers present in the sample. We present data comparing synthetic oligomer PLISAs in spiked buffer and body fluids (such as cerebrospinal fluid, brain extracts, or whole blood) to those from an ELISA and demonstrate better selectivity of the PLISA for amyloid β-42 oligomers versus monomers and fibrils. The detection limit, calculated as the mean (blank) plus three standard deviations, was in the range of 0.35-1.5 pM (32-135 ng/L) (oligomers contained approximately 20 monomers on average).

Role of inflammatory molecules in the Alzheimer's disease progression and diagnosis

Alzheimer's disease (AD) is a complex disorder and the most common form of neurodegenerative dementia. Several genetic, environmental, and physiological factors, including inflammations and metabolic influences, are involved in the progression of AD. Inflammations are composed of complicated networks of many chemokines and cytokines with diverse cells. Inflammatory molecules are needed for the protection against pathogens, and maintaining their balances is important for normal physiological function. Recent studies demonstrated that inflammation may be involved in neurodegenerative dementia. Cellular immune components, such as microglia or astrocytes, mediate the release of inflammatory molecules, including tumor necrosis factor, growth factors, adhesion molecules, or chemokines. Over- and underexpression of pro- and anti-inflammatory molecules, respectively, may result in neuroinflammation and thus disease initiation and progression. In addition, levels of several inflammatory factors were reported to be altered in the brain or bodily fluids of patients with AD, reflecting their neuropathological changes. Therefore, simultaneous detection of several inflammatory molecules in the early or pre-symptomatic stage may improve the early diagnosis of AD. Further studies are needed to determine, how induction or inhibition of inflammatory factors could be used for AD therapies. This review summarizes the role or possible role of immune cells and inflammatory molecules in disease progression or prevention.

Accelerated Brain Atrophy on Serial Computed Tomography: Potential Marker of the Progression of Alzheimer Disease

OBJECTIVE

The aim of this study was to validate computed tomography (CT)-based longitudinal markers of the progression of Alzheimer disease (AD).

MATERIALS AND METHODS

We retrospectively studied 33 AD patients and 39 nondemented patients with other neurological illnesses (non-AD) having 4 to 12 CT examinations of the head, with over a mean (SD) of 3.9 (1.7) years. At each time point, we applied an automatic software to measure whole brain, cerebrospinal fluid, and intracranial space volumes. Longitudinal measures were then related to disease status and time since the first scan using hierarchical models.

RESULTS

Absolute brain volume loss accelerated for non-AD patients by 0.86 mL/y (95% confidence interval [CI], 0.64-1.08 mL/y) and 1.5× faster, that is, 1.32 mL/y (95% CI, 1.09-1.56 mL/y) for AD patients (P = 0.006). In terms of brain volume normalized to intracranial space, the acceleration in atrophy rate for non-AD patients was 0.0578%/y (95% CI, 0.0389%/y to 0.0767%/y), again 1.5× faster, that is, 0.0919%/y (95% CI, 0.0716%/y to 0.1122%/y) for AD patients (P = 0.017). This translates to an increase in atrophy rate from 0.5% to 1.4% in AD versus to 1.1% in non-AD group after 10 years.

CONCLUSIONS

Brain volumetry on CT reliably detected accelerated volume loss in AD and significantly lower acceleration factor in age-matched non-AD patients, leading to the possibility of its use to monitor the progression of cognitive decline and dementia.

Inverse probability weighting estimation of the volume under the ROC surface in the presence of verification bias

In diagnostic medicine, the volume under the receiver operating characteristic (ROC) surface (VUS) is a commonly used index to quantify the ability of a continuous diagnostic test to discriminate between three disease states. In practice, verification of the true disease status may be performed only for a subset of subjects under study since the verification procedure is invasive, risky, or expensive. The selection for disease examination might depend on the results of the diagnostic test and other clinical characteristics of the patients, which in turn can cause bias in estimates of the VUS. This bias is referred to as verification bias. Existing verification bias correction in three-way ROC analysis focuses on ordinal tests. We propose verification bias-correction methods to construct ROC surface and estimate the VUS for a continuous diagnostic test, based on inverse probability weighting. By applying U-statistics theory, we develop asymptotic properties for the estimator. A Jackknife estimator of variance is also derived. Extensive simulation studies are performed to evaluate the performance of the new estimators in terms of bias correction and variance. The proposed methods are used to assess the ability of a biomarker to accurately identify stages of Alzheimer's disease.

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.

Alterations of the volatile metabolome in mouse models of Alzheimer's disease

In the present study, we tested whether the volatile metabolome was altered by mutations of the Alzheimer's disease (AD)-implicated amyloid precursor protein gene (APP) and comprehensively examined urinary volatiles that may potentially serve as candidate biomarkers of AD. Establishing additional biomarkers in screening populations for AD will provide enhanced diagnostic specificity and will be critical in evaluating disease-modifying therapies. Having strong evidence of gross changes in the volatile metabolome of one line of APP mice, we utilized three unique mouse lines which over-express human mutations of the APP gene and their respective non-transgenic litter-mates (NTg). Head-space gas chromatography/mass spectrometry (GC/MS) of urinary volatiles uncovered several aberrant chromatographic peak responses. We later employed linear discrimination analysis and found that the GC/MS peak responses provide accurate (>84%) genotype classification of urinary samples. These initial data in animal models show that mutant APP gene expression entails a uniquely identifiable urinary odor, which if uncovered in clinical AD populations, may serve as an additional biomarker for the disease.

Mild cognitive impairment due to alzheimer disease is less likely under the age of 65

Patients with amnestic mild cognitive impairment (aMCI) are considered to have a high risk for Alzheimer dementia (AD). Even high positive predictive values, however, cannot be guaranteed even by tests with high sensitivity and specificity when disease prevalence is low. If we regard the clinical criteria for aMCI as a test for predicting aMCI due to AD, the positive predictive value of the criteria will be low by definition in young patients with aMCI (age below 65 years) because of the low prevalence of AD in this age group. To test this hypothesis, we compared CSF biomarkers for AD between young (age below 65 years) and old (age 65 years or older) age groups of normal cognition, aMCI, and AD of the Alzheimer's Disease Neuroimaging Initiative database. Using these biomarkers, we observed that the prevalence of aMCI due to AD differed significantly between the young and the old. For example, only 28.2% young aMCI, but 63.2% old aMCI, had abnormal CSF amyloid measures consistent with AD pathology. As posited, the presence of aMCI due to AD was lower in young aMCI than in old aMCI. Given that the likelihood of aMCI due to AD is reduced in younger subjects, more attention to and evaluation of alternative diagnoses need to be considered in this group.

How many biomarkers to discriminate neurodegenerative dementia?

A number of cerebrospinal fluid (CSF) biomarkers are currently used for the diagnosis of dementia. Opposite changes in the level of amyloid-β(1-42) versus total tau and phosphorylated-tau181 in the CSF reflect the specific pathology of Alzheimer's disease (AD) in the brain. This panel of biomarkers has proven to be effective to differentiate AD from controls and from the major types of neurodegenerative dementia, and to evaluate the progression from mild cognitive impairment to AD. In the absence of specific biomarkers reflecting the pathologies of the other most common forms of dementia, such as Lewy Body disease, Frontotemporal lobar degeneration, Creutzfeldt-Jakob disease, etc., the evaluation of biomarkers of AD pathology is used, attempting to exclude rather than to confirm AD. Other biomarkers included in the common clinical practice do not clearly relate to the underlying pathology: progranulin (PGRN) is a selective marker of frontotemporal dementia with mutations in the PGRN gene; the 14-3-3 protein is a highly sensitive and specific marker for Creutzfeldt-Jakob disease, but has to be used carefully in differentiating rapid progressive dementia; and α-synuclein is an emerging candidate biomarker of the different forms of synucleinopathy. This review summarizes several biomarkers of neurodegenerative dementia validated based on the neuropathological processes occurring in brain tissue. Notwithstanding the paucity of pathologically validated biomarkers and their high analytical variability, the combinations of these biomarkers may well represent a key and more precise analytical and diagnostic tool in the complex plethora of degenerative dementia.

Variations in the FRA10AC1 Fragile Site and 15q21 Are Associated with Cerebrospinal Fluid Aβ1-42 Level

Proteolytic fragments of amyloid and post-translational modification of tau species in Cerebrospinal fluid (CSF) as well as cerebral amyloid deposition are important biomarkers for Alzheimer’s Disease. We conducted genome-wide association study to identify genetic factors influencing CSF biomarker level, cerebral amyloid deposition, and disease progression. The genome-wide association study was performed via a meta-analysis of two non-overlapping discovery sample sets to identify genetic variants other than APOE ε4 predictive of the CSF biomarker level (Aβ_1–42, t-Tau, p-Tau_181P, t-Tau:Aβ_1–42 ratio, and p-Tau_181P:Aβ_1–42 ratio) in patients enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. Loci passing a genome-wide significance threshold of P < 5 x 10⁻⁸ were followed-up for replication in an independent sample set. We also performed joint meta-analysis of both discovery sample sets together with the replication sample set. In the discovery phase, we identified variants in FRA10AC1 associated with CSF Aβ_1–42 level passing the genome-wide significance threshold (directly genotyped SNV rs10509663 P_FE = 1.1 x 10⁻⁹, imputed SNV rs116953792 P_FE = 3.5 x 10⁻¹⁰), rs116953792 (P_one-sided = 0.04) achieved replication. This association became stronger in the joint meta-analysis (directly genotyped SNV rs10509663 P_FE = 1.7 x 10⁻⁹, imputed SNV rs116953792 P_FE = 7.6 x 10⁻¹¹). Additionally, we identified locus 15q21 (imputed SNV rs1503351 P_FE = 4.0 x 10⁻⁸) associated with CSF Aβ_1–42 level. No other variants passed the genome-wide significance threshold for other CSF biomarkers in either the discovery sample sets or joint analysis. Gene set enrichment analyses suggested that targeted genes mediated by miR-33, miR-146, and miR-193 were enriched in various GWAS analyses. This finding is particularly important because CSF biomarkers confer disease susceptibility and may be predictive of the likelihood of disease progression in Alzheimer’s Disease.

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

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

Divergent CSF τ alterations in two common tauopathies: Alzheimer's disease and progressive supranuclear palsy

BACKGROUND

Elevated CSF τ is considered a biomarker of neuronal injury in newly developed Alzheimer's disease (AD) and mild cognitive impairment (MCI) criteria. However, previous studies have failed to detect alterations of τ species in other primary tauopathies. We assessed CSF τ protein abnormalities in AD, a tauopathy with prominent Aβ pathology, and progressive supranuclear palsy (PSP), a primary tauopathy characterised by deposition of four microtubule-binding repeat (4R) τ with minimal Aβ pathology.

METHODS

26 normal control (NC), 37 AD, and 24 patients with PSP participated in the study. AD and PSP were matched for severity using the clinical dementia rating sum of boxes (CDR-sb) scores. The INNO BIA AlzBio3 multiplex immunoassay was used to measure CSF Aβ, total τ, and ptau181. Additional, novel ELISAs targeting different N-terminal and central τ epitopes were developed to examine CSF τ components and to investigate interactions between diagnostic group, demographics and genetic variables.

RESULTS

PSP had lower CSF N-terminal and C-terminal τ concentrations than NC and AD measured with the novel τ ELISAs and the standard AlzBio3 τ and ptau assays. AD had higher total τ and ptau levels than NC and PSP. There was a gender by diagnosis interaction in AD and PSP for most τ species, with lower concentrations for male compared to female patients.

CONCLUSIONS

CSF τ fragment concentrations are different in PSP compared with AD despite the presence of severe τ pathology and neuronal injury in both disorders. CSF τ concentration likely reflects multiple factors in addition to the degree of neuronal injury.

Primary Prevention and Delay of Onset of AD/Dementia

Prevention in Alzheimer's disease and other dementias (AD/dementia) is defined on the basis of clinical states and their expressed symptoms. Primary prevention refers to delaying the development of the full-blown state of clinically expressed disease in normal individuals. Current primary prevention research is driven by evidence of AD/dementia protective factors that have emerged from epidemiological studies. The first randomized controlled trials (RCTs) of primary AD/dementia prevention have been designed to test the efficacy and safety of NSAIDs, hormonal therapy, antihypertensive drugs and antioxidants. The experience of these trials has indicated safety concerns as a key issue and highlighted significant design challenges in this type of research. These trials have required large sample sizes and unsustainable costs. There should be consideration given in future trials to enriching study samples with risk factors to increase progression rates to AD/dementia. Innovative strategies will also be needed to recruit and retain subjects given the long follow-up periods, modest perceived benefit and the potential for the risk-benefit ratio to change during the trial. It is foreseeable that regulatory authorities will be presented with primary prevention RCTs for approval and labelling, and that criteria to evaluate such evidence still need to be developed.

A systematic review of amyloid-β peptides as putative mediators of the association between affective disorders and Alzheimer׳s disease

BACKGROUND

Affective disorders are associated with an increased occurrence of cognitive deficits and have been linked to cognitive impairment and Alzheimer׳s disease. The putative molecular mechanisms involved in these associations are however not clear. The aim of this systematic review was to explore clinically founded evidence for amyloid-β peptides in cerebrospinal fluid and blood as putative biomarkers for affective disorders.

METHOD

Systematic searches in Embase and PubMed databases yielded 23 eligible, observational studies.

RESULTS

Despite inconsistencies that were partly ascribed to the application of different assay formats, study results indicate a potentially altered amyloid-β metabolism in affective disorder.

LIMITATIONS

Since most studies used a cross-sectional design, causality is difficult to establish. Moreover, methodological rigor of included studies varied and several studies were limited by very low sample numbers. Finally, different assays for amyloid-β were utilized in the different studies, thus hampering comparisons.

CONCLUSION

To unravel possible risk relations and causalities between affective disorder and Alzheimer׳s disease and to determine how amyloid-β concentrations change over time and are associated with cognition as well as affective symptomatology, future research should include prospective, longitudinal studies, implemented in large study populations, where peripheral and central amyloid-β ratios are quantified concomitantly and continuously across various affective phases. Also, to enable inter-survey comparisons, the use of standardized pre-analytical/analytical procedures is crucial.

Assessment of CSF Aβ42 as an aid to discriminating Alzheimer's disease from other dementias and mild cognitive impairment: a meta-analysis of 50 studies

Mild Alzheimer's disease (AD) is usually difficult to differentiate from other dementias or mild cognitive impairment (MCI). The aim of our study is to evaluate the clinical importance of cerebrospinal fluid (CSF) β-amyloid 42 (Aβ42) in MCI, AD and other dementias, more specifically: frontotemporal dementia (FTD), dementia with Lewy bodies (DLB), Parkinson's disease (PD) with dementia (PDD) and vascular dementia (VaD). Fifty eligible articles were identified by search of databases including PubMed, EMBASE, Elsevier, Springer Link and the Cochrane Library, from January 1990 to May 2014. The random effects model was used to calculate the standardized mean difference (SMD) with corresponding 95% CI by STATA 9.0 software. The subgroup analyses were made on the method (ELISA, xMAP). We found that CSF Aβ42 concentrations were significantly lower in AD compared to MCI (SMD: -0.68, 95% CI: [-0.80, -0.56], z=11.34, P<0.001), FTD (SMD: -1.09, 95% CI: [-1.41, -0.76], z=6.62, P<0.001), PDD (SMD: -0.75, 95% CI: [-1.39, -0.10], z=2.27, P=0.023), VaD (SMD: -0.95, 95% CI: [-1.30, -0.61], z=5.43, P<0.001). In addition, compared to DLB, Aβ42 concentrations are moderately lower in AD (SMD: -0.27, 95% CI: [-0.51, -0.03], z=2.20, P=0.028). Results from this meta-analysis hinted that CSF Aβ42 is a good biomarker for discriminating Alzheimer's disease from other dementias and MCI.

Altered proteolysis in fibroblasts of Alzheimer patients with predictive implications for subjects at risk of disease

There is great interest in developing reliable biomarkers to support antemortem diagnosis of late-onset Alzheimer's disease (AD). Early prediction and diagnosis of AD might be improved by the detection of a proteolytic dysfunction in extracts from cultured AD fibroblasts, producing altered isoelectrophoretic forms of the enzyme transketolase (TK-alkaline bands). The TK profile and apolipoprotein E (APOE) genotype were examined in fibroblasts from 36 clinically diagnosed probable late-onset sporadic AD patients and 38 of their asymptomatic relatives, 29 elderly healthy individuals, 12 neurological non-AD patients, and 5 early-onset AD patients. TK alterations occurred in (i) several probable AD patients regardless of age-of-onset and severity of disease; (ii) all early-onset AD patients and APOE ε 4/4 carriers; and (iii) nearly half of asymptomatic AD relatives. Normal subjects and non-AD patients were all negative. Notably, culture conditions promoting TK alterations were also effective in increasing active BACE1 levels. Overall, the TK assay might represent a low-cost laboratory tool useful for supporting AD differential diagnosis and identifying asymptomatic subjects who are at greater risk of AD and who should enter a follow-up study. Moreover, the cultured fibroblasts were confirmed as a useful in vitro model for further studies on the pathogenetic process of AD.

Does CSF p-tau181 help to discriminate Alzheimer's disease from other dementias and mild cognitive impairment? A meta-analysis of the literature

To evaluate the clinical importance of cerebrospinal fluid (CSF) phosphorylated tau 181 (p-tau181) in mild cognitive impairment (MCI), Alzheimer's disease (AD) and other dementias, more specifically: frontotemporal degeneration (FTD), dementia with Lewy bodies (DLB), vascular dementia (VaD) and Parkinson's disease (PD) with dementia (PDD). Fifty eligible articles were identified by search of databases including PubMed, EMBASE, Elsevier, Springer Link and the Cochrane Library, up to December 2013. The random effects model was used to calculate the standardized mean difference (SMD) with corresponding 95% CI by STATA 9.0 software. The subgroup analyses were made on the methods or PD with dementia. We found that CSF p-tau181 concentrations were significantly higher in AD compared to MCI [SMD: 0.61, 95% CI: (0.46, 0.76), z = 8.07, P < 0.001], FTD [SMD: 1.23, 95% CI: (0.89, 1.56), z = 7.19, P < 0.001], DLB [SMD: 1.08, 95% CI: (0.80, 1.37), z = 7.41, P < 0.001], PDD [SMD: 1.05, 95% CI: (0.02, 2.07), z = 2.00, P = 0.045] and VaD [SMD: 1.28, 95% CI: (0.68, 1.88), z = 4.19, P < 0.001]. Results from this meta-analysis implied that CSF p-tau181 is a good biomarker for discriminating Alzheimer's disease from other dementias and mild cognitive impairment.

A blood-based predictor for neocortical Aβ burden in Alzheimer's disease: results from the AIBL study

Dementia is a global epidemic with Alzheimer's disease (AD) being the leading cause. Early identification of patients at risk of developing AD is now becoming an international priority. Neocortical Aβ (extracellular β-amyloid) burden (NAB), as assessed by positron emission tomography (PET), represents one such marker for early identification. These scans are expensive and are not widely available, thus, there is a need for cheaper and more widely accessible alternatives. Addressing this need, a blood biomarker-based signature having efficacy for the prediction of NAB and which can be easily adapted for population screening is described. Blood data (176 analytes measured in plasma) and Pittsburgh Compound B (PiB)-PET measurements from 273 participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were utilised. Univariate analysis was conducted to assess the difference of plasma measures between high and low NAB groups, and cross-validated machine-learning models were generated for predicting NAB. These models were applied to 817 non-imaged AIBL subjects and 82 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) for validation. Five analytes showed significant difference between subjects with high compared to low NAB. A machine-learning model (based on nine markers) achieved sensitivity and specificity of 80 and 82%, respectively, for predicting NAB. Validation using the ADNI cohort yielded similar results (sensitivity 79% and specificity 76%). These results show that a panel of blood-based biomarkers is able to accurately predict NAB, supporting the hypothesis for a relationship between a blood-based signature and Aβ accumulation, therefore, providing a platform for developing a population-based screen.

Qualification of a surrogate matrix-based absolute quantification method for amyloid-β₄₂ in human cerebrospinal fluid using 2D UPLC-tandem mass spectrometry

The primary aims of this work were to: 1) establish a calibrator surrogate matrix for quantification of amyloid-β (Aβ)42 in human cerebrospinal fluid (CSF) and preparation of quality control samples for LC-MS-MS methodology, 2) validate analytical performance of the assay, and 3) evaluate its diagnostic utility and compare it with the AlzBio3 immunoassay. The analytical methodology was based on a 2D-UPLC-MS-MS platform. Sample pretreatment used 5 M guanidine hydrochloride and extraction on μElution SPE columns as previously described. A column cleaning procedure involved gradual removal of aqueous solvents by acetonitrile assured consistent long-term chromatography performance. Receiver-operator characteristic (ROC) curve and correlation analyses evaluated the diagnostic utility of UPLC-MS-MS compared to AlzBio3 immunoassay for detection of Alzheimer's disease (AD). The surrogate matrix, artificial CSF containing 4 mg/mL of BSA, provides linear and reproducible calibration comparable to human pooled CSF as calibration matrix. Appropriate cleaning of the trapping and analytical columns provided every-day, trouble-free runs. Analyses of CSF Aβ42 showed that UPLC-MS-MS distinguished neuropathologically-diagnosed AD subjects from healthy controls with at least equivalent diagnostic utility to AlzBio3. Comparison of ROC curves for these two assays showed no statistically significant difference (p = 0.2229). Linear regression analysis of Aβ42 concentrations measured by this mass spectrometry-based method compared to the AlzBio3 immunoassay showed significantly higher but highly correlated results. In conclusion, the newly established surrogate matrix for 2D-UPLC-MS-MS measurement of Aβ42 provides selective, reproducible, and accurate results. The documented analytical performance and diagnostic performance for AD versus controls supports consideration as a candidate reference method.