Longitudinal changes of CSF biomarkers in memory clinic patients

Cognitive correlates of cerebrospinal fluid biomarkers in frontotemporal dementia

OBJECTIVE

In this study we investigated the relationships between cerebrospinal fluid (CSF) biomarkers (tau and amyloid-β1-42 [Aβ1-42]) and cognition or behavior in patients with frontotemporal dementia (the behavioral variant, bvFTD).

METHODS

We included 58 patients with bvFTD. All patients underwent a neuropsychological assessment and lumbar puncture. Relationships between CSF biomarkers and cognition or behavior were assessed with linear regression analysis.

RESULTS

After correction for age, sex, and education, CSF tau levels were found to be negatively related to the Visual Association Test (standardized β = -0.3, P < .05), whereas CSF Aβ1-42 levels were found to be positively related to the Mini-Mental State Examination (β = 0.3, P < .05), the frontal assessment battery (β = 0.5, P < .05), and digit span backwards test (β = 0.3, P = .01). We did not find relations between CSF biomarkers and behavior (measured by the neuropsychiatric inventory). After excluding all patients with a CSF biomarker profile often seen in Alzheimer's disease (high levels of tau and low levels of Aβ1-42), we still found relations between CSF Aβ1-42 levels and Visual Association Test object naming (β = 0.4, P < .05), as well as between CSF Aβ1-42 levels and the frontal assessment battery (β = 0.5, P < .05, but there was no relation between CSF tau and cognition.

CONCLUSION

Low CSF Aβ1-42 levels are associated with worse general cognitive function and worse executive function in patients with bvFTD. Our results provide circumstantial evidence for a pathophysiological role of Aβ1-42 in bvFTD.

Development and advanced validation of an optimized method for the quantitation of Aβ42 in human cerebrospinal fluid

Cerebrospinal fluid (CSF) biomarkers have been extensively utilized in the diagnosis of Alzheimer's disease (AD) and characterization of progression. One important CSF biomarker is the amyloid beta 42 (Aβ(42)) peptide, a key player in AD pathogenesis. The INNOTEST® Aβ(42) ELISA kit has been widely used but an advanced level of method development and validation has not been reported. To support a clinical trial in AD, we successfully completed a Good Laboratory Practices (GLP)-level validation of the method to establish the parameters of precision, accuracy, parallelism, selectivity, specificity, and linearity of dilution of the assay in CSF matrix, as well as CSF storage stability. Several modifications were required to optimize the assay and ensure consistent results in a clinical-trial setting. These included the use of additional calibrators, an adjusted standard curve range, a minimum required dilution (MRD) of CSF by 6-fold to avoid matrix interference and mitigation of analyte adsorption to labware by the addition of Tween-20. The optimized method displayed a quantitative range of 375-4,500 pg/mL. The inter-assay precision was ≤12.1 % CV and the inter-assay relative accuracy was ≤10.9 % absolute bias, bringing the total error of the assay to ≤23 %. The intra-assay precision of the assay at the high validation standard and below was ≤5.5 % CV; this enables sensitive detection of biomarker changes across a therapeutic regime. The INNOTEST® Aβ(42) ELISA kit, modified as reported here, may be appropriate for many applications, including regulatory agency acceptable clinical diagnosis and pharmacodynamic assessment.

Longitudinal imaging of Alzheimer pathology using [11C]PIB, [18F]FDDNP and [18F]FDG PET

PURPOSE

[(11)C]PIB and [(18)F]FDDNP are PET tracers for in vivo detection of the neuropathology underlying Alzheimer's disease (AD). [(18)F]FDG is a glucose analogue and its uptake reflects metabolic activity. The purpose of this study was to examine longitudinal changes in these tracers in patients with AD or mild cognitive impairment (MCI) and in healthy controls.

METHODS

Longitudinal, paired, dynamic [(11)C]PIB and [(18)F]FDDNP (90 min each) and static [(18)F]FDG (15 min) PET scans were obtained in 11 controls, 12 MCI patients and 8 AD patients. The mean interval between baseline and follow-up was 2.5 years (range 2.0-4.0 years). Parametric [(11)C]PIB and [(18)F]FDDNP images of binding potential (BP(ND)) and [(18)F]FDG standardized uptake value ratio (SUVr) images were generated.

RESULTS

A significant increase in global cortical [(11)C]PIB BP(ND) was found in MCI patients, but no changes were observed in AD patients or controls. Subsequent regional analysis revealed that this increase in [(11)C]PIB BP(ND) in MCI patients was most prominent in the lateral temporal lobe (p < 0.05). For [(18)F]FDDNP, no changes in global BP(ND) were found. [(18)F]FDG uptake was reduced at follow-up in the AD group only, especially in frontal, parietal and lateral temporal lobes (all p < 0.01). Changes in global [(11)C]PIB binding (ρ = -0.42, p < 0.05) and posterior cingulate [(18)F]FDG uptake (ρ = 0.54, p < 0.01) were correlated with changes in Mini-Mental-State Examination score over time across groups, whilst changes in [(18)F]FDDNP binding (ρ = -0.18, p = 0.35) were not.

CONCLUSION

[(11)C]PIB and [(18)F]FDG track molecular changes in different stages of AD. We found increased amyloid load in MCI patients and progressive metabolic impairment in AD patients. [(18)F]FDDNP seems to be less useful for examining disease progression.

Predicting future clinical changes of MCI patients using longitudinal and multimodal biomarkers

Accurate prediction of clinical changes of mild cognitive impairment (MCI) patients, including both qualitative change (i.e., conversion to Alzheimer's disease (AD)) and quantitative change (i.e., cognitive scores) at future time points, is important for early diagnosis of AD and for monitoring the disease progression. In this paper, we propose to predict future clinical changes of MCI patients by using both baseline and longitudinal multimodality data. To do this, we first develop a longitudinal feature selection method to jointly select brain regions across multiple time points for each modality. Specifically, for each time point, we train a sparse linear regression model by using the imaging data and the corresponding clinical scores, with an extra 'group regularization' to group the weights corresponding to the same brain region across multiple time points together and to allow for selection of brain regions based on the strength of multiple time points jointly. Then, to further reflect the longitudinal changes on the selected brain regions, we extract a set of longitudinal features from the original baseline and longitudinal data. Finally, we combine all features on the selected brain regions, from different modalities, for prediction by using our previously proposed multi-kernel SVM. We validate our method on 88 ADNI MCI subjects, with both MRI and FDG-PET data and the corresponding clinical scores (i.e., MMSE and ADAS-Cog) at 5 different time points. We first predict the clinical scores (MMSE and ADAS-Cog) at 24-month by using the multimodality data at previous time points, and then predict the conversion of MCI to AD by using the multimodality data at time points which are at least 6-month ahead of the conversion. The results on both sets of experiments show that our proposed method can achieve better performance in predicting future clinical changes of MCI patients than the conventional methods.

Multi-modal multi-task learning for joint prediction of multiple regression and classification variables in Alzheimer's disease

Many machine learning and pattern classification methods have been applied to the diagnosis of Alzheimer's disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). Recently, rather than predicting categorical variables as in classification, several pattern regression methods have also been used to estimate continuous clinical variables from brain images. However, most existing regression methods focus on estimating multiple clinical variables separately and thus cannot utilize the intrinsic useful correlation information among different clinical variables. On the other hand, in those regression methods, only a single modality of data (usually only the structural MRI) is often used, without considering the complementary information that can be provided by different modalities. In this paper, we propose a general methodology, namely multi-modal multi-task (M3T) learning, to jointly predict multiple variables from multi-modal data. Here, the variables include not only the clinical variables used for regression but also the categorical variable used for classification, with different tasks corresponding to prediction of different variables. Specifically, our method contains two key components, i.e., (1) a multi-task feature selection which selects the common subset of relevant features for multiple variables from each modality, and (2) a multi-modal support vector machine which fuses the above-selected features from all modalities to predict multiple (regression and classification) variables. To validate our method, we perform two sets of experiments on ADNI baseline MRI, FDG-PET, and cerebrospinal fluid (CSF) data from 45 AD patients, 91 MCI patients, and 50 healthy controls (HC). In the first set of experiments, we estimate two clinical variables such as Mini Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), as well as one categorical variable (with value of 'AD', 'MCI' or 'HC'), from the baseline MRI, FDG-PET, and CSF data. In the second set of experiments, we predict the 2-year changes of MMSE and ADAS-Cog scores and also the conversion of MCI to AD from the baseline MRI, FDG-PET, and CSF data. The results on both sets of experiments demonstrate that our proposed M3T learning scheme can achieve better performance on both regression and classification tasks than the conventional learning methods.

Dementia: Alzheimer pathology and vascular factors: from mutually exclusive to interaction

Alzheimer's disease (AD) is the most common type of dementia. Both its incidence and prevalence are expected to increase exponentially as populations' age worldwide. Despite impressive efforts of research worldwide, neither cure nor effective preventive strategy is available for this devastating disease. Currently there are several hypotheses on what causes AD, with the amyloid hypothesis being the most investigated and accepted hypothesis over the past 20 years. However the exact role of amyloid-β in the onset and progression of AD is not yet fully understood, and even the validity of the amyloid hypothesis itself is still being discussed. This debate is fuelled by the vascular hypothesis, as increasing epidemiological, neuroimaging, pathological, pharmacotherapeutic and clinical studies suggest that vascular pathology plays a key role in the onset and progression of AD. We here will discuss arguments in favor and limitations of both hypotheses within the framework of available literature, but also provide arguments for convergence of both hypotheses. Finally we propose approaches that may aid in unraveling the etiology and treatment of AD. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

[Patients with mild cognitive impairment and a reduced CSF Aβ₁₋₄₂ protein progress rapidly to Alzheimer's disease]

INTRODUCTION

Some studies have shown that CSF amyloid-beta 1-42 (Aβ₁₋₄₂), total tau (T-tau) and tau phosphorylated at threonine 181 (P-tau(181p)) proteins are useful diagnostic markers for distinguishing between clinically stable mild cognitive impairment (MCI) patients and those who will develop Alzheimeŕs disease (AD). Our objective was to test the ability of this technique to discriminate in our cohort of MCI patients, according to the clinical outcome, one year after the lumbar puncture.

MATERIAL AND METHODS

A total of 36 MCI patients were included from the local hospital memory clinic. Using INNO-BIA Alzbio-3 reagents from Innogenetics, we measured CSF Aβ₁₋₄₂, T-tau and P-tau(181p) proteins, and calculated the T-tau/Aβ₁₋₄₂ y P-tau(181p)/Aβ₁₋₄₂ ratios. This project was approved by the local ethics committee.

RESULTS

One year after the lumbar puncture, 14 MCI patients (38%) developed AD. These patients had lower Aβ₁₋₄₂ protein levels (285.3 vs 377 ng/ml, P<.02) and higher P-tau(181p)/Aβ₁₋₄₂ ratio (0,25 vs 0,16, p<.02) than the clinically stable patients.

CONCLUSIONS

Our MCI patients with lower Aβ₁₋₄₂ protein levels and an increased P-tau(181p) /Aβ₁₋₄₂ ratio progressed quickly to AD. These results may help to identify those MCI patients with a poorer prognosis.

Multimodal classification of Alzheimer's disease and mild cognitive impairment

Effective and accurate diagnosis of Alzheimer's disease (AD), as well as its prodromal stage (i.e., mild cognitive impairment (MCI)), has attracted more and more attention recently. So far, multiple biomarkers have been shown to be sensitive to the diagnosis of AD and MCI, i.e., structural MR imaging (MRI) for brain atrophy measurement, functional imaging (e.g., FDG-PET) for hypometabolism quantification, and cerebrospinal fluid (CSF) for quantification of specific proteins. However, most existing research focuses on only a single modality of biomarkers for diagnosis of AD and MCI, although recent studies have shown that different biomarkers may provide complementary information for the diagnosis of AD and MCI. In this paper, we propose to combine three modalities of biomarkers, i.e., MRI, FDG-PET, and CSF biomarkers, to discriminate between AD (or MCI) and healthy controls, using a kernel combination method. Specifically, ADNI baseline MRI, FDG-PET, and CSF data from 51AD patients, 99 MCI patients (including 43 MCI converters who had converted to AD within 18 months and 56 MCI non-converters who had not converted to AD within 18 months), and 52 healthy controls are used for development and validation of our proposed multimodal classification method. In particular, for each MR or FDG-PET image, 93 volumetric features are extracted from the 93 regions of interest (ROIs), automatically labeled by an atlas warping algorithm. For CSF biomarkers, their original values are directly used as features. Then, a linear support vector machine (SVM) is adopted to evaluate the classification accuracy, using a 10-fold cross-validation. As a result, for classifying AD from healthy controls, we achieve a classification accuracy of 93.2% (with a sensitivity of 93% and a specificity of 93.3%) when combining all three modalities of biomarkers, and only 86.5% when using even the best individual modality of biomarkers. Similarly, for classifying MCI from healthy controls, we achieve a classification accuracy of 76.4% (with a sensitivity of 81.8% and a specificity of 66%) for our combined method, and only 72% even using the best individual modality of biomarkers. Further analysis on MCI sensitivity of our combined method indicates that 91.5% of MCI converters and 73.4% of MCI non-converters are correctly classified. Moreover, we also evaluate the classification performance when employing a feature selection method to select the most discriminative MR and FDG-PET features. Again, our combined method shows considerably better performance, compared to the case of using an individual modality of biomarkers.

Multi-Kernel Classification for Integration of Clinical and Imaging Data: Application to Prediction of Cognitive Decline in Older Adults

Diagnosis of neurologic and neuropsychiatric disorders typically involves considerable assessment including clinical observation, neuroimaging, and biological and neuropsychological measurements. While it is reasonable to expect that the integration of neuroimaging data and complementary non-imaging measures is likely to improve early diagnosis on individual basis, due to technical challenges associated with the task of combining different data types, medical image pattern recognition analysis has been largely focusing solely on neuroimaging evaluations. In this paper, we explore the potential of integrating neuroimaging and clinical information within a pattern classification framework, and propose that the multi-kernel learning (MKL) paradigm may be suitable for building a multimodal classifier of a disorder, as well as for automatic identification of the relevance of each information type. We apply our approach to the problem of detecting cognitive decline in healthy older adults from single-visit evaluations, and show that the performance of a classifier can be improved when nouroimaging and clinical evaluations are used simultaneously within a MKL-based classification framework.

Assessing the progression of mild cognitive impairment to Alzheimer's disease: current trends and future directions

With the advent of advances in biomarker detection and neuropsychological measurement, prospects have improved for identifying and tracking the progression of Alzheimer's disease (AD) from its earliest stages through dementia. While new diagnostic techniques have exciting implications for initiating treatment earlier in the disease process, much work remains to be done to optimize the contributions of the expanding range of tools at the disposal of researchers and clinicians. The present paper examines recent work in cerebrospinal fluid biomarkers, magnetic resonance imaging, positron emission tomography, neuropsychological measures, and functional assessment. The strengths and weaknesses of current methodologies are explored and discussed. It is concluded that AD from its mild cognitive impairment state through dementia represents a continuous process, and that progression over time can best be accomplished by interval-level variables. Biomarkers that are most sensitive to early AD may not be the most optimal for monitoring longitudinal change, and it is likely that multivariate models incorporating cognitive measures, functional variables and biomarker data will be the most fruitful avenues for future research.

Cerebrospinal fluid biomarkers in mild cognitive impairment and dementia

Given the magnitude of the public health problem of dementia in the elderly, there is a pressing need for research, development, and timely application of biomarkers that will identify latent and prodromal illness as well as dementia. Although identification of risk factors and neuroimaging measures will remain key to these efforts, this review focuses on recent progress in the discovery, validation, and standardization of cerebrospinal fluid (CSF) biomarkers, small molecules and macromolecules whose CSF concentration can aid in diagnosis at different stages of disease as well as in assessment of disease progression and response to therapeutics. A multimodal approach that brings independent information from risk factor assessment, neuroimaging, and biomarkers may soon guide physicians in the early diagnosis and management of cognitive impairment in the elderly.

Tau as a biomarker of neurodegenerative diseases

The microtubule-associated protein Tau is mainly expressed in neurons of the CNS and is crucial in axonal maintenance and axonal transport. The rationale for Tau as a biomarker of neurodegenerative diseases is that it is a major component of abnormal intraneuronal aggregates observed in numerous tauopathies, including Alzheimer's disease. The molecular diversity of Tau is very useful when analyzing it in the brain or in the peripheral fluids. Immunohistochemical and biochemical characterization of Tau aggregates in the brain allows the postmortem classification and differential diagnosis of tauopathies. As peripheral biomarkers of Alzheimer's disease in the cerebrospinal fluid, Tau proteins are now validated for diagnosis and predictive purposes. For the future, the detailed characterization of Tau in the brain and in peripheral fluids will lead to novel promising biomarkers for differential diagnosis of dementia and monitoring of therapeutics.

CSF phospho-tau correlates with behavioural decline and brain insoluble phospho-tau levels in a rat model of tauopathy

The aim of the present study was to identify the relationship between progressive neurobehavioural decline and phospho-tau levels (p-tau(181)) in the cerebrospinal fluid (CSF) and the brain in transgenic rats expressing human truncated tau protein. Behavioural analyses, as quantified using the NeuroScale scoring method, revealed that the transgenic rats fell into two main groups based on the baseline behavioural functioning: (1) mild neurobehavioural impairment (MNI, score 3.3-26) and (2) severe neurobehavioural impairment (SNI, score 36-44). SNI transgenic rats showed a significant increase in brain sarkosyl insoluble p-tau(181) when compared to their MNI counterparts. In order to determine whether CSF phospho-tau reflects the behavioural decline and increase in sarkosyl insoluble tau in the brain, p-tau(181) was measured in the CSF in a longitudinal study. The study showed a significant increase in CSF p-tau(181) during the progression of the disease from MNI to SNI. Moreover, increased levels of p-tau(181) in CSF correlated with an increase in the sarkosyl insoluble p-tau(181) levels in the brain. The increase in the CSF level of p-tau(181) during progressive behavioural decline suggests that it may represent a useful surrogate biomarker for preclinical drug development and a potential surrogate endpoint for clinical trials of disease-modifying therapy for Alzheimer's disease and related human tauopathies.

Glycemia and levels of cerebrospinal fluid amyloid and tau in patients attending a memory clinic

OBJECTIVES

To determine the association between markers of glycemia and cerebrospinal fluid (CSF) amyloid beta 1-42 (Abeta42) and tau levels in patients attending a memory clinic.

DESIGN

Cross-sectional study.

SETTING

Memory clinic.

PARTICIPANTS

Two hundred forty-five consecutive patients attending a memory clinic. Clinical diagnoses were subjective cognitive complaints (n=91), mild cognitive impairment (n=62), Alzheimer's disease (n=58), and other dementia (n=34). Twenty-one patients had diabetes mellitus.

MEASUREMENTS

Glycosylated hemoglobin (HbA1c); fasting blood glucose levels; and CSF levels of Abeta42, total tau, and p-tau 181.

RESULTS

In regression analyses across the whole study sample adjusted for age, sex, and diagnostic group, there was no relationship between HbA1c or fasting glucose and CSF tau, p-tau 182, or Abeta42 levels. Stratification for diabetes mellitus did not change the results.

CONCLUSION

These observations do not support the hypothesis that the association between dysglycemia and impaired cognitive functioning is mediated through aberrant amyloid or tau metabolism.

Proteomics-derived cerebrospinal fluid markers of autopsy-confirmed Alzheimer's disease

The diagnostic performance of several candidate cerebrospinal fluid (CSF) protein biomarkers in neuropathologically confirmed Alzheimer's disease (AD), non-demented (ND) elderly controls and non-AD dementias (NADD) was assessed. Candidate markers were selected on the basis of initial two-dimensional gel electrophoresis studies or by literature review. Markers selected by the former method included apolipoprotein A-1 (ApoA1), haemopexin (HPX), transthyretin (TTR) and pigment epithelium-derived factor (PEDF), while markers identified from the literature included Abeta1-40, Abeta1-42, total tau, phosphorylated tau, alpha-1 acid glycoprotein (A1GP), haptoglobin, zinc alpha-2 glycoprotein (Z2GP) and apolipoprotein E (ApoE). Ventricular CSF concentrations of the markers were measured by enzyme-linked immunosorbent assay (ELISA). The concentrations of Abeta1-42, ApoA1, A1GP, ApoE, HPX and Z2GP differed significantly among AD, ND and NADD subjects. Logistic regression analysis for the diagnostic discrimination of AD from ND found that Abeta1-42, ApoA1 and HPX each had significant and independent associations with diagnosis. The CSF concentrations of these three markers distinguished AD from ND subjects with 84% sensitivity and 72% specificity, with 78% of subjects correctly classified. By comparison, using Abeta1-42 alone gave 79% sensitivity and 61% specificity, with 68% of subjects correctly classified. For the diagnostic discrimination of AD from NADD, only the concentration of Abeta1-42 was significantly related to diagnosis, with a sensitivity of 58%, specificity of 86% and 86% correctly classified. The results indicate that for the discrimination of AD from ND control subjects, measurement of a set of markers including Abeta1-42, ApoA1 and HPX improved diagnostic performance over that obtained by measurement of Abeta1-42 alone. For the discrimination of AD from NADD subjects, measurement of Abeta1-42 alone was superior.

Amyloid-β(1–42), Total Tau, and Phosphorylated Tau as Cerebrospinal Fluid Biomarkers for the Diagnosis of Alzheimer Disease

Background: To improve ante mortem diagnostic accuracy of Alzheimer disease (AD), measurement of the biomarkers amyloid-β(1–42) (Aβ42), total tau (Tau), and tau phosphorylated at threonine181 (pTau) in cerebrospinal fluid (CSF) has been proposed. We have used these markers and evaluated their performance.

Methods: From January 2001 to January 2007, we assessed Aβ42, Tau, and pTau by commercial ELISAs in CSF from 248 consecutive AD patients and 131 patients with subjective memory complaints attending our outpatient memory clinic. Diagnoses were made blind to the results of the biomarker assays. We assessed sensitivity and specificity and analyzed trends over time.

Results: Interassay CVs from analysis of pools of surplus CSF specimens were mean 11.3% (SD 4.9%) for Aβ42; 9.3% (1.5%) for Tau, and 9.4% (2.5%) for pTau, respectively (n = 7–18). To achieve 85% sensitivity, cutoff values were 550 (95% CI 531–570) ng/L for Aβ42; 375 (325–405) ng/L for Tau, and 52 (48–56) ng/L for pTau. Corresponding specificities were 83% (95% CI 76%–89%) for Aβ42, 78% (70%–85%) for Tau, and 68% (60%–77%) for pTau. Logistic regression to investigate the simultaneous impact of the 3 CSF biomarkers on the diagnosis yielded a sensitivity of 93.5% and specificity of 82.7%, at a discrimination line of Aβ42 = 373 + 0.82 × Tau. The area under the ROC curves of Tau and pTau showed significant fluctuation over time.

Conclusions: CSF biomarkers Aβ42 and Tau can be used as a diagnostic aid in AD. pTau did not have additional value over these 2 markers. Cutoff values, sensitivities, specificities, and discrimination lines depend on the patient groups studied and laboratory experience.

Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade

Currently available evidence strongly supports the position that the initiating event in Alzheimer's disease (AD) is related to abnormal processing of beta-amyloid (Abeta) peptide, ultimately leading to formation of Abeta plaques in the brain. This process occurs while individuals are still cognitively normal. Biomarkers of brain beta-amyloidosis are reductions in CSF Abeta(42) and increased amyloid PET tracer retention. After a lag period, which varies from patient to patient, neuronal dysfunction and neurodegeneration become the dominant pathological processes. Biomarkers of neuronal injury and neurodegeneration are increased CSF tau and structural MRI measures of cerebral atrophy. Neurodegeneration is accompanied by synaptic dysfunction, which is indicated by decreased fluorodeoxyglucose uptake on PET. We propose a model that relates disease stage to AD biomarkers in which Abeta biomarkers become abnormal first, before neurodegenerative biomarkers and cognitive symptoms, and neurodegenerative biomarkers become abnormal later, and correlate with clinical symptom severity.

Baseline CSF p-tau levels independently predict progression of hippocampal atrophy in Alzheimer disease

OBJECTIVE

To investigate whether baseline CSF biomarkers are associated with hippocampal atrophy rate as a measure of disease progression in patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and controls, controlling for baseline neuropsychological and MRI findings.

METHODS

We assessed data from 31 patients with AD, 25 patients with MCI, and 19 controls (mean age 68 +/- 8 years; 39 [52%] female) who visited our memory clinic and had received serial MRI scanning (scan interval 1.7 +/- 0.7 years). At baseline, CSF biomarkers (amyloid beta 1-42, tau, and tau phosphorylated at threonine 181 [p-tau]) were obtained, as well as neuropsychological data. Baseline MRI scans were assessed using visual rating scales for medial temporal lobe atrophy (MTA), global cortical atrophy, and white matter hyperintensities. Hippocampal atrophy rates were estimated using regional nonlinear "fluid" registration of follow-up scan to baseline scan.

RESULTS

Stepwise multiple linear regression, adjusted for age and sex, showed that increased CSF p-tau levels (beta [standard error]: -0.79 [0.35]) at baseline was independently associated with higher subsequent hippocampal atrophy rates (p < 0.05), together with poorer memory performance (0.09 [0.04]) and more severe MTA (-0.60 [0.21]). The association of memory function with hippocampal atrophy rate was explained by the link with diagnosis, because it disappeared from the model after we additionally corrected for diagnosis.

CONCLUSIONS

Baseline CSF levels of tau phosphorylated at threonine 181 are independently associated with subsequent disease progression, as reflected by hippocampal atrophy rate. This effect is independent of baseline neuropsychological and MRI predictors. Our results imply that predicting disease progression can best be achieved by combining information from different modalities.

CSF levels of PSA and PSA-ACT complexes in Alzheimer's disease

BACKGROUND

Prostate-specific antigen (PSA) is a serine protease that in serum, is predominantly found complexed to the serine protease inhibitor alpha1-antichymotrypsin (ACT). ACT co-localizes with amyloid plaques in Alzheimer's disease (AD) brain and both PSA and ACT are detectable in cerebrospinal fluid (CSF). Therefore, we aimed to determine whether PSA is produced in the brain and whether PSA and PSA-ACT complex levels in CSF can be used as a biomarker for AD.

METHODS

Levels of ACT and PSA-ACT were determined by sandwich enzyme-linked immunosorbent assay in CSF and serum samples of AD (n = 16), frontotemporal lobe dementia (FTLD) (n = 19), mild cognitively impaired (MCI) patients (n = 19) and controls (n = 12). Total PSA was determined in a non-competitive immunoassay. Reverse transcriptase-polymerase chain reaction (RT-PCR) for PSA was performed on postmortem hippocampus and temporal cortex specimens from control and AD cases.

RESULTS

PSA is expressed in the brain, as detected by RT-PCR. PSA and PSA-ACT complexes were detectable in CSF of almost all male and only very few female subjects. The levels of PSA and PSA-ACT complexes in CSF did not differ between AD, FTLD, MCI and control groups. PSA CSF/serum quotients highly correlated with albumin CSF/serum quotients. Furthermore, the hydrodynamic radius of PSA was found to be 3 nm and the theoretical PSA quotient, derived from the Felgenhauer plot, corresponded well with the measured PSA quotient.

CONCLUSIONS

PSA is locally produced in the human brain; however, brain PSA hardly contributes to the CSF levels of PSA. PSA and PSA-ACT levels in CSF are not suitable as a biomarker for AD.

Relationship of cerebrospinal fluid markers to 11C-PiB and 18F-FDDNP binding

The purpose of this study was to investigate the potential relationships between cerebrospinal fluid (CSF) measurements of beta-amyloid-1-42 (Abeta(1-42)) and total tau to (11)C-Pittsburgh compound B ((11)C-PiB) and 2-(1-{6-[(2-(18)F-fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene) malononitrile ((18)F-FDDNP) binding as measured using PET.

METHODS

A total of 37 subjects were included, consisting of 15 patients with Alzheimer disease (AD), 12 patients with mild cognitive impairment, and 10 healthy controls. All subjects underwent a lumbar puncture and PET using both (11)C-PiB and (18)F-FDDNP. For both PET tracers, parametric images of binding potential were generated. Potential associations of CSF levels of Abeta(1-42) and tau with (11)C-PiB and (18)F-FDDNP binding were assessed using Pearson correlation coefficients and linear regression analyses.

RESULTS

For both global (11)C-PiB and (18)F-FDDNP binding, significant correlations with CSF levels of Abeta(1-42) (r = -0.72 and -0.37, respectively) and tau (r = 0.58 and 0.56, respectively) were found across groups (all P < 0.001, except P < 0.05 for correlation between (18)F-FDDNP and Abeta(1-42)). Linear regression analyses showed that, adjusted for regional volume, age, sex, and diagnosis, global (11)C-PiB uptake had an inverse association with Abeta(1-42) CSF levels (standardized beta = -0.50, P < 0.001), whereas there was a positive association between global (18)F-FDDNP binding and tau CSF levels (standardized beta = 0.62, P < 0.01).

CONCLUSION

The good agreement between these 2 different types of biomarkers (i.e., CSF and PET) provides converging evidence for their validity. The inverse association between (11)C-PiB and CSF tau Abeta(1-42) confirms that (11)C-PiB measures amyloid load in the brain. The positive association between (18)F-FDDNP and CSF tau suggests that at least part of the specific signal of (18)F-FDDNP in AD patients is due to tangle formation.

Longitudinal study of CSF biomarkers in patients with Alzheimer's disease

Background

The CSF biomarkers tau and Aβ42 can identify patients with AD, even during the preclinical stages. However, previous studies on longitudinal changes of tau and Aβ42 in individual patients with AD and elderly controls report somewhat inconsistent results.

Methodology/Principal Findings

We investigated the levels of tau and Aβ42 at baseline and after 1 year in 100 patients with AD. In a second cohort of 45 AD patients we measured the CSF biomarkers at baseline and after 2 years. Moreover, in 34 healthy elderly controls the CSF biomarkers were followed for 4 years. The baseline levels of tau were increased with >60% in AD patients compared to controls (p<0.001), while baseline Aβ42 levels were decreased with >50% (p<0.001). In the AD group followed for 2 years, tau increased with 16% compared to the baseline levels (p<0.05). However, the levels of tau were stable over 4 years in the controls. The levels of Aβ42 did not change significantly over time in any of the groups. In the patients with AD, tau was moderately associated with worse cognitive performance already at baseline (p<0.05).

Conclusions/Significance

Tau and Aβ42 in CSF seem to reflect the underlying disease state in both early and late stages of AD. The slight increase in tau over time observed in the patients with AD is modest when compared to the relatively large difference in absolute tau levels between AD patients and controls. Therefore, these markers maintain their usefulness as state markers over time and might serve as surrogate markers for treatment efficacy in clinical trials.

A worldwide multicentre comparison of assays for cerebrospinal fluid biomarkers in Alzheimer's disease

BACKGROUND

Different cerebrospinal fluid (CSF) amyloid-beta 1-42 (Abeta(1-42)), total Tau (Tau) and Tau phosphorylated at threonine 181 (P-Tau) levels are reported, but currently there is a lack of quality control programmes. The aim of this study was to compare the measurements of these CSF biomarkers, between and within centres.

METHODS

Three CSF-pool samples were distributed to 13 laboratories in 2004 and the same samples were again distributed to 18 laboratories in 2008. In 2004 six laboratories measured Abeta(1-42), Tau and P-Tau and seven laboratories measured one or two of these marker(s) by enzyme-linked immunosorbent assays (ELISAs). In 2008, 12 laboratories measured all three markers, three laboratories measured one or two marker(s) by ELISAs and three laboratories measured the markers by Luminex.

RESULTS

In 2004, the ELISA intercentre coefficients of variance (interCV) were 31%, 21% and 13% for Abeta(1-42), Tau and P-Tau, respectively. These were 37%, 16% and 15%, respectively, in 2008. When we restricted the analysis to the Innotest (N = 13) for Abeta(1-42), lower interCV were calculated (22%). The centres that participated in both years (N = 9) showed interCVs of 21%, 15% and 9% and intra-centre coefficients (intraCV) of variance of 25%,18% and 7% in 2008.

CONCLUSIONS

The highest variability was found for Abeta(1-42). The variabilities for Tau and P-Tau were lower in both years. The centres that participated in both years showed a high intraCV comparable to their interCV, indicating that there is not only a high variation between but also within centres. Besides a uniform standardization of (pre)analytical procedures, the same assay should be used to decrease the inter/intracentre variation.

CSF biomarkers, impairment of cerebral hemodynamics and degree of cognitive decline in Alzheimer's and mixed dementia

The in vivo diagnosis of Alzheimer's disease (AD) may be facilitated by cerebro-spinal fluid (CSF) biomarkers in combination with imaging and clinical assessments. By determining the concentration of beta amyloid fragments, total tau (t-tau) and phospho-tau (p-tau), it is possible to detect the conversion of mild cognitive impairment (MCI) to AD or distinguish AD vs. pseudo-dementia. However, these markers are poorly sensitive to the progressive disease stages. And far from clear is their role in "mixed" forms of dementia, as far as hemodynamic deficits complicate the clinical history. We have studied cerebral hemodynamic impairment in AD patients, relative to control subjects. Mean flow velocity (MFV), pulsatility index (PI) and cerebrovascular reactivity (assayed as breath-holding index, BHI) were evaluated by bilateral transcranial Doppler (TCD) monitoring of middle cerebral arteries. MFV and BHI were significantly lower and PI was significantly higher in AD patients with respect to control subjects. The presence of white-matter changes (WMC) in the AD cases did not influence any of the hemodynamic variables. Noticeably, MMSE score was correlated to BHI reduction (P<0.005). Our results, consistent with the recent literature indicate that hemodynamic impairment is a critical marker of cognitive decline and supports once more the hypothesis of a significant pathigenic role of vascular damage in AD. Similar functional alterations might be early hallmarks in a variety of dementia subtypes, including "mixed" dementia, whose prevalence is undoubtedly increased. Assessment of hemodynamic reactivity could provide valuable correlations with individual patient's cognitive profile, which in turn would assist in the identification of critical steps in disease progression and the validation of effective therapies.

Evolution of Abeta42 and Abeta40 levels and Abeta42/Abeta40 ratio in plasma during progression of Alzheimer's disease: a multicenter assessment

OBJECTIVE

To better understand the seemingly contradictory plasma beta-amyloid (Abeta) results in Alzheimer's disease (AD) patients by using a newly developed plasma Abeta assay, the INNO-BIA plasma Abeta forms, in a multicenter study.

METHODS

A combined retrospective analysis of plasma Abeta isoforms on mild cognitive impairment (MCI) from three large cross-sectional studies involving 643 samples from the participating German and Swedish centers.

RESULTS

Detection modules based on two different amino (N)-terminal specific Abeta monoclonal antibodies demonstrated that Abeta in plasma could be reliable quantified using a sandwich immunoassay technology with high precision, even for low Abeta42 plasma concentrations. Abeta40 and Abeta42 concentrations varied consistently with the ApoE genotype, while the Abeta42/Abeta40 ratio did not. Irrespective of the decrease of the Abeta42/Abeta40 ratio with age and MMSE, this parameter was strongly associated with AD, as defined in this study by elevated hyperphosphorylated (P-tau181P) levels in cerebrospinal fluid (CSF).

CONCLUSION

A highly robust assay for repeatedly measuring Abeta forms in plasma such as INNO-BIA plasma Abeta forms might be a useful tool in a future risk assessment of AD.

Neuroimaging outcomes in clinical trials in Alzheimer's disease

The first disease modifying drugs targeting beta amyloid that were tested in phase II and III clinical trials have been disappointing. We believe that failures descended from a leaky drug development pipeline where insufficient attention has been devoted to valid animal models and valid imaging markers of disease progression. In the future, valid animal models will need to take into greater consideration the natural and molecular history of AD, where both beta amyloid and tau play a key role. Valid imaging markers of disease progression will need to be identified in humans and translated into animal versions. Future testing of putative disease modifying drugs in valid animal models with valid imaging markers of disease progression will allow to maximize the predictability of their effect in phase II and III clinical trials.

Association between FDG uptake, CSF biomarkers and cognitive performance in patients with probable Alzheimer's disease

PURPOSE

Brain imaging of FDG uptake and cerebrospinal fluid (CSF) concentration of amyloid-beta 1-42 (Abeta(1-42)) or tau proteins are promising biomarkers in the diagnosis of Alzheimer's disease (AD). There is still uncertainty regarding any association between decreased FDG uptake and alterations in CSF markers.

METHODS

The relationship between FDG uptake, CSF Abeta(1-42) and total tau (T-tau), as well as the Mini-Mental State Examination (MMSE) score was investigated in 34 subjects with probable AD using step-wise linear regression. FDG uptake was scaled to the pons.

RESULTS

Scaled FDG uptake was significantly reduced in the probable AD subjects compared to 17 controls bilaterally in the precuneus/posterior cingulate area, angular gyrus/inferior parietal cortex, inferior temporal/midtemporal cortex, midfrontal cortex, and left caudate. Voxel-based single-subject analysis of the probable AD subjects at p < 0.001 (uncorrected) revealed a total volume of significant hypometabolism ranging from 0 to 452 ml (median 70 ml). The total hypometabolic volume was negatively correlated with the MMSE score, but it was not correlated with the CSF measures. VOI-based step-wise linear regression revealed that scaled FDG uptake in the precuneus/posterior cingulate was negatively correlated with CSF Abeta(1-42). Scaled FDG uptake in the caudate was positively correlated with CSF T-tau.

CONCLUSION

The extent and local severity of the reduction in FDG uptake in probable AD subjects are associated with cognitive impairment. In addition, there appears to be a relationship between local FDG uptake and CSF biomarkers which differs between different brain regions.

Variability in longitudinal cerebrospinal fluid tau and phosphorylated tau measurements

BACKGROUND

The influence of assay variation and duration of storage on changes in cerebrospinal fluid (CSF) levels of tau and phosphorylated (P)-tau with time was evaluated in 112 patients with various neurological disorders.

METHODS

These patients (aged 66+/-9 years, 52% male), referred to our memory clinic, underwent two spinal taps (mean interval 19 months) and the baseline samples were assayed twice in a sandwich enzyme-linked immunosorbent assay (ELISA): once after the first spinal tap (A1) and once in a separately stored aliquot (A2) simultaneous with the follow-up sample (B).

RESULTS

Coefficients of variances (CVs) of tau and P-tau levels determined in repeated spinal taps (DeltaB-A2) measured in one assay (10.9% and 7.6%) were lower (p<0.01) than the CVs observed in two different (DeltaB-A1) assays (16.5% and 11.7%). The CVs of tau and P-tau measurement of one CSF sample repeated on two occasions (DeltaA1-A2) were 12.3% and 8.6%. A difference in mean P-tau level was found if the same CSF samples were repeatedly measured in two different ELISAs (A1-A2).

CONCLUSIONS

Longitudinal CSF tau and P-tau are best measured in one assay resulting in a lower variability compared to measurement in two different assays. The within person variability in levels of these markers currently limits the use of these ELISAs in a longitudinal clinical setting.

Biomarkers for cognitive impairment and dementia in elderly people

The threat of a looming pandemic of dementia in elderly people highlights the compelling need for the development and validation of biomarkers that can be used to identify pre-clinical and prodromal stages of disease in addition to fully symptomatic dementia. Although predictive risk factors and correlative neuroimaging measures will have important roles in these efforts, this Review describes recent progress in the discovery, validation, and standardisation of molecular biomarkers--small molecules and macromolecules whose concentration in the brain or biological fluids can aid diagnosis at different stages of the more common dementing diseases and in the assessment of disease progression and response to therapeutics. An approach that efficiently combines independent information from risk-factor assessment, neuroimaging measures, and biomarkers might soon guide clinicians in the early diagnosis and management of cognitive impairment in elderly people.

Biomarkers for early diagnosis of Alzheimer disease: 'ALZheimer ASsociated gene'--a new blood biomarker?

Simple, non-invasive tests for an early detection of degenerative dementia by use of biomarkers are urgently required. However, up to the present, no validated extracerebral diagnostic markers (plasma/serum, platelets, urine, connective tissue) for the early diagnosis of Alzheimer disease (AD) are available. In disease stages with evident cognitive disturbances, the clinical diagnosis of probable AD is made with around 90% accuracy using modern clinical, neuropsychological and imaging methods. Diagnostic sensitivity and specificity even in early disease stages are improved by CSF markers, in particular combined tau and amyloid beta peptides (Abeta) and plasma markers (eg, Abeta-42/Abeta-40 ratio). Recently, a novel gene/protein--ALZAS (Alzheimer Associated Protein)--with a 79 amino acid sequence, containing the amyloid beta-42 fragment (Abeta-42), the amyloid precursor protein (APP) transmembrane signal and a 12 amino acid C-terminal, not present in any other known APP alleles, has been discovered on chromosome 21 within the APP region. Reverse transcriptase-PCR revealed the expression of the transcript of this protein in the cortex and hippocampal regions as well as in lymphocytes of human AD patients. The expression of ALZAS is mirrored by a specific autoimmune response in AD patients, directed against the ct-12 end of the ALZAS-peptide but not against the Abeta-sequence. ELISA studies of plasma detected highest titers of ALZAS in patients with mild cognitive impairment (presymptomatic AD), but only moderately increased titers in autopsy-confirmed AD, whereas low or undetectable ct-12 titers were found in cognitively intact age-matched subjects and young controls. The antigen, ALZAS protein, was detected in plasma in later clinical stages of AD. It is suggested that ALZAS represents an indicator in a dynamic equilibrium between both peripheral and brain degenerative changes in AD and may become a useful "non-invasive" diagnostic marker via a simple blood test.

Measuring target effect of proposed disease-modifying therapies in Alzheimer's disease

Alzheimer's disease (AD) is the most common cause of dementia and is an increasing public health problem. Because of the severity and increasing prevalence of the disease in the population, it is urgent that better treatments be developed. Active research efforts over the past several decades have produced a vast knowledge base regarding AD natural history, pathology, and key biological mediators involved in pathogenesis. As knowledge of the biomolecular mechanisms of AD has increased over the past several decades, there has been a growing consensus on the pathophysiology of the disease. These scientific advancements have led to proposals for disease-modifying therapeutic interventions that promise to significantly alter the course of AD. The translation from preclinical models to human studies requires therapeutic biomarkers to increase the likelihood of success. This review covers the current methods and technologies used in the therapeutic translation of proposed disease-modifying therapies for AD.

Plasma amyloid levels and the risk of AD in normal subjects in the Cardiovascular Health Study

OBJECTIVES

To examine the association between incident Alzheimer disease (AD), and plasma A beta 1-40 and A beta 1-42 levels in normal and mild cognitive impairment (MCI) subjects in a subgroup of participants of the Cardiovascular Health Study Cognition Study.

METHODS

We determined the plasma A beta 1-40 and A beta 1-42 levels of 274 nondemented subjects (232 normals and 42 with MCI) in 1998-1999 and repeated the measurements in 2002-2003. The mean age of the subjects at baseline was 79.3 +/- 3.6 years. We examined the association between A beta levels and incident AD over the ensuing 4.5 years, controlling for age, cystatin C level (marker of glomerular function), apolipoprotein E-4 allele, Modified-Mini-Mental State Examination scores, and MRI-identified infarcts.

RESULTS

In an unadjusted prospective model in normal subjects, both A beta 1-40 and A beta 1-42 levels in 1998-1999 were associated with incident AD (n = 55) in 2002-2003 (longitudinal analysis). In the fully adjusted multivariate model, neither A beta 1-42 nor A beta 1-40 nor their ratio was associated with incident AD. However, adjustment had a very small effect on point estimates for A beta 1-42, from an odds ratio (OR) of 1.61 (p = 0.007) in the unadjusted model to an OR of 1.46 (p = 0.08) in the fully adjusted model. In 2002-2003 (cross-sectional analysis), only the unadjusted models showed that both peptides were associated with AD.

CONCLUSIONS

Plasma A beta levels are affected by age and by systemic and CNS vascular risk factors. After controlling for these conditions, A beta-40 and A beta 1-42 are weak predictors of conversion to Alzheimer disease (AD) in normal subjects and are only weakly associated with AD in cross-sectional analysis. Consequently, plasma levels of A beta do not seem to be useful biomarkers for AD.

Dementia: is it time for a change in focus?

One of Dr Leon Thal's major contributions to Alzheimer's disease (AD) research was the network of clinical trials and his strong commitment to finding effective therapies for both the prevention and treatment of AD in the population. AD and dementia research has matured since the inception of the Alzheimer's Disease Center program from a primary social service problem to clinical-pathologic correlates and better definition of disease to evaluation of measures of cognition, in vivo images of the brain, and then to measures of beta amyloid and tau in vivo and relationship to clinical dementia. Unfortunately, we still do not know the etiology of AD or the relationship to other brain abnormalities such as vascular disease and Lewy bodies. We also do not have good preventive or treatment strategies. Both are badly needed. The critical question is whether this field is ready for a major change in focus from primarily a descriptive science to analytical, longitudinal studies testing new research hypotheses that will lead to better preventive and treatment approaches.