Biomarkers of Alzheimer's disease]

Recent researches of CSF biomarkers, such as combinations of tau, A beta40, A beta42, are now establishing clinical evidence. These specific biomarkers should be used in clinical practice. To detect incipient AD form MCI and very early AD, these CSF biomarkers are quite useful. Newly developing biomarkers, such as phosphorylated tau and plasma A beta, must be established by large scale prospective study and autopsy-correlations. Thus, the contribution of these biomarkers is desired for diagnosis and clinical practice for Alzheimer's disease.     

CSF markers for incipient Alzheimer's disease

Early diagnosis of Alzheimer's disease (AD) is needed to initiate symptomatic treatment with acetylcholinesterase inhibitors, and will be of even greater significance if drugs aimed at slowing down the degenerative process, such as vaccination regimes and beta-secretase and gamma-secretase inhibitors, prove to affect AD pathology and to have clinical effect. However, there is no clinical method to determine in which patients mild cognitive impairment (MCI) will progress to AD with dementia, and in which patients MCI is benign. Hence, there is a great clinical need for biomarkers to identify incipient AD in patients with MCI. The CSF biomarkers total tau protein, phosphorylated tau protein, and the 42 amino-acid residue form of amyloid-beta may, if put in the right clinical context, prove to have high enough diagnostic accuracy to meet this challenge.     

CSF biomarkers for mild cognitive impairment and early Alzheimer's disease

A correct clinical diagnosis, early in the course of Alzheimer's disease (AD), is of importance given the currently available symptomatic treatment with acetylcholine esterase inhibitors. The development of disease-modifying drugs like beta-sheet breakers or gamma- and beta-secretase inhibitors, emphasizes the need of improved diagnostic accuracy, especially in patients with mild cognitive impairment (MCI) that have incipient AD. Therefore, diagnostic markers in the cerebrospinal fluid (CSF) have become a rapidly growing research field. Three cerebrospinal fluid biomarkers (the 42 amino acid form of beta-amyloid (A beta), total tau, and phospho tau) have been evaluated in numerous scientific papers. These CSF markers have high sensitivity to differentiate early and incipient AD from normal aging, depression, alcohol dementia and Parkinson's disease, but lower specificity against other dementias, such as frontotemporal and Lewy body dementia. If these biomarkers are used in combination with a careful medical history, clinical examination, standard laboratory tests and imaging techniques of the brain, the diagnostic accuracy may be appropriate for the clinical evaluation of MCI cases.     

Intra-individual stability of CSF biomarkers for Alzheimer's disease over two years

This study examines the intra-individual stability of cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease (AD) over 2 years in 83 patients with mild cognitive impairment (MCI) and 17 cognitively healthy control individuals. All participants underwent clinical and neuropsychological evaluation and lumbar puncture at baseline and after 2 years at a university hospital memory clinic. CSF was analyzed for total tau (T-tau), phospho-tau(181) (P-tau(181)) and amyloid-beta(1-42) (Abeta(1-42)). During the 2-year observational time, 12 MCI patients progressed to AD and 3 progressed to vascular dementia, while 68 remained stable. Baseline T-tau and P-tau(181) levels were elevated in the MCI-AD group as compared to the stable MCI patients and the control group (p<0.01), while baseline Abeta(1-42) levels were lower (p<0.001). Stable MCI patients were biochemically indistinguishable from controls. The biomarker levels at baseline and after 2 years showed Pearson R values between 0.81 and 0.91 (p<0.001) and coefficients of variation of 7.2 to 8.7%. In conclusion, intra-individual biomarker levels are remarkably stable over 2 years. Thus, even minor biochemical changes induced by treatment against AD should be detectable using these biomarkers, which bodes well for their usefulness as surrogate markers for drug efficacy in clinical trials.     

Update on the biomarker core of the Alzheimer's Disease Neuroimaging Initiative subjects

Here, we review progress by the Penn Biomarker Core in the Alzheimer's Disease Neuroimaging Initiative (ADNI) toward developing a pathological cerebrospinal fluid (CSF) and plasma biomarker signature for mild Alzheimer's disease (AD) as well as a biomarker profile that predicts conversion of mild cognitive impairment (MCI) and/or normal control subjects to AD. The Penn Biomarker Core also collaborated with other ADNI Cores to integrate data across ADNI to temporally order changes in clinical measures, imaging data, and chemical biomarkers that serve as mileposts and predictors of the conversion of normal control to MCI as well as MCI to AD, and the progression of AD. Initial CSF studies by the ADNI Biomarker Core revealed a pathological CSF biomarker signature of AD defined by the combination of Aβ1-42 and total tau (T-tau) that effectively delineates mild AD in the large multisite prospective clinical investigation conducted in ADNI. This signature appears to predict conversion from MCI to AD. Data fusion efforts across ADNI Cores generated a model for the temporal ordering of AD biomarkers which suggests that Aβ amyloid biomarkers become abnormal first, followed by changes in neurodegenerative biomarkers (CSF tau, F-18 fluorodeoxyglucose-positron emission tomography, magnetic resonance imaging) with the onset of clinical symptoms. The timing of these changes varies in individual patients due to genetic and environmental factors that increase or decrease an individual's resilience in response to progressive accumulations of AD pathologies. Further studies in ADNI will refine this model and render the biomarkers studied in ADNI more applicable to routine diagnosis and to clinical trials of disease modifying therapies.     

Evaluation of CSF biomarkers as predictors of Alzheimer's disease: a clinical follow-up study of 4.7 years

In this study, we determined the diagnostic accuracy of cerebrospinal fluid (CSF) biomarkers to predict development of Alzheimer's disease (AD) within five years in patients with mild cognitive impairment (MCI). To do so, the levels of tau, phosphorylated tau, Aβ42, Aβ40, Aβ38, sAβPPα, and sAβPPβ were analyzed in 327 CSF samples obtained at baseline from patients with AD (n = 94), MCI (n = 166), depressive disorder (n = 29), and cognitively healthy controls (n = 38). In the cohort with MCI at baseline, 33% subsequently developed AD and 16% developed other types of dementia; however, 51% were still cognitively stable after a followup of 4.7 years (range 3.0-7.2). Optimal cutoffs for each biomarker or combinations of biomarkers were defined in the AD, control, and depressive disorder groups. Several combinations resulted in sensitivity and specificity levels > 85% for differentiation of AD from controls and depressive disorder. Using the previously established cutoffs, a combination of Aβ42 and tau could predict future development of AD in MCI patients with a sensitivity of 88%, specificity 82%, positive predictive value 71%, and negative predictive value 94%. MCI patients with both low Aβ42 and high tau levels had a substantially increased risk of developing AD (OR 20; 95% CI 6-58), even after adjustment for confounding factors. Ultimately, CSF biomarkers can stratify MCI patients into those with very low or high risk for future development of AD. However, the specificities and positive predictive values are still too low to be able to diagnose AD before the patients fulfill the clinical criteria.     

Relationship between CSF biomarkers of Alzheimer's disease and rates of regional cortical thinning in ADNI data

Previously it was reported that Alzheimer's disease (AD) patients have reduced amyloid (Aβ 1-42) and elevated total tau (t-tau) and phosphorylated tau (p-tau 181p) in the cerebro-spinal fluid (CSF), suggesting that these same measures could be used to detect early AD pathology in healthy elderly (CN) and mild cognitive impairment (MCI). In this study, we tested the hypothesis that there would be an association among rates of regional brain atrophy, the CSF biomarkers Aβ 1-42, t-tau, and p-tau 181p and ApoE ε4 status, and that the pattern of this association would be diagnosis specific. Our findings primarily showed that lower CSF Aβ 1-42 and higher tau concentrations were associated with increased rates of regional brain tissue loss and the patterns varied across the clinical groups. Taken together, these findings demonstrate that CSF biomarker concentrations are associated with the characteristic patterns of structural brain changes in CN and MCI that resemble to a large extent the pathology seen in AD. Therefore, the finding of faster progression of brain atrophy in the presence of lower Aβ 1-42 levels and higher p-tau levels supports the hypothesis that CSF Aβ 1-42 and tau are measures of early AD pathology. Moreover, the relationship among CSF biomarkers, ApoE ε4 status, and brain atrophy rates are regionally varying, supporting the view that the genetic predisposition of the brain to amyloid and tau mediated pathology is regional and disease stage specific.     

Value of CSF beta-amyloid1-42 and tau as predictors of Alzheimer's disease in patients with mild cognitive impairment

Subjects with mild cognitive impairment (MCI) are at a high risk of developing clinical Alzheimer's disease (AD). We asked to what extent the core biomarker candidates cerebro-spinal fluid (CSF) beta-amyloid(1-42) (Abeta(1-42)) and CSF tau protein concentrations predict conversion from MCI to AD. We studied 52 patients with MCI, 93 AD patients, and 10 healthy controls (HC). The MCI group was composed of 29 patients who had converted to AD during follow-up, and of 23 patients who showed no cognitive decline. CSF Abeta(1-42) and tau protein levels were assessed at baseline in all subjects, using enzyme-linked immunosorbent assays. For assessment of sensitivity and specificity, we used independently established reference values for CSF Abeta(1-42) and CSF tau. The levels of CSF tau were increased, whereas levels of Abeta(1-42) were decreased in MCI subjects. Abeta(1-42) predicted AD in converted MCI with a sensitivity of 59% and a specificity of 100% compared to HC. Tau yielded a greater sensitivity of 83% and a specificity of 90%. In a multiple Cox regression analysis within the MCI group, low baseline levels of Abeta(1-42), but not other predictor variables (tau protein, gender, age, apolipoprotein E epsilon4 carrier status, Mini Mental Status Examination score, observation time, antidementia therapy), correlated with conversion status (P<0.05). Our findings support the notion that CSF tau and Abeta(1-42) may be useful biomarkers in the early identification of AD in MCI subjects.     

The significance of Pin1 in the development of Alzheimer's disease

Pin1 protein, a peptidyl-prolyl cis-trans isomerase plays an important regulatory role in neuronal function. Recent studies indicate that Pin1 may promote the dephosphorylation of tau and restore its ability to bind to and polymerize microtubles. Previous studies on postmortem human brains showed that Pin1 is down-regulated in advanced Alzheimer's disease (AD) brains compared to age-matched non-demented controls. Because AD is a slowly progressive disease with a preclinical period that can last years, the abundance and regulatory function of Pin1 may vary on the course of the disease. In order to evaluate the potential contribution of Pin1 to AD pathogenesis, levels of mRNA, protein and isomerase activity of Pin1 and phosphorylated tau from postmortem brains of 10 persons with mild-cognitive impairment (MCI), 10 with AD and 10 age-matched no cognitive impairment (NCI) were measured. The relationship between Pin1 and phosphorylated tau as well as clinical and cognitive data were analyzed. The results indicated that Pin1 activity in MCI and AD were significantly higher than in NCI. Phosphorylated tau in MCI and AD was also higher than in NCI group. The positive correlation trend in MCI and the robust correlation in AD between Pin1 activity and phosphorylated tau implies that increasing phosphorylated tau during AD pathogenesis may induce the compensatory activation/up-regulation of Pin1, while the inverse correlation between Pin1 activity and phosphorylated tau in NCI group implies that decreased Pin1 may play a role in the initial accumulation of phosphorylated tau in AD pathogenesis.     

Preclinical Alzheimer's disease: diagnosis and prediction of progression

BACKGROUND: From the modest but important breakthroughs in the treatment of Alzheimer's disease (AD), diagnostic focus has increasingly shifted to the accurate detection of the earliest phase of the illness. The challenge of distinguishing preclinical AD from changes of normal ageing or established AD, has been recognised in several attempts at clinical classification. Of these attempts, Mayo Clinic's mild cognitive impairment (MCI) has received significant attention, although it has not been internationally accepted. Not all people diagnosed as having MCI will develop AD, hence there is a need to reliably predict progression. RECENT DEVELOPMENTS: Research in the identification of people with MCI who will develop AD via the use of neuropsychological tests, neuroimaging (both structural and functional), CSF analysis, and other biomarkers, either in isolation or in combination, has progressed rapidly. In this article we summarise findings from relevant recent longitudinal studies. WHERE NEXT?: There are increasing calls to recognise the pathological nature of MCI and to develop international diagnostic guidelines. Such uniform application of MCI criteria can then lead to clearer evidence of its diagnostic and therapeutic benefit. In developing these guidelines, the crucial presence of functional deficit arising from cognitive decline (which diagnoses dementia and excludes MCI) needs to be investigated in a standardised manner. Also needed are good-quality normal-values data on the various tests used to predict progression in preclinical AD.     

Plasma biomarkers for mild cognitive impairment and Alzheimer's disease

Purpose of review: With the move toward development of disease modifying treatments, there is a need for more specific diagnosis of early Alzheimer's disease (AD) and mild cognitive impairment (MCI), plasma biomarkers are likely to play an important role in this. We review the current state of knowledge on plasma biomarkers for MCI and AD, including unbiased proteomics and very recent longitudinal studies.Recent findings: With the use of proteomics methodologies, some proteins have been identified as potential biomarkers in plasma and serum of AD patients, including alpha-1-antitrypsin, complement factor H, alpha-2-macroglobulin, apolipoprotein J, apolipoprotein A-I. The findings of cross-sectional studies of plasma amyloid beta (Aβ) levels are conflicting, but some recent longitudinal studies have shown that low plasma Aβ1–42 or Aβ1–40 levels, or Aβ1–42/Aβ1–40 ratio may be markers of cognitive decline. Other potential biomarkers for MCI and AD reflecting a variety of pathophysiological processes have been assessed, including isoprostanes and homocysteine (oxidative stress), total cholesterol and ApoE4 allele (lipoprotein metabolism), and cytokines and acute phase proteins (inflammation). A panel of 18 signal proteins was reported as markers of MCI and AD.Summary: A variety of potential plasma biomarkers for AD and MCI have been identified, however the findings need replication in longitudinal studies. This area of research promises to yield interesting results in the near future.     

Longitudinal changes of CSF biomarkers in Alzheimer's disease

Longitudinal changes of cerebrospinal fluid (CSF) biomarkers in Alzheimer's disease (AD) have been studied, but there are few consistent conclusions and even less is known about their variation during the different stages of the disease. We hypothesized that changes in CSF biomarker values would correlate with the progression of the cognitive decline in AD. One hundred and thirty-one memory clinic patients [56 AD, 57 mild cognitive impairment (MCI), 10 other neurological disorders, eight unimpaired subjects] underwent a clinical follow-up with repeated Mini-Mental Status Examination (MMSE) tests and two lumbar punctures with a median interval of 3 years. Levels of CSF amyloid-β (Aβ)(42), tau, and p-tau-181 were measured using commercially available ELISA. Twenty-one of the MCI subjects progressed to AD, whereas 26 subjects remained stable and 56 subjects had AD already at the baseline. The subjects displaying the most rapid MMSE decline rate had the lowest baseline Aβ(42), highest tau, and highest p-tau-181 CSF concentrations. An annual decrease of 2.20 pg/ml/year in the CSF p-tau-181 concentration was seen in AD-AD patients (p = 0.001). The difference was significant compared to stable MCI-MCI (increase of 1.24 pg/ml/year, p = 0.001) and cognitively healthy (increase of 0.84 pg/ml/year, p = 0.013) subjects (p for group difference 0.004). The decrease rate of p-tau-181 correlated with the MMSE decrease rate in AD subjects (r = 0.579, p < 0.001). The CSF Aβ(42) level decreased in the AD-AD group (decrease 11.9 pg/ml/year, p < 0.001). Concentrations of hyperphosphorylated tau decline in the late stages of the AD process. The decrease of p-tau-181 appears to correlate with cognitive functioning and probably reflects neuronal loss. More longitudinal studies of CSF biomarker dynamics are needed, especially in patients during the preclinical stage of the disease.     

Disease tracking markers for Alzheimer's disease at the prodromal (MCI) stage

Older persons with Mild Cognitive Impairment (MCI) feature neurobiological Alzheimer's Disease (AD) in 50% to 70% of the cases and develop dementia within the next 5 to 7 years. Current evidence suggests that biochemical, neuroimaging, electrophysiological, and neuropsychological markers can track the disease over time since the MCI stage (also called prodromal AD). The amount of evidence supporting their validity is of variable strength. We have reviewed the current literature and categorized evidence of validity into three classes: Class A, availability of multiple serial studies; Class B a single serial study or multiple cross sectional studies of patients with increasing disease severity from MCI to probable AD; and class C, multiple cross sectional studies of patients in the dementia stage, not including the MCI stage. Several Class A studies suggest that episodic memory and semantic fluency are the most reliable neuropsychological markers of progression. Hippocampal atrophy, ventricular volume and whole brain atrophy are structural MRI markers with class A evidence. Resting-state fMRI and connectivity, and diffusion MR markers in the medial temporal white matter (parahippocampus and posterior cingulum) and hippocampus are promising but require further validation. Change in amyloid load in MCI patients warrant further investigations, e.g. over longer period of time, to assess its value as marker of disease progression. Several spectral markers of resting state EEG rhythms that might reflect neurodegenerative processes in the prodromal stage of AD (EEG power density, functional coupling, spectral coherence, and synchronization) suffer from lack of appropriately designed studies. Although serial studies on late event-related potentials (ERPs) in healthy elders or MCI patients are inconclusive, others tracking disease progression and effects of cholinesterase inhibiting drugs in AD, and cross-sectional including MCI or predicting development of AD offer preliminary evidence of validity as a marker of disease progression from the MCI stage. CSF Markers, such as Aβ 1-42, t-tau and p-tau are valuable markers which support the clinical diagnosis of Alzheimer's disease. However, these markers are not sensitive to disease progression and cannot be used to monitor the severity of Alzheimer's disease. For Isoprostane F2 some evidence exists that its increase correlates with the progression and the severity of AD.     

Review and meta-analysis of biomarkers and diagnostic imaging in Alzheimer's disease

Mild Alzheimer's disease (AD) is often difficult to differentiate from mild cognitive impairment (MCI) or non-AD dementias. A multitude of diagnostic biomarkers and advanced imaging strategies have been developed to aid in the diagnosis and management of AD. We sought to review and analyze the published evidence on key test characteristics of major diagnostic strategies to formulate best estimates of sensitivity (SN) and specificity (SP). A systematic review was undertaken to locate and abstract all studies of biomarkers or diagnostic imaging for AD published in English from January 1990 to March 2010 that provided estimates of SN and SP. Meta-analysis was performed using a bivariate mixed-effects binary regression model. We calculated -SN, SP, and area under the receiver operating curves (AUROC), with confidence and prediction contours. Of 1,840 unique studies identified, 119 presented primary data sufficient for analysis. SN and SP were calculated against non-demented controls, non-AD dementias with and without MCI, if available. Compared to non-demented controls, FDG-PET demonstrated the highest AUROC (0.96), with 90% SN (95%CI 84% to 94%), and 89% SP (95% CI 81% to 94%). FDG-PET also was most accurate in discriminating AD from demented controls (including MCI) with AUROC 0.91, and 92% SN (95%CI 84% to 96%) and 78% SP (95% CI 69% to 85%). For discrimination of AD from non-AD dementias (excluding MCI), CSF Ptau, and SPECT produced identical AUROC (0.86). Diagnostic strategies for AD show wide variation in test characteristics and some show promise for use in clinical practice.     

Biological markers of Alzheimer's disease and mild cognitive impairment

The diagnosis of Alzheimer's disease (AD) is mainly performed by excluding other disorders with similar clinical features. In addition, an analysis of symptoms and signs, blood studies and brain imaging are major ingredients of the clinical diagnostic work-up. However, the diagnosis based on these instruments is unsatisfactory, indicating the need of a highly sensitive and reliable approaches, selective for AD and based on biological markers. Ideally, such markers should reflect the pathophysiological mechanisms of AD, which according to the current hypotheses, derive from the actions of two major protein aggregates, the extracellular beta-amyloid (Abeta) plaques and the neurofibrillary tangles. Since AD is a multifactorial disease, other factors that cause neuronal insult and that contribute to neuronal degeneration in AD include free radical and oxidative stress promoting molecules, proinflammatory cytokines and neurotoxic agents. In this context, the search for anomalous levels or changes in the molecular patterns of Abeta(1-42) or Abeta(1-40), hyperphosphorylated tau isoforms, oxidation products in the cell or cytokines such as interleukin-1 or 6 facilitates the selection of biomarkers in AD. There is clear evidence that the cerebrospinal fluid (CSF) levels of beta(1-42) are significantly reduced in AD patients as compared with senile controls, while increased levels of tau have been revealed. The CSF levels of these proteins reflect their metabolism in the central nervous system. Approaches using ELISA and immunochemical methods for the quantification of these markers in CSF have been preferentially used. Diagnosis criteria and number of patients exhibits variations in the different reports, while clinico-pathological studies are scarce. An increasing number of studies suggest that supplementary use of these CSF markers preferably in combination, adds to the accuracy of an AD diagnosis.     

Assessing candidate serum biomarkers for Alzheimer's disease: a longitudinal study

Because of the growing impact of late onset cognitive loss, considerable effort has been directed toward the development of improved diagnostic techniques for Alzheimer's disease (AD) that may pave the way for earlier (and more effective) therapeutic efforts. Serum-based biomarkers are the least expensive and invasive modality for screening and routine monitoring. We systematically reviewed the literature to assemble a list of serum biomarkers relevant to AD. In parallel, we conducted a proteomic LC-MS/MS analysis of serum collected from neurologically normal subjects and subjects with mild cognitive impairment (MCI) and early AD (n = 6 in all). Complement C3 and alpha-2-macroglobulin were identified from both the literature review and our proteomic screen for further validation. For these two candidates, ELISA was performed on serum collected from a small independent cohort of subjects for longitudinal analysis. Serum was serially collected from neurologically normal subjects (n = 5) and subjects with MCI who were subsequently followed for a period of two years (n = 5) and regrouped into stable MCI and progressive MCI or AD (n = 6). The ability of each marker to predict which subjects with MCI would progress to dementia and which would remain cognitively stable was assessed. Patients with probable cerebral amyloid angiopathy were also identified (n = 3). This preliminary analysis tested the most-promising serum protein biomarkers for AD and we concluded that none are yet ready for use in the clinical diagnosis and management of dementia. However, a more thorough assessment in longitudinal studies with higher statistical power is warranted.     

Independent component analysis-based classification of Alzheimer's disease MRI data

There is an unmet medical need to identify neuroimaging biomarkers that allow us to accurately diagnose and monitor Alzheimer's disease (AD) at its very early stages and to assess the response to AD-modifying therapies. To a certain extent, volumetric and functional magnetic resonance imaging (fMRI) studies can detect changes in structure, cerebral blood flow, and blood oxygenation that distinguish AD and mild cognitive impairment (MCI) subjects from healthy control (HC) subjects. However, it has been challenging to use fully automated MRI analytic methods to identify potential AD neuroimaging biomarkers. We have thus proposed a method based on independent component analysis (ICA) for studying potential AD-related MR image features that can be coupled with the use of support vector machine (SVM) for classifying scans into categories of AD, MCI, and HC subjects. The MRI data were selected from the Open Access Series of Imaging Studies (OASIS) and the Alzheimer's Disease Neuroimaging Initiative databases. The experimental results showed that the ICA method coupled with SVM classifier can differentiate AD and MCI patients from HC subjects, although further methodological improvement in the analytic method and inclusion of additional variables may be required for optimal classification.     

The search for antecedent biomarkers of Alzheimer's disease

Alzheimer's disease (AD) will likely become the greatest public health crisis in the United States within the next 2-3 decades if left unchecked. There are no proven treatments that delay the onset or prevent the progression of AD, although a few promising candidates are under development. Even the earliest clinical symptoms of AD are accompanied by, and likely due to, neuronal/synaptic dysfunction and/or cell death. Thus, it is critical to identify individuals with "preclinical AD", prior to the development of clinical symptoms and concomitant neuronal loss, so new therapies will have the greatest clinical impact. At present, there are no antecedent biomarkers that will identify individuals with preclinical AD, however ongoing investigations of "at risk" populations, including those with Mild Cognitive Impairment (MCI), presymptomatic individuals harboring known disease-causing familial AD mutations or carriers of the epsilon4 allele of apolipoprotein E are offering insights into possible biomarkers of early disease processes. To discover antecedent biomarkers of AD, a prospective, longitudinal study of middle-aged individuals with positive or negative family history of AD has been initiated at Washington University in St. Louis. The Adult Children Study provides an opportunity to discuss the challenges and goals for investigations of antecedent AD biomarkers.     

Biochemical characterization of Abeta and tau pathologies in mild cognitive impairment and Alzheimer's disease

We report a post mortem biochemical analysis of amyloid-beta (Abeta) (ELISA) and tau (Western immunoblots) in the temporo-parietal neocortex of subjects with a clinical diagnosis of mild cognitive impairment (MCI, n=12), Alzheimer's disease (AD, n=12) or no cognitive impairment (NCI, n=12). Levels of Abeta _{42} in the detergent-insoluble protein fractions were significantly higher in persons with AD but did not differentiate individuals with MCI. Conversion of tau into its insoluble form (soluble/insoluble tau ratio) or into paired helical filament tau (PHF_{tau}) were the biochemical variables most closely related to clinical and neuropathological diagnoses, but they did not distinguished MCI from the two other groups. Interestingly, soluble/insoluble total tau ratio, PHF_{tau} and insoluble Abeta_{42} concentrations in the cortex correlated strongly with global cognition scores proximate to death and with immunohistochemical and histological quantification of Abeta and tau pathologies. Our data suggest that 1) insoluble Abeta _{42} and insoluble tau (total or PHF_{tau}) show a significant relationship with the clinical and neuropathological diagnosis of AD; 2) Although MCI appears to represent an intermediate stage between NCI and AD, the quantification of cortical Abeta and tau pathologies did not significantly distinguish subjects with MCI from either group.     

Association between CSF biomarkers and incipient Alzheimer's disease in patients with mild cognitive impairment: a follow-up study

BACKGROUND: Disease-modifying treatment strategies for Alzheimer's disease have led to an urgent need for biomarkers to identify the disease at a very early stage. Here, we assess the association between CSF biomarkers and incipient Alzheimer's in patients with mild cognitive impairment (MCI). METHODS: From a series of 180 consecutive patients with MCI, we assessed 137 who underwent successful lumbar puncture at baseline. Patients at risk of developing dementia were followed clinically for 4-6 years. Additionally, 39 healthy individuals, cognitively stable over 3 years, served as controls. We analysed CSF concentrations of beta amyloid(1-42) (Abeta42), total tau (T-tau), and phosphorylated tau (P-tau181) using Luminex xMAP technology. FINDINGS: During follow-up, 57 (42%) patients with MCI developed Alzheimer's disease, 21 (15%) developed other forms of dementia, and 56 (41%) remained cognitively stable for 5.2 years (range 4.0-6.8). A combination of CSF T-tau and Abeta42 at baseline yielded a sensitivity of 95% and a specificity of 83% for detection of incipient AD in patients with MCI. The relative risk of progression to Alzheimer's disease was substantially increased in patients with MCI who had pathological concentrations of T-tau and Abeta42 at baseline (hazard ratio 17.7, p<0.0001). The association between pathological CSF and progression to Alzheimer's disease was much stronger than, and independent of, established risk factors including age, sex, education, APOE genotype, and plasma homocysteine. The combination of T-tau and Abeta42/P-tau181 ratio yielded closely similar results (sensitivity 95%, specificity 87%, hazard ratio 19.8). INTERPRETATION: Concentrations of T-tau, P-tau181, and Abeta42 in CSF are strongly associated with future development of Alzheimer's disease in patients with MCI.