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Purpose of review

This review describes the evolution of the clinical criteria for Alzheimer’s disease over the past 25 years, with special emphasis on those recently published that have incorporated the use of biomarkers.

Recent findings

One of the most important advances in the knowledge of Alzheimer’s disease was the development of cerebrospinal fluid, PET and MRI biomarkers. These have shown that the Alzheimer’s disease is present in cognitively normal individuals, suggesting that there is a long incubation process that precedes the onset of the symptoms. Although there are diagnostic criteria for Alzheimer’s disease, the National Institute on Aging and the Alzheimer’s Association has proposed a set of diagnostic criteria oriented to provide a unified vision of the pathological process from preclinical, to mild cognitive impairment, and to full-blown dementia. These new criteria take advantage of different biomarkers to support the clinical diagnosis of the different stages of the disease.

Summary

The new guidelines provide a definition of the dementia syndrome and core diagnostic features to be used in research and clinical practice, although they caution about the use of biomarkers, since they still require validation, and the longitudinal interaction and dynamics of these biomarkers in relationship to the manifestation of the symptoms are not fully understood.

Biomarkers are likely to be important in the study of Alzheimer disease (AD) for a variety of reasons. A clinical diagnosis of Alzheimer disease is inaccurate even among experienced investigators in about 10% to 15% of cases, and biomarkers might improve the accuracy of diagnosis. Importantly for the development of putative disease-modifying drugs for Alzheimer disease, biomarkers might also serve as indirect measures of disease severity. When used in this way, sample sizes of clinical trials might be reduced, and a change in biomarker could be considered supporting evidence of disease modification. This review summarizes a meeting of the Alzheimer’s Association’s Research Roundtable, during which existing and emerging biomarkers for AD were evaluated. Imaging biomarkers including volumetric magnetic resonance imaging and positron emission tomography assessing either glucose utilization or ligands binding to amyloid plaque are discussed. Additionally, biochemical biomarkers in blood or cerebrospinal fluid are assessed. Currently appropriate uses of biomarkers in the study of Alzheimer disease, and areas where additional work is needed, are discussed.

OBJECTIVE

Cerebrospinal fluid (CSF) biomarkers of Alzheimer’s disease (AD) are currently being considered for inclusion in revised diagnostic criteria for research and/or clinical purposes to increase the certainty of ante-mortem diagnosis. Establishing biomarker validity requires demonstration that the assays are true markers of underlying disease pathology (e.g., amyloid plaques and/or neurofibrillary tangles) in living individuals.

DESIGN

We compared the performances of the two most commonly used platforms, INNOTEST® ELISA and INNO-BIA AlzBio3 for measurement of CSF amyloid-beta (Aβ) and tau(s), for identifying the presence of amyloid plaques in a research cohort (n=103). Values obtained for CSF Aβ1-42, total tau and phosphorylated tau181 (p-tau181) using the two assay platforms were compared to brain amyloid load as assessed by positron emission tomography using the amyloid imaging agent, Pittsburgh Compound B (PIB).

SUBJECTS

Research volunteers who are cognitively normal or have very mild to moderate AD dementia.

RESULTS

The two assay platforms yielded different (~2–6-fold) absolute values for the various analytes, but relative values were highly correlated. CSF Aβ1-42 correlated inversely, and tau and p-tau181 correlated positively, with the amount of cortical PIB binding, albeit to differing degrees. Both assays yielded similar patterns of CSF biomarker correlations with amyloid load. The ratios of total tau/Aβ1-42 and p-tau181/Aβ1-42 outperformed any single analyte, including Aβ1-2, in discriminating individuals with versus without cortical amyloid.

CONCLUSIONS

The INNOTEST® and INNO-BIA CSF platforms performed equally well in identifying individuals with underlying amyloid plaque pathology. Differences in absolute values, however, point to the need for assay-specific diagnostic cut-point values.

Objective

Cerebrospinal fluid (CSF) levels of Aβ peptide 1-42 (Aβ42), tau, and phosphorylated tau (ptau) are potential biomarkers of Alzheimer's disease (AD). We hypothesized that these biomarkers might predict the rate of cognitive change in individuals with very mild dementia of the Alzheimer type (DAT).

Design

Retrospective analysis of CSF biomarkers and clinical data.

Setting

An academic Alzheimer's Disease Research Center.

Participants

Research volunteers in a longitudinal study of aging and cognition. Participants (n=49) had a clinical diagnosis of very mild DAT with a Clinical Dementia Rating (CDR) of 0.5 at the time of lumbar puncture. All participants had at least one follow-up assessment (mean years of follow-up = 3.5 ± 1.8 years).

Main outcome measures

Baseline CSF levels of Aβ42, Aβ40, tau and tau phosphorylated at threonine 181 (ptau181), rate of dementia progression as measured by CDR-sum of boxes (CDR-SB) and by psychometric performance,

Results

The rate of dementia progression was significantly more rapid in individuals with lower baseline CSF Aβ42, with higher tau or ptau181, or high tau/Aβ42 ratio. For example, the annual change in CDR-SB was 1.1 for the lowest two tertiles of Aβ42 values and 0.3 for the highest tertile of Aβ42 values.

Conclusions

In individuals with very mild DAT, lower CSF Aβ42, high tau or ptau181, or a high tau/Aβ42 ratio quantitatively predict more rapid progression of cognitive deficits and dementia. CSF biomarkers may be useful prognostically and to identify individuals who are more likely to progress for participation in therapeutic clinical trials.

Objective

To empirically assess the concept that Alzheimer’s disease (AD) biomarkers significantly depart from normality in a temporally ordered manner.

Design

Validation sample

Setting

Multi-site, referral centers

Patients

We studied 401 elderly cognitively normal (CN), Mild Cognitive Impairment (MCI) and AD dementia subjects from the Alzheimer’s Disease Neuroimaging Initiative. We compared the proportions of three AD biomarkers – CSF Aβ42, CSF total tau (t-tau), and hippocampal volume adjusted by intra-cranial volume (HVa) - that were abnormal as cognitive impairment worsened. Cut-points demarcating normal vs. abnormal for each biomarker were established by maximizing diagnostic accuracy in independent autopsy samples.

Interventions

None

Main Outcome measures

AD biomarkers

Results

Within each clinical group in the entire sample (n=401) CSF Aβ42 was abnormal more often than t-tau or HVa. Among the 298 subjects with both baseline and 12 month data, the proportion of subjects with abnormal Aβ42 did not change from baseline to 12 months in any group. The proportion of subjects with abnormal t-tau increased from baseline to 12 months in CN (p=0.05) but not in MCI or dementia. In 209 subjects with abnormal CSF AB42 at baseline, the percent abnormal HVa, but not t-tau, increased from baseline to 12 months in MCI.

Conclusions

Reduction in CSF Aβ42 denotes a pathophysiological process that significantly departs from normality (i.e., becomes dynamic) early, while t-tau and HVa are biomarkers of downstream pathophysiological processes. T-tau becomes dynamic before HVa, but HVa is more dynamic in the clinically symptomatic MCI and dementia phases of the disease than t-tau.

Alzheimer's disease is the most common form of dementia affecting millions of individuals worldwide. It is currently diagnosed only via clinical assessments and confirmed by postmortem brain pathology. The development of validated biomarkers for Alzheimer's disease is essential to improve diagnosis and accelerate the development of new therapies. Biochemical and neuroimaging markers could facilitate diagnosis, predict AD progression from a pre-AD state of mild cognitive impairment (MCI), and be used to monitor efficacies of disease-modifying therapies. Cerebrospinal fluid (CSF) levels of Aβ40, Aβ42, total tau, and phosphorylated tau have diagnostic values in AD. Measurements of the above CSF markers in combination are useful in predicting the risk of progression from MCI to AD. New potential biomarkers are emerging, and CSF or plasma marker profiles may eventually become part of the clinician's toolkit for accurate AD diagnosis and management. These biomarkers along with clinical assessment, neuropsychological testing, and neuroimaging could achieve a much higher diagnostic accuracy for AD and related disorders in the future.

Ante-mortem diagnosis of neurodegenerative disorders based on clinical features alone is associated with variable sensitivity and specificity, and biomarkers can potentially improve the accuracy of clinical diagnosis. In patients suspected of having Alzheimer’s disease (AD), alterations in cerebrospinal fluid (CSF) biomarkers that reflect the neuropathologic changes of AD strongly support the diagnosis, although there is a trade-off between sensitivity and specificity due to similar changes in cognitively healthy subjects. Here we review the current approaches in using CSF AD biomarkers (total tau, p-tau181, and Aβ42) to predict the presence of AD pathology, and our recent work using multi-analyte profiling to derive novel biomarkers for biofluid-based AD diagnosis. We also review our use of the multi-analyte profiling strategy to identify novel biomarkers that can distinguish between subtypes of frontotemporal lobar degeneration, and those at risk of developing cognitive impairment in Parkinson’s disease. Multi-analyte profiling is a powerful tool for biomarker discovery in complex neurodegenerative disorders, and analytes associated with one or more diseases may shed light on relevant biological pathways and potential targets for intervention.

Background

Alterations in cerebrospinal fluid (CSF) tau and β–amyloid peptide 1–42 (Aβ42) levels and rates of cerebral glucose (CMRglu) on fluorodeoxyglucose positron emission tomography (FDG PET) occur years before clinical symptoms of Alzheimer’s disease (AD) become manifest, but their relationship remains unclear.

Objective

To determine whether CSF AD biomarker levels and CMRglu in healthy individuals correlate in brain structures affected early in AD.

Design

Cohort study.

Setting

Alzheimer’s disease research center.

Participants

Twenty individuals without dementia, aged 46 to 83 years.

Interventions

Lumbar CSF sampling and FDG-PET imaging of CMRglu. The CSF Aβ42, tau, and tau phosphorylated at threonine 181 (p–tau181) levels were measured using immunobead–based multiplex assays.

Main Outcome Measures

Correlations between CMRglu and CSF biomarker levels were analyzed via voxel–based and volume–of–interest approaches.

Results

Voxel–based analyses demonstrated significant negative correlations between CSF tau and p–tau181 levels and CMRglu in the posterior cingulate, precuneus, and parahippocampal regions. In contrast, a limited positive correlation was found between CSF Aβ42 levels and CMRglu in the inferior temporal cortex. Volume–of–interest analyses confirmed negative associations between CSF tau and p–tau181 levels and CMRglu in the parietal and medial parietal lobes and a positive association between CSF Aβ42 levels and CMRglu in the parahippocampal gyrus.

Conclusions

In healthy individuals, higher CSF tau and p–tau181 concentrations were associated with more severe hypometabolism in several brain regions affected very early in AD, whereas lower CSF Aβ42 concentrations were associated with hypometabolism only in the medial temporal lobe. This suggests that early tau and Aβ abnormalities may be associated with subtle synaptic changes in brain regions vulnerable to AD. A longitudinal assessment of CSF and FDG–PET biomarkers is needed to determine whether these changes predict cognitive impairment and incipient AD.

Recent research progress has given detailed knowledge on the molecular pathogenesis of Alzheimer’s disease (AD), which has been translated into an intense, ongoing development of disease-modifying treatments. Most new drug candidates are targeted on inhibiting amyloid β (Aβ) production and aggregation. In drug development, it is important to co-develop biomarkers for Aβ-related mechanisms to enable early diagnosis and patient stratification in clinical trials, and to serve as tools to identify and monitor the biochemical effect of the drug directly in patients. Biomarkers are also requested by regulatory authorities to serve as safety measurements. Molecular aberrations in the AD brain are reflected in the cerebrospinal fluid (CSF). Core CSF biomarkers include Aβ isoforms (Aβ40/Aβ42), soluble APP isoforms, Aβ oligomers and β-site APP-cleaving enzyme 1 (BACE1). This article reviews recent research advances on core candidate CSF and plasma Aβ-related biomarkers, and gives a conceptual review on how to implement biomarkers in clinical trials in AD.

Objective

To characterize the shape of the trajectories of Alzheimer’s Disease (AD) biomarkers as a function of MMSE.

Design

Longitudinal registries from the Mayo Clinic and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

Patients

Two different samples (n=343 and n=598) were created that spanned the cognitive spectrum from normal to AD dementia. Subgroup analyses were performed in members of both cohorts (n=243 and n=328) who were amyloid positive at baseline.

Main Outcome Measures

The shape of biomarker trajectories as a function of MMSE, adjusted for age, was modeled and described as baseline (cross-sectional) and within-subject longitudinal effects. Biomarkers evaluated were cerebro spinal fluid (CSF) Aβ42 and tau; amyloid and fluoro deoxyglucose position emission tomography (PET) imaging, and structural magnetic resonance imaging (MRI).

Results

Baseline biomarker values generally worsened (i.e., non-zero slope) with lower baseline MMSE. Baseline hippocampal volume, amyloid PET and FDG PET values plateaued (i.e., non-linear slope) with lower MMSE in one or more analyses. Longitudinally, within-subject rates of biomarker change were associated with worsening MMSE. Non-constant within-subject rates (deceleration) of biomarker change were found in only one model.

Conclusions

Biomarker trajectory shapes by MMSE were complex and were affected by interactions with age and APOE status. Non-linearity was found in several baseline effects models. Non-constant within-subject rates of biomarker change were found in only one model, likely due to limited within-subject longitudinal follow up. Creating reliable models that describe the full trajectories of AD biomarkers will require significant additional longitudinal data in individual participants.

Background

The clinical diagnosis of dementing diseases largely depends upon the subjective interpretation of patient symptoms. Consensus panels are frequently used in research to determine diagnoses when definitive pathological findings are unavailable. Nevertheless, research on group decision-making indicates many factors can adversely influence panel performance.

Objective

To determine conditions that improve consensus panel diagnosis.

Design

Comparison of neuropathological diagnoses with individual and consensus panel diagnoses based on clinical summaries, FDG-PET scans, and summaries with scans.

Setting

Expert and trainee individual and consensus panel deliberations using a modified Delphi method in a pilot research study of the diagnostic utility of FDG-PET imaging.

Patients and Methods

Forty-five patients with pathologically confirmed Alzheimer’s disease or frontotemporal dementia. Statistical measures of diagnostic accuracy, agreement, and confidence for individual raters and panelists before and after consensus deliberations.

Results

The consensus protocol using trainees and experts surpassed the accuracy of individual expert diagnoses when clinical information elicited diverse judgments. In these situations, consensus was 3.5 times more likely to produce positive rather than negative changes in the accuracy and diagnostic certainty of individual panelists. A rule that forced group consensus was at least as accurate as majority and unanimity rules.

Conclusions

Using a modified Delphi protocol to arrive at a consensus diagnosis is a reasonable substitute for pathologic information. This protocol improves diagnostic accuracy and certainty when panelist judgments differ and is easily adapted to other research and clinical settings while avoiding potential pitfalls of group decision-making.

Background

Today, dementias are diagnosed late in the course of disease. Future treatments have to start earlier in the disease process to avoid disability requiring new diagnostic tools. The objective of this study is to develop a new method for the differential diagnosis and identification of new biomarkers of Alzheimer's disease (AD) using capillary-electrophoresis coupled to mass-spectrometry (CE-MS) and to assess the potential of early diagnosis of AD.

Methods and Findings

Cerebrospinal fluid (CSF) of 159 out-patients of a memory-clinic at a University Hospital suffering from neurodegenerative disorders and 17 cognitively-healthy controls was used to create differential peptide pattern for dementias and prospective blinded-comparison of sensitivity and specificity for AD diagnosis against the Criterion standard in a naturalistic prospective sample of patients. Sensitivity and specificity of the new method compared to standard diagnostic procedures and identification of new putative biomarkers for AD was the main outcome measure. CE-MS was used to reliably detect 1104 low-molecular-weight peptides in CSF. Training-sets of patients with clinically secured sporadic Alzheimer's disease, frontotemporal dementia, and cognitively healthy controls allowed establishing discriminative biomarker pattern for diagnosis of AD. This pattern was already detectable in patients with mild cognitive impairment (MCI). The AD-pattern was tested in a prospective sample of patients (n = 100) and AD was diagnosed with a sensitivity of 87% and a specificity of 83%. Using CSF measurements of beta-amyloid1-42, total-tau, and phospho181-tau, AD-diagnosis had a sensitivity of 88% and a specificity of 67% in the same sample. Sequence analysis of the discriminating biomarkers identified fragments of synaptic proteins like proSAAS, apolipoprotein J, neurosecretory protein VGF, phospholemman, and chromogranin A.

Conclusions

The method may allow early differential diagnosis of various dementias using specific peptide fingerprints and identification of incipient AD in patients suffering from MCI. Identified biomarkers facilitate face validity for the use in AD diagnosis.

One of the current challenge in Alzheimer’s disease (AD) is the identification of reliable biomarkers that might improve diagnostic accuracy, possibly correlating with the disease progression and patient’s response to therapy. As the clinically validated AD biomarkers evaluate cerebrospinal fluid (CSF) parameters, the need for less invasive diagnostic markers is well evident. To this respect, blood circulating cytokines or growth factors have provided some encouraging results, even though no clinically validated to date. In 2007 Ray et al suggested a panel of 18 circulating molecules that might increase AD diagnostic accuracy. In an attempt of replicating their data, we designed a multiplex fluorimetric assay comprising 16 independent analytes and covering 15 out of the 18 described proteins. We collected serum samples from three diagnostic groups: probable AD (n=33), matched healthy controls (CNT, n=23) and non AD demented (NAD, n=14). After correction for age, we found an increased level of EGF-1 in AD in comparison to CNT and NAD, while an increase of TRAIL-R4 was found in NAD. However, evaluation of specificity/sensitivity by ROC curve analysis gave weak evidence of diagnostic accuracy (area under the curve = 0.63 and 0.66 for EGF and TRAIL-R4, respectively). Finally, we tried to find a diagnostic classifier by a multivariate algorithm. We found indication of diagnostic evidence for AD only, while NAD samples did not show a diagnostic pattern.

Context

There is no rapid and cost effective tool that can be implemented as a front-line screening tool for Alzheimer's disease (AD) at the population level.

Objective

To generate and cross-validate a blood-based screener for AD that yields acceptable accuracy across both serum and plasma.

Design, Setting, Participants

Analysis of serum biomarker proteins were conducted on 197 Alzheimer's disease (AD) participants and 199 control participants from the Texas Alzheimer's Research Consortium (TARC) with further analysis conducted on plasma proteins from 112 AD and 52 control participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The full algorithm was derived from a biomarker risk score, clinical lab (glucose, triglycerides, total cholesterol, homocysteine), and demographic (age, gender, education, APOE*E4 status) data.

Major Outcome Measures

Alzheimer's disease.

Results

11 proteins met our criteria and were utilized for the biomarker risk score. The random forest (RF) biomarker risk score from the TARC serum samples (training set) yielded adequate accuracy in the ADNI plasma sample (training set) (AUC = 0.70, sensitivity (SN) = 0.54 and specificity (SP) = 0.78), which was below that obtained from ADNI cerebral spinal fluid (CSF) analyses (t-tau/Aβ ratio AUC = 0.92). However, the full algorithm yielded excellent accuracy (AUC = 0.88, SN = 0.75, and SP = 0.91). The likelihood ratio of having AD based on a positive test finding (LR+) = 7.03 (SE = 1.17; 95% CI = 4.49–14.47), the likelihood ratio of not having AD based on the algorithm (LR−) = 3.55 (SE = 1.15; 2.22–5.71), and the odds ratio of AD were calculated in the ADNI cohort (OR) = 28.70 (1.55; 95% CI = 11.86–69.47).

Conclusions

It is possible to create a blood-based screening algorithm that works across both serum and plasma that provides a comparable screening accuracy to that obtained from CSF analyses.

Alzheimer’s disease will reach epidemic proportions within the next 20–30 years if left unchecked. Currently, there are no treatments that prevent or slow Alzheimer’s disease but many are being developed. Parallel efforts to develop biomarkers to aid in disease diagnosis and prognosis, and assess disease risk are currently underway. Clinicopathological and biomarker studies have demonstrated that Alzheimer’s disease pathology can be detected preclinically. Using biomarkers to identify affected individuals prior to the onset of clinical symptoms and associated synaptic/neuronal loss should enable novel clinical trial design and early mechanism-based therapeutic intervention. This article summarizes the most promising cerebrospinal fluid biomarkers, highlights novel applications and current challenges, and provides a prediction on how the field may evolve in 5–10 years.

As Alzheimer's disease remains a clinical diagnosis, and as clinical diagnosis can be difficult, it makes sense to look for so-called biomarkers. A biomarker predicts who is likely to have the illness and who is not. Some biomarkers might even correlate with a clinically meaningful response to treatment. Developing biomarkers is often characterized as searching for a diagnostic gold standard that can seem appealing in its promise of certainty. Even so, considering both the economic history of the gold standard and the results of neuropathological studies, framing the search for measurable, biological correlates of dementia syndromes in this way is likely to be self-defeating. Instead of considering biomarkers as providing certainty through referent criterion validation, currently it makes more sense to test their construct validity and their predictive ability. This means that while biomarkers should inform, they will not dictate clinical meaningfulness. For the foreseeable future, even were they to inform diagnosis, biomarkers cannot substitute for understanding whether patients and caregivers find a given dementia treatment effective. Instead, clinicians should recognize their own determining role, both in dementia diagnosis and in the evaluation of treatment. These roles will best be executed by hearing what patients and caregivers tell us about dementia, and its response to treatment.

Background

We previously created a serum-based algorithm that yielded excellent diagnostic accuracy in Alzheimer's disease. The current project was designed to refine that algorithm by reducing the number of serum proteins and by including clinical labs. The link between the biomarker risk score and neuropsychological performance was also examined.

Methods

Serum-protein multiplex biomarker data from 197 patients diagnosed with Alzheimer's disease and 203 cognitively normal controls from the Texas Alzheimer's Research Consortium were analyzed. The 30 markers identified as the most important from our initial analyses and clinical labs were utilized to create the algorithm.

Results

The 30-protein risk score yielded a sensitivity, specificity, and AUC of 0.88, 0.82, and 0.91, respectively. When combined with demographic data and clinical labs, the algorithm yielded a sensitivity, specificity, and AUC of 0.89, 0.85, and 0.94, respectively. In linear regression models, the biomarker risk score was most strongly related to neuropsychological tests of language and memory.

Conclusions

Our previously published diagnostic algorithm can be restricted to only 30 serum proteins and still retain excellent diagnostic accuracy. Additionally, the revised biomarker risk score is significantly related to neuropsychological test performance.

In view of the growing prevalence of Alzheimer's disease (AD) worldwide, there is an urgent need for the development of better diagnostic tools and more effective therapeutic interventions. At the earliest stages of AD, no significant cognitive or functional impairment is detected by conventional clinical methods. However, new technologies based on structural and functional neuroimaging, and on the biochemical analysis of cerebrospinal fluid (CSF) may reveal correlates of intracerebral pathology in individuals with mild, predementia symptoms. These putative correlates are commonly referred to as AD-related biomarkers. The relevance of the early diagnosis of AD relies on the hypothesis that pharmacological interventions with disease-modifying compounds are likely to produce clinically relevant benefits if started early enough in the continuum towards dementia. Here we review the clinical characteristics of the prodromal and transitional states from normal cognitive ageing to dementia in AD. We further address recent developments in biomarker research to support the early diagnosis and prediction of dementia, and point out the challenges and perspectives for the translation of research data into clinical practice.

Recent advances in biomarker studies on dementia are summarized here. CSF Aβ40, Aβ42, total tau, and phosphorylated tau are the most sensitive biomarkers for diagnosis of Alzheimer's disease (AD) and prediction of onset of AD from mild cognitive impairment (MCI). Based on this progress, new diagnostic criteria for AD, MCI, and preclinical AD were proposed by National Institute of Aging (NIA) and Alzheimer's Association in August 2010. In these new criteria, progress in biomarker identification and amyloid imaging studies in the past 10 years have added critical information. Huge contributions of basic and clinical studies have established clinical evidence supporting these markers. Based on this progress, essential therapy for cure of AD is urgently expected.

Background

Clinicopathological studies suggest that Alzheimer's disease (AD) pathology begins ∼10–15 years before the resulting cognitive impairment draws medical attention. Biomarkers that can detect AD pathology in its early stages and predict dementia onset would, therefore, be invaluable for patient care and efficient clinical trial design. We utilized a targeted proteomics approach to discover novel cerebrospinal fluid (CSF) biomarkers that can augment the diagnostic and prognostic accuracy of current leading CSF biomarkers (Aβ42, tau, p-tau181).

Methods and Findings

Using a multiplexed Luminex platform, 190 analytes were measured in 333 CSF samples from cognitively normal (Clinical Dementia Rating [CDR] 0), very mildly demented (CDR 0.5), and mildly demented (CDR 1) individuals. Mean levels of 37 analytes (12 after Bonferroni correction) were found to differ between CDR 0 and CDR>0 groups. Receiver-operating characteristic curve analyses revealed that small combinations of a subset of these markers (cystatin C, VEGF, TRAIL-R3, PAI-1, PP, NT-proBNP, MMP-10, MIF, GRO-α, fibrinogen, FAS, eotaxin-3) enhanced the ability of the best-performing established CSF biomarker, the tau/Aβ42 ratio, to discriminate CDR>0 from CDR 0 individuals. Multiple machine learning algorithms likewise showed that the novel biomarker panels improved the diagnostic performance of the current leading biomarkers. Importantly, most of the markers that best discriminated CDR 0 from CDR>0 individuals in the more targeted ROC analyses were also identified as top predictors in the machine learning models, reconfirming their potential as biomarkers for early-stage AD. Cox proportional hazards models demonstrated that an optimal panel of markers for predicting risk of developing cognitive impairment (CDR 0 to CDR>0 conversion) consisted of calbindin, Aβ42, and age.

Conclusions/Significance

Using a targeted proteomic screen, we identified novel candidate biomarkers that complement the best current CSF biomarkers for distinguishing very mildly/mildly demented from cognitively normal individuals. Additionally, we identified a novel biomarker (calbindin) with significant prognostic potential.

Objective

To determine whether cerebrospinal fluid (CSF) biomarkers for Alzheimer disease fluctuate significantly over time in a cohort of older, mildly symptomatic individuals.

Design

Biomarker validation in a clinical cohort.

Setting

University hospital inpatient unit.

Participants

Ten patients admitted for CSF drainage for diagnostic purposes.

Main Outcome Measures

The CSF levels of Aβ1–40, Aβ1–42, tau, and phosphorylated tau on threonine 181 (p-tau181) were measured every 6 hours for 24 or 36 hours.

Results

The mean coefficient of variation values for each biomarker assessed in our 10 patients were 5.5% (95% CI, 3.8%–10.0%) for Aβ1–42, 12.2% (9.0%–24.2%) for Aβ1–40, 8.2% (5.7%–15.1%) for total tau, and 11.9% (8.5%–23.0%) for p-tau181. These values are only slightly higher than the variability in the assay. In addition, no significant circadian fluctuation in any Alzheimer disease biomarker was observed given the limitations of our sampling frequency.

Conclusion

In a cohort of elderly patients, little fluctuation in the levels of important Alzheimer disease biomarkers in lumbar CSF is seen as a function of time.

Accurate ante mortem diagnosis in frontotemporal lobar degeneration (FTLD) is crucial to the development and implementation of etiology-based therapies. Several neurodegenerative disease-associated proteins, including the major protein constituents of inclusions in Alzheimer's disease (AD) associated with amyloid-beta (Aβ1−42) plaque and tau neurofibrillary tangle pathology, can be measured in cerebrospinal fluid (CSF) for diagnostic applications. Comparative studies using autopsy-confirmed samples suggest that CSF total-tau (t-tau) and Aβ1−42 levels can accurately distinguish FTLD from AD, with a high t-tau to Aβ1−42 ratio diagnostic of AD; however, there is also an urgent need for FTLD-specific biomarkers. These analytes will require validation in large autopsy-confirmed cohorts and face challenges of standardization of within- and between-laboratory sources of error. In addition, CSF biomarkers with prognostic utility and longitudinal study of CSF biomarker levels over the course of disease are also needed. Current goals in the field include identification of analytes that are easily and reliably measured and can be used alone or in a multi-modal approach to provide an accurate prediction of underlying neuropathology for use in clinical trials of disease modifying treatments in FTLD. To achieve these goals it will be of the utmost importance to view neurodegenerative disease, including FTLD, as a clinicopathological entity, rather than exclusively a clinical syndrome.

Neurochemical biomarkers for diagnosing dementias are currently under intensive investigation and the field is rapidly expanding. The main protagonists and the best defined among them are cerebrospinal fluid levels of Aβ42, tau and its phosphorylated forms (p-tau). In addition, novel cerebrospinal fluid biomarkers are emerging and their multiparametric assessment seems most promising for increasing the accuracy in neurochemical dementia diagnostics. The combined assessment of Aβ42 and p-tau has recently shown value for diagnosing prodromal states of Alzheimer’s dementia, that is, mild cognitive impairment. Disease-specific biomarkers for other degenerative dementias are still missing, but some progress has recently been made. As lumbar puncture is an additional burden for the patient, blood-based neurochemical biomarkers are definitely warranted and promising new discoveries have been made in this direction. These diagnostic developments have implicit therapeutic consequences and give rise to new requirements for future neurochemical dementia diagnostics.

Alzheimer’s disease (AD) is the leading cause of dementia in elderly populations throughout the world and its incidence is on the rise. Current clinical diagnosis of AD requires intensive examination that includes neuropsychological testing and costly brain imaging techniques, and a definitive diagnosis can only be made upon postmortem neuropathological examination. Additionally, antemortem clinical AD diagnosis is typically administered following onset of cognitive and behavioral symptoms. As these symptoms emerge relatively late in disease progression, therapeutic intervention occurs after significant neurodegeneration, thereby limiting efficacy. The identification of noninvasive diagnostic biomarkers of AD is becoming increasingly important to make diagnosis more widely available to clinics with limited access to neuropsychological testing or state-of-the-art brain imaging, reduce the cost of clinical diagnosis, provide a biological measure to track the course of therapeutic intervention, and most importantly, allow for earlier diagnosis – possibly even during the prodromal phase – with hopes of therapeutic intervention prior to appreciable neurodegeneration. Circulating leukocytes are attractive candidate AD biomarkers as they can be obtained in a minimally invasive manner and are easily analyzed by widely available flow cytometry techniques. In this review, we critically analyze the potential utility of peripheral leukocytes as biological markers for AD.

SPECT allows registration of regional cerebral blood flow (rCBF) which is altered in a characteristic temporoparietal pattern in Alzheimer's Dementia. Numerous studies have shown the diagnostic value of reduced cerebral blood flow and metabolic changes using perfusion SPECT and FDG-PEPT in AD diagnosis as well as in differential diagnosis against frontotemporal dementia, dementia with Lewy bodies and vascular disease. Recently more pathophysiology-based biomarkers in CSF and Amyloid-PET tracers have been developed that probably have a higher diagnostic accuracy than the more indirect rCBF changes seen in perfusion SPECT. In the paper review, we describe recent advances in AD biomarkers as well as improvements in the SPECT technique.