Biomarker progressions explain higher variability in stage-specific cognitive decline than baseline values in Alzheimer disease

BackgroundIt is unknown which commonly used Alzheimer disease (AD) biomarker values—baseline or progression—best predict longitudinal cognitive decline.Methods526 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). ADNI composite memory and executive scores were the primary outcomes. Individual-specific slope of the longitudinal trajectory of each biomarker was first estimated. These estimates and observed baseline biomarker values were used as predictors of cognitive declines. Variability in cognitive declines explained by baseline biomarker values was compared with variability explained by biomarker progression values.ResultsAbout 40% of variability in memory and executive function declines was explained by ventricular volume progression among mild cognitive impairment patients. A total of 84% of memory and 65% of executive function declines were explained by fluorodeoxyglucose positron emission tomography (FDG-PET) score progression and ventricular volume progression, respectively, among AD patients.ConclusionsFor most biomarkers, biomarker progressions explained higher variability in cognitive decline than biomarker baseline values. This has important implications for clinical trials targeted to modify AD biomarkers.     

Extension and refinement of the predictive value of different classes of markers in ADNI: Four-year follow-up data

BackgroundThis study examined the predictive value of different classes of markers in the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) over an extended 4-year follow-up in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.MethodsMCI patients were assessed for clinical, cognitive, magnetic resonance imaging (MRI), positron emission tomography–fluorodeoxyglucose (PET-FDG), and cerebrospinal fluid (CSF) markers at baseline and were followed on a yearly basis for 4 years to ascertain progression to AD. Logistic regression models were fitted in clusters, including demographics, APOE genotype, cognitive markers, and biomarkers (morphometric, PET-FDG, CSF, amyloid-β, and tau).ResultsThe predictive model at 4 years revealed that two cognitive measures, an episodic memory measure and a Clock Drawing screening test, were the best predictors of conversion (area under the curve = 0.78).ConclusionsThis model of prediction is consistent with the previous model at 2 years, thus highlighting the importance of cognitive measures in progression from MCI to AD. Cognitive markers were more robust predictors than biomarkers.     

The Alzheimer's Disease Neuroimaging Initiative: Annual change in biomarkers and clinical outcomes

BackgroundThe Alzheimer's Disease Neuroimaging Initiative Phase 1 (ADNI-1) is a multisite prospective study designed to examine potential cerebrospinal fluid and imaging markers of Alzheimer's disease (AD) and their relationship to cognitive change. The objective of this study was to provide a global summary of the overall results and patterns of change observed in candidate markers and clinical measures over the first 2 years of follow-up.MethodsChange was summarized for 210 normal controls, 357 mild cognitive impairment, and 162 AD subjects, with baseline and at least one cognitive follow-up assessment. Repeated measures and survival models were used to assess baseline biomarker levels as predictors. Potential for improving clinical trials was assessed by comparison of precision of markers for capturing change in hypothetical trial designs.ResultsThe first 12 months of complete data on ADNI participants demonstrated the potential for substantial advances in characterizing trajectories of change in a range of biomarkers and clinical outcomes, examining their relationship and timing, and assessing the potential for improvements in clinical trial design. Reduced metabolism and greater brain atrophy in the mild cognitive impairment at baseline are associated with more rapid cognitive decline and a higher rate of conversion to AD. Use of biomarkers as study entry criteria or as outcomes could reduce the number of participants required for clinical trials.ConclusionsAnalyses and comparisons of ADNI data strongly support the hypothesis that measurable change occurs in cerebrospinal fluid, positron emission tomography, and magnetic resonance imaging well in advance of the actual diagnosis of AD.     

The Alzheimer's Disease Neuroimaging Initiative: Progress report and future plans

The Alzheimer's Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year research project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer's disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C-11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid β (Aβ) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C-11 Pittsburgh compound B PET, and CSF measurements of Aβ and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI-like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD.     

Biological heterogeneity in ADNI amnestic mild cognitive impairment

BackgroundPrevious work examining normal controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI) identified substantial biological heterogeneity. We hypothesized that ADNI mild cognitive impairment (MCI) subjects would also exhibit heterogeneity with possible clinical implications.MethodsADNI subjects diagnosed with amnestic MCI (n = 138) were clustered based on baseline magnetic resonance imaging, cerebrospinal fluid, and serum biomarkers. The clusters were compared with respect to longitudinal atrophy, cognitive trajectory, and time to conversion.ResultsFour clusters emerged with distinct biomarker patterns: The first cluster was biologically similar to normal controls and rarely converted to Alzheimer's disease (AD) during follow-up. The second cluster had characteristics of early Alzheimer's pathology. The third cluster showed the most severe atrophy but barely abnormal tau levels and a substantial proportion converted to clinical AD. The fourth cluster appeared to be pre-AD and nearly all converted to AD.ConclusionsSubjects with MCI who were clinically similar showed substantial heterogeneity in biomarkers.     

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.     

Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects

Objective

Develop a cerebrospinal fluid biomarker signature for mild Alzheimer's disease (AD) in Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects.

Methods

Amyloid‐β 1 to 42 peptide (Aβ_1–42), total tau (t‐tau), and tau phosphorylated at the threonine 181 were measured in (1) cerebrospinal fluid (CSF) samples obtained during baseline evaluation of 100 mild AD, 196 mild cognitive impairment, and 114 elderly cognitively normal (NC) subjects in ADNI; and (2) independent 56 autopsy‐confirmed AD cases and 52 age‐matched elderly NCs using a multiplex immunoassay. Detection of an AD CSF profile for t‐tau and Aβ_1–42 in ADNI subjects was achieved using receiver operating characteristic cut points and logistic regression models derived from the autopsy‐confirmed CSF data.

Results

CSF Aβ_1–42 was the most sensitive biomarker for AD in the autopsy cohort of CSF samples: receiver operating characteristic area under the curve of 0.913 and sensitivity for AD detection of 96.4%. In the ADNI cohort, a logistic regression model for Aβ_1–42, t‐tau, and APOε4 allele count provided the best assessment delineation of mild AD. An AD‐like baseline CSF profile for t‐tau/Aβ_1–42 was detected in 33 of 37 ADNI mild cognitive impairment subjects who converted to probable AD during the first year of the study.

Interpretation

The CSF biomarker signature of AD defined by Aβ_1–42 and t‐tau in the autopsy‐confirmed AD cohort and confirmed in the cohort followed in ADNI for 12 months detects mild AD in a large, multisite, prospective clinical investigation, and this signature appears to predict conversion from mild cognitive impairment to AD. Ann Neurol 2009     

The pilot European Alzheimer's Disease Neuroimaging Initiative of the European Alzheimer's Disease Consortium

BackgroundIn North America, the Alzheimer's Disease Neuroimaging Initiative (ADNI) has established a platform to track the brain changes of Alzheimer's disease. A pilot study has been carried out in Europe to test the feasibility of the adoption of the ADNI platform (pilot E-ADNI).MethodsSeven academic sites of the European Alzheimer's Disease Consortium (EADC) enrolled 19 patients with mild cognitive impairment (MCI), 22 with AD, and 18 older healthy persons by using the ADNI clinical and neuropsychological battery. ADNI compliant magnetic resonance imaging (MRI) scans, cerebrospinal fluid, and blood samples were shipped to central repositories. Medial temporal atrophy (MTA) and white matter hyperintensities (WMH) were assessed by a single rater by using visual rating scales.ResultsRecruitment rate was 3.5 subjects per month per site. The cognitive, behavioral, and neuropsychological features of the European subjects were very similar to their U.S. counterparts. Three-dimensional T1-weighted MRI sequences were successfully performed on all subjects, and cerebrospinal fluid samples were obtained from 77%, 68%, and 83% of AD patients, MCI patients, and controls, respectively. Mean MTA score showed a significant increase from controls (left, right: 0.4, 0.3) to MCI patients (0.9, 0.8) to AD patients (2.3, 2.0), whereas mean WMH score did not differ among the three diagnostic groups (between 0.7 and 0.9). The distribution of both MRI markers was comparable to matched US-ADNI subjects.ConclusionsAcademic EADC centers can adopt the ADNI platform to enroll MCI and AD patients and older controls with global cognitive and structural imaging features remarkably similar to those of the US-ADNI.     

The clinical use of cerebrospinal fluid biomarker testing for Alzheimer's disease diagnosis: A consensus paper from the Alzheimer's Biomarkers Standardization Initiative

BackgroundCerebrospinal fluid (CSF) biomarkers β-amyloid 1-42 (Aβ_1-42), also expressed as Aβ_1-42:Aβ_1-40 ratio, T-tau, and P-tau_181P, have proven diagnostic accuracy for mild cognitive impairment and Alzheimer's disease (AD). How to use, interpret, and disclose biomarker results drives the need for standardization.MethodsPrevious Alzheimer's Biomarkers Standardization Initiative meetings discussed preanalytical issues affecting Aβ_1-42 and tau in CSF. This second round of consensus meetings focused on issues related to clinical use of AD CSF biomarkers.ResultsConsensus was reached that lumbar puncture for AD CSF biomarker analysis be considered as a routine clinical test in patients with early-onset dementia, at the prodromal stage or with atypical AD. Moreover, consensus was reached on which biomarkers to use, how results should be interpreted, and potential confounding factors.ConclusionsChanges in Aβ_1-42, T-tau, and P-tau_181P allow diagnosis of AD in its prodromal stage. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up.     

CSF α-synuclein improves diagnostic and prognostic performance of CSF tau and Aβ in Alzheimer’s disease

Alzheimer’s disease (AD) and Lewy body diseases (LBD), e.g., Parkinson’s disease (PD) dementia and dementia with Lewy bodies (DLB), are common causes of geriatric cognitive impairments. In addition, AD and LBD are often found in the same patients at autopsy; therefore, biomarkers that can detect the presence of both pathologies in living subjects are needed. In this investigation, we report the assessment of α-synuclein (α-syn) in cerebrospinal fluid (CSF) and its association with CSF total tau (t-tau), phosphorylated tau₁₈₁ (p-tau₁₈₁), and amyloid beta_1-42 (Aβ_1-42) in subjects of the Alzheimer’s Disease Neuroimaging Initiative (ADNI; n = 389), with longitudinal clinical assessments. A strong correlation was noted between α-syn and t-tau in controls, as well as in patients with AD and mild cognitive impairment (MCI). However, the correlation is not specific to subjects in the ADNI cohort, as it was also seen in PD patients and controls enrolled in the Parkinson’s Progression Markers Initiative (PPMI; n = 102). A bimodal distribution of CSF α-syn levels was observed in the ADNI cohort, with high levels of α-syn in the subjects with abnormally increased t-tau values. Although a correlation was also noted between α-syn and p-tau₁₈₁, there was a mismatch (α-syn–p-tau₁₈₁-Mis), i.e., higher p-tau₁₈₁ levels accompanied by lower α-syn levels in a subset of ADNI patients. We hypothesize that this α-syn–p-tau₁₈₁-Mis is a CSF signature of concomitant LBD pathology in AD patients. Hence, we suggest that inclusion of measures of CSF α-syn and calculation of α-syn–p-tau₁₈₁-Mis improves the diagnostic sensitivity/specificity of classic CSF AD biomarkers and better predicts longitudinal cognitive changes.     

Inflammation,negative affect,and amyloid burden in Alzheimer’s disease: Insights from the kynurenine pathway

BackgroundDepressive symptoms in Alzheimer’s disease (AD) predict worse cognitive and functional outcomes. Both AD and major depression inflammatory processes are characterized by shunted tryptophan metabolism away from serotonin (5-HT) and toward the neuroinflammatory kynurenine (Kyn) pathway. The present study assessed associations between Kyn and behavioral, neuroanatomical, neuropathological, and physiological outcomes common to both AD and negative affect across the AD continuum.MethodsIn 58 cognitively normal, 396 mild cognitive impairment, and 112 AD participants from the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI1) cohort, serum markers of 5-HT, tryptophan, and Kyn were measured and their relationships investigated with immunologic markers, affect and functional outcomes, CSF markers of beta-amyloid (Aβ) and tau, and regional gray matter.ResultsA higher Kyn/Tryptophan ratio was linked to many inflammatory markers, as well as lower functional independence and memory scores. A higher Kyn/5-HT ratio showed similar associations, but also strong relationships with negative affect and neuropsychiatric disturbance, executive dysfunction, and global cognitive decline. Further, gray matter atrophy was seen in hippocampus, anterior cingulate, and prefrontal cortices, as well as greater amyloid and total tau deposition. Finally, using moderated-mediation, several pro-inflammatory factors partially mediated Kyn/5-HT and negative affect scores in participants with subclinical Aβ (i.e., Aβ−), whereas such associations were fully mediated by Complement 3 in Aβ+ participants.ConclusionThese findings suggest that inflammatory signaling cascades may occur during AD, which is associated with increased Kyn metabolism that influences the pathogenesis of negative affect. Aβ and the complement system may be critical contributing factors in this process.     

The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151–3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [¹⁸F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.     

Relations between personality changes and cerebrospinal fluid biomarkers of Alzheimer's disease pathology

Specific changes in personality profiles may represent early non-cognitive symptoms of Alzheimer's disease (AD). Evaluating the subject's personality changes may add significant clinical information, as well as help to better understand the interaction between personality change, cognitive decline, and cerebral pathology. With this study we aimed to describe the relationship between personality changes and cerebrospinal fluid (CSF) markers of AD pathology at early clinical stages of the disease. One hundred and ten subjects, of whom 66 cognitively impaired patients (57 with mild cognitive impairment (MCI), and 9 with mild dementia) and 44 healthy controls, had neuropsychological examination as well as lumbar puncture to determine concentrations of CSF biomarkers of AD pathology (amyloid beta_1-42 (Aβ_1-42), phosphorylated tau (ptau-181), and total-tau (tau)). The Revised NEO Personality Inventory (NEO-PI-R) was administered twice, once to evaluate subjects' current personality and once to assess personality traits retrospectively 5 years before evaluation. Subjects with an AD CSF biomarker profile showed significant increase in neuroticism and decrease in conscientiousness over time as compared to non-AD CSF biomarker group. In regression analysis controlling for global cognition as measured by the MMSE score, increasing neuroticism and decreasing extraversion, openness to experience and conscientiousness were associated with lower Aβ_1-42 concentrations but not with tau and ptau-181 concentrations. Our findings suggest that early and specific changes in personality are associated with cerebral AD pathology. Concentrations of CSF biomarkers, additionally to severity of the cognitive impairment, significantly contribute in predicting specific personality changes.     

Primary fatty amides in plasma associated with brain amyloid burden,hippocampal volume,and memory in the European Medical Information Framework for Alzheimer's Disease biomarker discovery cohort

IntroductionA critical and as-yet unmet need in Alzheimer's disease (AD) is the discovery of peripheral small molecule biomarkers. Given that brain pathology precedes clinical symptom onset, we set out to test whether metabolites in blood associated with pathology as indexed by cerebrospinal fluid (CSF) AD biomarkers.MethodsThis study analyzed 593 plasma samples selected from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, of individuals who were cognitively healthy (n = 242), had mild cognitive impairment (n = 236), or had AD-type dementia (n = 115). Logistic regressions were carried out between plasma metabolites (n = 883) and CSF markers, magnetic resonance imaging, cognition, and clinical diagnosis.ResultsEight metabolites were associated with amyloid β and one with t-tau in CSF, these were primary fatty acid amides (PFAMs), lipokines, and amino acids. From these, PFAMs, glutamate, and aspartate also associated with hippocampal volume and memory.DiscussionPFAMs have been found increased and associated with amyloid β burden in CSF and clinical measures.     

The Association Between Biomarkers and Neuropsychiatric Symptoms Across the Alzheimer's Disease Spectrum

ObjectiveTo investigate the relationship between Alzheimer's disease biomarkers and neuropsychiatric symptoms.MethodsData from two large cohort studies, the Dutch Parelsnoer Institute – Neurodegenerative Diseases and the Alzheimer's Disease Neuroimaging Initiative was used, including subjects with subjective cognitive decline (N = 650), mild cognitive impairment (N = 887), and Alzheimer's disease dementia (N = 626). Cerebrospinal fluid (CSF) levels of Aβ₄₂, t-tau, p-tau, and hippocampal volume were associated with neuropsychiatric symptoms (measured with the Neuropsychiatric Inventory) using multiple logistic regression analyses. The effect of the Mini-Mental State Examination (as proxy for cognitive functioning) on these relationships was assessed with mediation analyses.ResultsAlzheimer's disease biomarkers were not associated with depression, agitation, irritability, and sleep disturbances. Lower levels of CSF Aβ₄₂, higher levels of t- and p-tau were associated with presence of anxiety. Lower levels of CSF Aβ₄₂ and smaller hippocampal volumes were associated with presence of apathy. All associations were mediated by cognitive functioning.ConclusionThe association between Alzheimer's disease pathology and anxiety and apathy is partly due to impairment in cognitive functioning.     

Beta amyloid, tau, neuroimaging, and cognition: sequence modeling of biomarkers for Alzheimer’s Disease

Alzheimer’s disease (AD) is associated with a cascade of pathological events involving formation of amyloid-based neuritic plaques and tau-based neurofibrillary tangles, changes in brain structure and function, and eventually, cognitive impairment and functional disability. The precise sequence of when each of these disease markers becomes abnormal is not yet clearly understood. The present study systematically tested the relationship between classes of biomarkers according to a proposed model of temporal sequence by Jack et al. (Lancet Neurology 9:119–128, 2010). We examined temporal relations among four classes of biomarkers: CSF Aβ, CSF tau, neuroimaging variables (hippocampal volume, ventricular volume, FDG PET), and cognitive variables (memory and executive function). Random effects modeling of longitudinal data obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) was used to test hypotheses that putative earlier markers of AD predicted change in later markers, and that intervening markers reduced effects of earlier on later markers. Specifically, we hypothesized that CSF tau would explain CSF Aβ’s relation to neuroimaging and cognitive variables, and neuroimaging variables would explain tau’s relation to cognitive variables. Consistent with hypotheses, results indicated that CSF Aβ effects on cognition change were substantially attenuated by CSF tau and measures of brain structure and function, and CSF tau effects on cognitive change were attenuated by neuroimaging variables. Contrary to hypotheses, CSF Aβ and CSF tau were observed to have independent effects on neuroimaging and CSF tau had a direct effect on baseline cognition independent of brain structure and function. These results have implications for clarifying the temporal sequence of AD changes and corresponding biomarkers.     

Emerging cerebrospinal fluid biomarkers in autosomal dominant Alzheimer's disease

IntroductionFour less well-studied but promising “emerging” cerebrospinal fluid (CSF) biomarkers are elevated in late-onset Alzheimer disease (AD): neurogranin, synaptosomal-associated protein-25 (SNAP-25), visinin-like protein 1 (VILIP-1), and chitinase-3-like protein 1 (YKL-40).MethodsCSF neurogranin, SNAP-25, VILIP-1, and YKL-40 were measured in families carrying autosomal-dominant AD mutations.ResultsThe four emerging CSF biomarkers were significantly elevated in the mutation carriers (n = 235) versus noncarriers (n = 145). CSF SNAP-25, VILIP-1, and YKL-40 were altered very early in the AD time course, approximately 15–19 years before estimated symptom onset. All CSF biomarkers predicted important AD-related outcomes including performance on a cognitive composite, brain amyloid burden as measured by amyloid positron emission tomography, and the estimated years from symptom onset.DiscussionEarly abnormalities in CSF tTau, pTau, SNAP-25, VILIP-1, and YKL-40 suggest that synaptic damage, neuronal injury, and neuroinflammation begin shortly after the commencement of brain amyloid accumulation.     

Clinical indications for analysis of Alzheimer's disease CSF biomarkers

The cerebrospinal fluid (CSF) biomarkers β-amyloid_1-42 (Aβ_1-42), total tau protein (T-tau) and hyperphosphorylated tau (P-tau_181P) are well-validated and are increasingly used in clinical practice as an affirmative diagnostic tool for Alzheimer's disease (AD). These biomarkers have also been implemented in the revised diagnostic criteria of AD. The combination of the CSF biomarkers Aβ_1-42, T-tau and P-tau_181P results in high levels of sensitivity, specificity and diagnostic accuracy for discriminating AD from controls (including psychiatric disorders like depression). These biomarkers can be applied for diagnosing AD in the prodromal phase of the disease (mild cognitive impairment). In case of doubt between vascular dementia (VaD) or mixed AD-VaD pathology in dementia patients, the determination of CSF Aβ_1-42, T-tau and P-tau_181P levels is of help to confirm or exclude the AD component in the pathophysiology of the dementia syndrome. However, their discriminatory power for the differential diagnosis of dementia is suboptimal. Other CSF biomarkers like Aβ_1-40, and those that are reflective of the pathology of non-AD dementias, could improve the accuracy of differential dementia diagnosis. The added differential diagnostic value of the CSF biomarkers Aβ_1-42, T-tau and P-tau_181P could lie within those cases in which the routine clinical diagnostic work-up is not able to discriminate between AD or non-AD dementias. In summary, the CSF biomarkers Aβ_1-42, T-tau and P-tau_181P can be used in clinical practice to discriminate AD from healthy aging (including psychiatric disorders like depression), to diagnose AD in its prodromal phase or in atypical forms with prominent non-memory impairment, to identify AD in patients with mixed pathologies and in case of an ambiguous (AD versus non-AD) dementia diagnosis.     

Longitudinal change in CSF Tau and Aβ biomarkers for up to 48 months in ADNI

The dynamics of cerebrospinal fluid (CSF) tau and Aβ biomarkers over time in Alzheimer’s disease (AD) patients from prodromal pre-symptomatic to severe stages of dementia have not been clearly defined and recent studies, most of which are cross-sectional, present conflicting findings. To clarify this issue, we analyzed the longitudinal CSF tau and Aβ biomarker data from 142 of the AD Neuroimaging Initiative (ADNI) study subjects [18 AD, 74 mild cognitive impairment (MCI), and 50 cognitively normal subjects (CN)]. Yearly follow-up CSF collections and studies were conducted for up to 48 months (median = 36 months) for CSF Aβ_1–42, phosphorylated tau (p-tau₁₈₁), and total tau (t-tau). An unsupervised analysis of longitudinal measurements revealed that for Aβ_1–42 and p-tau₁₈₁ biomarkers there was a group of subjects with stable longitudinal CSF biomarkers measures and a group of subjects who showed a decrease (Aβ_1–42, mean = ?9.2 pg/ml/year) or increase (p-tau₁₈₁, mean = 5.1 pg/ml/year) of these biomarker values. Low baseline Aβ_1–42 values were associated with longitudinal increases in p-tau₁₈₁. Conversely, high baseline p-tau₁₈₁ values were not associated with changes in Aβ_1–42 levels. When the subjects with normal baseline biomarkers and stable concentrations during follow-up were excluded, the expected time to reach abnormal CSF levels and the mean AD values was significantly shortened. Thus, our data demonstrate for the first time that there are distinct populations of ADNI subjects with abnormal longitudinal changes in CSF p-tau₁₈₁ and Aβ_1–42 levels, and our longitudinal results favor the hypothesis that Aβ_1–42 changes precede p-tau₁₈₁ changes.     

Nonlinear biomarker interactions in conversion from mild cognitive impairment to Alzheimer's disease

Multiple biomarkers can capture different facets of Alzheimer's disease. However, statistical models of biomarkers to predict outcomes in Alzheimer's rarely model nonlinear interactions between these measures. Here, we used Gaussian Processes to address this, modelling nonlinear interactions to predict progression from mild cognitive impairment (MCI) to Alzheimer's over 3 years, using Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Measures included: demographics, APOE4 genotype, CSF (amyloid‐β42, total tau, phosphorylated tau), [18^F]florbetapir, hippocampal volume and brain‐age. We examined: (a) the independent value of each biomarker; and (b) whether modelling nonlinear interactions between biomarkers improved predictions. Each measured added complementary information when predicting conversion to Alzheimer's. A linear model classifying stable from progressive MCI explained over half the variance (R² = 0.51, p < .001); the strongest independently contributing biomarker was hippocampal volume (R² = 0.13). When comparing sensitivity of different models to progressive MCI (independent biomarker models, additive models, nonlinear interaction models), we observed a significant improvement (p < .001) for various two‐way interaction models. The best performing model included an interaction between amyloid‐β‐PET and P‐tau, while accounting for hippocampal volume (sensitivity = 0.77, AUC = 0.826). Closely related biomarkers contributed uniquely to predict conversion to Alzheimer's. Nonlinear biomarker interactions were also implicated, and results showed that although for some patients adding additional biomarkers may add little value (i.e., when hippocampal volume is high), for others (i.e., with low hippocampal volume) further invasive and expensive examination may be warranted. Our framework enables visualisation of these interactions, in individual patient biomarker ‘space', providing information for personalised or stratified healthcare or clinical trial design.