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 order and magnitude of pathologic processes in Alzheimer’s disease are not well understood, partly because the disease develops over many years. Autosomal dominant Alzheimer’s disease has a predictable age at onset and provides an opportunity to determine the sequence and magnitude of pathologic changes that culminate in symptomatic disease.

METHODS

In this prospective, longitudinal study, we analyzed data from 128 participants who underwent baseline clinical and cognitive assessments, brain imaging, and cerebrospinal fluid (CSF) and blood tests. We used the participant’s age at baseline assessment and the parent’s age at the onset of symptoms of Alzheimer’s disease to calculate the estimated years from expected symptom onset (age of the participant minus parent’s age at symptom onset). We conducted cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to determine the relative order and magnitude of pathophysiological changes.

RESULTS

Concentrations of amyloid-beta (Aβ)42 in the CSF appeared to decline 25 years before expected symptom onset. Aβ deposition, as measured by positron-emission tomography with the use of Pittsburgh compound B, was detected 15 years before expected symptom onset. Increased concentrations of tau protein in the CSF and an increase in brain atrophy were detected 15 years before expected symptom onset. Cerebral hypometabolism and impaired episodic memory were observed 10 years before expected symptom onset. Global cognitive impairment, as measured by the Mini–Mental State Examination and the Clinical Dementia Rating scale, was detected 5 years before expected symptom onset, and patients met diagnostic criteria for dementia at an average of 3 years after expected symptom onset.

CONCLUSIONS

We found that autosomal dominant Alzheimer’s disease was associated with a series of pathophysiological changes over decades in CSF biochemical markers of Alzheimer’s disease, brain amyloid deposition, and brain metabolism as well as progressive cognitive impairment. Our results require confirmation with the use of longitudinal data and may not apply to patients with sporadic Alzheimer’s disease. (Funded by the National Institute on Aging and others; DIAN ClinicalTrials.gov number, NCT00869817.)

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 controls and $67 million funding was provided by both the public and private sectors including the National Institutes on Aging, thirteen pharmaceutical companies and two Foundations that provided support through the Foundation for NIH (FNIH). 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 1) the development of standardized methods for clinical, magnetic resonance imaging (MRI) and positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in a multi-center setting; 2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control, MCI and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β amyloid (Aβ) cascade [1] and tau mediated neurodegeneration hypotheses for AD while 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, FDG-PET, CSF biomarkers and clinical tests; 4) the development of methods for the early detection of AD. CSF biomarkers, Aβ42 and tau as well as amyloid PET may reflect the earliest steps in AD pathology in mildly or even non-symptomatic 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 two year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI2) in October, 2010 through to 2016, with enrollment of an additional 550 participants.

Objective

To determine if the addition of delayed recall (DR) assessment adds sensitivity to the cognitive subscale of the Alzheimer Disease Assessment Scale (ADAS-cog) in clinical trials in mild cognitive impairment (MCI) and Alzheimer Disease (AD).

Background

Memory, particularly DR, is the most sensitive test for early detection of AD and MCI. However, it is not clear that assessment of DR adds benefit for measuring change over time after a diagnosis is made or in clinical trials. The ADAS-cog is the most commonly used tool to assess treatment efficacy in AD clinical trials. In an attempt to improve sensitivity to change, assessment of DR after the 3-trial, 10-word list was added to the standard 11-item ADAS-cog. We examined the added value of the DR in participants with MCI and AD followed for at least 1 year.

Design/Methods

Data from 111 subjects with AD and 259 subjects with MCI who were randomly assigned to the placebo arm of 2 clinical trials were included. Participants with AD had Mini- Mental State Examination scores of 13 to 27 and those with MCI had 24 to 30. We calculated the ADAS-cog11 score based on the original 11 items (range: best to worse, 0 to 70), the DR item score (range: 0 to 10 words not recalled), and the ADAS-cog12 (range: 0 to 80). We assessed the rate of missing items for DR over time, the change scores, the association between scores and baseline performance, and used longitudinal mixed effects regression models to examine the rate of change.

Results

At baseline AD subjects were near floor on DR (8.93 ± 1.6 SD) and showed little change over 1 year (0.12 ± 1.34); the MCI subjects baseline DR was 6.2 ± 2.2 with 1-year change of 0.20 ± 1.7. We compared standardized change (change/SD) for ADAS-cog11, and 12 in MCI and found a 10% improvement with ADAS-cog12; there was no improvement in the AD group. In a subset of MCI and AD cases with matching Mini-Mental State Examination (23 to 27), the ADAS-cog12 provided an 18% improvement in standardized change in MCI subjects, with no benefit in the AD cohort, primarily owing to increased variance.

Conclusions/Relevance

The addition of DR to the ADAS-cog score increased the ability to detect change in subjects with MCI over 1 year compared with the ADAS-cog11 but increased the variance in subjects with AD, even in those with mild impairment These findings speak to the need to tailor outcome measures to the specific study population and diagnosis for maximal efficiency and economy when conducting clinical trials.

In recent years, advances in Alzheimer’s disease (AD) biomarker research have provided powerful tools to improve trial design. In particular, biomarkers provide powerful methods for the selection of individuals with AD prior to the onset of dementia. Data suggests that neuroimaging biomarkers will be useful as endpoints for trials in very early, even asymptomatic disease, though further work is necessary to establish validity for regulatory purposes.

The relationship between neurodegeneration and the two hallmark proteins of Alzheimer's disease, amyloid-β (Aβ) and tau, is still unclear. Here, we examined 286 non-demented participants (107 cognitively normal older adults and 179 memory impaired individuals) who underwent longitudinal MR imaging and lumbar puncture. Using mixed effects models, we investigated the relationship between longitudinal entorhinal cortex atrophy, CSF p-tau181p and CSF Aβ1-42. We found a significant relationship between elevated entorhinal cortex atrophy and decreased CSF Aβ1-42 only with elevated CSF p-tau181p. Our findings indicate that Aβ-associated volume loss occurs only in the presence of phospho-tauin humans at risk for dementia.

Previous studies of Aβ plasma as a biomarker for Alzheimer’s disease (AD) obtained conflicting results. We here included 715 subjects with baseline Aβ1–40 and Aβ1–42 plasma measurement (50% with 4 serial annual measurements): 205 cognitively normal controls (CN), 348 patients mild cognitive impairment (MCI) and 162 with AD. We assessed the factors that modified their concentrations and correlated these values with PIB PET, MRI and tau and Aβ1–42 measures in cerebrospinal fluid (CSF). Association between Aβ and diagnosis (baseline and prospective) was assessed. A number of health conditions were associated with altered concentrations of plasma Aβ. The effect of age differed according to AD stage. Plasma Aβ1–42 showed mild correlation with other biomarkers of Aβ pathology and were associated with infarctions in MRI. Longitudinal measurements of Aβ1–40 and Aβ1–42 plasma levels showed modest value as a prognostic factor for clinical progression. Our longitudinal study of complementary measures of Aβ pathology (PIB, CSF and plasma Aβ) and other biomarkers in a cohort with an extensive neuropsychological battery is significant because it shows that plasma Aβ measurements have limited value for disease classification and modest value as prognostic factors over the 3-year follow-up. However, with longer follow-up, within subject plasma Aβ measurements could be used as a simple and minimally invasive screen to identify those at increased risk for AD. Our study emphasizes the need for a better understanding of the biology and dynamics of plasma Aβ as well as the need for longer term studies to determine the clinical utility of measuring plasma Aβ.

Objective

To elucidate the relationship between the two hallmark proteins of Alzheimer's disease (AD), amyloid-β (Aβ) and tau, and clinical decline over time among cognitively normal older individuals.

Design

A longitudinal cohort of clinically and cognitively normal older individuals assessed with baseline lumbar puncture and longitudinal clinical assessments.

Setting

Research centers across the United States and Canada.

Patients

We examined one hundred seven participants with a Clinical Dementia Rating (CDR) of 0 at baseline examination.

Main Outcome Measures

Using linear mixed effects models, we investigated the relationship between CSF p-tau181p, CSF Aβ1-42 and clinical decline as assessed using longitudinal change in global CDR, CDR-Sum of Boxes (CDR-SB), and the Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog).

Results

We found a significant relationship between decreased CSF Aβ1-42 and longitudinal change in global CDR, CDR-SB, and ADAS-cog in individuals with elevated CSF p-tau181p. In the absence of CSF p-tau181p, the effect of CSF Aβ1-42 on longitudinal clinical decline was not significantly different from zero.

Conclusions

In cognitively normal older individuals, Aβ-associated clinical decline over a mean of three years may occur only in the presence of ongoing, “downstream” neurodegeneration.

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.

Objective

To evaluate the safety and tolerability of PF-04494700, an oral Inhibitor of receptor for advanced glycation end products (RAGE), in subjects with mild-to-moderate dementia of the Alzheimer’s type.

Methods

Subjects 50 years and older who met NINCDS-ADRDA criteria for AD with an MMSE score between 12–26 (inclusive) were randomized to 10-weeks of double-blind treatment with either a 10 mg “low dose” of PF-04494700 (after a 6-day loading dose of 30 mg/d to); or a 20 mg “high dose” of PF-04494700 (after a loading dose of 60 mg/d); or placebo. Safety measures included adverse events, laboratory tests, vital signs, and 12-lead ECG.

Results

27 subjects received PF-04494700 30/10 mg (female, 63%; mean age, 74.6 years; mean MMSE, 21.1), 28 subjects received PF-04494700 60/20 mg (female, 57%; mean age, 76.6 years; mean MMSE, 21.6), and 12 subjects received placebo (female, 67%; mean age, 74.1 years; mean MMSE, 19.2). A higher proportion of subjects completed 10 weeks of double-blind treatment on both the “low dose” regimen of PF-04494700 (88.9%) and the “high dose” regimen (85.7%) than completed on placebo (66.7%). Discontinuation due to adverse events, and incidence of severe adverse events, respectively, were lower on the “low dose” regimen (7.4%,11.1%) and the “high dose” regimen (3.6%,10.7%) compared to placebo (25.0%,16.7%). There were no clinically meaningful differences in vital signs, laboratory test results, or mean ECG parameters in subjects treated with PF-04494700. PF-04494700 had no consistent effect on plasma levels of Aβ, inflammatory biomarkers, or secondary cognitive outcomes.

Conclusions

Ten weeks of treatment with PF-04494700 was safe and well-tolerated in subjects with mild-to-moderate AD, indicating the feasibility of a larger long-term efficacy trial.

The pathophysiological process of Alzheimer's disease (AD) is thought to begin many years before the diagnosis of AD dementia. This long “preclinical” phase of AD would provide a critical opportunity for therapeutic intervention; however, we need to further elucidate the link between the pathological cascade of AD and the emergence of clinical symptoms. The National Institute on Aging and the Alzheimer's Association convened an international workgroup to review the biomarker, epidemiological, and neuropsychological evidence, and to develop recommendations to determine the factors which best predict the risk of progression from “normal” cognition to mild cognitive impairment and AD dementia. We propose a conceptual framework and operational research criteria, based on the prevailing scientific evidence to date, to test and refine these models with longitudinal clinical research studies. These recommendations are solely intended for research purposes and do not have any clinical implications at this time. It is hoped that these recommendations will provide a common rubric to advance the study of preclinical AD, and ultimately, aid the field in moving toward earlier intervention at a stage of AD when some disease-modifying therapies may be most efficacious.

Background

PIB PET and CSF Aβ42 demonstrate a highly significant inverse correlation. Both are presumed to measure brain Aβ amyloid load. Our objectives were to develop a method to transform CSF Aβ42 measures into calculated PIB measures (PIBcalc) of Aβ amyloid load, and to partially validate the method in an independent sample of subjects.

Methods

Forty-one ADNI subjects underwent PIB PET imaging and lumbar puncture (LP) at the same time. This sample, referred to as the “training” sample (9 cognitively normal (CN), 22 MCI, and 10 AD), was used to develop a regression model by which CSF Aβ42 (with APOE ε4 genotype as a covariate) was transformed into units of PIB PET (PIBcalc). An independent “supporting” sample of 362 (105 CN, 164 MCI, 93AD) ADNI subjects who underwent LP but not PIB PET imaging had their CSF Aβ42 values converted to PIBcalc. These values were compared to the overall PIB PET distribution found in the ADNI subjects (n = 102).

Results

A linear regression model demonstrates good prediction of actual PIB PET from CSF Aβ42 measures obtained in the training sample (R2 = 0.77, P<0.001). PIBcalc data (derived from CSF Aβ42) in the supporting sample of 362 ADNI subjects who underwent LP but not PIB PET imaging demonstrates group-wise distributions that are highly consistent with the larger ADNI PIB PET distribution and with published PIB PET imaging studies.

Conclusion

Although the precise parameters of this model are specific for the ADNI sample, we conclude that CSF Aβ42 can be transformed into calculated PIB (PIBcalc) measures of Aβ amyloid load. Brain Aβ amyloid load can be ascertained at baseline in therapeutic or observational studies by either CSF or amyloid PET imaging and the data can be pooled using well-established multiple imputation techniques that account for the uncertainty in a CSF-based calculated PIB value.

In this work we consider marketed drugs for Alzheimer disease (AD) including acetylcholinesterase inhibitors (AChE-Is) and antiglutamatergic treatment involving the N-methyl-d-aspartate (NMDA) receptor. We discuss medications and substances available for use as cognitive enhancers that are not approved for AD or cognitive impairment, and other neurotransmitter-related therapies in development or currently being researched. We also review putative therapies that aim to slow disease progression by mechanisms not directly related to amyloid or tau.

Acetylcholinesterase inhibitors (e.g., tacrine) and the NMDA receptor antagonist memantine are FDA-approved for treating Alzheimer disease. Numerous additional medications and substances also aim to slow disease progression.

We used a Guttman model to represent responses to test items over time as an approximation of what is often referred to as “points lost” in studies of cognitive decline or interventions. To capture this meaning of “point loss”, over four successive assessments, we assumed that once an item is incorrect, it cannot be correct at a later visit. If the loss of a point represents actual decline, then failure of an item to fit the Guttman model over time can be considered measurement error. This representation and definition of measurement error also permits testing the hypotheses that measurement error is constant for items in a test, and that error is independent of “true score”, which are two key consequences of the definition of “measurement error” –and thereby, reliability- under Classical Test Theory. We tested the hypotheses by fitting our model to, and comparing our results from, four consecutive annual evaluations in three groups of elderly persons: a) cognitively normal (NC, N = 149); b) diagnosed with possible or probable AD (N = 78); and c) cognitively normal initially and a later diagnosis of AD (converters, N = 133). Of 16 items that converged, error-free measurement of “cognitive loss” was observed for 10 items in NC, eight in converters, and two in AD. We found that measurement error, as we defined it, was inconsistent over time and across cognitive functioning levels, violating the theory underlying reliability and other psychometric characteristics, and key regression assumptions.

Context

Docosahexaenoic acid (DHA) is the most abundant long-chain polyunsaturated fatty acid in the brain. Epidemiological studies suggest that consumption of DHA is associated with a reduced incidence of Alzheimer disease. Animal studies demonstrate that oral intake of DHA reduces Alzheimer-like brain pathology.

Objective

To determine if supplementation with DHA slows cognitive and functional decline in individuals with Alzheimer disease.

Design, Setting, and Patients

A randomized, double-blind, placebo-controlled trial of DHA supplementation in individuals with mild to moderate Alzheimer disease (Mini-Mental State Examination scores, 14–26) was conducted between November 2007 and May 2009 at 51 US clinical research sites of the Alzheimer’s Disease Cooperative Study.

Intervention

Participants were randomly assigned to algal DHA at a dose of 2 g/d or to identical placebo (60% were assigned to DHA and 40% were assigned to placebo). Duration of treatment was 18 months.

Main Outcome Measures

Change in the cognitive subscale of the Alzheimer’s Disease Assessment Scale (ADAS-cog) and change in the Clinical Dementia Rating (CDR) sum of boxes. Rate of brain atrophy was also determined by volumetric magnetic resonance imaging in a subsample of participants (n = 102).

Results

A total of 402 individuals were randomized and a total of 295 participants completed the trial while taking study medication (DHA: 171; placebo: 124). Supplementation with DHA had no beneficial effect on rate of change on ADAS-cog score, which increased by a mean of 7.98 points (95% confidence interval [CI], 6.51–9.45 points) for the DHA group during 18 months vs 8.27 points (95% CI, 6.72–9.82 points) for the placebo group (linear mixed-effects model: P = .41). The CDR sum of boxes score increased by 2.87 points (95% CI, 2.44–3.30 points) for the DHA group during 18 months compared with 2.93 points (95% CI, 2.44–3.42 points) for the placebo group (linear mixed-effects model: P = .68). In the subpopulation of participants (DHA: 53; placebo: 49), the rate of brain atrophy was not affected by treatment with DHA. Individuals in the DHA group had a mean decline in total brain volume of 24.7 cm3 (95% CI, 21.4–28.0 cm3) during 18 months and a 1.32% (95% CI, 1.14%–1.50%) volume decline per year compared with 24.0 cm3 (95% CI, 20–28 cm3) for the placebo group during 18 months and a 1.29% (95% CI, 1.07%–1.51%) volume decline per year (P = .79).

Conclusion

Supplementation with DHA compared with placebo did not slow the rate of cognitive and functional decline in patients with mild to moderate Alzheimer disease.

Background

Apolipoprotein E ε4 (APOEε4) allele carrier status has been well established as a risk factor for developing Alzheimer’s disease. However, the specific influence of APOEε4 allele status on cognitive and functional rates of decline in MCI is poorly understood. We examine the prospective association of APOEε4 allele status on measures of cognitive and functional decline in subjects with amnestic Mild Cognitive Impairment (aMCI).

Methods

516 aMCI participants aged 55 to 90 who received placebo or Vitamin E from the Alzheimer’s Disease Cooperative Study’s MCI treatment trial were evaluated. During the 36 month study period, neurocognitive and functional measures were collected. These measures were assessed over time for change and association with APOEε4 status. Generalized Estimating Equations were performed to model each outcome measure over the study period.

Results

APOEε4 status had a significant impact on cognitive and functional decline on multiple measures; those who were APOEε4 positive had significantly more rapid decline in performance on all cognitive and functional measures except Number Cancellation and Maze tracing (p<0.05). The greatest decline was seen in global measures of cognition and function including the Clinical Diagnostic Rating scale, followed by the MMSE, Global Deterioration scale, and the ADAS-cog.

Conclusions

These findings demonstrate that APOEε4 genotype is predictive of increased general rates of decline with global measures of cognition and function most affected. With accelerated declines in common clinical trial primary efficacy measures, APOEε4 status needs to be accounted for in treatment trials of mild cognitive impairment.

Previously it was reported that Alzheimer's disease (AD) patients have reduced amyloid (Aβ1-42) and elevated total tau (t-tau) and phosphorylated tau (p-tau181p) in the cerebrospinal 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 Aβ1-42, t-tau, and p-tau181p and ApoE ε4 status, and that the pattern of this association would be diagnosis specific. Our findings primarily showed that lower CSF Aβ1-42 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 Aβ1-42 levels and higher p-tau levels supports the hypothesis that CSF Aβ1-42 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.

Autosomal-dominant Alzheimer's disease has provided significant understanding of the pathophysiology of Alzheimer's disease. The present review summarizes clinical, pathological, imaging, biochemical, and molecular studies of autosomal-dominant Alzheimer's disease, highlighting the similarities and differences between the dominantly inherited form of Alzheimer's disease and the more common sporadic form of Alzheimer's disease. Current developments in autosomal-dominant Alzheimer's disease are presented, including the international Dominantly Inherited Alzheimer Network and this network's initiative for clinical trials. Clinical trials in autosomal-dominant Alzheimer's disease may test the amyloid hypothesis, determine the timing of treatment, and lead the way to Alzheimer's disease prevention.

Background

Analytic models of Alzheimer’s disease (AD) tend to focus on one type of symptom and assume implicitly that no measurement error is present. These tendencies render changes in symptom domains difficult to model mathematically, although latent variable methods can accommodate both multiple symptom domains and error. This study formulated and compared underlying (latent) factor structures representing previously reported dependence and independence of symptoms of cognitive decline, functional impairment, and behavioral disturbance in AD.

Methods

In confirmatory factor analyses of data from 2 cohorts of AD patients, 2 levels of latent variables were conceptualized. One general neurologic factor represented disease, and symptom factors represented cognition, function, and behavior. Two “null” models had either a single factor or 3 symptom factors. Two 2-level models treated the general factor as underlying both the observed variables and the symptom factors or treated the symptom factors as explaining variability in the observed variables after taking the general factor into account (“residualized”).

Results/Conclusions

The residualized model fit the data in both cohorts significantly better than the other models, and relations in this model between some observed and latent variables were different across cohorts. Neither cohort supported a single factor model; both cohorts independently supported a residualized model that may permit differentiation of symptom- from disease-modifying effects of treatment.

This review summarizes the scientific talks presented at the conference “Therapeutics for Cognitive Aging,” hosted by the New York Academy of Sciences and the Alzheimer’s Drug Discovery Foundation on May 15, 2009. Attended by scientists from industry and academia, as well as by a number of lay people—approximately 200 in all—the conference specifically tackled the many aspects of developing therapeutic interventions for cognitive impairment. Discussion also focused on how to define cognitive aging and whether it should be considered a treatable, tractable disease.

Here we review progress by the Penn Biomarker Core in the Alzheimer's disease Neuroimaging Initiative (ADNI) towards 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 (NC) 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 NC 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, FDG-PET, MRI) and 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.

We applied the hippocampal radial atrophy mapping technique to the baseline and follow-up magnetic resonance image data of 169 amnestic mild cognitive impairment (MCI) participants in the imaging arm of the Alzheimer's Disease Cooperative Study MCI Donepezil/Vitamin E trial. Sixty percent of the subjects with none to mild hippocampal atrophy rated with the visual medial temporal atrophy rating scale (MTA score < 2) and 33.8% of the subjects with moderate to severe (MTA ≥ 2) hippocampal atrophy converted to Alzheimer's disease (AD) during 3-year follow-up. MTA ≥ 2 showed a trend for greater left sided hippocampal atrophy versus MTA < 2 groups at baseline (Pcorrected = 0.08). Higher MTA scores were associated with progressive atrophy of the subiculum and the CA1–3 subregions. The MTA < 2 group demonstrated significant bilateral atrophy progression at follow-up (left Pcorrected = 0.008; right Pcorrected = 0.05). Relative to MTA < 2 nonconverters, MTA < 2 converters showed further involvement of the subiculum and CA1 and additional involvement of CA2–3 at follow-up. Right CA1 atrophy was significantly associated with conversion to dementia (for 1 mm greater right CA1 radial distance subjects had 50% reduced hazard for conversion). Greater CA1 and subicular atrophy can be demonstrated early and is predictive of future conversion to AD, whereas CA2–3 involvement becomes more evident as the disease progresses.

The objective of this study was to investigate how a measure of educational and occupational attainment, a component of cognitive reserve, modifies the relationship between biomarkers of pathology and cognition in Alzheimer's disease. The biomarkers evaluated quantified neurodegeneration via atrophy on magnetic resonance images, neuronal injury via cerebral spinal fluid t-tau, brain amyloid-β load via cerebral spinal fluid amyloid-β1–42 and vascular disease via white matter hyperintensities on T2/proton density magnetic resonance images. We included 109 cognitively normal subjects, 192 amnestic patients with mild cognitive impairment and 98 patients with Alzheimer's disease, from the Alzheimer's Disease Neuroimaging Initiative study, who had undergone baseline lumbar puncture and magnetic resonance imaging. We combined patients with mild cognitive impairment and Alzheimer's disease in a group labelled ‘cognitively impaired’ subjects. Structural Abnormality Index scores, which reflect the degree of Alzheimer's disease-like anatomic features on magnetic resonance images, were computed for each subject. We assessed Alzheimer's Disease Assessment Scale (cognitive behaviour section) and mini-mental state examination scores as measures of general cognition and Auditory–Verbal Learning Test delayed recall, Boston naming and Trails B scores as measures of specific domains in both groups of subjects. The number of errors on the American National Adult Reading Test was used as a measure of environmental enrichment provided by educational and occupational attainment, a component of cognitive reserve. We found that in cognitively normal subjects, none of the biomarkers correlated with the measures of cognition, whereas American National Adult Reading Test scores were significantly correlated with Boston naming and mini-mental state examination results. In cognitively impaired subjects, the American National Adult Reading Test and all biomarkers of neuronal pathology and amyloid load were independently correlated with all cognitive measures. Exceptions to this general conclusion were absence of correlation between cerebral spinal fluid amyloid-β1–42 and Boston naming and Trails B. In contrast, white matter hyperintensities were only correlated with Boston naming and Trails B results in the cognitively impaired. When all subjects were included in a flexible ordinal regression model that allowed for non-linear effects and interactions, we found that the American National Adult Reading Test had an independent additive association such that better performance was associated with better cognitive performance across the biomarker distribution. Our main conclusions included: (i) that in cognitively normal subjects, the variability in cognitive performance is explained partly by the American National Adult Reading Test and not by biomarkers of Alzheimer's disease pathology; (ii) in cognitively impaired subjects, the American National Adult Reading Test, biomarkers of neuronal pathology (structural magnetic resonance imaging and cerebral spinal fluid t-tau) and amyloid load (cerebral spinal fluid amyloid-β1–42) all independently explain variability in general cognitive performance; and (iii) that the association between cognition and the American National Adult Reading Test was found to be additive rather than to interact with biomarkers of Alzheimer's disease pathology.