In 2010, the authors published a hypothetical model of the major biomarkers of Alzheimer’s disease (AD). The model was received with interest because we described the temporal evolution of AD biomarkers in relation to each other and to the onset and progression of clinical symptoms. In the interim, evidence has accumulated that supports the major assumptions of this model. Evidence has also appeared that challenges some of the assumptions underlying our original model. Recent evidence has allowed us to modify our original model. Refinements include indexing subjects by time rather than clinical symptom severity; incorporating inter-subject variability in cognitive response to the progression of AD pathophysiology; modifications of the specific temporal ordering of some biomarkers; and, recognition that the two major proteinopathies underlying AD biomarker changes, Aβ and tau, may be initiated independently in late onset AD where we hypothesize that an incident Aβopathy can accelerate an antecedent tauopathy.
Despite the enormous public health impact of Alzheimer’s disease (AD), no disease modifying treatment has yet been proven to be efficacious in humans. A rate-limiting step in the discovery of potential therapies for humans is the absence of efficient non-invasive methods of evaluating drugs in animal models of disease. Magnetic resonance spectroscopy (MRS) provides noninvasive way to evaluate the animals at baseline, at the end of treatment, and serially to better understand treatment effects. In this study, MRS was assessed as potential outcome measure for detecting disease modification in a transgenic mouse model of AD. Passive immunization with two different antibodies, which have been previously shown to reduce plaque accumulation in transgenic AD mice, was used as intervention. Treatment effects were detected by MRS, and the most striking finding was attenuation of myo-inositol increases in APP-PS1 mice with both treatments. Additionally, a dose dependent effect was observed with one of the treatments for myo-inositol. MRS appears to be a valid in vivo measure of anti-Aβ therapeutic efficacy in pre-clinical studies. Because it is noninvasive, and can detect treatment effects, use of MRS-based endpoints could substantially accelerate drug discovery.
MRS; treatment detection; myo-inositol; N-acetylaspartate
One of the hallmark pathologies of Alzheimer’s disease (AD) is amyloid plaque deposition. Plaques appear hypointense on T2- and T2*-weighted MR images probably due to the presence of endogenous iron, but no quantitative comparison of various imaging techniques has been reported. We estimated the T1, T2, T2*, and proton density values of cortical plaques and normal cortical tissue and analyzed the plaque contrast generated by a collection of T2-, T2*-, and susceptibility-weighted imaging (SWI) methods in ex vivo transgenic mouse specimens. The proton density and T1 values were similar for both cortical plaques and normal cortical tissue. The T2 and T2* values were similar in cortical plaques, which indicates that the iron content of cortical plaques may not be as large as previously thought. Ex vivo plaque contrast was increased compared to a previously reported spin echo sequence by summing multiple echoes and by performing SWI; however, gradient echo and susceptibility weighted imaging was found to be impractical for in vivo imaging due to susceptibility interface-related signal loss in the cortex.
MR microscopy; Alzheimer’s disease; magnetic resonance imaging; magnetic resonance micro imaging; transgenic mice; susceptibility weighted imaging
Microtubule-associated protein tau encoded by the MAPT gene binds to microtubules and is important for maintaining neuronal morphology and function. Alternative splicing of MAPT pre-mRNA generates six major tau isoforms in the adult central nervous system resulting in tau proteins with three or four microtubule-binding repeat domains. In a group of neurodegenerative disorders called tauopathies, tau becomes aberrantly hyperphosphorylated and dissociates from microtubules, resulting in a progressive accumulation of intracellular tau aggregates. The spectrum of sporadic frontotemporal lobar degeneration associated with tau pathology includes progressive supranuclear palsy, corticobasal degeneration, and Pick’s disease. Alzheimer’s disease is considered the most prevalent tauopathy. This review is divided into two broad sections. In the first section we discuss the molecular classification of sporadic tauopathies, with a focus on describing clinicopathologic relationships. In the second section we discuss the neuroimaging methodologies that are available for measuring tau pathology (directly using tau positron emission tomography ligands) and tau-mediated neuronal injury (magnetic resonance imaging and fluorodeoxyglucose positron emission tomography). Both sections have detailed descriptions of the following neurodegenerative dementias – Alzheimer’s disease, progressive supranuclear palsy, corticobasal degeneration and Pick’s disease.
Microbleeds have been associated with Alzheimer’s disease (AD), although it is unclear whether they occur in atypical presentations of AD, such as the logopenic variant of primary progressive aphasia (lvPPA). We aimed to assess the presence and clinical correlates of microbleeds in lvPPA.
Thirteen lvPPA subjects underwent 3T T2*-weighted and fluid-attenuated inversion recovery MRI and Pittsburgh Compound B (PiB) PET imaging. Microbleeds were identified on manual review and assigned a regional location. Total and regional white matter hyperintensity (WMH) burden was measured.
Microbleeds were observed in four lvPPA subjects (31%); most common in frontal lobe. Subjects with microbleeds were older, more likely female, and had a greater burden of WMH than those without microbleeds. The regional distribution of microbleeds did not match the regional distribution of WMH. All cases were PiB-positive.
Microbleeds occur in approximately 1/3 subjects with lvPPA, with older women at the highest risk.
Logopenic variant of primary progressive aphasia; Alzheimer’s disease; microbleeds; white matter hyperintensities
Alzheimer's disease (AD) is a slowly progressing disorder in which pathophysiological abnormalities, detectable in vivo by biomarkers, precede overt clinical symptoms by many years to decades. Five AD biomarkers are sufficiently validated to have been incorporated into clinical diagnostic criteria and commonly used in therapeutic trials. Current AD biomarkers fall into 2 categories: biomarkers of amyloid-β plaques and of tau-related neurodegeneration. Three of the 5 are imaging measures and two are cerebrospinal fluid analytes. AD biomarkers do not evolve in an identical manner but rather in a sequential but temporally overlapping manner. Models of the temporal evolution of AD biomarkers can take the form of plots of biomarker severity (degree of abnormality) vs. time. In this review we discuss several time-dependent models of AD which take into consideration varying age of onset (early vs. late) and the influence of aging and co-occurring brain pathologies that commonly arise in the elderly.
Alzheimer's disease; Alzheimer's biomarkers; amyloid imaging; Alzheimer's imaging; Alzheimer's modeling; PET AND Alzheimer's; MRI AND Alzheimer's
Intellectual lifestyle enrichment throughout life is increasingly viewed as a protective strategy against commonly observed cognitive decline in the elderly.
To investigate the association of lifetime intellectual enrichment with baseline cognitive performance and rate of cognitive decline in a non-demented elderly population and to estimate difference (in years) associated with lifetime intellectual enrichment to the onset of cognitive impairment.
DESIGN, SETTING, PARTICIPANTS
Prospective analysis of subjects enrolled in the Mayo Clinic Study of Aging (MCSA), a longitudinal population-based study of cognitive aging in Olmsted County, Minnesota. We studied 1995 non-demented (1718 cognitively normal, 277 MCI) participants in MCSA who completed intellectual lifestyle measures at baseline and underwent at least one follow-up visit.
MAIN OUTCOMES AND MEASURES
We studied the effect of lifetime intellectual enrichment by separating the variables into two non-overlapping principal components: education/occupation-score and mid/late-life cognitive activity measure based on self-report questionnaires. A global cognitive Z-score served as our summary cognition measure. We used linear mixed-effects models to investigate the associations of demographic and intellectual enrichment measures with global cognitive Z-score trajectories.
Baseline cognitive performance was lower in older subjects and in those with lower education/occupation, lower mid/late-life cognitive activity, apolipoprotein E4 (APOE) genotype, and in men. The interaction between the two intellectual enrichment measures was significant such that the beneficial effect of mid/late-life cognitive activity on baseline cognitive performance was reduced with increasing education/occupation. Only baseline age, mid/late-life cognitive activity, and APOE4 genotype were significantly associated with longitudinal change in cognitive performance from baseline. For APOE4 carriers with high lifetime intellectual enrichment (75th percentile of both education/occupation and mid/late-life cognitive activity), the onset of cognitive impairment was about 8.7 years later compared with low lifetime intellectual enrichment (25th percentile of both education/occupation and mid/late-life cognitive activity) in an 80 year old subject.
CONCLUSIONS AND RELEVANCE
Higher levels of education/occupation were associated with higher levels of cognition. Higher levels of mid/late-life leisure activity were also associated with higher levels of cognition, but the slope of this relationship slightly increased over time. Lifetime intellectual enrichment might delay the onset of cognitive impairment and be used as a successful preventive intervention to reduce the impending dementia epidemic.
Biomarkers of Alzheimer's disease (AD) are increasingly important. All modern AD therapeutic trials employ AD biomarkers in some capacity. In addition, AD biomarkers are an essential component of recently updated diagnostic criteria for AD from the National Institute on Aging – Alzheimer's Association. Biomarkers serve as proxies for specific pathophysiological features of disease. The 5 most well established AD biomarkers include both brain imaging and cerebrospinal fluid (CSF) measures – CSF Abeta and tau, amyloid positron emission tomography (PET), fluorodeoxyglucose (FDG) PET, and structural magnetic resonance imaging (MRI). This article reviews evidence supporting the position that MRI is a biomarker of neurodegenerative atrophy. Topics covered include methods of extracting quantitative and semi quantitative information from structural MRI; imaging-autopsy correlation; and evidence supporting diagnostic and prognostic value of MRI measures. Finally, the place of MRI in a hypothetical model of temporal ordering of AD biomarkers is reviewed.
To characterize the shape of the trajectories of Alzheimer’s Disease (AD) biomarkers as a function of MMSE.
Longitudinal registries from the Mayo Clinic and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).
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).
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.
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.
Alzheimer’s disease biomarkers; Magnetic Resonance Imaging; cerebro spinal fluid; amyloid PET imaging; FDG PET imaging
Autosomal dominant Alzheimer disease (ADAD) is caused by rare genetic
mutations in three specific genes, in contrast to late-onset Alzheimer
Disease (LOAD), which has a more polygenetic risk profile.
Design, Setting, and Participants
We analyzed functional connectivity in multiple brain resting state
networks (RSNs) in a cross-sectional cohort of ADAD (N=79) and LOAD (N=444)
human participants using resting state functional connectivity MRI
(rs-fcMRI) at multiple international academic sites.
Main Outcomes and Measures
For both types of AD, we quantified and compared functional
connectivity changes in RSNs as a function of dementia severity as measured
by clinical dementia rating (CDR). In ADAD, we qualitatively investigated
functional connectivity changes with respect to estimated years from onset
of symptoms within five RSNs.
Functional connectivity decreases with increasing CDR were similar
for both LOAD and ADAD in multiple RSNs. Ordinal logistic regression models
constructed in each type of AD accurately predicted CDR stage in the other,
further demonstrating similarity of functional connectivity loss in each
disease type. Among ADAD participants, functional connectivity in multiple
RSNs appeared qualitatively lower in asymptomatic mutation carriers near
their anticipated age of symptom onset compared to asymptomatic mutation
Conclusions and Relevance
rs-fcMRI changes with progressing AD severity are similar between
ADAD and LOAD. Rs-fcMRI may be a useful endpoint for LOAD and ADAD therapy
trials. ADAD disease process may be an effective model for LOAD disease
Resting-state functional connectivity; autosomal dominant Alzheimer's disease; late-onset Alzheimer's disease; default mode network; apolipoprotein E (APOE)
A workgroup commissioned by the Alzheimer’s Association (AA) and the National Institute on Aging (NIA) recently published research criteria for preclinical Alzheimer’s disease (AD). We performed a preliminary assessment of these guidelines.
We employed Pittsburgh compound B positron emission tomography (PET) imaging as our biomarker of cerebral amyloidosis and 18fluorodeoxyglucose PET imaging and hippocampal volume as biomarkers of neurodegeneration. A group of 42 clinically diagnosed AD subjects was used to create imaging biomarker cut-points. A group of 450 cognitively normal (CN) subjects from a population based sample was used to develop cognitive cut-points and to assess population frequencies of the different preclinical AD stages using different cut-point criteria.
The new criteria subdivide the preclinical phase of AD into stages 1–3. To classify our CN subjects, two additional categories were needed. Stage 0 denotes subjects with normal AD biomarkers and no evidence of subtle cognitive impairment. Suspected Non-AD Pathophysiology (SNAP) denotes subjects with normal amyloid PET imaging, but abnormal neurodegeneration biomarker studies. At fixed cut-points corresponding to 90% sensitivity for diagnosing AD and the 10th percentile of CN cognitive scores, 43% of our sample was classified as stage 0; 16% stage 1; 12 % stage 2; 3% stage 3; and 23% SNAP.
This cross-sectional evaluation of the NIA-AA criteria for preclinical AD indicates that the 1–3 staging criteria coupled with stage 0 and SNAP categories classify 97% of CN subjects from a population-based sample, leaving just 3% unclassified. Future longitudinal validation of the criteria will be important.
Dysfunctional insulin signaling may affect brain metabolism or amyloid deposition. We investigated the associations of type 2 diabetes with amyloid accumulation measured using 11C-Pittsburgh Compound B (PiB) and brain hypometabolism measured using 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET).
We studied a sample of non-demented participants from the population-based Mayo Clinic Study of Aging. All subjects underwent MRI, amyloid PET and FDG PET. Alzheimer’s disease (AD) signature and region of interest (ROI) measures for PiB retention ratio and FDG ratio were measured. Diabetes was assessed from the Rochester Epidemiology Project medical records-linkage system.
Among 749 participants (median age 79.0 years; 56.5% male, 81.0% cognitively normal; 20.6% diabetics), FDG hypometabolism (FDG ratio < 1.31) in the AD signature meta-ROI was more common in diabetics (48.1%) than in non-diabetics (28.9%; p <0.001). The median FDG ratio was lower in diabetics vs. non-diabetics in the AD signature meta-ROI (1.32 vs. 1.40, p < 0.001), and in the angular (1.40 vs. 1.48, p < 0.001) and posterior cingulate gyri ROIs (1.63 vs. 1.72, p < 0.001). The odds ratio (OR [95% confidence interval]) for abnormal AD signature FDG hypometabolism was elevated (OR, 2.28 [1.56, 3.33]) in diabetics vs. non-diabetics after adjustment for age, sex, and education, and after additional adjustment for Apolipoprotein ε4 allele, glycemic level, and cognitive status (OR, 1.69 [1.10, 2.60]). However, AD signature PiB retention ratio was similar in diabetics vs. non-diabetics (OR, 1.03 [0.71, 1.51]; p = 0.87). In post-hoc analyses in non-diabetics, a 1% increase in HBA1c was associated with greater AD signature hypometabolism in cognitively normal subjects (OR, 1.93 [1.03, 3.62; p = 0.04]) and in the total cohort (OR 1.59 [0.92, 2.75; p = 0.10).
Diabetes and poor glycemic control in non-diabetics may enhance glucose hypometabolism in AD signature regions. These factors should be investigated in longitudinal studies for their role in detecting onset of symptoms in AD.
Diabetes; cerebral glucose metabolism; FDG- and PiB-PET imaging; hemoglobin A1c; amyloid accumulation
Neurofibrillary tangles (NFTs) are one of the key histological lesions of Alzheimer’s disease (AD) and are associated with brain atrophy. We assessed regional NFT density in 30 patients with AD, 10 of which presented as the logopenic variant of primary progressive aphasia (lvPPA) and 20 that presented as dementia of the Alzheimer’s type (DAT). Regional grey matter volumes were measured using antemortem MRI. NFT density was significantly higher in left temporoparietal cortices in lvPPA compared to DAT, with no differences observed in hippocampus. There was a trend for the ratio of temporoparietal-to-hippocampal NFT density to be higher in lvPPA. The imaging findings mirrored the pathological findings, with smaller left temporoparietal volumes observed in lvPPA compared to DAT, and no differences observed in hippocampal volume. This study demonstrates that lvPPA is associated with a phenomenon of enhanced temporoparietal neurodegeneration, a finding that improves our understanding of the biological basis of lvPPA.
Primary progressive aphasia; Logopenic variant of primary progressive aphasia; Alzheimer’s disease; Neurofibrillary tangles; Hippocampus; MRI; Apolipoprotein E; TDP-43; Voxel-based morphometry; Alzheimer’s dementia
The purpose of this study was to examine the association between aphasia severity and neurocognitive function, disease duration and temporoparietal atrophy in 21 individuals with the logopenic variant of primary progressive aphasia (lvPPA). We found significant correlations between aphasia severity and neurocognitive severity as well as temporoparietal atrophy; but not disease duration. Cluster analysis identified three variants of lvPPA: (1) subjects with mild aphasia and short disease duration (mild typical lvPPA); (2) subjects with mild aphasia and long disease duration (mild atypical lvPPA); and, (3) subjects with severe aphasia and relatively long disease duration (severe typical lvPPA). All three variants showed temporoparietal atrophy, with the mild atypical group showing the least atrophy despite the longest disease duration. The mild atypical group also showed mild neuropsychological impairment. The subjects with mild aphasia and neuropsychological impairment despite long disease duration may represent a slowly progressive variant of lvPPA.
Primary progressive aphasia; Logopenic aphasia; Neurocognitive impairment; Temporoparietal atrophy; Voxel-based morphometry
The devastating effects of the still incurable Alzheimer's disease (AD) project an ever increasing shadow of burden on the health care system and society in general. In this ominous context, amyloid (Aβ) imaging is considered by many of utmost importance for progress towards earlier AD diagnosis and for potential development of effective therapeutic interventions. Amyloid imaging positron emission tomography procedures offer the opportunity for accurate mapping and quantification of amyloid-Aβ neuroaggregate deposition in the living brain of AD patients. This review analyzes the perceived value of current Aβ imaging probes and their clinical utilization and, based on amyloid imaging results, offers a hypothesis on the effects of amyloid deposition on the biology of AD and its progression. It also analyzes lingering questions permeating the field of amyloid imaging on the apparent contradictions between imaging results and known neuropathology brain regional deposition of Aβ aggregates. As a result, the review also discusses literature evidence as to whether brain Aβ deposition is truly visualized and measured with these amyloid imaging agents, which would have significant implications in the understanding of the biological AD cascade and in the monitoring of therapeutic interventions with these surrogate Aβ markers.
Aβ; Alzheimer's disease; Amyloid imaging; Florbetapir; Neuropathological correlations; Neuropathological diagnostic criteria; Pittsburgh Compound B
Migraine is associated with white matter hyperintensities (WMH) cross-sectionally, but its effect on WMH progression is uncertain.
Participants in the Atherosclerosis Risk in Communities cohort study (n = 10,924) completed a standardized headache questionnaire between 1993 and 1995. A subset of participants (n = 1,028) received 2 MRIs 8 to 12 years apart: once at the time of headache ascertainment, and again from 2004 to 2006. WMH were quantified using both a visually graded score (0–9) and semiautomated volumetric analysis. Linear and logistic regression models adjusted for age, sex, and other vascular risk factors were constructed.
Individuals who had migraine without aura were cross-sectionally associated with an 87% greater odds of having a WMH score ≥3 than individuals without headache (adjusted odds ratio = 1.87; 95% confidence interval [CI]: 1.04, 3.37). Participants with migraine had an average of 2.65 cm3 more WMH than those without headache (95% CI: 0.06, 5.24). However, there was no significant difference in WMH progression over the study period between individuals with and without migraine (1.58 cm3 more progression for individuals with migraine compared to those without; 95% CI: −0.37, 3.53).
Migraine is associated with WMH volume cross-sectionally but not with WMH progression over time. This suggests that the association between migraine and WMH is stable in older age and may be primarily attributable to changes occurring earlier in life, although further work is needed to confirm these findings.
Prevalence and risk factors for focal hemosiderin deposits are important considerations when planning amyloid–modifying trials for treatment and prevention of Alzheimer’s disease (AD).
Subjects were cognitively normal (n=171), early-mild cognitive impairment (MCI) (n=240), late-MCI (n=111) and AD (n=40) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Microhemorrhages and superficial siderosis were assessed at baseline and on all available MRIs at 3, 6 and 12 months. β-amyloid load was assessed with 18F-florbetapir PET.
Prevalence of superficial siderosis was 1% and prevalence of microhemorrhages was 25% increasing with age (p<0.001) and β-amyloid load (p<0.001). Topographic densities of microhemorrhages were highest in the occipital lobes and lowest in the deep/infratentorial regions. A greater number of microhemorrhages at baseline was associated with a greater annualized rate of additional microhemorrhages by last follow-up (rank correlation=0.49;P<0.001).
Focal hemosiderin deposits are relatively common in the ADNI cohort and are associated with β-amyloid load.
ADNI; microhemorrhage; superficial siderosis; MRI; Amyloid; PET; Florbetapir; Alzheimer’s disease; mild cognitive impairment; early mild cognitive impairment
Midbrain atrophy is a characteristic feature of progressive supranuclear palsy (PSP), although it is unclear whether it is associated with the PSP syndrome (PSPS) or PSP pathology. We aimed to determine whether midbrain atrophy is a useful biomarker of PSP pathology, or whether it is only associated with typical PSPS.
We identified all autopsy-confirmed subjects with the PSP clinical phenotype (i.e. PSPS) or PSP pathology and a volumetric MRI. Of 24 subjects with PSP pathology, 11 had a clinical diagnosis of PSPS (PSP-PSPS), and 13 had a non-PSPS clinical diagnosis (PSP-other). Three subjects had PSPS and corticobasal degeneration pathology (CBD-PSPS). Healthy control and disease control groups (i.e. a group without PSPS or PSP pathology) and a group with CBD pathology and corticobasal syndrome (CBD-CBS) were selected. Midbrain area was measured in all subjects.
Midbrain area was reduced in each group with clinical PSPS (with and without PSP pathology). The group with PSP pathology and non-PSPS clinical syndromes did not show reduced midbrain area. Midbrain area was smaller in the subjects with PSPS compared to those without PSPS (p<0.0001), with an area under the receiver-operator-curve of 0.99 (0.88,0.99). A midbrain area cut-point of 92 mm2 provided optimum sensitivity (93%) and specificity (89%) for differentiation.
Midbrain atrophy is associated with the clinical presentation of PSPS, but not with the pathological diagnosis of PSP in the absence of the PSPS clinical syndrome. This finding has important implications for the utility of midbrain measurements as diagnostic biomarkers for PSP pathology.
Progressive supranuclear palsy; tau; neuropathology; MRI; midbrain
Diffusion weighted magnetic resonance imaging (DW-MRI) are now widely used to assess brain integrity in clinical populations. The growing interest in mapping brain connectivity has made it vital to consider what scanning parameters affect the accuracy, stability, and signal-to-noise of Diffusion measures. Trade-offs between scan parameters can only be optimized if their effects on various commonly derived measures are better understood. To explore angular versus spatial resolution trade-offs in standard tensor-derived measures, and in measures that use the full angular information in diffusion signal, we scanned eight subjects twice, two weeks apart, using three protocols that took the same amount of time (7 minutes). Scans with 3, 2.7, 2.5 mm isotropic voxels were collected using 48, 41, and 37 diffusion-sensitized gradients to equalize scan times. A specially designed DTI phantom was also scanned with the same protocols, and different b-values. We assessed how several diffusion measures including fractional anisotropy (FA), mean diffusivity (MD), and the full 3D orientation distribution function (ODF) depended on the spatial/angular resolution and the SNR. We also created maps of stability over time in the FA, MD, ODF, skeleton FA of 14 TBSS-derived ROIs, and an information uncertainty index derived from the tensor distribution function, which models the signal using a continuous mixture of tensors. In scans of the same duration, higher angular resolution and larger voxels boosted SNR and improved stability over time. The increased partial voluming in large voxels also led to bias in estimating FA, but this was partially addressed by using “beyond-tensor” models of diffusion.
High Angular Resolution Diffusion Imaging; Diffusion Tensor Imaging; Spatial Resolution; Angular Resolution; Orientation Distribution Function; Tensor Distribution Function; reproducibility
The promise of Alzheimer’s disease (AD) biomarkers has led to their incorporation in new diagnostic criteria and in therapeutic trials; however, significant barriers exist to widespread use. Chief among these is the lack of internationally accepted standards for quantitative metrics. Hippocampal volumetry is the most widely studied quantitative magnetic resonance imaging (MRI) measure in AD and thus represents the most rational target for an initial effort at standardization.
Methods and Results
The authors of this position paper propose a path toward this goal. The steps include: 1) Establish and empower an oversight board to manage and assess the effort, 2) Adopt the standardized definition of anatomic hippocampal boundaries on MRI arising from the EADC-ADNI hippocampal harmonization effort as a Reference Standard, 3) Establish a scientifically appropriate, publicly available Reference Standard Dataset based on manual delineation of the hippocampus in an appropriate sample of subjects (ADNI), and 4) Define minimum technical and prognostic performance metrics for validation of new measurement techniques using the Reference Standard Dataset as a benchmark.
Although manual delineation of the hippocampus is the best available reference standard, practical application of hippocampal volumetry will require automated methods. Our intent is to establish a mechanism for credentialing automated software applications to achieve internationally recognized accuracy and prognostic performance standards that lead to the systematic evaluation and then widespread acceptance and use of hippocampal volumetry. The standardization and assay validation process outlined for hippocampal volumetry is envisioned as a template that could be applied to other imaging biomarkers.
Alzheimer’s disease; biomarkers; Magnetic resonance imaging; hippocampus; biomarker standards
To empirically assess the concept that Alzheimer’s disease (AD) biomarkers significantly depart from normality in a temporally ordered manner.
Multi-site, referral centers
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.
Main Outcome measures
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.
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 biomarkers; Magnetic Resonance Imaging; CSF tau; CSF Abeta; Alzheimer’s disease staging
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.
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).
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.
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.
Alzheimer's disease; Pittsburgh Compound B; amyloid imaging; Aβ amyloid; cerebrospinal fluid; Alzheimer's disease biomarkers
Deposition of amyloid-β (Aβ) in the cerebral cortex is thought to be a pivotal event in Alzheimer’s disease (AD) pathogenesis with a significant genetic contribution. Molecular imaging can provide an early noninvasive phenotype but small samples have prohibited genome-wide association studies (GWAS) of cortical Aβ load until now. We employed florbetapir (18F) positron emission tomography (PET) imaging to assess brain Aβ levels in vivo for 555 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). More than six million common genetic variants were tested for association to quantitative global cortical Aβ load controlling for age, gender, and diagnosis. Independent genome-wide significant associations were identified on chromosome 19 within APOE (rs429358, p = 5.5 × 10−14) and on chromosome 3 upstream of BCHE (rs509208, p = 2.7 × 10−8) in a region previously associated with serum butyrylcholinesterase activity. Together, these loci explained 15% of the variance in cortical Aβ levels in this sample (APOE 10.7%, BCHE 4.3%). Suggestive associations were identified within ITGA6, near EFNA5, EDIL3, ITGA1, PIK3R1, NFIB, and ARID1B, and between NUAK1 and C12orf75. These results confirm the association of APOE with Aβ deposition and represent the largest known effect of BCHE on an AD-related phenotype. Butyrylcholinesterase has been found in senile plaques and this new association of genetic variation at the BCHE locus with Aβ burden in humans may have implications for potential disease-modifying effects of butyrylcholinesterase-modulating agents in the AD spectrum.
Alzheimer’s disease (AD); amyloid; apolipoprotein E (APOE); butyrylcholinesterase (BCHE); florbetapir (AV-45); genome-wide association study (GWAS)