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.
To evaluate the proton MR spectroscopy (1H MRS) changes in carriers of a novel octapeptide repeat insertion in the Prion Protein Gene (PRNP) and family history of frontotemporal dementia with ataxia. Four at-risk mutation carriers and 13 controls were compared using single voxel, short TE, 1H MRS from the posterior cingulate gyrus. The mutation carriers had an increased choline/creatine, p=0.003 and increased myoinositol/creatine ratio, p=0.003. 1H MRS identified differences in markers of glial activity and choline metabolism in pre- and early symptomatic carriers of a novel PRNP gene octapeptide insertion. These findings expand the possible diagnostic utility of 1H MRS in familial prion disorders.
MRS; MRI; familial prion disorders; frontotemporal dementia
Diffusion imaging and brain connectivity analyses can monitor white matter deterioration, revealing how neural pathways break down in aging and Alzheimer's disease (AD). Here we tested how AD disrupts the ‘rich club’ effect – a network property found in the normal brain – where high-degree nodes in the connectivity network are more heavily interconnected with each other than expected by chance. We analyzed 3-Tesla whole-brain diffusionweighted images (DWI) from 66 subjects (22 AD/44 normal elderly). We performed whole-brain tractography based on the orientation distribution functions. Connectivity matrices were compiled, representing the proportion of detected fibers interconnecting 68 cortical regions. As expected, AD patients had a lower nodal degree (average number of connections) in cortical regions implicated in the disease. Unexpectedly, the normalized rich club coefficient was higher in AD. AD disrupts cortical networks by removing connections; when these networks are thresholded, organizational properties are disrupted leading to additional new biomarkers of AD.
Delta opioid receptors are implicated in a variety of psychiatric and neurological disorders. These receptors play a key role in the reinforcing properties of drugs of abuse, and polymorphisms in OPRD1 (the gene encoding delta opioid receptors) are associated with drug addiction. Delta opioid receptors are also involved in protecting neurons against hypoxic and ischemic stress. Here, we first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer’s Disease Neuroimaging Initiative. We hypothesized that common variants in OPRD1 would be associated with differences in brain structure, particularly in regions relevant to addictive and neurodegenerative disorders. One very common variant (rs678849) predicted differences in regional brain volumes. We replicated the association of this single-nucleotide polymorphism with regional tissue volumes in a large sample of young participants in the Queensland Twin Imaging study. Although the same allele was associated with reduced volumes in both cohorts, the brain regions affected differed between the two samples. In healthy elderly, exploratory analyses suggested that the genotype associated with reduced brain volumes in both cohorts may also predict cerebrospinal fluid levels of neurodegenerative biomarkers, but this requires confirmation. If opiate receptor genetic variants are related to individual differences in brain structure, genotyping of these variants may be helpful when designing clinical trials targeting delta opioid receptors to treat neurological disorders.
neuroimaging; genetics; neurodegeneration; drug addiction; opiates
We describe the operationalization of the National Institute on Aging–Alzheimer’s Association (NIA-AA) workgroup diagnostic guidelines pertaining to Alzheimer disease (AD) dementia in a large multicenter group of subjects with AD dementia.
Subjects with AD dementia from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) with at least 1 amyloid biomarker (n = 211) were included in this report. Biomarker data from CSF Aβ42, amyloid PET, fluorodeoxyglucose-PET, and MRI were examined. The biomarker results were assessed on a per-patient basis and the subject categorization as defined in the NIA-AA workgroup guidelines was determined.
When using a requirement that subjects have a positive amyloid biomarker and single neuronal injury marker having an AD pattern, 87% (48% for both neuronal injury biomarkers) of the subjects could be categorized as “high probability” for AD. Amyloid status of the combined Pittsburgh compound B–PET and CSF results showed an amyloid-negative rate of 10% in the AD group. In the ADNI AD group, 5 of 92 subjects fit the category “dementia unlikely due to AD” when at least one neuronal injury marker was negative.
A large proportion of subjects with AD dementia in ADNI may be categorized more definitively as high-probability AD using the proposed biomarker scheme in the NIA-AA criteria. A minority of subjects may be excluded from the diagnosis of AD by using biomarkers in clinically categorized AD subjects. In a well-defined AD dementia population, significant biomarker inconsistency can be seen on a per-patient basis.
Progressive apraxia of speech (AOS) can result from neurodegenerative disease and can occur in isolation or in the presence of agrammatic aphasia. We aimed to determine the neuroanatomical and metabolic correlates of progressive AOS and aphasia. Thirty-six prospectively recruited subjects with progressive AOS or agrammatic aphasia, or both, underwent the Western Aphasia Battery (WAB) and Token Test to assess aphasia, an AOS rating scale (ASRS), 3T MRI and 18-F fluorodeoxyglucose (FDG) PET. Correlations between clinical measures and imaging were assessed. The only region that correlated to ASRS was left superior premotor volume. In contrast, WAB and Token Test correlated with hypometabolism and volume of a network of left hemisphere regions, including pars triangularis, pars opercularis, pars orbitalis, middle frontal gyrus, superior temporal gyrus, precentral gyrus and inferior parietal lobe. Progressive agrammatic aphasia and AOS have non-overlapping regional correlations, suggesting that these are dissociable clinical features that have different neuroanatomical underpinnings.
apraxia of speech; aphasia; atrophy; Broca’s area; premotor cortex; hypometabolism
Deficits in lentiform nucleus volume and morphometry are implicated in a number of genetically influenced disorders, including Parkinson’s disease, schizophrenia, and ADHD. Here we performed genome-wide searches to discover common genetic variants associated with differences in lentiform nucleus volume in human populations. We assessed structural MRI scans of the brain in two large genotyped samples: the Alzheimer’s Disease Neuroimaging Initiative (ADNI; N=706) and the Queensland Twin Imaging Study (QTIM; N=639). Statistics of association from each cohort were combined meta-analytically using a fixed-effects model to boost power and to reduce the prevalence of false positive findings. We identified a number of associations in and around the flavin-containing monooxygenase (FMO) gene cluster. The most highly associated SNP, rs1795240, was located in the FMO3 gene; after meta-analysis, it showed genome-wide significant evidence of association with lentiform nucleus volume (PMA=4.79×10−8). This commonly-carried genetic variant accounted for 2.68 % and 0.84 % of the trait variability in the ADNI and QTIM samples, respectively, even though the QTIM sample was on average 50 years younger. Pathway enrichment analysis revealed significant contributions of this gene to the cytochrome P450 pathway, which is involved in metabolizing numerous therapeutic drugs for pain, seizures, mania, depression, anxiety, and psychosis. The genetic variants we identified provide replicated, genome-wide significant evidence for the FMO gene cluster’s involvement in lentiform nucleus volume differences in human populations.
Basal ganglia; Genome-wide association study (GWAS); MRI; Replication; Morphometry; Drug metabolism
To test the hypotheses predicted in a hypothetical model of Alzheimer disease (AD) biomarkers that rates of β-amyloid (Aβ) accumulation on PET imaging are not related to hippocampal neurodegeneration whereas rates of neurodegenerative brain atrophy depend on the presence of both amyloid and neurodegeneration in a population-based sample.
A total of 252 cognitively normal (CN) participants from the Mayo Clinic Study of Aging had 2 or more serial visits with both amyloid PET and MRI. Subjects were classified into 4 groups based on baseline positive/negative amyloid PET (A+ or A−) and baseline hippocampal volume (N+ or N−). We compared rates of amyloid accumulation and rates of brain atrophy among the 4 groups.
At baseline, 148 (59%) were amyloid negative and neurodegeneration negative (A−N−), 29 (12%) amyloid negative and neurodegeneration positive (A−N+), 56 (22%) amyloid positive and neurodegeneration negative (A+N−), and 19 (8%) amyloid positive and neurodegeneration positive (A+N+). High rates of Aβ accumulation were found in those with abnormal amyloid at baseline and were not influenced by hippocampal neurodegeneration at baseline. In contrast, rates of brain atrophy were greatest in A+N+.
We describe a 2-feature biomarker approach to classifying elderly CN subjects that is complementary to the National Institute on Aging–Alzheimer's Association preclinical staging criteria. Our results support 2 key concepts in a model of the temporal evolution of AD biomarkers. First, the rate of Aβ accumulation is not influenced by neurodegeneration and thus may be a biologically independent process. Second, Aβ pathophysiology increases or catalyzes neurodegeneration.
The ADNI 3D T1-weighted MRI acquisitions provide a rich dataset for developing and testing analysis techniques for extracting structural endpoints. To promote greater rigor in analysis and meaningful comparison of different algorithms, the ADNI MRI Core has created standardized analysis sets of data comprising scans that met minimum quality control requirements. We encourage researchers to test and report their techniques against these data. Standard analysis sets of volumetric scans from ADNI-1 have been created, comprising: screening visits, 1 year completers (subjects who all have screening, 6 and 12 month scans), two year annual completers (screening, 1, and 2 year scans), two year completers (screening, 6 months, 1 year, 18 months (MCI only) and 2 years) and complete visits (screening, 6 months, 1 year, 18 months (MCI only), 2, and 3 year (normal and MCI only) scans). As the ADNI-GO/ADNI-2 data becomes available, updated standard analysis sets will be posted regularly.
We propose a new method to maximize biomarker efficiency for detecting anatomical change over time in serial MRI. Drug trials using neuroimaging become prohibitively costly if vast numbers of subjects must be assessed, so it is vital to develop efficient measures of brain change. A popular measure of efficiency is the minimal sample size (n80) needed to detect 25% change in a biomarker, with 95% confidence and 80% power. For multivariate measures of brain change, we can directly optimize n80 based on a Linear Discriminant Analysis (LDA). Here we use a supervised learning framework to optimize n80, offering two alternative solutions. With a new medial surface modeling method, we track 3D dynamic changes in the lateral ventricles in 2065 ADNI scans. We apply our LDA-based weighting to the results. Our best average n80—in two-fold nested cross-validation—is 104 MCI subjects (95% CI: [94,139]) for a 1-year drug trial, and 75 AD subjects [64,102]. This compares favorably with other MRI analysis methods. The standard “statistical ROI” approach applied to the same ventricular surfaces requires 165 MCI or 94 AD subjects. At 2 years, the best LDA measure needs only 67 MCI and 52 AD subjects, versus 119 MCI and 80 AD subjects for the stat-ROI method. Our surface-based measures are unbiased: they give no artifactual additive atrophy over three time points. Our results suggest that statistical weighting may boost efficiency of drug trials that use brain maps.
Linear Discriminant Analysis; Shape analysis; ADNI; Lateral ventricles; Alzheimer’s disease; Mild cognitive impairment; Biomarker; Drug trial; Machine learning
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.
Primary progressive apraxia of speech, a motor speech disorder of planning and programming is a tauopathy that has overlapping histological features with progressive supranuclear palsy. We aimed to compare, for the first time, atrophy patterns, as well as white matter tract degeneration, between these two syndromes.
Sixteen primary progressive apraxia of speech subjects were age and gender-matched to 16 progressive supranuclear palsy subjects and 20 controls. All subjects were prospectively recruited, underwent neurological and speech evaluations, and 3.0 Tesla magnetic resonance imaging. Grey and white matter atrophy was assessed using voxel-based morphometry and atlas-based parcellation, and white matter tract degeneration was assessed using diffusion tensor imaging.
All progressive supranuclear palsy subjects had typical occulomotor/gait impairments but none had speech apraxia. Both syndromes showed grey matter loss in supplementary motor area, white matter loss in posterior frontal lobes and degeneration of the body of the corpus callosum. While lateral grey matter loss was focal, involving superior premotor cortex, in primary progressive apraxia of speech, loss was less focal extending into prefrontal cortex in progressive supranuclear palsy. Caudate volume loss and tract degeneration of superior cerebellar peduncles was also observed in progressive supranuclear palsy. Interestingly, area of the midbrain was reduced in both syndromes compared to controls, although this was greater in progressive supranuclear palsy.
Although neuroanatomical differences were identified between these distinctive clinical syndromes, substantial overlap was also observed, including midbrain atrophy, suggesting these two syndromes may have common pathophysiological underpinnings.
Progressive supranuclear palsy; apraxia of speech; voxel-based morphometry; diffusion tensor imaging; midbrain
Poor kidney function is associated with increased risk of cognitive decline and generalized brain atrophy. Chronic kidney disease impairs glomerular filtration rate (eGFR), and this deterioration is indicated by elevated blood levels of kidney biomarkers such as creatinine (SCr) and cystatin C (CysC). Here we hypothesized that impaired renal function would be associated with brain deficits in regions vulnerable to neurodegeneration.
Using tensor-based morphometry, we related patterns of brain volumetric differences to SCr, CysC levels, and eGFR in a large cohort of 738 (mean age: 75.5±6·8 years; 438 men/300 women) elderly Caucasian subjects scanned as part of the Alzheimer’s Disease Neuroimaging Initiative.
Elevated kidney biomarkers were associated with volume deficits in the white matter region of the brain. All the three renal parameters in our study showed significant associations consistently with a region that corresponds with the anterior limb of internal capsule, bilaterally.
This is the first study to report a marked profile of structural alterations in the brain associated with elevated kidney biomarkers; helping us explain the cognitive deficits.
creatinine; cystatin C; GFR; kidney function; brain volumes; brain structure; brain atrophy; neuroimaging; cognitive deficits
The new criteria for preclinical Alzheimer’s Disease (AD) proposed 3 stages: abnormal levels of β-amyloid (stage 1); stage 1 plus evidence of brain injury (stage 2); and stage 2 plus subtle cognitive changes (stage 3). However, a large group of subjects with normal β-amyloid biomarkers have evidence of brain injury; we labeled them as “suspected non-Alzheimer pathway” (sNAP) group. The characteristics of the sNAP group are poorly understood.
Using the preclinical AD classification, 430 cognitively normal subjects from the Mayo Clinic Study of Aging who underwent brain MR, 18fluorodeoxyglucose (FDG) and Pittsburgh compound B (PiB) positron emission tomography (PET) were evaluated with FDG PET regional volumetrics, MR regional brain volumetrics, white matter hyperintensity (WMH) volume and number of infarcts. We examined cross-sectional associations across AD preclinical stages, those with all biomarkers normal, and the sNAP group.
The sNAP group had a lower proportion (14%) with APOE ε4 genotype than the preclinical AD stages 2 + 3. The sNAP group did not show any group differences compared to stages 2 + 3 of the preclinical AD group on measures of FDG PET regional hypometabolism, MR regional brain volume loss, cerebrovascular imaging lesions, vascular risk factors, imaging changes associated with α-synucleinopathy or physical findings of parkinsonism.
Cognitively normal persons with brain injury biomarker abnormalities, with or without abnormal levels of β-amyloid, were indistinguishable on a variety of imaging markers, clinical features and risk factors. The initial appearance of brain injury biomarkers that occurs in cognitively normal persons with preclinical AD may not depend on β-amyloidosis.
Alzheimer’s disease; PET imaging; MR imaging; Epidemiology
We analyzed the baseline and 3-year T1-weighted magnetic resonance imaging data of 110 amnestic mild cognitive impairment (MCI) participants with minimal hippocampal atrophy at baseline from the Alzheimer’s Disease Cooperative Study group (ADCS) MCI Donepezil/Vitamin E trial. 46 subjects converted to AD (MCIc) while 64 remained stable (MCInc). We used the radial distance technique to examine the differences in lateral ventricle shape and size between MCIc and MCInc and the associations between ventricular enlargement and cognitive decline.
MCIc group had significantly larger frontal and right body/occipital horns relative to MCInc at baseline and significantly larger bilateral frontal, body/occipital and left temporal horns at follow-up. Global cognitive decline measured with ADAScog and MMSE and decline in activities of daily living (ADL) were associated with posterior lateral ventricle enlargement. Decline in ADAScog and ADL were associated with left temporal and decline in MMSE with right temporal horn enlargement. After correction for baseline hippocampal volume decline in ADL showed a significant association with right frontal horn enlargement. Executive decline was associated with right frontal and left temporal horn enlargement.
Alzheimer’s disease; AD; mild cognitive impairment; MCI; imaging; MRI; brain atrophy; ventricular enlargement
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
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
To determine the association of conventional cardiovascular risk factors, markers of platelet activation, and thrombogenic blood-borne microvesicles with white matter hyperintensity (WMH) load and progression in recently menopausal women.
Women (n = 95) enrolled in the Mayo Clinic Kronos Early Estrogen Prevention Study underwent MRI at baseline and at 18, 36, and 48 months after randomization to hormone treatments. Conventional cardiovascular risk factors, carotid intima-medial thickness, coronary arterial calcification, plasma lipids, markers of platelet activation, and thrombogenic microvesicles were measured at baseline. WMH volumes were calculated using a semiautomated segmentation algorithm based on fluid-attenuated inversion recovery MRI. Correlations of those parameters with baseline WMH and longitudinal change in WMH were adjusted for age, months past menopause, and APOE ε4 status in linear regression analysis.
At baseline, WMH were present in all women. The WMH to white matter volume fraction at baseline was 0.88% (0.69%, 1.16%). WMH volume increased by 122.1 mm3 (95% confidence interval: −164.3, 539.5) at 36 months (p = 0.003) and 155.4 mm3 (95% confidence interval: −92.13, 599.4) at 48 months (p < 0.001). These increases correlated with numbers of platelet-derived and total thrombogenic microvesicles at baseline (p = 0.03).
Associations of platelet-derived, thrombogenic microvesicles at baseline and increases in WMH suggest that in vivo platelet activation may contribute to a cascade of events leading to development of WMH in recently menopausal women.
To model the temporal trajectory of β-amyloid accumulation using serial amyloid PET imaging.
Participants, aged 70–92 years, were enrolled in either the Mayo Clinic Study of Aging (n = 246) or the Mayo Alzheimer's Disease Research Center (n = 14). All underwent 2 or more serial amyloid PET examinations. There were 205 participants classified as cognitively normal and 55 as cognitively impaired (47 mild cognitive impairment and 8 Alzheimer dementia). We measured baseline amyloid PET-relative standardized uptake values (SUVR) and, for each participant, estimated a slope representing their annual amyloid accumulation rate. We then fit regression models to predict the rate of amyloid accumulation given baseline amyloid SUVR, and evaluated age, sex, clinical group, and APOE as covariates. Finally, we integrated the amyloid accumulation rate vs baseline amyloid PET SUVR association to an amyloid PET SUVR vs time association.
Rates of amyloid accumulation were low at low baseline SUVR. Rates increased to a maximum at baseline SUVR around 2.0, above which rates declined—reaching zero at baseline SUVR above 2.7. The rate of amyloid accumulation as a function of baseline SUVR had an inverted U shape. Integration produced a sigmoid curve relating amyloid PET SUVR to time. The average estimated time required to travel from an SUVR of 1.5–2.5 is approximately 15 years.
This roughly 15-year interval where the slope of the amyloid SUVR vs time curve is greatest and roughly linear represents a large therapeutic window for secondary preventive interventions.
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.
Various neuroimaging measures are being evaluated for tracking Alzheimer’s disease (AD) progression in therapeutic trials, including measures of structural brain change based on repeated scanning of patients with magnetic resonance imaging (MRI). Methods to compute brain change must be robust to scan quality. Biases may arise if any scans are thrown out, as this can lead to the true changes being overestimated or underestimated. Here we analyzed the full MRI dataset from the first phase of Alzheimer’s Disease Neuroimaging Initiative (ADNI-1) from the first phase of Alzheimer’s Disease Neuroimaging Initiative (ADNI-1) and assessed several sources of bias that can arise when tracking brain changes with structural brain imaging methods, as part of a pipeline for tensor-based morphometry (TBM). In all healthy subjects who completed MRI scanning at screening, 6, 12, and 24 months, brain atrophy was essentially linear with no detectable bias in longitudinal measures. In power analyses for clinical trials based on these change measures, only 39 AD patients and 95 mild cognitive impairment (MCI) subjects were needed for a 24-month trial to detect a 25% reduction in the average rate of change using a two-sided test (α=0.05, power=80%). Further sample size reductions were achieved by stratifying the data into Apolipoprotein E (ApoE) ε4 carriers versus non-carriers. We show how selective data exclusion affects sample size estimates, motivating an objective comparison of different analysis techniques based on statistical power and robustness. TBM is an unbiased, robust, high-throughput imaging surrogate marker for large, multi-site neuroimaging studies and clinical trials of AD and MCI.
Alzheimer’s disease; Mild cognitive impairment; Aging; ADNI; Tensor-based morphometry; Drug trial
Most subjects with logopenic primary progressive aphasia (lvPPA) have beta-amyloid (Aβ) deposition on Pittsburgh Compound B PET (PiB-PET), usually affecting prefrontal and temporoparietal cortices, with less occipital involvement.
To assess clinical and imaging features in lvPPA subjects with unusual topographic patterns of Aβ deposition with highest uptake in occipital lobe.
Thirty-three lvPPA subjects with Aβ deposition on PiB-PET were included in this case-control study. Line-plots of regional PiB uptake were created, including frontal, temporal, parietal and occipital regions, for each subject. Subjects in which the line sloped downwards in occipital lobe (lvPPA-low), representing low uptake, were separated from those where the line sloped upwards in occipital lobe (lvPPA-high), representing unusually high occipital uptake compared to other regions. Clinical variables, atrophy on MRI, hypometabolism on F18-fluorodeoxyglucose PET, and presence and distribution of microbleeds and white matter hyperintensities (WMH) were assessed.
Seventeen subjects (52%) were classified as lvPPA-high. Mean occipital PiB uptake in lvPPA-high was higher than all other regions, and higher than all regions in lvPPA-low. The lvPPA-high subjects performed more poorly on cognitive testing, including executive and visuospatial testing, but the two groups did not differ in aphasia severity. Proportion of microbleeds and WMH was higher in lvPPA-high than lvPPA-low. Parietal hypometabolism was greater in lvPPA-high than lvPPA-low.
Unusually high occipital Aβ deposition is associated with widespread cognitive impairment and different imaging findings in lvPPA. These findings help explain clinical heterogeneity in lvPPA, and suggest that Aβ influences severity of overall cognitive impairment but not aphasia.
We aimed to assess associations between clinical, imaging, pathological and genetic features and frontal lobe asymmetry in behavioral variant frontotemporal dementia (bvFTD). Volumes of the left and right dorsolateral, medial and orbital frontal lobes were measured in 80 bvFTD subjects and subjects were classified into three groups according to the degree of asymmetry (asymmetric left, asymmetric right, symmetric) using cluster analysis. The majority of subjects were symmetric (65%), with 20% asymmetric left and 15% asymmetric right. There were no clinical differences across groups, although there was a trend for greater behavioral dyscontrol in right asymmetric compared to left asymmetric subjects. More widespread atrophy involving the parietal lobe was observed in the symmetric group. Genetic features differed across groups with symmetric frontal lobes associated with C9ORF72 and tau mutations, while asymmetric frontal lobes were associated with progranulin mutations. These findings therefore suggest that neuroanatomical patterns of frontal lobe atrophy in bvFTD are influenced by specific gene mutations.
Frontotemporal dementia; frontal lobes; MRI; asymmetry; microtubule associated protein tau; progranulin; C9ORF72; pathology
Four subtypes of frontotemporal lobar degeneration with TDP-43 immunoreactive inclusions have been described (types A–D). Of these four subtypes, motor neuron disease is more commonly associated with type B pathology, but has also been reported with type A pathology. We have noted, however, the unusual occurrence of cases of type C pathology having corticospinal tract degeneration. We aimed to assess the severity of corticospinal tract degeneration in a large cohort of cases with type C (n = 31). Pathological analysis included semi-quantitation of myelin loss of fibres of the corticospinal tract and associated macrophage burden, as well as axonal loss, at the level of the medullary pyramids. We also assessed for motor cortex degeneration and fibre loss of the medial lemniscus/olivocerebellar tract. All cases were subdivided into three groups based on the degree of corticospinal tract degeneration: (i) no corticospinal tract degeneration; (ii) equivocal corticospinal tract degeneration; and (iii) moderate to very severe corticospinal tract degeneration. Clinical, genetic, pathological and imaging comparisons were performed across groups. Eight cases had no corticospinal tract degeneration, and 14 cases had equivocal to mild corticospinal tract degeneration. Nine cases, however, had moderate to very severe corticospinal tract degeneration with myelin and axonal loss. In these nine cases, there was degeneration of the motor cortex without lower motor neuron degeneration or involvement of other brainstem tracts. These cases most commonly presented as semantic dementia, and they had longer disease duration (mean: 15.3 years) compared with the other two groups (10.8 and 9.9 years; P = 0.03). After adjusting for disease duration, severity of corticospinal tract degeneration remained significantly different across groups. Only one case, without corticospinal tract degeneration, was found to have a hexanucleotide repeat expansion in the C9ORF72 gene. All three groups were associated with anterior temporal lobe atrophy on MRI; however, the cases with moderate to severe corticospinal tract degeneration showed right-sided temporal lobe asymmetry and greater involvement of the right temporal lobe and superior motor cortices than the other groups. In contrast, the cases with no or equivocal corticospinal tract degeneration were more likely to show left-sided temporal lobe asymmetry. For comparison, the corticospinal tract was assessed in 86 type A and B cases, and only two cases showed evidence of corticospinal tract degeneration without lower motor neuron degeneration. These findings confirm that there exists a unique association between frontotemporal lobar degeneration with type C pathology and corticospinal tract degeneration, with this entity showing a predilection to involve the right temporal lobe.
TDP-43 type C; corticospinal tract; MRI; semantic dementia; right temporal lobe
The appearance of β-amyloidosis and brain injury biomarkers in cognitively normal (CN) persons is thought to define risk for the future development of cognitive impairment due to Alzheimer’s disease (AD), but their interaction is poorly understood.
To test the hypothesis that the joint presence of β-amyloidosis and brain injury biomarkers would lead to more rapid neurodegeneration.
Longitudinal Cohort Study
Population-based Mayo Clinic Study of Aging.
191 CN persons (median age 77, range 71–93) in the Mayo Clinic Study of Aging who underwent MR, FDG PET and PiB PET imaging at least twice 15 months apart. Subjects were grouped according to the recommendations of the NIA-AA Preclinical AD criteria, based on the presence of β-amyloidosis, defined as a PiB PET SUVr >1.5, alone (Stage 1) or with brain injury (stage 2+3), defined as hippocampal atrophy or FDG hypometabolism. We also studied a group of MCI (n=17) and dementia (n=9) patients from the Mayo Clinic Study of Aging or the Mayo Alzheimer Center with similar follow-up times who had had comparable imaging and who all had PiB PET SUVr >1.5.
Main Outcome Measures
Rate of change of cortical volume on volumetric MR scans and rate of change of glucose metabolism on FDG PET scans.
There were 25 CN subjects with both high PiB retention and low hippocampal volume or FDG hypometabolism at baseline (Preclinical AD stages 2+3). On follow-up scans, the Preclinical AD stages 2+3 subjects had greater loss of medial temporal lobe volume and greater glucose hypometabolism in the medial temporal lobe compared to other CN groups. The changes were similar to the cognitively impaired participants. Extra-temporal regions did not show similar changes.
Higher rates of medial temporal neurodegeneration occurred in CN individuals who, on their initial scans, had abnormal levels of both β-amyloid and brain injury biomarkers.
Alzheimer’s disease; PET imaging; MR imaging; Epidemiology