•How proteinopathies damage brain networks is a key issue in neurodegenerative disease.•Here, we outline a solution based on the concept of ‘molecular nexopathies’.•The concept is founded on specific interactions of network and protein properties.•This new paradigm has far-reaching biological and clinical implications.
Neural networks provide candidate substrates for the spread of proteinopathies causing neurodegeneration, and emerging data suggest that macroscopic signatures of network disintegration differentiate diseases. However, how do protein abnormalities produce network signatures? The answer may lie with ‘molecular nexopathies’: specific, coherent conjunctions of pathogenic protein and intrinsic network characteristics that define network signatures of neurodegenerative pathologies. Key features of the paradigm that we propose here include differential intrinsic network vulnerability to propagating protein abnormalities, in part reflecting developmental structural and functional factors; differential vulnerability of neural connection types (e.g., clustered versus distributed connections) to particular pathogenic proteins; and differential impact of molecular effects (e.g., toxic-gain-of-function versus loss-of-function) on gradients of network damage. The paradigm has implications for understanding and predicting neurodegenerative disease biology.
neurodegeneration; dementia; neural network; nexopathy
We report a family with a novel CSF1R mutation causing hereditary diffuse leucoencephalopathy with axonal spheroids. Family members presented with neuropsychiatric and behavioural symptoms, with subsequent development of motor symptoms and gait disturbance. MRI brain showed extensive white matter change with a frontal predominance and associated atrophy in two members of the family. Genetic testing revealed a novel mutation c.2342C > T (p.A781V) in the CSF1R gene in two brothers of the family. This report highlights the difficulties in diagnosing HDLS and discusses the indications for testing for mutations in the CSF1R gene.
CSF1R; HDLS; Leucoencephalopathy; Dementia; Frontal dementia; Behavioural change
Posterior cortical atrophy (PCA) is a neurodegenerative syndrome that is characterized by a progressive decline in visuospatial, visuoperceptual, literacy and praxic skills. The progressive neurodegeneration affecting parietal, occipital and occipito-temporal cortices which underlies PCA is attributable to Alzheimer's disease (AD) in the majority of patients. However, alternative underlying aetiologies including Dementia with Lewy Bodies (DLB), corticobasal degeneration (CBD) and prion disease have also been identified, and not all PCA patients have atrophy on clinical imaging. This heterogeneity has led to diagnostic and terminological inconsistencies, caused difficulty comparing studies from different centres, and limited the generalizability of clinical trials and investigations of factors driving phenotypic variability. Significant challenges remain in identifying the factors associated with both the selective vulnerability of posterior cortical regions and the young age of onset seen in PCA. Greater awareness of the syndrome and agreement over the correspondence between syndrome-and disease-level classifications are required in order to improve diagnostic accuracy, research study design and clinical management.
Huntington’s disease (HD) is an autosomal dominant, fully penetrant, neurodegenerative disease that most commonly affects adults in mid-life. Our aim was to identify sensitive and reliable biomarkers in premanifest carriers of mutated HTT and in individuals with early HD that could provide essential methodology for the assessment of therapeutic interventions.
This multicentre study uses an extensive battery of novel assessments, including multi-site 3T MRI, clinical, cognitive, quantitative motor, oculomotor, and neuropsychiatric measures. Blinded analyses were done on the baseline cross-sectional data from 366 individuals: 123 controls, 120 premanifest (pre-HD) individuals, and 123 patients with early HD.
The first participant was enrolled in January, 2008, and all assessments were completed by August, 2008. Cross-sectional analyses identified significant changes in whole-brain volume, regional grey and white matter differences, impairment in a range of voluntary neurophysiological motor, and oculomotor tasks, and cognitive and neuropsychiatric dysfunction in premanifest HD gene carriers with normal motor scores through to early clinical stage 2 disease.
We show the feasibility of rapid data acquisition and the use of multi-site 3T MRI and neurophysiological motor measures in a large multicentre study. Our results provide evidence for quantifiable biological and clinical alterations in HTT expansion carriers compared with age-matched controls. Many parameters differ from age-matched controls in a graded fashion and show changes of increasing magnitude across our cohort, who range from about 16 years from predicted disease diagnosis to early HD. These findings might help to define novel quantifiable endpoints and methods for rapid and reliable data acquisition, which could aid the design of therapeutic trials.
CHDI/High Q Foundation.
The primary progressive aphasias (PPA) are a heterogeneous group of language-led neurodegenerative diseases resulting from large-scale brain network degeneration. White matter (WM) pathways bind networks together, and might therefore hold information about PPA pathogenesis. Here we used diffusion tensor imaging and tract-based spatial statistics to compare WM tract changes between PPA syndromes and with respect to Alzheimer's disease and healthy controls in 33 patients with PPA (13 nonfluent/agrammatic PPA); 10 logopenic variant PPA; and 10 semantic variant PPA. Nonfluent/agrammatic PPA was associated with predominantly left-sided and anterior tract alterations including uncinate fasciculus (UF) and subcortical projections; semantic variant PPA with bilateral alterations in inferior longitudinal fasciculus and UF; and logopenic variant PPA with bilateral but predominantly left-sided alterations in inferior longitudinal fasciculus, UF, superior longitudinal fasciculus, and subcortical projections. Tract alterations were more extensive than gray matter alterations, and the extent of alteration across tracts and PPA syndromes varied between diffusivity metrics. These WM signatures of PPA syndromes illustrate the selective vulnerability of brain language networks in these diseases and might have some pathologic specificity.
Primary progressive aphasia; DTI; Networks; White matter
Amyloid imaging studies of presymptomatic familial Alzheimer’s disease have revealed the striatum and thalamus to be the earliest sites of amyloid deposition. This study aimed to investigate whether there are associated volume and diffusivity changes in these subcortical structures during the presymptomatic and symptomatic stages of familial Alzheimer’s disease. As the thalamus and striatum are involved in neural networks subserving complex cognitive and behavioural functions, we also examined the diffusion characteristics in connecting white matter tracts. A cohort of 20 presenilin 1 mutation carriers underwent volumetric and diffusion tensor magnetic resonance imaging, neuropsychological and clinical assessments; 10 were symptomatic, 10 were presymptomatic and on average 5.6 years younger than their expected age at onset; 20 healthy control subjects were also studied. We conducted region of interest analyses of volume and diffusivity changes in the thalamus, caudate, putamen and hippocampus and examined diffusion behaviour in the white matter tracts of interest (fornix, cingulum and corpus callosum). Voxel-based morphometry and tract-based spatial statistics were also used to provide unbiased whole-brain analyses of group differences in volume and diffusion indices, respectively. We found that reduced volumes of the left thalamus and bilateral caudate were evident at a presymptomatic stage, together with increased fractional anisotropy of bilateral thalamus and left caudate. Although no significant hippocampal volume loss was evident presymptomatically, reduced mean diffusivity was observed in the right hippocampus and reduced mean and axial diffusivity in the right cingulum. In contrast, symptomatic mutation carriers showed increased mean, axial and in particular radial diffusivity, with reduced fractional anisotropy, in all of the white matter tracts of interest. The symptomatic group also showed atrophy and increased mean diffusivity in all of the subcortical grey matter regions of interest, with increased fractional anisotropy in bilateral putamen. We propose that axonal injury may be an early event in presymptomatic Alzheimer’s disease, causing an initial fall in axial and mean diffusivity, which then increases with loss of axonal density. The selective degeneration of long-coursing white matter tracts, with relative preservation of short interneurons, may account for the increase in fractional anisotropy that is seen in the thalamus and caudate presymptomatically. It may be owing to their dense connectivity that imaging changes are seen first in the thalamus and striatum, which then progress to involve other regions in a vulnerable neuronal network.
familial Alzheimer’s disease; presenilin 1 (PSEN1, PS1); presymptomatic; diffusion tensor imaging; subcortical atrophy
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.
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.
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.
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.)
Whole brain extraction is an important pre-processing step in neuro-image analysis. Manual or semi-automated brain delineations are labour-intensive and thus not desirable in large studies, meaning that automated techniques are preferable. The accuracy and robustness of automated methods are crucial because human expertise may be required to correct any sub-optimal results, which can be very time consuming. We compared the accuracy of four automated brain extraction methods: Brain Extraction Tool (BET), Brain Surface Extractor (BSE), Hybrid Watershed Algorithm (HWA) and a Multi-Atlas Propagation and Segmentation (MAPS) technique we have previously developed for hippocampal segmentation. The four methods were applied to extract whole brains from 682 1.5T and 157 3T T1-weighted MR baseline images from the Alzheimer’s Disease Neuroimaging Initiative database. Semi-automated brain segmentations with manual editing and checking were used as the gold-standard to compare with the results. The median Jaccard index of MAPS was higher than HWA, BET and BSE in 1.5T and 3T scans (p < 0.05, all tests), and the 1st-99th centile range of the Jaccard index of MAPS was smaller than HWA, BET and BSE in 1.5T and 3T scans (p < 0.05, all tests). HWA and MAPS were found to be best at including all brain tissues (median false negative rate ≤ 0.010% for 1.5T scans and ≤ 0.019% for 3T scans, both methods). The median Jaccard index of MAPS were similar in both 1.5T and 3T scans, whereas those of BET, BSE and HWA were higher in 1.5T scans than 3T scans (p < 0.05, all tests). We found that the diagnostic group had a small effect on the median Jaccard index of all four methods. In conclusion, MAPS had relatively high accuracy and low variability compared to HWA, BET and BSE in MR scans with and without atrophy.
Automated brain extraction; skull-stripping; segmentation; MAPS; BET; BSE; HWA
Thickness measurements of the cerebral cortex can aid diagnosis and provide valuable information about the temporal evolution of diseases such as Alzheimer's, Huntington's, and schizophrenia. Methods that measure the thickness of the cerebral cortex from in-vivo magnetic resonance (MR) images rely on an accurate segmentation of the MR data. However, segmenting the cortex in a robust and accurate way still poses a challenge due to the presence of noise, intensity non-uniformity, partial volume effects, the limited resolution of MRI and the highly convoluted shape of the cortical folds. Beginning with a well-established probabilistic segmentation model with anatomical tissue priors, we propose three post-processing refinements: a novel modification of the prior information to reduce segmentation bias; introduction of explicit partial volume classes; and a locally varying MRF-based model for enhancement of sulci and gyri. Experiments performed on a new digital phantom, on BrainWeb data and on data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) show statistically significant improvements in Dice scores and PV estimation (p<10−3) and also increased thickness estimation accuracy when compared to three well established techniques.
Gaussian mixture model; Expectation-maximization; Markov Random Field; Cortical segmentation; Partial volume effect
Neuronal intermediate filament inclusion disease and atypical frontotemporal lobar degeneration are rare diseases characterized by ubiquitin-positive inclusions lacking transactive response DNA-binding protein-43 and tau. Recently, mutations in the fused in sarcoma gene have been shown to cause familial amyotrophic lateral sclerosis and fused in sarcoma-positive neuronal inclusions have subsequently been demonstrated in neuronal intermediate filament inclusion disease and atypical frontotemporal lobar degeneration with ubiquitinated inclusions. Here we provide clinical, imaging, morphological findings, as well as genetic and biochemical data in 14 fused in sarcoma proteinopathy cases. In this cohort, the age of onset was variable but included cases of young-onset disease. Patients with atypical frontotemporal lobar degeneration with ubiquitinated inclusions all presented with behavioural variant frontotemporal dementia, while the clinical presentation in neuronal intermediate filament inclusion disease was more heterogeneous, including cases with motor neuron disease and extrapyramidal syndromes. Neuroimaging revealed atrophy of the frontal and anterior temporal lobes as well as the caudate in the cases with atypical frontotemporal lobar degeneration with ubiquitinated inclusions, but was more heterogeneous in the cases with neuronal intermediate filament inclusion disease, often being normal to visual inspection early on in the disease. The distribution and severity of fused in sarcoma-positive neuronal cytoplasmic inclusions, neuronal intranuclear inclusions and neurites were recorded and fused in sarcoma was biochemically analysed in both subgroups. Fused in sarcoma-positive neuronal cytoplasmic and intranuclear inclusions were found in the hippocampal granule cell layer in variable numbers. Cortical fused in sarcoma-positive neuronal cytoplasmic inclusions were often ‘Pick body-like’ in neuronal intermediate filament inclusion disease, and annular and crescent-shaped inclusions were seen in both conditions. Motor neurons contained variable numbers of compact, granular or skein-like cytoplasmic inclusions in all fused in sarcoma-positive cases in which brainstem and spinal cord motor neurons were available for study (five and four cases, respectively). No fused in sarcoma mutations were found in any cases. Biochemically, two major fused in sarcoma species were found and shown to be more insoluble in the atypical frontotemporal lobar degeneration with ubiquitinated inclusions subgroup compared with neuronal intermediate filament inclusion disease. There is considerable overlap and also significant differences in fused in sarcoma-positive pathology between the two subgroups, suggesting they may represent a spectrum of the same disease. The co-existence of fused in sarcoma-positive inclusions in both motor neurons and extramotor cerebral structures is a characteristic finding in sporadic fused in sarcoma proteinopathies, indicating a multisystem disorder.
frontotemporal lobar degeneration; FUS; clinical presentation; neuropathology; biochemistry
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
Global gray matter (GM) atrophy rates were quantified from magnetic resonance imaging (MRI) over 6- and 12-month intervals in 37 patients with Alzheimer's disease (AD) and 19 controls using: (1) nonlinear registration and integration of Jacobian values, and (2) segmentation and subtraction of serial GM volumes. Sample sizes required to power treatment trials using global GM atrophy rate as an outcome measure were estimated and compared between the 2 techniques, and to global brain atrophy measures quantified using the boundary shift integral (brain boundary shift integral; BBSI) and structural image evaluation, using normalization, of atrophy (SIENA). Increased GM atrophy rates (approximately 2% per year) were observed in patients compared with controls. Although mean atrophy rates provided by Jacobian integration were smaller than those from segmentation and subtraction of GM volumes, measurement variance was reduced. The number of patients required per treatment arm to detect a 20% reduction in GM atrophy rate over a 12-month follow-up (90% power) was 202 (95% confidence interval [CI], 118–423) using Jacobian integration and 2047 (95% CI 271 to > 10 000) using segmentation and subtraction. Comparable sample sizes for whole brain atrophy were 240 (95% CI, 142–469) using the BBSI and 196 (95% CI, 110–425) using SIENA. Jacobian integration could be useful for measuring GM atrophy rate in Alzheimer's disease as a marker of disease progression and treatment efficacy.
Gray matter; Atrophy rate; Alzheimer's disease; Sample sizes; MRI
Imaging has played a variety of roles in the study of Alzheimer disease (AD) over the past four decades. Initially, computed tomography (CT) and then magnetic resonance imaging (MRI) were used diagnostically to rule out other causes of dementia. More recently, a variety of imaging modalities including structural and functional MRI and positron emission tomography (PET) studies of cerebral metabolism with fluoro-deoxy-d-glucose (FDG) and amyloid tracers such as Pittsburgh Compound-B (PiB) have shown characteristic changes in the brains of patients with AD, and in prodromal and even presymptomatic states that can help rule-in the AD pathophysiological process. No one imaging modality can serve all purposes as each have unique strengths and weaknesses. These modalities and their particular utilities are discussed in this article. The challenge for the future will be to combine imaging biomarkers to most efficiently facilitate diagnosis, disease staging, and, most importantly, development of effective disease-modifying therapies.
Various neuroimaging modalities (e.g., MRI and PET) have shown characteristic changes in the brains of patients with Alzheimer disease. Identifying imaging biomarkers will facilitate diagnosis, disease staging, and drug development.
The National Institute on Aging and the Alzheimer’s Association charged a workgroup with the task of developing criteria for the symptomatic predementia phase of Alzheimer’s disease (AD), referred to in this article as mild cognitive impairment due to AD. The workgroup developed the following two sets of criteria: (1) core clinical criteria that could be used by healthcare providers without access to advanced imaging techniques or cerebrospinal fluid analysis, and (2) research criteria that could be used in clinical research settings, including clinical trials. The second set of criteria incorporate the use of biomarkers based on imaging and cerebrospinal fluid measures. The final set of criteria for mild cognitive impairment due to AD has four levels of certainty, depending on the presence and nature of the biomarker findings. Considerable work is needed to validate the criteria that use biomarkers and to standardize biomarker analysis for use in community settings.
Mild cognitive impairment; AD dementia; Diagnosis
Medial temporal lobe atrophy (MTA) is a recognized marker of Alzheimer's disease (AD), however, it can be prominent in frontotemporal lobar degeneration (FTLD). There is an increasing awareness that posterior atrophy (PA) is important in AD and may aid the differentiation of AD from FTLD. Visual rating scales are a convenient way of assessing atrophy in a clinical setting. In this study, 2 visual rating scales measuring MTA and PA were used to compare atrophy patterns in 62 pathologically-confirmed AD and 40 FTLD patients. Anatomical correspondence of MTA and PA was assessed using manually-delineated regions of the hippocampus and posterior cingulate gyrus, respectively. Both MTA and PA scales showed good inter- and intrarater reliabilities (kappa > 0.8). MTA scores showed a good correspondence with manual hippocampal volumes. Thirty percent of the AD patients showed PA in the absence of MTA. Adding the PA to the MTA scale improved discrimination of AD from FTLD, and early-onset AD from normal aging. These results underline the importance of considering PA in AD diagnosis, particularly in younger patients where medial temporal atrophy may be less conspicuous.
Visual rating scales; Posterior atrophy; Medial temporal lobe atrophy; MRI; Dementia; Pathology; Manual volumes
An expanded hexanucleotide repeat in the C9ORF72 gene has recently been identified as a major cause of familial frontotemporal lobar degeneration and motor neuron disease, including cases previously identified as linked to chromosome 9. Here we present a detailed retrospective clinical, neuroimaging and histopathological analysis of a C9ORF72 mutation case series in relation to other forms of genetically determined frontotemporal lobar degeneration ascertained at a specialist centre. Eighteen probands (19 cases in total) were identified, representing 35% of frontotemporal lobar degeneration cases with identified mutations, 36% of cases with clinical evidence of motor neuron disease and 7% of the entire cohort. Thirty-three per cent of these C9ORF72 cases had no identified relevant family history. Families showed wide variation in clinical onset (43–68 years) and duration (1.7–22 years). The most common presenting syndrome (comprising a half of cases) was behavioural variant frontotemporal dementia, however, there was substantial clinical heterogeneity across the C9ORF72 mutation cohort. Sixty per cent of cases developed clinical features consistent with motor neuron disease during the period of follow-up. Anxiety and agitation and memory impairment were prominent features (between a half to two-thirds of cases), and dominant parietal dysfunction was also frequent. Affected individuals showed variable magnetic resonance imaging findings; however, relative to healthy controls, the group as a whole showed extensive thinning of frontal, temporal and parietal cortices, subcortical grey matter atrophy including thalamus and cerebellum and involvement of long intrahemispheric, commissural and corticospinal tracts. The neuroimaging profile of the C9ORF72 expansion was significantly more symmetrical than progranulin mutations with significantly less temporal lobe involvement than microtubule-associated protein tau mutations. Neuropathological examination in six cases with C9ORF72 mutation from the frontotemporal lobar degeneration series identified histomorphological features consistent with either type A or B TAR DNA-binding protein-43 deposition; however, p62-positive (in excess of TAR DNA-binding protein-43 positive) neuronal cytoplasmic inclusions in hippocampus and cerebellum were a consistent feature of these cases, in contrast to the similar frequency of p62 and TAR DNA-binding protein-43 deposition in 53 control cases with frontotemporal lobar degeneration–TAR DNA-binding protein. These findings corroborate the clinical importance of the C9ORF72 mutation in frontotemporal lobar degeneration, delineate phenotypic and neuropathological features that could help to guide genetic testing, and suggest hypotheses for elucidating the neurobiology of a culprit subcortical network.
frontotemporal lobar degeneration; motor neuron disease; neurodegenerative disorders; neuroimaging; genetics
Short echo time localized proton magnetic resonance spectroscopy provides quantification of brain metabolites, including N-acetyl-aspartate, myo-inositol, creatine/phosphocreatine and choline-containing compounds, which may be useful biomarkers for monitoring Alzheimer's disease. We aimed to quantify the rate of metabolite change in Alzheimer's disease, to assess factors influencing changes and to investigate the potential for serial magnetic resonance spectroscopy as an Alzheimer's disease trial biomarker. A total of 42 patients and 22 controls each had up to six magnetic resonance spectroscopy examinations over a 2-year period, using a midline posterior cingulate single-voxel point resolved spectroscopy sequence (1.5 T; time to repetition = 2000 ms; echo time = 30 ms; 192 averages). Metabolite ratios N-acetyl-aspartate:creatine/phosphocreatine, choline-containing compounds:creatine/phosphocreatine, and myo-inositol:creatine/phosphocreatine were measured using online software (PROBE-Q) and the N-acetyl-aspartate:myo-inositol ratio was derived. Baseline ratios were compared between patients and controls. A linear mixed model was used to quantify longitudinal changes and extended to assess the effect of age, disease severity and baseline use of acetylcholinesterase inhibitors. Patients and controls were matched for age (patients: 68.9 ± 7.2 years; controls: 69.1 ± 6.7 years); 71% of the patients were on acetylcholinesterase inhibitors at baseline; mean Mini-Mental State Examination for patients was 19.4 ± 4.1. A total of 307 spectra were acquired. In cross-sectional analyses, patients were significantly different from controls for N-acetyl-aspartate:creatine/phosphocreatine (11% lower, P < 0.001), N-acetyl-aspartate:myo-inositol (24% lower, P < 0.001), and myo-inositol:creatine/phosphocreatine (17% higher, P < 0.001). After adjustment for N-acetyl-aspartate:myo-inositol, none of the other variables differed significantly. In patients there was significant decline in N-acetyl-aspartate:creatine/phosphocreatine (mean: 2.2%/year; 95% confidence interval: 0.9–3.5) and N-acetyl-aspartate:myo-inositol (mean: 3.7%/year; 95% confidence interval: 1.7–5.7), with no evidence for influence by age, disease severity or acetylcholinesterase inhibitor use. There was significant excess decline in patients compared with controls only in N-acetyl-aspartate:myo-inositol (mean: 3.6%/year; 95% confidence interval: 0.8–6.4; P = 0.014). Between-subject standard deviation for N-acetyl-aspartate:myo-inositol was 0% for controls and 3.5%/year for patients; within-subject standard deviation for a 1 year, two-time-point study was 9.2%/year for both patients and controls. These results confirm that magnetic resonance spectroscopy can be used to quantify excess metabolite decline in Alzheimer's disease, which may provide a useful measure of disease progression. We found no evidence that age, disease severity or acetylcholinesterase inhibitor use influenced rate of decline, although numbers were small. The substantial variability in longitudinal measurements that drives sample size requirements is principally within-subject and technique related: technical developments to reduce this variability may make serial magnetic resonance spectroscopy a viable biomarker in clinical trials for Alzheimer's disease.
Alzheimer's disease; magnetic resonance spectroscopy; clinical trial design
Relating clinical symptoms to neuroanatomical profiles of brain damage and ultimately to tissue pathology is a key challenge in the field of neurodegenerative disease and particularly relevant to the heterogeneous disorders that comprise the frontotemporal lobar degeneration spectrum. Here we present a retrospective analysis of clinical, neuropsychological and neuroimaging (volumetric and voxel-based morphometric) features in a pathologically ascertained cohort of 95 cases of frontotemporal lobar degeneration classified according to contemporary neuropathological criteria. Forty-eight cases (51%) had TDP-43 pathology, 42 (44%) had tau pathology and five (5%) had fused-in-sarcoma pathology. Certain relatively specific clinicopathological associations were identified. Semantic dementia was predominantly associated with TDP-43 type C pathology; frontotemporal dementia and motoneuron disease with TDP-43 type B pathology; young-onset behavioural variant frontotemporal dementia with FUS pathology; and the progressive supranuclear palsy syndrome with progressive supranuclear palsy pathology. Progressive non-fluent aphasia was most commonly associated with tau pathology. However, the most common clinical syndrome (behavioural variant frontotemporal dementia) was pathologically heterogeneous; while pathologically proven Pick's disease and corticobasal degeneration were clinically heterogeneous, and TDP-43 type A pathology was associated with similar clinical features in cases with and without progranulin mutations. Volumetric magnetic resonance imaging, voxel-based morphometry and cluster analyses of the pathological groups here suggested a neuroanatomical framework underpinning this clinical and pathological diversity. Frontotemporal lobar degeneration-associated pathologies segregated based on their cerebral atrophy profiles, according to the following scheme: asymmetric, relatively localized (predominantly temporal lobe) atrophy (TDP-43 type C); relatively symmetric, relatively localized (predominantly temporal lobe) atrophy (microtubule-associated protein tau mutations); strongly asymmetric, distributed atrophy (Pick's disease); relatively symmetric, predominantly extratemporal atrophy (corticobasal degeneration, fused-in-sarcoma pathology). TDP-43 type A pathology was associated with substantial individual variation; however, within this group progranulin mutations were associated with strongly asymmetric, distributed hemispheric atrophy. We interpret the findings in terms of emerging network models of neurodegenerative disease: the neuroanatomical specificity of particular frontotemporal lobar degeneration pathologies may depend on an interaction of disease-specific and network-specific factors.
frontotemporal dementia; frontotemporal lobar degeneration; voxel-based morphometry; MRI; neural network
Volume and change in volume of the hippocampus are both important markers of Alzheimer's disease (AD). Delineation of the structure on MRI is time-consuming and therefore reliable automated methods are required. We describe an improvement (multiple-atlas propagation and segmentation (MAPS)) to our template library-based segmentation technique. The improved technique uses non-linear registration of the best-matched templates from our manually-segmented library to generate multiple segmentations and combines them using the simultaneous truth and performance level estimation (STAPLE) algorithm. Change in volume over 12 months (MAPS-HBSI) was measured by applying the boundary shift integral using MAPS regions. Methods were developed and validated against manual measures using subsets from Alzheimer's Disease Neuroimaging Initiative (ADNI). The best method was applied to 682 ADNI subjects, at baseline and 12-month follow-up, enabling assessment of volumes and atrophy rates in control, mild cognitive impairment (MCI) and AD groups, and within MCI subgroups classified by subsequent clinical outcome. We compared our measures with those generated by SNT (Surgical Navigation Technologies) available from ADNI. The accuracy of our volumes was one of the highest reported (mean(SD) Jaccard Index 0.80(0.04) (N=30)). Both MAPS baseline volume and MAPS-HBSI atrophy rate distinguished between control, MCI and AD groups. Comparing MCI subgroups (reverters, stable and converters): volumes were lower and rates higher in converters compared with stable and reverter groups (p≤0.03). MAPS-HBSI required the lowest sample sizes (68 subjects) for a hypothetical trial. In conclusion, the MAPS and MAPS-HBSI methods give accurate and reliable volumes and atrophy rates across the clinical spectrum from healthy aging to AD.
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.
Functions of the ADNI MRI core fall into three categories: (1) those of the central MRI core lab at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data, and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present (“ADNI-GO”) and future (“ADNI-2”, if funded) MRI protocol will be to maintain MRI methodological consistency in previously enrolled “ADNI-1” subjects who are followed longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor specific pilot sub-studies of arterial spin labeling perfusion, resting state functional connectivity and diffusion tensor imaging. One each of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multi-center (but single vendor) setting for these three emerging MRI applications.
Tinnitus and hyperacusis are common symptoms of excessive auditory perception in the general population; however, their anatomical substrates and disease associations continue to be defined. Patients with semantic dementia (SemD) frequently report tinnitus and hyperacusis but the significance and basis for these symptoms have not been elucidated.
43 patients with a diagnosis of SemD attending a specialist cognitive disorders clinic were retrospectively studied. 14 patients (32% of the cohort) reported at least moderately severe chronic auditory symptoms: seven had tinnitus and a further seven had hyperacusis, and all had brain MRI while symptomatic. MRI data from SemD patients with and without auditory symptoms were compared using voxel based morphometry in order to identify neuroanatomical associations of tinnitus and hyperacusis.
Compared with SemD patients with no history of auditory symptoms, patients with tinnitus or hyperacusis had relative preservation of grey matter in the posterior superior temporal lobe and reduced grey matter in the orbitofrontal cortex and medial geniculate nucleus.
Tinnitus and hyperacusis may be a significant issue in SemD. Neuroanatomical evidence in SemD supports previous work implicating a distributed cortico-subcortical auditory and limbic network in the pathogenesis of these abnormal auditory percepts.
We describe an improved method of measuring brain atrophy rates from serial MRI for multi-site imaging studies of Alzheimer’s disease (AD). The method (referred to as KN-BSI) improves an existing brain atrophy measurement technique—the boundary shift integral (classic-BSI), by performing tissue-specific intensity normalization and parameter selection. We applied KN-BSI to measure brain atrophy rates of 200 normal and 141 AD subjects using baseline and 1-year MRI scans downloaded from the Alzheimer’s Disease Neuroimaging Initiative database. Baseline and repeat images were reviewed as pairs by expert raters and given quality scores. Including all image pairs, regardless of quality score, mean KN-BSI atrophy rates were 0.09% higher (95% CI 0.03% to 0.16%, p=0.007) than classic-BSI rates in controls and 0.07% higher (−0.01% to 0.16%, p=0.07) higher in ADs. The SD of the KN-BSI rates was 22% lower (15% to 29%, p<0.001) in controls and 13% lower (6% to 20%, p=0.001) in ADs, compared to classic-BSI. Using these results, the estimated sample size (needed per treatment arm) for a hypothetical trial of a treatment for AD (80% power, 5% significance to detect a 25% reduction in atrophy rate) would be reduced from 120 to 81 (a 32% reduction, 95% CI=18% to 45%, p<0.001) when using KN-BSI instead of classic-BSI. We concluded that KN-BSI offers more robust brain atrophy measurement than classic-BSI and substantially reduces sample sizes needed in clinical trials.
Alzheimer’s disease; Atrophy; MRI; Boundary shift integral; Intensity normalization; BSI; KN-BSI
Structural imaging based on magnetic resonance is an integral part of the clinical assessment of patients with suspected Alzheimer dementia. Prospective data on the natural history of change in structural markers from preclinical to overt stages of Alzheimer disease are radically changing how the disease is conceptualized, and will influence its future diagnosis and treatment. Atrophy of medial temporal structures is now considered to be a valid diagnostic marker at the mild cognitive impairment stage. Structural imaging is also included in diagnostic criteria for the most prevalent non-Alzheimer dementias, reflecting its value in differential diagnosis. In addition, rates of whole-brain and hippocampal atrophy are sensitive markers of neurodegeneration, and are increasingly used as outcome measures in trials of potentially disease-modifying therapies. Large multicenter studies are currently investigating the value of other imaging and nonimaging markers as adjuncts to clinical assessment in diagnosis and monitoring of progression. The utility of structural imaging and other markers will be increased by standardization of acquisition and analysis methods, and by development of robust algorithms for automated assessment.
Neural network breakdown is a key issue in neurodegenerative disease, but the mechanisms are poorly understood. Here we investigated patterns of brain atrophy produced by defined molecular lesions in the two common forms of genetically mediated frontotemporal lobar degeneration (FTLD). Nine patients with progranulin (GRN) mutations and eleven patients with microtubule-associated protein tau (MAPT) mutations had T1 MR brain imaging. Brain volumetry and grey and white matter voxel-based morphometry (VBM) were used to assess patterns of cross-sectional atrophy in the two groups. In a subset of patients with longitudinal MRI rates of whole-brain atrophy were derived using the brain-boundary-shift integral and a VBM-like analysis of voxel-wise longitudinal volume change was performed. The GRN mutation group showed asymmetrical atrophy whereas the MAPT group showed symmetrical atrophy. Brain volumes were smaller in the GRN group with a faster rate of whole-brain atrophy. VBM delineated a common anterior cingulate–prefrontal–insular pattern of atrophy in both disease groups. Additional disease-specific profiles of grey and white matter loss were identified on both cross-sectional and longitudinal imaging: GRN mutations were associated with asymmetrical inferior frontal, temporal and inferior parietal lobe grey matter atrophy and involvement of long intrahemispheric association white matter tracts, whereas MAPT mutations were associated with symmetrical anteromedial temporal lobe and orbitofrontal grey matter atrophy and fornix involvement. The findings suggest that the effects of GRN and MAPT mutations are expressed in partly overlapping but distinct anatomical networks that link specific molecular dysfunction with clinical phenotype.
Frontotemporal dementia; Frontotemporal lobar degeneration; Progranulin; Tau