To quantify the regional and global cerebral atrophy rates and assess acceleration rates in healthy controls, subjects with mild cognitive impairment (MCI), and subjects with mild Alzheimer disease (AD).
Using 0-, 6-, 12-, 18-, 24-, and 36-month MRI scans of controls and subjects with MCI and AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we calculated volume change of whole brain, hippocampus, and ventricles between all pairs of scans using the boundary shift integral.
We found no evidence of acceleration in whole-brain atrophy rates in any group. There was evidence that hippocampal atrophy rates in MCI subjects accelerate by 0.22%/year2 on average (p = 0.037). There was evidence of acceleration in rates of ventricular enlargement in subjects with MCI (p = 0.001) and AD (p < 0.001), with rates estimated to increase by 0.27 mL/year2 (95% confidence interval 0.12, 0.43) and 0.88 mL/year2 (95% confidence interval 0.47, 1.29), respectively. A post hoc analysis suggested that the acceleration of hippocampal loss in MCI subjects was mainly driven by the MCI subjects that were observed to progress to clinical AD within 3 years of baseline, with this group showing hippocampal atrophy rate acceleration of 0.50%/year2 (p = 0.003).
The small acceleration rates suggest a long period of transition to the pathologic losses seen in clinical AD. The acceleration in hippocampal atrophy rates in MCI subjects in the ADNI seems to be driven by those MCI subjects who concurrently progressed to a clinical diagnosis of AD.
Structural MRI is widely used for investigating brain atrophy in many neurodegenerative disorders, with several research groups developing and publishing techniques to provide quantitative assessments of this longitudinal change. Often techniques are compared through computation of required sample size estimates for future clinical trials. However interpretation of such comparisons is rendered complex because, despite using the same publicly available cohorts, the various techniques have been assessed with different data exclusions and different statistical analysis models. We created the MIRIAD atrophy challenge in order to test various capabilities of atrophy measurement techniques. The data consisted of 69 subjects (46 Alzheimer's disease, 23 control) who were scanned multiple (up to twelve) times at nine visits over a follow-up period of one to two years, resulting in 708 total image sets. Nine participating groups from 6 countries completed the challenge by providing volumetric measurements of key structures (whole brain, lateral ventricle, left and right hippocampi) for each dataset and atrophy measurements of these structures for each time point pair (both forward and backward) of a given subject. From these results, we formally compared techniques using exactly the same dataset. First, we assessed the repeatability of each technique using rates obtained from short intervals where no measurable atrophy is expected. For those measures that provided direct measures of atrophy between pairs of images, we also assessed symmetry and transitivity. Then, we performed a statistical analysis in a consistent manner using linear mixed effect models. The models, one for repeated measures of volume made at multiple time-points and a second for repeated “direct” measures of change in brain volume, appropriately allowed for the correlation between measures made on the same subject and were shown to fit the data well. From these models, we obtained estimates of the distribution of atrophy rates in the Alzheimer's disease (AD) and control groups and of required sample sizes to detect a 25% treatment effect, in relation to healthy ageing, with 95% significance and 80% power over follow-up periods of 6, 12, and 24 months. Uncertainty in these estimates, and head-to-head comparisons between techniques, were carried out using the bootstrap. The lateral ventricles provided the most stable measurements, followed by the brain. The hippocampi had much more variability across participants, likely because of differences in segmentation protocol and less distinct boundaries. Most methods showed no indication of bias based on the short-term interval results, and direct measures provided good consistency in terms of symmetry and transitivity. The resulting annualized rates of change derived from the model ranged from, for whole brain: − 1.4% to − 2.2% (AD) and − 0.35% to − 0.67% (control), for ventricles: 4.6% to 10.2% (AD) and 1.2% to 3.4% (control), and for hippocampi: − 1.5% to − 7.0% (AD) and − 0.4% to − 1.4% (control). There were large and statistically significant differences in the sample size requirements between many of the techniques. The lowest sample sizes for each of these structures, for a trial with a 12 month follow-up period, were 242 (95% CI: 154 to 422) for whole brain, 168 (95% CI: 112 to 282) for ventricles, 190 (95% CI: 146 to 268) for left hippocampi, and 158 (95% CI: 116 to 228) for right hippocampi. This analysis represents one of the most extensive statistical comparisons of a large number of different atrophy measurement techniques from around the globe. The challenge data will remain online and publicly available so that other groups can assess their methods.
•We compared numerous brain atrophy measurement techniques using multiple metrics.•Each participant produced measures on the exact same dataset, blinded to disease.•A central statistical analysis using linear mixed effect models was performed.•Head to head comparisons for each region were performed using sample size estimates.•Brain and ventricle measures were more consistent across groups than for hippocampi.
Brain atrophy measured using structural magnetic resonance imaging (MRI) has been widely used as an imaging biomarker for disease diagnosis and tracking of pathologic progression in neurodegenerative diseases. In this work, we present a generalized and extended formulation of the boundary shift integral (gBSI) using probabilistic segmentations to estimate anatomic changes between 2 time points. This method adaptively estimates a non-binary exclusive OR region of interest from probabilistic brain segmentations of the baseline and repeat scans to better localize and capture the brain atrophy. We evaluate the proposed method by comparing the sample size requirements for a hypothetical clinical trial of Alzheimer's disease to that needed for the current implementation of BSI as well as a fuzzy implementation of BSI. The gBSI method results in a modest but reduced sample size, providing increased sensitivity to disease changes through the use of the probabilistic exclusive OR region.
boundary shift integral; Alzheimer's disease; Clinical trials; MRI; Biomarker
Frontotemporal lobar degeneration (FTLD) is a neurodegenerative disorder which presents with either behavioural or language impairment. The two language syndromes are known as progressive nonfluent aphasia (PNFA) and semantic dementia (SD). While cross-sectional imaging patterns of brain atrophy are well-described in FTLD fewer studies have investigated longitudinal imaging changes. We measured longitudinal hemispheric and lobar atrophy rates using serial MRI in a cohort of 18 patients with PNFA and 17 patients with SD as well as 14 cognitively-normal control subjects. We subsequently calculated sample size estimates for clinical trials. Rates of left hemisphere atrophy were greater than rates of right hemisphere atrophy in both PNFA and SD with no significant differences between the groups. The disease groups showed asymmetrical atrophy (more severe on the left) at baseline with significantly increasing asymmetry over time. Within a hemisphere, the fastest rate of atrophy varied between lobes: in SD temporal > frontal > parietal > occipital, whilst in PNFA frontal > temporal/parietal > occipital. In SD using temporal lobe measures of atrophy in clinical trials would provide the lowest sample sizes necessary whilst in PNFA left hemisphere atrophy measures provided the lowest sample size. These patterns provide information about disease evolution in the FTLD language variants that is of both clinical and neurobiological relevance.
frontotemporal dementia (29); primary progressive aphasia
Tract-based spatial statistics (TBSS) is a popular method for the analysis of diffusion tensor imaging data. TBSS focuses on differences in white matter voxels with high fractional anisotropy (FA), representing the major fibre tracts, through registering all subjects to a common reference and the creation of a FA skeleton. This work considers the effect of choice of reference in the TBSS pipeline, which can be a standard template, an individual subject from the study, a study-specific template or a group-wise average. While TBSS attempts to overcome registration error by searching the neighbourhood perpendicular to the FA skeleton for the voxel with maximum FA, this projection step may not compensate for large registration errors that might occur in the presence of pathology such as atrophy in neurodegenerative diseases. This makes registration performance and choice of reference an important issue. Substantial work in the field of computational anatomy has shown the use of group-wise averages to reduce biases while avoiding the arbitrary selection of a single individual. Here, we demonstrate the impact of the choice of reference on: (a) specificity (b) sensitivity in a simulation study and (c) a real-world comparison of Alzheimer's disease patients to controls. In (a) and (b), simulated deformations and decreases in FA were applied to control subjects to simulate changes of shape and WM integrity similar to what would be seen in AD patients, in order to provide a “ground truth” for evaluating the various methods of TBSS reference. Using a group-wise average atlas as the reference outperformed other references in the TBSS pipeline in all evaluations.
Frontotemporal dementia (FTD) is a complex disorder characterised by a broad range of clinical manifestations, differential pathological signatures, and genetic variability. Mutations in three genes—MAPT, GRN, and C9orf72—have been associated with FTD. We sought to identify novel genetic risk loci associated with the disorder.
We did a two-stage genome-wide association study on clinical FTD, analysing samples from 3526 patients with FTD and 9402 healthy controls. All participants had European ancestry. In the discovery phase (samples from 2154 patients with FTD and 4308 controls), we did separate association analyses for each FTD subtype (behavioural variant FTD, semantic dementia, progressive non-fluent aphasia, and FTD overlapping with motor neuron disease [FTD-MND]), followed by a meta-analysis of the entire dataset. We carried forward replication of the novel suggestive loci in an independent sample series (samples from 1372 patients and 5094 controls) and then did joint phase and brain expression and methylation quantitative trait loci analyses for the associated (p<5 × 10−8) and suggestive single-nucleotide polymorphisms.
We identified novel associations exceeding the genome-wide significance threshold (p<5 × 10−8) that encompassed the HLA locus at 6p21.3 in the entire cohort. We also identified a potential novel locus at 11q14, encompassing RAB38/CTSC, for the behavioural FTD subtype. Analysis of expression and methylation quantitative trait loci data suggested that these loci might affect expression and methylation incis.
Our findings suggest that immune system processes (link to 6p21.3) and possibly lysosomal and autophagy pathways (link to 11q14) are potentially involved in FTD. Our findings need to be replicated to better define the association of the newly identified loci with disease and possibly to shed light on the pathomechanisms contributing to FTD.
The National Institute of Neurological Disorders and Stroke and National Institute on Aging, the Wellcome/ MRC Centre on Parkinson’s disease, Alzheimer’s Research UK, and Texas Tech University Health Sciences Center.
Alzheimer’s disease (AD) is recognized to have a long presymptomatic period, during which there is progressive accumulation of molecular pathology, followed by inexorable neuronal damage. The ability to identify presymptomatic individuals with evidence of neurodegenerative change, to stage their disease, and to track progressive changes will be important for early diagnosis and for prevention trials. Despite recent advances, particularly in magnetic resonance imaging, our ability to identify early neurodegenerative changes reliably is limited. The development of diffusion-weighted magnetic resonance imaging, which is sensitive to microstructural changes not visible with conventional volumetric techniques, has led to a number of diffusion imaging studies in AD; these have largely focused on white matter changes. However, in AD cerebral grey matter is affected very early, with pathological studies suggesting that grey matter changes predate those in white matter. In this article we review the growing number of studies that assess grey matter diffusivity changes in AD. Although use of the technique is still at a relatively early stage, results so far have been promising. Initial studies identified changes in diffusion measures in the hippocampi of patients with mild cognitive impairment, which predated macroscopic volume loss, with positive predictive value for progression to AD dementia. More recent studies have identified abnormalities in multiple neocortical areas (particularly the posterior cingulate) at various stages of disease progression. Studies of patients who carry genetic mutations predisposing to autosomal dominant familial AD have shown cortical and subcortical grey matter diffusivity changes several years before the expected onset of the first clinical symptoms. The technique is not without potential methodological difficulties, especially relating to partial volume effects, although recent advances appear to be reducing such issues. Going forward, further utilization of grey matter diffusion measurements in AD may improve our understanding with regards to the timing and nature of the earliest presymptomatic neurodegenerative changes. This imaging technique may also be useful in comparing and contrasting subtle variations in different disease subgroups, and as a sensitive outcome measure for presymptomatic clinical trials in AD and other neurodegenerative diseases.
The alternative splicing of the tau gene, MAPT, generates six protein isoforms in the adult human central nervous system (CNS). Tau splicing is developmentally regulated and dysregulated in disease. Mutations in MAPT that alter tau splicing cause frontotemporal dementia (FTD) with tau pathology, providing evidence for a causal link between altered tau splicing and disease. The use of induced pluripotent stem cell (iPSC)-derived neurons has revolutionized the way we model neurological disease in vitro. However, as most tau mutations are located within or around the alternatively spliced exon 10, it is important that iPSC–neurons splice tau appropriately in order to be used as disease models. To address this issue, we analyzed the expression and splicing of tau in iPSC-derived cortical neurons from control patients and FTD patients with the 10 + 16 intronic mutation in MAPT. We show that control neurons only express the fetal tau isoform (0N3R), even at extended time points of 100 days in vitro. Neurons from FTD patients with the 10 + 16 mutation in MAPT express both 0N3R and 0N4R tau isoforms, demonstrating that this mutation overrides the developmental regulation of exon 10 inclusion in our in vitro model. Further, at extended time points of 365 days in vitro, we observe a switch in tau splicing to include six tau isoforms as seen in the adult human CNS. Our results demonstrate the importance of neuronal maturity for use in in vitro modeling and provide a system that will be important for understanding the functional consequences of altered tau splicing.
Impairments of social cognition are often leading features in frontotemporal lobar degeneration (FTLD) and likely to reflect large-scale brain network disintegration. However, the neuroanatomical basis of impaired social cognition in FTLD and the role of white matter connections have not been defined. Here we assessed social cognition in a cohort of patients representing two core syndromes of FTLD, behavioural variant frontotemporal dementia (bvFTD; n = 29) and semantic variant primary progressive aphasia (svPPA; n = 15), relative to healthy older individuals (n = 37) using two components of the Awareness of Social Inference Test, canonical emotion identification and sarcasm identification. Diffusion tensor imaging (DTI) was used to derive white matter tract correlates of social cognition performance and compared with the distribution of grey matter atrophy on voxel-based morphometry. The bvFTD and svPPA groups showed comparably severe deficits for identification of canonical emotions and sarcasm, and these deficits were correlated with distributed and overlapping white matter tract alterations particularly affecting frontotemporal connections in the right cerebral hemisphere. The most robust DTI associations were identified in white matter tracts linking cognitive and evaluative processing with emotional responses: anterior thalamic radiation, fornix (emotion identification) and uncinate fasciculus (sarcasm identification). DTI associations of impaired social cognition were more consistent than corresponding grey matter associations. These findings delineate a brain network substrate for the social impairment that characterises FTLD syndromes. The findings further suggest that DTI can generate sensitive and functionally relevant indexes of white matter damage in FTLD, with potential to transcend conventional syndrome boundaries.
•Social cognition deficits define frontotemporal dementias but are poorly understood.•We studied brain network correlates of sarcasm processing in these dementias with DTI.•Sarcasm deficits were particularly linked to right frontotemporal tract changes.•DTI generates functionally relevant metrics of white matter damage in these dementias.
Frontotemporal dementia; Social cognition; Sarcasm; Emotion; Diffusion tensor imaging; Voxel based morphometry
Our primary objective was to compare the performance of unaccelerated vs. accelerated structural MRI for measuring disease progression using serial scans in Alzheimer’s disease (AD).
We identified cognitively normal (CN), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI) and AD subjects from all available Alzheimer’s Disease Neuroimaging Initiative (ADNI) subjects with usable pairs of accelerated and unaccelerated scans. There were a total of 696 subjects with baseline and 3 month scans, 628 subjects with baseline and 6 month scans and 464 subjects with baseline and 12 month scans available. We employed the Symmetric Diffeomorphic Image Normalization method (SyN) for normalization of the serial scans to obtain Tensor Based Morphometry (TBM) maps which indicate the structural changes between pairs of scans. We computed a TBM-SyN summary score of annualized structural changes over 31 regions of interest (ROIs) that are characteristically affected in AD. TBM-SyN scores were computed using accelerated and unaccelerated scan pairs and compared in terms of agreement, group-wise discrimination, and sample size estimates for a hypothetical therapeutic trial.
We observed a number of systematic differences between TBM-SyN scores computed from accelerated and unaccelerated pairs of scans. TBM-SyN scores computed from accelerated scans tended to have overall higher estimated values than those from unaccelerated scans. However, the performance of accelerated scans was comparable to unaccelerated scans in terms of discrimination between clinical groups and sample sizes required in each clinical group for a therapeutic trial. We also found that the quality of both accelerated vs. unaccelerated scans were similar.
Accelerated scanning protocols reduce scan time considerably. Their group-wise discrimination and sample size estimates were comparable to those obtained with unaccelerated scans. The two protocols did not produce interchangeable TBM-SyN estimates, so it is arguably important to use either accelerated pairs of scans or unaccelerated pairs of scans throughout the study duration.
To identify factors influencing age at symptom onset and disease course in autosomal dominant Alzheimer disease (ADAD), and develop evidence-based criteria for predicting symptom onset in ADAD.
We have collected individual-level data on ages at symptom onset and death from 387 ADAD pedigrees, compiled from 137 peer-reviewed publications, the Dominantly Inherited Alzheimer Network (DIAN) database, and 2 large kindreds of Colombian (PSEN1 E280A) and Volga German (PSEN2 N141I) ancestry. Our combined dataset includes 3,275 individuals, of whom 1,307 were affected by ADAD with known age at symptom onset. We assessed the relative contributions of several factors in influencing age at onset, including parental age at onset, age at onset by mutation type and family, and APOE genotype and sex. We additionally performed survival analysis using data on symptom onset collected from 183 ADAD mutation carriers followed longitudinally in the DIAN Study.
We report summary statistics on age at onset and disease course for 174 ADAD mutations, and discover strong and highly significant (p < 10−16, r2 > 0.38) correlations between individual age at symptom onset and predicted values based on parental age at onset and mean ages at onset by mutation type and family, which persist after controlling for APOE genotype and sex.
Significant proportions of the observed variance in age at symptom onset in ADAD can be explained by family history and mutation type, providing empirical support for use of these data to estimate onset in clinical research.
Total intracranial volume (TIV/ICV) is an important covariate for volumetric analyses of the brain and brain regions, especially in the study of neurodegenerative diseases, where it can provide a proxy of maximum pre-morbid brain volume. The gold-standard method is manual delineation of brain scans, but this requires careful work by trained operators. We evaluated Statistical Parametric Mapping 12 (SPM12) automated segmentation for TIV measurement in place of manual segmentation and also compared it with SPM8 and FreeSurfer 5.3.0. For T1-weighted MRI acquired from 288 participants in a multi-centre clinical trial in Alzheimer's disease we find a high correlation between SPM12 TIV and manual TIV (R2 = 0.940, 95% Confidence Interval (0.924, 0.953)), with a small mean difference (SPM12 40.4 ± 35.4 ml lower than manual, amounting to 2.8% of the overall mean TIV in the study). The correlation with manual measurements (the key aspect when using TIV as a covariate) for SPM12 was significantly higher (p < 0.001) than for either SPM8 (R2 = 0.577 CI (0.500, 0.644)) or FreeSurfer (R2 = 0.801 CI (0.744, 0.843)). These results suggest that SPM12 TIV estimates are an acceptable substitute for labour-intensive manual estimates even in the challenging context of multiple centres and the presence of neurodegenerative pathology. We also briefly discuss some aspects of the statistical modelling approaches to adjust for TIV.
•288 T1 MRI from multiple scanners were manually segmented for intracranial volume.•We compare SPM12 with the current methods of estimating intracranial volume.•SPM12 shows a very high correlation with manual measures and little bias.•Newer automated volume measures are more accurate controls for head size variation.
Intracranial volume; Statistical Parametric Mapping; SPM; Freesurfer; Evaluation; Alzheimer's disease; TIV; ICV
As the need to develop a successful disease-modifying treatment for Alzheimer’s disease (AD) becomes more urgent, imaging is increasingly used in therapeutic trials. We provide an overview of how the different imaging modalities are used in AD studies and the current regulatory guidelines for their use in clinical trials as endpoints. We review the current literature for results of imaging endpoints of efficacy and safety in published clinical trials. We start with trials in mild to moderate AD, where imaging (largely magnetic resonance imaging (MRI)) has long played a role in inclusion and exclusion criteria; more recently, MRI has been used to identify adverse events and to measure rates of brain atrophy. The advent of amyloid imaging using positron emission tomography has led to trials incorporating amyloid measurements as endpoints and incidentally to the recognition of the high proportion of amyloid-negative individuals that may be recruited into these trials. Ongoing and planned trials now commonly include multimodality imaging: amyloid positron emission tomography, MRI and other modalities. At the same time, the failure of recent large profile trials in mild to moderate AD together with the realisation that there is a long prodromal period to AD has driven a push to move studies to earlier in the disease. Imaging has particularly important roles, alongside other biomarkers, in assessing efficacy because conventional clinical outcomes may have limited ability to detect treatment effects in these early stages.
Electronic supplementary material
The online version of this article (doi:10.1186/s13195-014-0087-9) contains supplementary material, which is available to authorized users.
Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by impaired higher visual processing skills; however, motor features more commonly associated with corticobasal syndrome may also occur. We investigated the frequency and clinical characteristics of motor features in 44 PCA patients and, with 30 controls, conducted voxel-based morphometry, cortical thickness, and subcortical volumetric analyses of their magnetic resonance imaging. Prominent limb rigidity was used to define a PCA-motor subgroup. A total of 30% (13) had PCA-motor; all demonstrating asymmetrical left upper limb rigidity. Limb apraxia was more frequent and asymmetrical in PCA-motor, as was myoclonus. Tremor and alien limb phenomena only occurred in this subgroup. The subgroups did not differ in neuropsychological test performance or apolipoprotein E4 allele frequency. Greater asymmetry of atrophy occurred in PCA-motor, particularly involving right frontoparietal and peri-rolandic cortices, putamen, and thalamus. The 9 patients (including 4 PCA-motor) with pathology or cerebrospinal fluid all showed evidence of Alzheimer's disease. Our data suggest that PCA patients with motor features have greater atrophy of contralateral sensorimotor areas but are still likely to have underlying Alzheimer's disease.
•We investigated motor features and their neuroimaging correlates in 44 posterior cortical atrophy (PCA) patients.•A total of 30% had asymmetrical left upper limb rigidity and were termed the “PCA-motor” group.•Limb apraxia was more frequent and asymmetrical in PCA-motor, as was myoclonus.•PCA-motor had greater asymmetry of atrophy, involving the right sensorimotor areas.•The subgroup with pathology or cerebrospinal fluid all showed evidence of Alzheimer's disease.
Posterior cortical atrophy; Corticobasal syndrome; Alzheimer's disease; Phenotype; Asymmetric atrophy
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)
The leukodystrophies comprise a clinically and genetically heterogeneous group of progressive hereditary neurological disorders mainly affecting the myelin in the central nervous system. Their onset is variable from childhood to adulthood and presentation can be with a variety of clinical features that include mainly for adult-onset cases cognitive decline, seizures, parkinsonism, muscle weakness, neuropathy, spastic paraplegia, personality/behavioral problems, and dystonia. Recently, Rademakers and colleagues identified mutations in the CSF1R gene as the cause of hereditary diffuse leukoencephalopathy with spheroids (HDLS), offering the possibility for an in-life diagnosis. The detection of mutations in this gene in cases diagnosed with different clinical entities further demonstrated the difficulties in the clinical diagnosis of HDLS.
To better understand the genetic role of mutations in this gene, we sequenced a large cohort of adult-onset leukodystrophy cases.
Whole-exome sequencing and follow up-screening by Sanger sequencing.
Collaborative study between the Institute of Neurology, University College London and the Inserm, Paris, France.
A total of 114 probands, mostly European patients, with a diagnosis of adult-onset leukodystrophy or atypical cases that could fit within a picture of leukodystrophy. These included 3 extended families within the spectrum of leukodystrophy phenotype.
Whole-exome sequencing in a family and Sanger sequencing of CSF1R.
Main Outcomes and Measures
Mutations in CSF1R.
We identified 12 probands with mutations in CSF1R. The clinical diagnoses given to these patients included dementia with spastic paraplegia, corticobasal degeneration syndrome, and stroke disorders. Our study shows that CSF1R mutations are responsible for a significant proportion of clinically and pathologically proven HDLS.
Conclusions and Relevance
These results give an indication of the frequency of CSF1R mutations in a European leukodystrophy series and expand the phenotypic spectrum of disorders that should be screened for this gene.
Bapineuzumab, a humanized anti–amyloid-beta monoclonal antibody, is in clinical development for the treatment of Alzheimer’s disease.
We conducted two double-blind, randomized, placebo-controlled, phase 3 trials involving patients with mild-to-moderate Alzheimer’s disease — one involving 1121 carriers of the apolipoprotein E (APOE) ε4 allele and the other involving 1331 noncarriers. Bapineuzumab or placebo, with doses varying by study, was administered by intravenous infusion every 13 weeks for 78 weeks. The primary outcome measures were scores on the 11-item cognitive subscale of the Alzheimer’s Disease Assessment Scale (ADAS-cog11, with scores ranging from 0 to 70 and higher scores indicating greater impairment) and the Disability Assessment for Dementia (DAD, with scores ranging from 0 to 100 and higher scores indicating less impairment). A total of 1090 carriers and 1114 noncarriers were included in the efficacy analysis. Secondary outcome measures included findings on positron-emission tomographic amyloid imaging with the use of Pittsburgh compound B (PIB-PET) and cerebrospinal fluid phosphorylated tau (phospho-tau) concentrations.
There were no significant between-group differences in the primary outcomes. At week 78, the between-group differences in the change from baseline in the ADAS-cog11 and DAD scores (bapineuzumab group minus placebo group) were −0.2 (P = 0.80) and −1.2 (P = 0.34), respectively, in the carrier study; the corresponding differences in the noncarrier study were −0.3 (P = 0.64) and 2.8 (P = 0.07) with the 0.5-mg-per-kilogram dose of bapineuzumab and 0.4 (P = 0.62) and 0.9 (P = 0.55) with the 1.0-mg-per-kilogram dose. The major safety finding was amyloid-related imaging abnormalities with edema among patients receiving bapineuzumab, which increased with bapineuzumab dose and APOE ε4 allele number and which led to discontinuation of the 2.0-mg-per-kilogram dose. Between-group differences were observed with respect to PIB-PET and cerebrospinal fluid phospho-tau concentrations in APOE ε4 allele carriers but not in noncarriers.
Bapineuzumab did not improve clinical outcomes in patients with Alzheimer’s disease, despite treatment differences in biomarkers observed in APOE ε4 carriers. (Funded by Janssen Alzheimer Immunotherapy and Pfizer; Bapineuzumab 301 and 302 ClinicalTrials.gov numbers, NCT00575055 and NCT00574132, and EudraCT number, 2009-012748-17.)
The aim of this investigation was to assess the effect of galantamine, an acetylcholinesterase inhibitor and allosteric modulator of nicotinic receptors, on brain atrophy in individuals with mild cognitive impairment (MCI), and to assess effect modification by apolipoprotein E (APOE) genotype.
We used data from the Galantamine-International-11 (Gal-Int-11) trial, a 24-month, randomized, double blind, placebo-controlled, flexible-dose (16 to 24 mg daily) study in patients with MCI. Brain magnetic resonance imaging (MRI), including a 3-dimensional T1-weighted gradient echo volumetric sequence, was performed at screening and at 24 months. We recorded whole brain and hippocampal volumes, and calculated annual atrophy rates. Linear regression analysis was used to calculate adjusted mean differences in the rate of whole brain and hippocampal atrophy, between MCI patients treated with galantamine and with placebo. Additionally, we performed stratified analyses according to APOE genotype.
Data from 364 MCI patients with 24-month MRI data (galantamine, n = 176; placebo, n = 188) were included in the volumetric analysis. Subjects treated with galantamine demonstrated a lower rate of whole brain atrophy compared to those treated with placebo (adjusted mean difference 0.18% per year (95% confidence interval (CI) 0.04; 0.30)). Stratified analyses according to APOE genotype, showed that this effect was confined to patients who carried an APOE ϵ4 allele (adjusted mean difference 0.28% per year (95% CI 0.07; 0.50)). Rates of hippocampal atrophy did not differ significantly between study groups.
Patients with MCI who were treated with galantamine demonstrated a lower rate of whole brain atrophy, but not of hippocampal atrophy, over a 24-month treatment period, compared to those treated with placebo. This protective effect of galantamine on whole brain atrophy rate in MCI was only present in APOE ϵ4 carriers.
Young et al. reformulate an event-based model for the progression of Alzheimer's disease to make it applicable to a heterogeneous sporadic disease population. The enhanced model predicts the ordering of biomarker abnormality in sporadic Alzheimer's disease independently of clinical diagnoses or biomarker cut-points, and shows state-of-the-art diagnostic classification performance.
We demonstrate the use of a probabilistic generative model to explore the biomarker changes occurring as Alzheimer’s disease develops and progresses. We enhanced the recently introduced event-based model for use with a multi-modal sporadic disease data set. This allows us to determine the sequence in which Alzheimer’s disease biomarkers become abnormal without reliance on a priori clinical diagnostic information or explicit biomarker cut points. The model also characterizes the uncertainty in the ordering and provides a natural patient staging system. Two hundred and eighty-five subjects (92 cognitively normal, 129 mild cognitive impairment, 64 Alzheimer’s disease) were selected from the Alzheimer’s Disease Neuroimaging Initiative with measurements of 14 Alzheimer’s disease-related biomarkers including cerebrospinal fluid proteins, regional magnetic resonance imaging brain volume and rates of atrophy measures, and cognitive test scores. We used the event-based model to determine the sequence of biomarker abnormality and its uncertainty in various population subgroups. We used patient stages assigned by the event-based model to discriminate cognitively normal subjects from those with Alzheimer’s disease, and predict conversion from mild cognitive impairment to Alzheimer’s disease and cognitively normal to mild cognitive impairment. The model predicts that cerebrospinal fluid levels become abnormal first, followed by rates of atrophy, then cognitive test scores, and finally regional brain volumes. In amyloid-positive (cerebrospinal fluid amyloid-β1–42 < 192 pg/ml) or APOE-positive (one or more APOE4 alleles) subjects, the model predicts with high confidence that the cerebrospinal fluid biomarkers become abnormal in a distinct sequence: amyloid-β1–42, phosphorylated tau, total tau. However, in the broader population total tau and phosphorylated tau are found to be earlier cerebrospinal fluid markers than amyloid-β1–42, albeit with more uncertainty. The model’s staging system strongly separates cognitively normal and Alzheimer’s disease subjects (maximum classification accuracy of 99%), and predicts conversion from mild cognitive impairment to Alzheimer’s disease (maximum balanced accuracy of 77% over 3 years), and from cognitively normal to mild cognitive impairment (maximum balanced accuracy of 76% over 5 years). By fitting Cox proportional hazards models, we find that baseline model stage is a significant risk factor for conversion from both mild cognitive impairment to Alzheimer’s disease (P = 2.06 × 10−7) and cognitively normal to mild cognitive impairment (P = 0.033). The data-driven model we describe supports hypothetical models of biomarker ordering in amyloid-positive and APOE-positive subjects, but suggests that biomarker ordering in the wider population may diverge from this sequence. The model provides useful disease staging information across the full spectrum of disease progression, from cognitively normal to mild cognitive impairment to Alzheimer’s disease. This approach has broad application across neurodegenerative disease, providing insights into disease biology, as well as staging and prognostication.
event-based model; disease progression; Alzheimer’s disease; biomarkers; biomarker ordering
Amyloid-related imaging abnormalities (ARIA) have been reported in
Alzheimer’s disease (AD) patients treated with bapineuzumab, a
humanized monoclonal antibody to amyloid-β. ARIA includes MRI signal
abnormalities suggestive of vasogenic edema and sulcal effusions (ARIA-E)
and hemosiderin deposits (ARIA-H). A better understanding of the incidence
and risk factors for ARIA may further the development of amyloid-modifying
treatments for AD.
Two neuroradiologists independently reviewed (kappa=0.76) and then
reached consensus reads on over 2500 FLAIR-MRIs from 262 participants in
three phase 2 studies of bapineuzumab. Subjects (n=210) were included in
risk analyses if they had no evidence of ARIA-E on pre-treatment MRI,
received bapineuzumab, and had at least one post-treatment MRI.
36/210 (17%) subjects developed ARIA-E during treatment; 28
of these 36 (78%) did not report associated symptoms. Adverse events
reported in 8 symptomatic patients included headache, confusion,
neuropsychiatric and gastrointestinal symptoms. 15/36 of the ARIA-E cases
(42%) were detected only on central review. 13/15 received
additional infusions while ARIA-E was present, without any associated
symptoms reported. ARIA-E incidence increased with bapineuzumab dose (Hazard
Ratio [HR] 2.24 per mg/kg increase in dose; p<0·001) and
with APOE ε4 allele number (HR 2.55 per allele;
ARIA appears to represent a spectrum of imaging findings with
variable clinical correlates, with some cases remaining asymptomatic even
when treated through ARIA-E. The increased risk of ARIA with APOE ε4
and bapineuzumab dose, and the time course in relation to dosing, is
consistent with alterations in vascular amyloid burden.
Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls.
In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10−6) and 14 (IGHV1-67 p = 7.9×10−8) which indexed novel susceptibility loci.
The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
Eleven susceptibility loci for late-onset Alzheimer’s disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer’s disease cases and 37,154 controls. In stage 2,11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer’s disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer’s disease.
To investigate whether APOE ε4 carriers have higher hippocampal atrophy rates than non-carriers in Alzheimer's disease (AD), mild cognitive impairment (MCI) and controls, and if so, whether higher hippocampal atrophy rates are still observed after adjusting for concurrent whole-brain atrophy rates.
MRI scans from all available visits in ADNI (148 AD, 307 MCI, 167 controls) were used. MCI subjects were divided into “progressors” (MCI-P) if diagnosed with AD within 36 months or “stable” (MCI-S) if a diagnosis of MCI was maintained. A joint multi-level mixed-effect linear regression model was used to analyse the effect of ε4 carrier-status on hippocampal and whole-brain atrophy rates, adjusting for age, gender, MMSE and brain-to-intracranial volume ratio. The difference in hippocampal rates between ε4 carriers and non-carriers after adjustment for concurrent whole-brain atrophy rate was then calculated.
Mean adjusted hippocampal atrophy rates in ε4 carriers were significantly higher in AD, MCI-P and MCI-S (p≤0.011, all tests) compared with ε4 non-carriers. After adjustment for whole-brain atrophy rate, the difference in mean adjusted hippocampal atrophy rate between ε4 carriers and non-carriers was reduced but remained statistically significant in AD and MCI-P.
These results suggest that the APOE ε4 allele drives atrophy to the medial-temporal lobe region in AD.
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.