Neuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally.
To ...characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures.
A total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials.
The subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimer's Disease Assessment Scale-Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Abeta-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures.
The Alzheimer's Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.
Deposition of amyloid-β (Aβ) in the cerebral cortex is thought to be a pivotal event in Alzheimer's disease (AD) pathogenesis with a significant genetic contribution. Molecular imaging can provide an ...early noninvasive phenotype, but small samples have prohibited genome-wide association studies (GWAS) of cortical Aβ load until now. We employed florbetapir ((18)F) positron emission tomography (PET) imaging to assess brain Aβ levels in vivo for 555 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). More than six million common genetic variants were tested for association to quantitative global cortical Aβ load controlling for age, gender and diagnosis. Independent genome-wide significant associations were identified on chromosome 19 within APOE (apolipoprotein E) (rs429358, P=5.5 × 10(-14)) and on chromosome 3 upstream of BCHE (butyrylcholinesterase) (rs509208, P=2.7 × 10(-8)) in a region previously associated with serum BCHE activity. Together, these loci explained 15% of the variance in cortical Aβ levels in this sample (APOE 10.7%, BCHE 4.3%). Suggestive associations were identified within ITGA6, near EFNA5, EDIL3, ITGA1, PIK3R1, NFIB and ARID1B, and between NUAK1 and C12orf75. These results confirm the association of APOE with Aβ deposition and represent the largest known effect of BCHE on an AD-related phenotype. BCHE has been found in senile plaques and this new association of genetic variation at the BCHE locus with Aβ burden in humans may have implications for potential disease-modifying effects of BCHE-modulating agents in the AD spectrum.
Whole-exome sequencing of individuals with mild cognitive impairment, combined with genotype imputation, was used to identify coding variants other than the apolipoprotein E (APOE) ε4 allele ...associated with rate of hippocampal volume loss using an extreme trait design. Matched unrelated APOE ε3 homozygous male Caucasian participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were selected at the extremes of the 2-year longitudinal change distribution of hippocampal volume (eight subjects with rapid rates of atrophy and eight with slow/stable rates of atrophy). We identified 57 non-synonymous single nucleotide variants (SNVs) which were found exclusively in at least 4 of 8 subjects in the rapid atrophy group, but not in any of the 8 subjects in the slow atrophy group. Among these SNVs, the variants that accounted for the greatest group difference and were predicted in silico as 'probably damaging' missense variants were rs9610775 (CARD10) and rs1136410 (PARP1). To further investigate and extend the exome findings in a larger sample, we conducted quantitative trait analysis including whole-brain search in the remaining ADNI APOE ε3/ε3 group (N=315). Genetic variation within PARP1 and CARD10 was associated with rate of hippocampal neurodegeneration in APOE ε3/ε3. Meta-analysis across five independent cross sectional cohorts indicated that rs1136410 is also significantly associated with hippocampal volume in APOE ε3/ε3 individuals (N=923). Larger sequencing studies and longitudinal follow-up are needed for confirmation. The combination of next-generation sequencing and quantitative imaging phenotypes holds significant promise for discovery of variants involved in neurodegeneration.
Recommendations for the diagnosis of preclinical Alzheimer disease (AD) have been formulated by a workgroup of the National Institute on Aging and Alzheimer's Association. Three stages of preclinical ...AD were described. Stage 1 is characterized by abnormal levels of β-amyloid. Stage 2 represents abnormal levels of β-amyloid and evidence of brain neurodegeneration. Stage 3 includes the features of stage 2 plus subtle cognitive changes. Stage 0, not explicitly defined in the criteria, represents subjects with normal biomarkers and normal cognition. The ability of the recommended criteria to predict progression to cognitive impairment is the crux of their validity.
Using previously developed operational definitions of the 3 stages of preclinical AD, we examined the outcomes of subjects from the Mayo Clinic Study of Aging diagnosed as cognitively normal who underwent brain MRI or (18)Ffluorodeoxyglucose and Pittsburgh compound B PET, had global cognitive test scores, and were followed for at least 1 year.
Of the 296 initially normal subjects, 31 (10%) progressed to a diagnosis of mild cognitive impairment (MCI) or dementia (27 amnestic MCI, 2 nonamnestic MCI, and 2 non-AD dementias) within 1 year. The proportion of subjects who progressed to MCI or dementia increased with advancing stage (stage 0, 5%; stage 1, 11%; stage 2, 21%; stage 3, 43%; test for trend, p < 0.001).
Despite the short follow-up period, our operationalization of the new preclinical AD recommendations confirmed that advancing preclinical stage led to higher proportions of subjects who progressed to MCI or dementia.
To test the hypothesis that the atrophy rate measured from serial MRI studies is associated with time to subsequent clinical conversion to a more impaired state in both cognitively healthy elderly ...subjects and in subjects with amnestic mild cognitive impairment (MCI).
Ninety-one healthy elderly patients and 72 patients with amnestic MCI who met inclusion criteria were identified from the Mayo Alzheimer's Disease Research Center and Alzheimer's Disease Patient Registry. Atrophy rates of four different brain structures--hippocampus, entorhinal cortex, whole brain, and ventricle--were measured from a pair of MRI studies separated by 1 to 2 years. The time of the second scan marked the beginning of the clinical observation period.
During follow-up, 13 healthy patients converted to MCI or Alzheimer disease (AD), whereas 39 MCI subjects converted to AD. Among those healthy at baseline, only larger ventricular annual percent volume change (APC) was associated with a higher risk of conversion (hazard ratio for a 1-SD increase 1.9, p = 0.03). Among MCI subjects, both greater ventricular volume APC (hazard ratio for a 1-SD increase 1.7, p < 0.001) and greater whole brain APC (hazard ratio for a 1-SD increase 1.4, p = 0.007) increased the risk of conversion to AD. Both ventricular APC (hazard ratio for a 1-SD increase 1.59, p = 0.001) and whole brain APC (hazard ratio for a 1-SD increase 1.32, p = 0.009) provided additional predictive information to covariate-adjusted cross-sectional hippocampal volume at baseline about the risk of converting from MCI to AD.
Higher whole brain and ventricle atrophy rates 1 to 2 years before baseline are associated with an increased hazard of conversion to a more impaired state. Combining a measure of hippocampal volume at baseline with a measure of either whole brain or ventricle atrophy rates from serial MRI scans provides complimentary predictive information about the hazard of subsequent conversion from mild cognitive impairment to Alzheimer disease. However, overlap among those who did vs those who did not convert indicate that these measures are unlikely to provide absolute prognostic information for individual patients.
A variety of measurements have been individually linked to decline in mild cognitive impairment (MCI), but the identification of optimal markers for predicting disease progression remains unresolved. ...The goal of this study was to evaluate the prognostic ability of genetic, CSF, neuroimaging, and cognitive measurements obtained in the same participants.
APOE epsilon4 allele frequency, CSF proteins (Abeta(1-42), total tau, hyperphosphorylated tau p-tau(181p)), glucose metabolism (FDG-PET), hippocampal volume, and episodic memory performance were evaluated at baseline in patients with amnestic MCI (n = 85), using data from a large multisite study (Alzheimer's Disease Neuroimaging Initiative). Patients were classified as normal or abnormal on each predictor variable based on externally derived cutoffs, and then variables were evaluated as predictors of subsequent conversion to Alzheimer disease (AD) and cognitive decline (Alzheimer's Disease Assessment Scale-Cognitive Subscale) during a variable follow-up period (1.9 +/- 0.4 years).
Patients with MCI converted to AD at an annual rate of 17.2%. Subjects with MCI who had abnormal results on both FDG-PET and episodic memory were 11.7 times more likely to convert to AD than subjects who had normal results on both measures (p <or= 0.02). In addition, the CSF ratio p-tau(181p)/Abeta(1-42) (beta = 1.10 +/- 0.53; p = 0.04) and, marginally, FDG-PET predicted cognitive decline.
Baseline FDG-PET and episodic memory predict conversion to AD, whereas p-tau(181p)/Abeta(1-42) and, marginally, FDG-PET predict longitudinal cognitive decline. Complementary information provided by these biomarkers may aid in future selection of patients for clinical trials or identification of patients likely to benefit from a therapeutic intervention.
To investigate the relationship between baseline MRI and CSF biomarkers and subsequent change in continuous measures of cognitive and functional abilities in cognitively normal (CN) subjects and ...patients with amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD) and to examine the ability of these biomarkers to predict time to conversion from aMCI to AD.
Data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN, aMCI, and AD cohorts with both CSF and MRI, were used. Baseline CSF (t-tau, Abeta(1-42), and p-tau(181P)) and MRI scans were obtained in 399 subjects (109 CN, 192 aMCI, 98 AD). Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like features in MRI, were computed for each subject.
Change on continuous measures of cognitive and functional performance was modeled as average Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination scores over a 2-year period. STAND was a better predictor of subsequent cognitive/functional change than CSF biomarkers. Single-predictor Cox proportional hazard models for time to conversion from aMCI to AD showed that STAND and log (t-tau/Abeta(1-42)) were both predictive of future conversion. The age-adjusted hazard ratio for an interquartile change (95% confidence interval) of STAND was 2.6 (1.7, 4.2) and log (t-tau/Abeta(1-42)) was 2.0 (1.1, 3.4). Both MRI and CSF provided information about future cognitive change even after adjusting for baseline cognitive performance.
MRI and CSF provide complimentary predictive information about time to conversion from amnestic mild cognitive impairment to Alzheimer disease and combination of the 2 provides better prediction than either source alone. However, we found that MRI was a slightly better predictor of future clinical/functional decline than the CSF biomarkers tested.
Right temporal frontotemporal dementia (FTD) is an anatomic variant of FTD associated with relatively distinct behavioral and cognitive symptoms. We aimed to determine whether right temporal FTD is a ...homogeneous clinical, imaging, and pathologic/genetic entity.
In this case-control study, 101 subjects with FTD were identified. Atlas-based parcellation generated temporal, frontal, and parietal grey matter volumes which were used to identify subjects with a right temporal dominant atrophy pattern. Clinical, neuropsychological, genetic, and neuropathologic features were reviewed. The subjects with right temporal FTD were grouped by initial clinical diagnosis and voxel-based morphometry was used to assess grey matter loss in the different groups, compared to controls, and each other.
We identified 20 subjects with right temporal FTD. Twelve had been initially diagnosed with behavioral variant FTD (bvFTD), and the other 8 with semantic dementia (SMD). Personality change and inappropriate behaviors were more frequent in the bvFTD group, while prosopagnosia, word-finding difficulties, comprehension problems, and topographagnosia were more frequent in the SMD group. The bvFTD group showed greater loss in frontal lobes than the SMD group. The SMD group showed greater fusiform loss than the bvFTD group. All 8 bvFTD subjects with pathologic/genetic diagnosis showed abnormalities in tau protein (7 with tau mutations), while all three SMD subjects with pathology showed abnormalities in TDP-43 (p = 0.006).
We have identified 2 subtypes of right temporal variant frontotemporal dementia (FTD) allowing further differentiation of FTD subjects with underlying tau pathology from those with TDP-43 pathology.
To investigate age-related default mode network (DMN) connectivity in a large cognitively normal elderly cohort and in patients with Alzheimer disease (AD) compared with age-, gender-, and ...education-matched controls.
We analyzed task-free-fMRI data with both independent component analysis and seed-based analysis to identify anterior and posterior DMNs. We investigated age-related changes in connectivity in a sample of 341 cognitively normal subjects. We then compared 28 patients with AD with 56 cognitively normal noncarriers of the APOE ε4 allele matched for age, education, and gender.
The anterior DMN shows age-associated increases and decreases in fontal lobe connectivity, whereas the posterior DMN shows mainly age-associated declines in connectivity throughout. Relative to matched cognitively normal controls, subjects with AD display an accelerated pattern of the age-associated changes described above, except that the declines in frontal lobe connectivity did not reach statistical significance. These changes survive atrophy correction and are correlated with cognitive performance.
The results of this study indicate that the DMN abnormalities observed in patients with AD represent an accelerated aging pattern of connectivity compared with matched controls.
To assess the correlations of both MRI and CSF biomarkers with clinical diagnosis and with cognitive performance in cognitively normal (CN) subjects and patients with amnestic mild cognitive ...impairment (aMCI) and Alzheimer disease (AD).
This is a cross-sectional study with data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN subjects, subjects with aMCI, and subjects with AD with both CSF and MRI. Baseline CSF (t-tau, Abeta(1-42), and p-tau(181P)) and MRI scans were obtained in 399 subjects (109 CN, 192 aMCI, 98 AD). Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like anatomic features on MRI, were computed for each subject.
We found no significant correlation between CSF biomarkers and cognitive scores in any of the 3 clinical groups individually. Conversely, STAND scores correlated with both Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination in aMCI and AD (p < or = 0.01). While STAND and all CSF biomarkers were predictors of clinical group membership (CN, aMCI, or AD) univariately (p < 0.001), STAND was more predictive than CSF both univariately and in combined models.
CSF and MRI biomarkers independently contribute to intergroup diagnostic discrimination and the combination of CSF and MRI provides better prediction than either source of data alone. However, MRI provides greater power to effect cross-sectional groupwise discrimination and better correlation with general cognition and functional status cross-sectionally. We therefore conclude that although MRI and CSF provide complementary information, MRI reflects clinically defined disease stage better than the CSF biomarkers tested.
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