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1.  Effect of Apolipoprotein E on Biomarkers of Amyloid Load and Neuronal Pathology in Alzheimer Disease 
Annals of neurology  2010;67(3):308-316.
Objective
To study the effect of apolipoprotein E ε4 status on biomarkers of neurodegeneration (atrophy on magnetic resonance imaging [MRI]), neuronal injury (cerebrospinal fluid [CSF] t-tau), and brain Aβ amyloid load (CSF Aβ1–42) in cognitively normal subjects (CN), amnestic subjects with mild cognitive impairment (aMCI), and patients with Alzheimer disease (AD).
Methods
We included all 399 subjects (109 CN, 192 aMCI, 98 AD) from the Alzheimer's Disease Neuroimaging Initiative study with baseline CSF and MRI scans. Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like anatomic features on MRI, were computed for each subject.
Results
A clear ε4 allele dose effect was seen on CSF Aβ1–42 levels within each clinical group. In addition, the proportion of the variability in Aβ1–42 levels explained by APOE ε4 dose was significantly greater than the proportion of the variability explained by clinical diagnosis. On the other hand, the proportion of the variability in CSF t-tau and MRI atrophy explained by clinical diagnosis was greater than the proportion of the variability explained by APOE ε4 dose; however, this effect was only significant for STAND scores.
Interpretation
Low CSF Aβ1–42 (surrogate for Aβ amyloid load) is more closely linked to the presence of APOE ε4 than to clinical status. In contrast, MRI atrophy (surrogate for neurodegeneration) is closely linked with cognitive impairment, whereas its association with APOE ε4 is weaker. The data in this paper support a model of AD in which CSF Aβ1–42 is the earliest of the 3 biomarkers examined to become abnormal in both APOE carriers and noncarriers.
doi:10.1002/ana.21953
PMCID: PMC2886799  PMID: 20373342
2.  MRI and CSF biomarkers in normal, MCI, and AD subjects 
Neurology  2009;73(4):287-293.
Objective:
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).
Methods:
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, Aβ1-42, and p-tau181P) 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.
Results:
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 ≤ 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.
Conclusions:
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.
GLOSSARY
= Alzheimer disease;
= Alzheimer's Disease Neuroimaging Initiative;
= amnestic mild cognitive impairment;
= area under the receiver operating characteristic curve;
= Clinical Dementia Rating–sum of boxes score;
= confidence interval;
= cognitively normal;
= evidence-based medicine;
= entorhinal cortex;
= Mini-Mental State Examination;
= neurofibrillary tangle;
= proportional odds logistic regression;
= Structural Abnormality Index.
doi:10.1212/WNL.0b013e3181af79e5
PMCID: PMC2715210  PMID: 19636048
3.  Early diagnosis of Alzheimer's disease using cortical thickness: impact of cognitive reserve 
Brain  2009;132(8):2036-2047.
Brain atrophy measured by magnetic resonance structural imaging has been proposed as a surrogate marker for the early diagnosis of Alzheimer's disease. Studies on large samples are still required to determine its practical interest at the individual level, especially with regards to the capacity of anatomical magnetic resonance imaging to disentangle the confounding role of the cognitive reserve in the early diagnosis of Alzheimer's disease. One hundred and thirty healthy controls, 122 subjects with mild cognitive impairment of the amnestic type and 130 Alzheimer's disease patients were included from the ADNI database and followed up for 24 months. After 24 months, 72 amnestic mild cognitive impairment had converted to Alzheimer's disease (referred to as progressive mild cognitive impairment, as opposed to stable mild cognitive impairment). For each subject, cortical thickness was measured on the baseline magnetic resonance imaging volume. The resulting cortical thickness map was parcellated into 22 regions and a normalized thickness index was computed using the subset of regions (right medial temporal, left lateral temporal, right posterior cingulate) that optimally distinguished stable mild cognitive impairment from progressive mild cognitive impairment. We tested the ability of baseline normalized thickness index to predict evolution from amnestic mild cognitive impairment to Alzheimer's disease and compared it to the predictive values of the main cognitive scores at baseline. In addition, we studied the relationship between the normalized thickness index, the education level and the timeline of conversion to Alzheimer's disease. Normalized thickness index at baseline differed significantly among all the four diagnosis groups (P < 0.001) and correctly distinguished Alzheimer's disease patients from healthy controls with an 85% cross-validated accuracy. Normalized thickness index also correctly predicted evolution to Alzheimer's disease for 76% of amnestic mild cognitive impairment subjects after cross-validation, thus showing an advantage over cognitive scores (range 63–72%). Moreover, progressive mild cognitive impairment subjects, who converted later than 1 year after baseline, showed a significantly higher education level than those who converted earlier than 1 year after baseline. Using a normalized thickness index-based criterion may help with early diagnosis of Alzheimer's disease at the individual level, especially for highly educated subjects, up to 24 months before clinical criteria for Alzheimer's disease diagnosis are met.
doi:10.1093/brain/awp105
PMCID: PMC2714060  PMID: 19439419
Early Alzheimer's disease; individual diagnosis; mild cognitive impairment; magnetic resonance imaging (MRI); cognitive reserve
4.  MRI and CSF biomarkers in normal, MCI, and AD subjects 
Neurology  2009;73(4):294-301.
Objective:
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.
Methods:
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, Aβ1–42, and p-tau181P) 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.
Results:
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/Aβ1–42) 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/Aβ1–42) was 2.0 (1.1, 3.4). Both MRI and CSF provided information about future cognitive change even after adjusting for baseline cognitive performance.
Conclusions:
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.
GLOSSARY
= Alzheimer disease;
= Alzheimer's Disease Neuroimaging Initiative;
= amnestic mild cognitive impairment;
= Clinical Dementia Rating–sum of boxes score;
= confidence interval;
= cognitively normal;
= hazard ratio;
= Mini-Mental State Examination;
= neurofibrillary tangle;
= Structural Abnormality Index.
doi:10.1212/WNL.0b013e3181af79fb
PMCID: PMC2715214  PMID: 19636049
5.  Shapes of the Trajectories of Five Major Biomarkers of Alzheimer’s Disease 
Archives of neurology  2012;69(7):856-867.
Objective
To characterize the shape of the trajectories of Alzheimer’s Disease (AD) biomarkers as a function of MMSE.
Design
Longitudinal registries from the Mayo Clinic and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).
Patients
Two different samples (n=343 and n=598) were created that spanned the cognitive spectrum from normal to AD dementia. Subgroup analyses were performed in members of both cohorts (n=243 and n=328) who were amyloid positive at baseline.
Main Outcome Measures
The shape of biomarker trajectories as a function of MMSE, adjusted for age, was modeled and described as baseline (cross-sectional) and within-subject longitudinal effects. Biomarkers evaluated were cerebro spinal fluid (CSF) Aβ42 and tau; amyloid and fluoro deoxyglucose position emission tomography (PET) imaging, and structural magnetic resonance imaging (MRI).
Results
Baseline biomarker values generally worsened (i.e., non-zero slope) with lower baseline MMSE. Baseline hippocampal volume, amyloid PET and FDG PET values plateaued (i.e., non-linear slope) with lower MMSE in one or more analyses. Longitudinally, within-subject rates of biomarker change were associated with worsening MMSE. Non-constant within-subject rates (deceleration) of biomarker change were found in only one model.
Conclusions
Biomarker trajectory shapes by MMSE were complex and were affected by interactions with age and APOE status. Non-linearity was found in several baseline effects models. Non-constant within-subject rates of biomarker change were found in only one model, likely due to limited within-subject longitudinal follow up. Creating reliable models that describe the full trajectories of AD biomarkers will require significant additional longitudinal data in individual participants.
doi:10.1001/archneurol.2011.3405
PMCID: PMC3595157  PMID: 22409939
Alzheimer’s disease biomarkers; Magnetic Resonance Imaging; cerebro spinal fluid; amyloid PET imaging; FDG PET imaging
6.  Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer’s disease 
Brain  2010;133(11):3336-3348.
Biomarkers of brain Aβ amyloid deposition can be measured either by cerebrospinal fluid Aβ42 or Pittsburgh compound B positron emission tomography imaging. Our objective was to evaluate the ability of Aβ load and neurodegenerative atrophy on magnetic resonance imaging to predict shorter time-to-progression from mild cognitive impairment to Alzheimer’s dementia and to characterize the effect of these biomarkers on the risk of progression as they become increasingly abnormal. A total of 218 subjects with mild cognitive impairment were identified from the Alzheimer’s Disease Neuroimaging Initiative. The primary outcome was time-to-progression to Alzheimer’s dementia. Hippocampal volumes were measured and adjusted for intracranial volume. We used a new method of pooling cerebrospinal fluid Aβ42 and Pittsburgh compound B positron emission tomography measures to produce equivalent measures of brain Aβ load from either source and analysed the results using multiple imputation methods. We performed our analyses in two phases. First, we grouped our subjects into those who were ‘amyloid positive’ (n = 165, with the assumption that Alzheimer's pathology is dominant in this group) and those who were ‘amyloid negative’ (n = 53). In the second phase, we included all 218 subjects with mild cognitive impairment to evaluate the biomarkers in a sample that we assumed to contain a full spectrum of expected pathologies. In a Kaplan–Meier analysis, amyloid positive subjects with mild cognitive impairment were much more likely to progress to dementia within 2 years than amyloid negative subjects with mild cognitive impairment (50 versus 19%). Among amyloid positive subjects with mild cognitive impairment only, hippocampal atrophy predicted shorter time-to-progression (P < 0.001) while Aβ load did not (P = 0.44). In contrast, when all 218 subjects with mild cognitive impairment were combined (amyloid positive and negative), hippocampal atrophy and Aβ load predicted shorter time-to-progression with comparable power (hazard ratio for an inter-quartile difference of 2.6 for both); however, the risk profile was linear throughout the range of hippocampal atrophy values but reached a ceiling at higher values of brain Aβ load. Our results are consistent with a model of Alzheimer’s disease in which Aβ deposition initiates the pathological cascade but is not the direct cause of cognitive impairment as evidenced by the fact that Aβ load severity is decoupled from risk of progression at high levels. In contrast, hippocampal atrophy indicates how far along the neurodegenerative path one is, and hence how close to progressing to dementia. Possible explanations for our finding that many subjects with mild cognitive impairment have intermediate levels of Aβ load include: (i) individual subjects may reach an Aβ load plateau at varying absolute levels; (ii) some subjects may be more biologically susceptible to Aβ than others; and (iii) subjects with mild cognitive impairment with intermediate levels of Aβ may represent individuals with Alzheimer’s disease co-existent with other pathologies.
doi:10.1093/brain/awq277
PMCID: PMC2965425  PMID: 20935035
mild cognitive impairment; amyloid imaging; magnetic resonance imaging; cerebrospinal fluid; Alzheimer’s disease biomarkers
7.  Relationships between biomarkers in aging and dementia 
Neurology  2009;73(15):1193-1199.
Background:
PET imaging using [18F]fluorodeoxyglucose (FDG) and [11C]Pittsburgh compound B (PIB) have been proposed as biomarkers of Alzheimer disease (AD), as have CSF measures of the 42 amino acid β-amyloid protein (Aβ1-42) and total and phosphorylated tau (t-tau and p-tau). Relationships between biomarkers and with disease severity are incompletely understood.
Methods:
Ten subjects with AD, 11 control subjects, and 34 subjects with mild cognitive impairment from the Alzheimer’s Disease Neuroimaging Initiative underwent clinical evaluation; CSF measurement of Aβ1-42, t-tau, and p-tau; and PIB-PET and FDG-PET scanning. Data were analyzed using continuous regression and dichotomous outcomes with subjects classified as “positive” or “negative” for AD based on cutoffs established in patients with AD and controls from other cohorts.
Results:
Dichotomous categorization showed substantial agreement between PIB-PET and CSF Aβ1-42 measures (91% agreement, κ = 0.74), modest agreement between PIB-PET and p-tau (76% agreement, κ = 0.50), and minimal agreement for other comparisons (κ <0.3). Mini-Mental State Examination score was significantly correlated with FDG-PET but not with PIB-PET or CSF Aβ1-42. Regression models adjusted for diagnosis showed that PIB-PET was significantly correlated with Aβ1-42, t-tau, and p-tau181p, whereas FDG-PET was correlated only with Aβ1-42.
Conclusions:
PET and CSF biomarkers of Aβ agree with one another but are not related to cognitive impairment. [18F]fluorodeoxyglucose-PET is modestly related to other biomarkers but is better related to cognition. Different biomarkers for Alzheimer disease provide different information from one another that is likely to be complementary.
GLOSSARY
β1-42 = 42 amino acid β-amyloid protein;
= Alzheimer disease;
= Alzheimer’s Disease Neuroimaging Initiative;
= Clinical Dementia Rating;
= confidence interval;
= [18F]fluorodeoxyglucose;
= mild cognitive impairment;
= Mini-Mental State Examination;
= magnetic resonance;
= [11C]Pittsburgh compound B;
= phosphorylated tau;
= receiver operating characteristic;
= region of interest;
= standardized uptake value ratio;
= total tau;
= Wechsler Memory Scale–Revised.
doi:10.1212/WNL.0b013e3181bc010c
PMCID: PMC2764726  PMID: 19822868
8.  Biomarker-based prediction of progression in MCI: Comparison of AD signature and hippocampal volume with spinal fluid amyloid-β and tau 
Objective: New diagnostic criteria for mild cognitive impairment (MCI) due to Alzheimer's disease (AD) have been developed using biomarkers aiming to establish whether the clinical syndrome is likely due to underlying AD. We investigated the utility of magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) biomarkers in predicting progression from amnesic MCI to dementia, testing the hypotheses that (1) markers of amyloid and neurodegeneration provide distinct and complementary prognostic information over different time intervals, and that (2) evidence of neurodegeneration in amyloid-negative MCI individuals would be useful prognostically.
Methods: Data were obtained from the ADNI-1 (Alzheimer's Disease Neuroimaging Initiative Phase 1) database on all individuals with a baseline diagnosis of MCI, baseline MRI and CSF data, and at least one follow-up visit. MRI data were processed using a published set of a priori regions of interest to derive a measure known as the ``AD signature,'' as well as hippocampal volume. The CSF biomarkers amyloid-β, total tau, and phospho tau were also examined. We performed logistic regression analyses to identify the best baseline biomarker predictors of progression to dementia over 1 or 3 years, and Cox regression models to test the utility of these markers for predicting time-to-dementia.
Results: For prediction of dementia in MCI, the AD signature cortical thickness biomarker performed better than hippocampal volume. Although CSF tau measures were better than CSF amyloid-β at predicting dementia within 1 year, the AD signature was better than all CSF measures at prediction over this relatively short-term interval. CSF amyloid-β was superior to tau and AD signature at predicting dementia over 3 years. When CSF amyloid-β was dichotomized using previously published cutoff values and treated as a categorical variable, a multivariate stepwise Cox regression model indicated that both the AD signature MRI marker and the categorical CSF amyloid-β marker were useful in predicting time-to-event diagnosis of AD dementia.
Conclusion: In amnesic MCI, short-term (1 year) prognosis of progression to dementia relates strongly to baseline markers of neurodegeneration, with the AD signature MRI biomarker of cortical thickness performing the best among MRI and CSF markers studied here. Longer-term (3 year) prognosis in these individuals was better predicted by a marker indicative of brain amyloid. Prediction of time-to-event in a survival model was predicted by the combination of these biomarkers. These results provide further support for emerging models of the temporal relationship of pathophysiologic events in AD and demonstrate the utility of these biomarkers at the prodromal stage of the illness.
doi:10.3389/fnagi.2013.00055
PMCID: PMC3795312  PMID: 24130528
Alzheimer's disease; MRI; biomarkers; mild cognitive impairment; CSF biomarkers
9.  Neuroimaging and Other Biomarkers for Alzheimer's Disease: The Changing Landscape of Early Detection 
The goal of this review is to provide an overview of biomarkers for Alzheimer's disease (AD), with emphasis on neuroimaging and cerebrospinal fluid (CSF) biomarkers. We first review biomarker changes in patients with late-onset AD, including findings from studies using structural and functional magnetic resonance imaging (MRI), advanced MRI techniques (diffusion tensor imaging, magnetic resonance spectroscopy, perfusion), positron emission tomography with fluorodeoxyglucose, amyloid tracers, and other neurochemical tracers, and CSF protein levels. Next, we evaluate findings from these biomarkers in preclinical and prodromal stages of AD including mild cognitive impairment (MCI) and pre-MCI conditions conferring elevated risk. We then discuss related findings in patients with dominantly inherited AD. We conclude with a discussion of the current theoretical framework for the role of biomarkers in AD and emergent directions for AD biomarker research.
doi:10.1146/annurev-clinpsy-050212-185535
PMCID: PMC3955298  PMID: 23297785
mild cognitive impairment (MCI); preclinical Alzheimer's disease (AD); magnetic resonance imaging (MRI); functional MRI (fMRI); positron emission tomography (PET); cerebrospinal fluid (CSF); genetics
10.  Diagnosis-Independent Alzheimer Disease Biomarker Signature in Cognitively Normal Elderly People 
Archives of neurology  2010;67(8):949-956.
Objective
To identify biomarker patterns typical for Alzheimer disease (AD) in an independent, unsupervised way, without using information on the clinical diagnosis.
Design
Mixture modeling approach.
Setting
Alzheimer’s Disease Neuroimaging Initiative database.
Patients or Other Participants
Cognitively normal persons, patients with AD, and individuals with mild cognitive impairment.
Main Outcome Measures
Cerebrospinal fluid–derived β-amyloid protein 1–42, total tau protein, and phosphorylated tau181P protein concentrations were used as biomarkers on a clinically well-characterized data set. The outcome of the qualification analysis was validated on 2 additional data sets, 1 of which was autopsy confirmed.
Results
Using the US Alzheimer’s Disease Neuroimaging Initiative data set, a cerebrospinal fluid β-amyloid protein 1–42/phosphorylated tau181P biomarker mixture model identified 1 feature linked to AD, while the other matched the “healthy” status. The AD signature was found in 90%, 72%, and 36% of patients in the AD, mild cognitive impairment, and cognitively normal groups, respectively. The cognitively normal group with the AD signature was enriched in apolipoprotein E ε4 allele carriers. Results were validated on 2 other data sets. In 1 study consisting of 68 autopsy-confirmed AD cases, 64 of 68 patients (94% sensitivity) were correctly classified with the AD feature. In another data set with patients (n = 57) with mild cognitive impairment followed up for 5 years, the model showed a sensitivity of 100% in patients progressing to AD.
Conclusions
The mixture modeling approach, totally independent of clinical AD diagnosis, correctly classified patients with AD. The unexpected presence of the AD signature in more than one-third of cognitively normal subjects suggests that AD pathology is active and detectable earlier than has heretofore been envisioned.
doi:10.1001/archneurol.2010.179
PMCID: PMC2963067  PMID: 20697045
11.  CATEGORICAL AND CORRELATIONAL ANALYSES OF BASELINE FLUORODEOXYGLUCOSE POSITRON EMISSION TOMOGRAPHY IMAGES FROM THE ALZHEIMER’S DISEASE NEUROIMAGING INITIATIVE (ADNI) 
NeuroImage  2009;45(4):1107-1116.
In mostly small single-center studies, Alzheimer’s disease (AD) is associated with characteristic and progressive reductions in fluorodeoxyglucose positron emission tomography (PET) measurements of the regional cerebral metabolic rate for glucose (CMRgl). The AD Neuroimaging Initiative (ADNI) is acquiring FDG PET, volumetric magnetic resonance imaging, and other biomarker measurements in a large longitudinal multi-center study of initially mildly affected probable AD (pAD) patients, amnestic mild cognitive impairment (aMCI) patients, who are at increased AD risk, and cognitively normal controls (NC), and we are responsible for analyzing the PET images using statistical parametric mapping (SPM). Here we compare baseline CMRgl measurements from 74 pAD patients and 142 aMCI patients to those from 82 NC, we correlate CMRgl with categorical and continuous measures of clinical disease severity, and we compare apolipoprotein E (APOE) ε4 carriers to non-carriers in each of these subject groups. In comparison with NC, the pAD and aMCI groups each had significantly lower CMRgl bilaterally in posterior cingulate, precuneus, parietotemporal and frontal cortex. Similar reductions were observed when categories of disease severity or lower Mini-Mental State Exam (MMSE) scores were correlated with lower CMRgl. However, when analyses were restricted to the pAD patients, lower MMSE scores were significantly correlated with lower left frontal and temporal CMRgl. These findings from a large, multi-site study support previous single-site findings, supports the characteristic pattern of baseline CMRgl reductions in AD and aMCI patients, as well as preferential anterior CMRgl reductions after the onset of AD dementia.
doi:10.1016/j.neuroimage.2008.12.072
PMCID: PMC2886795  PMID: 19349228
Alzheimer’s disease; MCI; MMSE; Positron Emission Tomography
12.  Risk of dementia in MCI 
Neurology  2009;72(17):1519-1525.
Objective:
To investigate the combined ability of hippocampal volumes, 1H magnetic resonance spectroscopy (MRS) metabolites, and cerebrovascular disease to predict the risk of progression to dementia in mild cognitive impairment (MCI).
Methods:
We identified 151 consecutively recruited subjects with MCI from the Mayo Clinic Alzheimer’s Disease Research Center and Patient Registry who underwent MRI and 1H MRS studies at baseline and were followed up with approximately annual clinical examinations. A multivariable proportional hazards model that considered all imaging predictors simultaneously was used to determine whether hippocampal volumes, posterior cingulate gyrus 1H MRS metabolites, white matter hyperintensity load, and presence of cortical and subcortical infarctions are complementary in predicting the risk of progression from MCI to dementia.
Results:
Seventy-five subjects with MCI progressed to dementia by last follow-up. The model that best predicted progression to dementia included age, sex, hippocampal volumes, N-acetylaspartate (NAA)/creatine (Cr) on 1H MRS, and cortical infarctions. Based on age- and sex-adjusted Kaplan–Meier plots, we estimated that by 3 years, 26% of the MCI patients with normal hippocampal volumes, NAA/Cr ratios >1 SD, and no cortical infarctions will progress to dementia, compared with 78% of the MCI patients with hippocampal atrophy, low NAA/Cr (≤1 SD), and cortical infarction.
Conclusions:
Multiple magnetic resonance (MR) markers of underlying dementia pathologies improve the ability to identify patients with prodromal dementia over a single MR marker, supporting the concept that individuals with multiple brain pathologies have increased odds of dementia compared with individuals with a single pathology.
GLOSSARY
= Alzheimer disease;
= Alzheimer’s Disease Patient Registry;
= Alzheimer’s Disease Research Center;
= Akaike Information Criteria;
= amnestic mild cognitive impairment;
= Clinical Dementia Rating;
= choline;
= confidence interval;
= creatine;
= dementia with Lewy bodies;
= Diagnostic and Statistical Manual of Mental Disorders;
= fluid-attenuated inversion recovery;
= frontotemporal lobar degeneration;
= hazard ratio;
= mild cognitive impairment;
= myoinositol;
= Mini-Mental State Examination;
= magnetic resonance;
= magnetic resonance spectroscopy;
= N-acetylaspartate;
= nonamnestic mild cognitive impairment;
= National Institute on Aging;
= white matter hyperintensity.
doi:10.1212/WNL.0b013e3181a2e864
PMCID: PMC2843530  PMID: 19398707
13.  Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: implications for sequence of pathological events in Alzheimer's disease 
Brain  2009;132(5):1355-1365.
The purpose of this study was to use serial imaging to gain insight into the sequence of pathologic events in Alzheimer's disease, and the clinical features associated with this sequence. We measured change in amyloid deposition over time using serial 11C Pittsburgh compound B (PIB) positron emission tomography and progression of neurodegeneration using serial structural magnetic resonance imaging. We studied 21 healthy cognitively normal subjects, 32 with amnestic mild cognitive impairment and 8 with Alzheimer's disease. Subjects were drawn from two sources—ongoing longitudinal registries at Mayo Clinic, and the Alzheimer's disease Neuroimaging Initiative (ADNI). All subjects underwent clinical assessments, MRI and PIB studies at two time points, approximately one year apart. PIB retention was quantified in global cortical to cerebellar ratio units and brain atrophy in units of cm3 by measuring ventricular expansion. The annual change in global PIB retention did not differ by clinical group (P = 0.90), and although small (median 0.042 ratio units/year overall) was greater than zero among all subjects (P < 0.001). Ventricular expansion rates differed by clinical group (P < 0.001) and increased in the following order: cognitively normal (1.3 cm3/year) <  amnestic mild cognitive impairment (2.5 cm3/year) <  Alzheimer's disease (7.7 cm3/year). Among all subjects there was no correlation between PIB change and concurrent change on CDR-SB (r = −0.01, P = 0.97) but some evidence of a weak correlation with MMSE (r =−0.22, P = 0.09). In contrast, greater rates of ventricular expansion were clearly correlated with worsening concurrent change on CDR-SB (r = 0.42, P < 0.01) and MMSE (r =−0.52, P < 0.01). Our data are consistent with a model of typical late onset Alzheimer's disease that has two main features: (i) dissociation between the rate of amyloid deposition and the rate of neurodegeneration late in life, with amyloid deposition proceeding at a constant slow rate while neurodegeneration accelerates and (ii) clinical symptoms are coupled to neurodegeneration not amyloid deposition. Significant plaque deposition occurs prior to clinical decline. The presence of brain amyloidosis alone is not sufficient to produce cognitive decline, rather, the neurodegenerative component of Alzheimer's disease pathology is the direct substrate of cognitive impairment and the rate of cognitive decline is driven by the rate of neurodegeneration. Neurodegeneration (atrophy on MRI) both precedes and parallels cognitive decline. This model implies a complimentary role for MRI and PIB imaging in Alzheimer's disease, with each reflecting one of the major pathologies, amyloid dysmetabolism and neurodegeneration.
doi:10.1093/brain/awp062
PMCID: PMC2677798  PMID: 19339253
Alzheimer's disease; amyloid imaging; magnetic resonance imaging, longitudinal imaging; mild cognitive impairment; Pittsburgh compound B
14.  The Dynamics of Cortical and Hippocampal Atrophy in Alzheimer Disease 
Archives of neurology  2011;68(8):1040-1048.
Objective
To characterize rates of regional Alzheimer disease (AD)–specific brain atrophy across the presymptomatic, mild cognitive impairment, and dementia stages.
Design
Multicenter case-control study of neuroimaging, cerebrospinal fluid, and cognitive test score data from the Alzheimer’s Disease Neuroimaging Initiative.
Setting
Research centers across the United States and Canada.
Patients
We examined a total of 317 participants with base-line cerebrospinal fluid biomarker measurements and 3T1-weighted magnetic resonance images obtained within 1 year.
Main Outcome Measures
We used automated tools to compute annual longitudinal atrophy in the hippocampus and cortical regions targeted in AD. We used Mini-Mental State Examination scores as a measure of cognitive performance. We performed a cross-subject analysis of atrophy rates and acceleration on individuals with an AD-like cerebrospinal fluid molecular profile.
Results
In presymptomatic individuals harboring indicators of AD, baseline thickness in AD-vulnerable cortical regions was significantly reduced compared with that of healthy control individuals, but baseline hippocampal volume was not. Across the clinical spectrum, rates of AD-specific cortical thinning increased with decreasing cognitive performance before peaking at approximately the Mini-Mental State Examination score of 21, beyond which rates of thinning started to decline. Annual rates of hippocampal volume loss showed a continuously increasing pattern with decreasing cognitive performance as low as the Mini-Mental State Examination score of 15. Analysis of the second derivative of imaging measurements revealed that AD-specific cortical thinning exhibited early acceleration followed by deceleration. Conversely, hippocampal volume loss exhibited positive acceleration across all study participants.
Conclusions
Alzheimer disease–specific cortical thinning and hippocampal volume loss are consistent with a sigmoidal pattern, with an acceleration phase during the early stages of the disease. Clinical trials should carefully consider the nonlinear behavior of these AD biomarkers.
doi:10.1001/archneurol.2011.167
PMCID: PMC3248949  PMID: 21825241
15.  MRI of hippocampal volume loss in early Alzheimer's disease in relation to ApoE genotype and biomarkers 
Brain  2009;132(4):1067-1077.
Hippocampal volume change over time, measured with MRI, has huge potential as a marker for Alzheimer's disease. The objectives of this study were: (i) to test if constant and accelerated hippocampal loss can be detected in Alzheimer's disease, mild cognitive impairment and normal ageing over short periods, e.g. 6–12 months, with MRI in the large multicentre setting of the Alzheimer's Disease Neuroimaging Initiative (ADNI); (ii) to determine the extent to which the polymorphism of the apolipoprotein E (ApoE) gene modulates hippocampal change; and (iii) to determine if rates of hippocampal loss correlate with cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease, such as the β-amyloid (Aβ1–42) and tau proteins (tau). The MRI multicentre study included 112 cognitive normal elderly individuals, 226 mild cognitive impairment and 96 Alzheimer's disease patients who all had at least three successive MRI scans, involving 47 different imaging centres. The mild cognitive impairment and Alzheimer's disease groups showed hippocampal volume loss over 6 months and accelerated loss over 1 year. Moreover, increased rates of hippocampal loss were associated with presence of the ApoE allele ɛ4 gene in Alzheimer's disease and lower CSF Aβ1–42 in mild cognitive impairment, irrespective of ApoE genotype, whereas relations with tau were only trends. The power to measure hippocampal change was improved by exploiting correlations statistically between successive MRI observations. The demonstration of considerable hippocampal loss in mild cognitive impairment and Alzheimer's disease patients over only 6 months and accelerated loss over 12 months illustrates the power of MRI to track morphological brain changes over time in a large multisite setting. Furthermore, the relations between faster hippocampal loss in the presence of ApoE allele ɛ4 and decreased CSF Aβ1–42 supports the concept that increased hippocampal loss is an indicator of Alzheimer's disease pathology and a potential marker for the efficacy of therapeutic interventions in Alzheimer's disease.
doi:10.1093/brain/awp007
PMCID: PMC2668943  PMID: 19251758
MRI; mild cognitive impairment; ageing; human brain mapping; hippocampus
16.  Association of total tau and phosphorylated tau 181 protein levels in cerebrospinal fluid with cerebral atrophy in mild cognitive impairment and Alzheimer disease 
Background
We sought to examine the association of levels of total tau (t-tau) and phosphorylated tau 181 (p-tau181) protein with brain morphology in mild cognitive impairment, as defined by the concept of aging-associated cognitive decline (AACD) and Alzheimer disease.
Methods
Twenty-three participants with AACD, 16 with Alzheimer disease and 15 healthy controls underwent magnetic resonance imaging and lumbar puncture. We performed voxel-based morphometry to investigate the association between tau levels in cerebrospinal fluid (CSF) and cerebral grey matter density throughout the entire brain.
Results
Voxel-based morphometry revealed that both elevated t-tau and p-tau181 concentrations were associated with reduced grey matter density in temporal, parietal and frontal regions. Among participants with AACD, elevated levels of p-tau181 (but not t-tau) in CSF were correlated with a pronounced atrophy in the right hippocampus.
Limitations
Our study was limited by the small sample, especially with respect to the analysis comprising the AACD subgroups. Moreover, we did not correct our voxel-based morphometry analyses for multiple dependent comparisons, therefore they harbour a risk of false-positive results.
Conclusion
Elevated levels of t-tau and p-tau181 in CSF reflect degenerative processes in the cortical regions typically affected in Alzheimer disease. Our findings in participants with AACD support the hypothesis that p-tau181 might be more specifically related to neurodegenerative changes in early Alzheimer disease.
PMCID: PMC2647572  PMID: 19270764
17.  The Alzheimer’s Disease Neuroimaging Initiative: Progress report and future plans 
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year re-search project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer’s disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C-11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid β (Aβ) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C-11 Pittsburgh compound B PET, and CSF measurements of Aβ and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI-like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD.
doi:10.1016/j.jalz.2010.03.007
PMCID: PMC2927112  PMID: 20451868
ADNI; Alzheimer’s disease; MRI; PET; Amyloid; Memory; Tau
18.  Requiring an amyloid-β1-42 biomarker for prodromal Alzheimer’s disease or mild cognitive impairment does not lead to more efficient clinical trials 
Background
Low cerebrospinal fluid (CSF) amyloid-β1-42 concentration and high total-tau/Aβ1-42 ratio have been recommended to support the diagnosis of prodromal Alzheimer’s disease (AD) in patients with amnestic mild cognitive impairment (aMCI) and also to select patients for clinical trials.
Methods
We tested this recommendation with clinical trials simulations using patients from the Alzheimer Disease Neuroimaging Initiative who fulfilled the following entry criteria: (1) aMCI, (2) aMCI with CSF Aβ1-42 ≤192 mg/mL, (3) and aMCI with total-tau/Aβ1-42 >.0.39. For each criterion, we randomly resampled the database obtaining samples for 1000 trials for each trial scenario, planning for 1 or 2 year trials with samples from 50 to 400 patients per treatment or placebo group, with up to 40% dropouts, outcomes after using the AD assessment scale-cognitive subscale and clinical dementia rating scale with effect sizes ranging from 0.15 to 0.75, and calculated statistical power.
Findings
Approximately 70% to 74% of aMCI patients with CSF measures met biomarker criteria. The addition of the low Aβ1-42 or high tau/Aβ1-42 requirement resulted in minimal or no increase in the power of the trials compared with enrolling aMCI without requiring the biomarker criteria. Slightly larger mean differences between the placebo and treatment groups fulfilling biomarker criteria were offset by increased outcome variability within the groups.
Interpretations
Although patients with aMCI or patients with prodromal AD meeting CSF biomarkers criteria were slightly more cognitively impaired and showed greater decline than patients with aMCI diagnosed without considering the biomarkers, the requirement of biomarker-positive patients would most likely not result in more efficient clinical trials, and trials would take longer because fewer patients would be available. A CSF Aβ1-42 marker, however, could be useful as an explanatory variable or covariate when warranted by the action of a drug.
doi:10.1016/j.jalz.2010.07.004
PMCID: PMC2947209  PMID: 20813339
Alzheimer disease; Mild cognitive impairment; Biomarkers; Clinical trials; Simulations; Amyloid-beta protein; Alzheimer’s disease neuroimaging initiative (ADNI); Alzheimer’s disease assessment scale; Clinical dementia rating
19.  Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans 
The role of the Alzheimer’s Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome-wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within Alzheimer’s Disease Neuroimaging Initiative. Genome-wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer’s disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials.
doi:10.1016/j.jalz.2010.03.013
PMCID: PMC2868595  PMID: 20451875
Alzheimer’s Disease Neuroimaging Initiative (ADNI); Alzheimer’s disease; Mild cognitive impairment (MCI); Genome-wide association studies (GWAS); Copy number variation (CNV); Magnetic resonance imaging (MRI); Cerebrospinal fluid (CSF)
20.  Spatial Distribution of White-Matter Hyperintensities in Alzheimer Disease, Cerebral Amyloid Angiopathy, and Healthy Aging 
Background and Purpose
White-matter hyperintensities (WMHs) detected by magnetic resonance imaging are thought to represent the effects of cerebral small-vessel disease and neurodegenerative changes. We sought to determine whether the spatial distribution of WMHs discriminates between different disease groups and healthy aging individuals and whether these distributions are related to local cerebral perfusion patterns.
Methods
We examined the pattern of WMHs by T2/fluid-attenuated inversion recovery–weighted magnetic resonance imaging in 3 groups of subjects: cerebral amyloid angiopathy (n=32), Alzheimer disease or mild cognitive impairment (n=41), and healthy aging (n=29). WMH frequency maps were calculated for each group, and spatial distributions were compared by voxel-wise logistic regression. WMHs were also analyzed as a function of normal cerebral perfusion patterns by overlaying a single photon emission computed tomography atlas.
Results
Although WMH volume was greater in cerebral amyloid angiopathy and Alzheimer disease/mild cognitive impairment than in healthy aging, there was no consistent difference in the spatial distributions when controlling for total WMH volume. Hyperintensities were most frequent in the deep periventricular WM in all 3 groups. A strong inverse correlation between hyperintensity frequency and normal perfusion was demonstrated in all groups, demonstrating that WMHs were most common in regions of relatively lower normal cerebral perfusion.
Conclusions
WMHs show a common distribution pattern and predilection for cerebral WM regions with lower atlas-derived perfusion, regardless of the underlying diagnosis. These data suggest that across diverse disease processes, WM injury may occur in a pattern that reflects underlying tissue properties, such as relative perfusion.
doi:10.1161/STROKEAHA.107.497438
PMCID: PMC2754400  PMID: 18292383
Alzheimer disease; cerebral amyloid angiopathy; magnetic resonance imaging; perfusion; white-matter hyperintensities
21.  Subtypes based on CSF and MRI markers in normal elderly predict cognitive decline 
Neurobiology of aging  2010;31(8):1419-1428.
Background
Cerebrospinal fluid (CSF) and structural magnetic resonance imaging (MRI) show patterns of change in Alzheimer’s disease (AD) that precede dementia. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) studied normal controls (NC), subjects with mild cognitive impairment (MCI) and AD to identify patterns of biomarkers to aid in early diagnosis and effective treatment of AD.
Methods
222 NC underwent baseline MRI and clinical examination at baseline and at least one follow-up. 112 also provided CSF at baseline. Unsupervised clustering based on initial CSF and MRI measures was used to identify clusters of participants with similar profiles. Repeated measures regression modeling assessed the relationship of individual measures, and of cluster membership, to cognitive change over three years.
Results
Most individuals showed little cognitive change. Individual biomarkers had limited predictive value for cognitive decline, but membership in the cluster with the most extreme profile was associated with more rapid decline in ADAS-COG.
Conclusions
Subtypes among NC based on multiple biomarkers may represent the earliest stages of subclinical cognitive decline and AD.
doi:10.1016/j.neurobiolaging.2010.04.025
PMCID: PMC2902683  PMID: 20542598
Alzheimer’s disease; Dementia; Early diagnosis; Cerebrospinal fluid; Tau protein; Amyloid beta-protein; Structural magnetic resonance imaging; Hippocampal volume; Cognition; Clustering; Normal controls
22.  Subgroup of ADNI Normal Controls Characterized by Atrophy and Cognitive Decline Associated With Vascular Damage 
Psychology and aging  2013;28(1):191-201.
Previous work examining Alzheimer’s Disease Neuroimaging Initiative (ADNI) normal controls using cluster analysis identified a subgroup characterized by substantial brain atrophy and white matter hyperintensities (WMH). We hypothesized that these effects could be related to vascular damage. Fifty-three individuals in the suspected vascular cluster (Normal 2) were compared with 31 individuals from the cluster characterized as healthy/typical (Normal 1) on a variety of outcomes, including magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) biomarkers, vascular risk factors and outcomes, cognitive trajectory, and medications for vascular conditions. Normal 2 was significantly older but did not differ on ApoE4+ prevalence. Normal 2 differed significantly from Normal 1 on all MRI measures but not on Amyloid-Beta1-42 or total tau protein. Normal 2 had significantly higher body mass index (BMI), Hachinksi score, and creatinine levels, and took significantly more medications for vascular conditions. Normal 2 had marginally significantly higher triglycerides and blood glucose. Normal 2 had a worse cognitive trajectory on the Rey’s Auditory Verbal Learning Test (RAVLT) 30-min delay test and the Functional Activity Questionnaire (FAQ). Cerebral atrophy associated with multiple vascular risks is common among cognitively normal individuals, forming a distinct subgroup with significantly increased cognitive decline. Further studies are needed to determine the clinical impact of these findings.
doi:10.1037/a0031063
PMCID: PMC3751169  PMID: 23527743
ADNI; vascular; cognitive decline; biomarkers; cluster
23.  Differential White Matter Connectivity in Early Mild Cognitive Impairment According to CSF Biomarkers 
PLoS ONE  2014;9(3):e91400.
Mild cognitive impairment (MCI) is a heterogeneous group and certain MCI subsets eventually convert to dementia. Cerebrospinal fluid (CSF) biomarkers are known to predict this conversion. We sought evidence for the differences in white matter connectivity between early amnestic MCI (EMCI) subgroups according to a CSF phosphorylated tau181p/amyloid beta1–42 ratio of 0.10. From the Alzheimer's Disease Neuroimaging Initiative database, 16 high-ratio, 25 low-ratio EMCI patients, and 20 normal controls with diffusion tensor images and CSF profiles were included. Compared to the high-ratio group, radial diffusivity significantly increased in both sides of the corpus callosum and the superior and inferior longitudinal fasciculus in the low-ratio group. In widespread white matter skeleton regions, the low-ratio group showed significantly increased mean, axial, and radial diffusivity compared to normal controls. However, the high-ratio group showed no differences when compared to the normal group. In conclusion, our study revealed that there were significant differences in white matter connectivity between EMCI subgroups according to CSF phosphorylated tau181p/amyloid beta1–42ratios.
doi:10.1371/journal.pone.0091400
PMCID: PMC3948821  PMID: 24614676
24.  Is it time for biomarker-based diagnostic criteria for prodromal Alzheimer's disease? 
Drug candidates targeting amyloid-β (Aβ) pathology in Alzheimer's disease are in different phases of clinical trials. These treatments will probably be most effective in the earlier stages of the disease, before neurodegeneration is too severe, but at the same time symptoms are vague and the clinical diagnosis is difficult. Recent research advances have resulted in promising biomarkers, including cerebrospinal fluid analyses for tau and Aβ, magnetic resonance imaging measurement of atrophy, and positron emission tomography imaging of glucose metabolism and Aβ pathology, which allow identification of prodromal Alzheimer's disease. More details are needed, however, on how these biomarkers can be standardized, to allow a general implementation in the clinical routine diagnostic work-up of patients with cognitive disturbances.
doi:10.1186/alzrt31
PMCID: PMC2876786  PMID: 20441609
25.  Biomarkers in Alzheimer’s Disease 
Alzheimer’s disease (AD) is the most common form of dementia in the elderly, and it is characterized by progressive impairment in multiple cognitive domains of sufficient severity to interfere with individuals’ daily living activities. Historically, the diagnosis of AD has been based on the identification of a clinical syndrome, and accuracy studies of the current clinical criteria conducted in referral clinics have shown high sensitivity for AD. However, the identification of the disease is still not perfect, and there is growing evidence that the use of biomarkers will increase our ability to better indentify the underlying biology of AD, especially in its early stages. These biomarkers will improve the detection of the patients suitable for research studies and drug trials, and they will contribute to a better management of the disease in the clinical practice. In this review, we discuss the most studied biomarkers in AD: cerebrospinal fluid proteins, structural magnetic resonance imaging, functional neuroimaging techniques, and amyloid imaging.
doi:10.3389/fneur.2011.00046
PMCID: PMC3139171  PMID: 21808632
Alzheimer’s disease; mild cognitive impairment; biomarker; cerebrospinal fluid; magnetic resonance imaging; positron emission tomography

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