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1.  APOE ε4 does not modulate amyloid-β associated neurodegeneration in preclinical Alzheimer’s disease 
Background and Purpose
Among cognitively normal older individuals, the relationship between the two hallmark proteins of Alzheimer’s disease (AD), amyloid-β (Aβ) and tau, the ε4 allele of apolipoprotein E (APOE ε4), and neurodegeneration is not well understood.
Materials and Methods
We examined 107 cognitively healthy older adults who underwent longitudinal MR imaging and baseline lumbar puncture. Within the same linear mixed effects model, we concurrently investigated main and interactive effects between APOE ε4 genotype and CSF Aβ1-42, CSF phospo-tau (p-tau181p) and CSF Aβ1-42, and APOE ε4 genotype and CSF p-tau181p on entorhinal cortex atrophy rate. We also examined the relationship between APOE ε4, CSF p-tau181p, and CSF Aβ1-42 on atrophy rate of other AD-vulnerable neuroanatomic regions.
Results
The full model with main and interactive effects demonstrated a significant interaction only between CSF p-tau181p and CSF Aβ1-42 on entorhinal cortex atrophy rate indicating elevated atrophy over time in individuals with increased CSF p-tau181p and decreased CSF Aβ1-42. APOE ε4 genotype was significantly and specifically associated with CSF Aβ1-42. However, the interaction between APOE ε4 genotype and either CSF Aβ1-42 or CSF p-tau181p on entorhinal cortex atrophy rate was not significant. We found similar results in other AD-vulnerable regions.
Conclusions
Based upon our findings and building upon prior experimental evidence, we propose a model of the pathogenic cascade underlying preclinical AD where APOE ε4 primarily influences Alzheimer’s pathology via Aβ-related mechanisms and in turn, Aβ-associated neurodegeneration occurs only in the presence of phospho-tau.
doi:10.3174/ajnr.A3267
PMCID: PMC4041629  PMID: 22976236
preclinical AD; neurodegeneration; p-tau; amyloid-β; APOE
2.  Higher Rates of Decline for Women and APOE ε4 Carriers 
Background and Purpose
Age and the ε4 allele of apolipoprotein E (APOE ε4) are well-known risk factors for Alzheimer disease (AD), but whether female sex is also a risk factor remains controversial. It is also unclear how these risk factors affect rates of structural brain and clinical decline across the spectrum of preclinical to clinical AD. Our objective is to estimate the effects of APOE ε4 and sex on age-specific rates of morphometric and clinical decline in late onset sporadic AD.
Materials and Methods
Using linear mixed effects models, we examined the effect of age, APOE ε4, and sex on longitudinal brain atrophy and clinical decline among cognitively normal older individuals, and individuals with mild cognitive impairment and AD (total = 688). We also evaluated the relationship between these effects and cerebrospinal fluid (CSF) biomarkers of AD pathology.
Results
APOE ε4 significantly accelerated rates of decline, and women in all cohorts experienced higher rates of decline than men. The magnitude of the sex effect on rates of decline were as large as those of ε4, yet their relationship to measures of CSF biomarkers were weaker.
Conclusion
These results indicate that in addition to APOE ε4 status, diagnostic and therapeutic strategies should take into account the effect of female sex on the Alzheimer disease process.
doi:10.3174/ajnr.A3601
PMCID: PMC3894062  PMID: 23828104
3.  Heart fatty acid binding protein and Aβ-associated Alzheimer’s neurodegeneration 
Background
Epidemiological and molecular findings suggest a relationship between Alzheimer’s disease (AD) and dyslipidemia, although the nature of this association is not well understood.
Results
Using linear mixed effects models, we investigated the relationship between CSF levels of heart fatty acid binding protein (HFABP), a lipid binding protein involved with fatty acid metabolism and lipid transport, amyloid-β (Aβ), phospho-tau, and longitudinal MRI-based measures of brain atrophy among 295 non-demented and demented older individuals. Across all participants, we found a significant association of CSF HFABP with longitudinal atrophy of the entorhinal cortex and other AD-vulnerable neuroanatomic regions. However, we found that the relationship between CSF HABP and brain atrophy was significant only among those with low CSF Aβ1–42 and occurred irrespective of phospho-tau181p status.
Conclusions
Our findings indicate that Aβ-associated volume loss occurs in the presence of elevated HFABP irrespective of phospho-tau. This implicates a potentially important role for fatty acid binding proteins in Alzheimer’s disease neurodegeneration.
doi:10.1186/1750-1326-8-39
PMCID: PMC3850652  PMID: 24088526
Alzheimer’s disease; Fatty acids; Lipids; Amyloid; Tau; Brain atrophy
4.  Improved Detection of Common Variants Associated with Schizophrenia and Bipolar Disorder Using Pleiotropy-Informed Conditional False Discovery Rate 
PLoS Genetics  2013;9(4):e1003455.
Several lines of evidence suggest that genome-wide association studies (GWAS) have the potential to explain more of the “missing heritability” of common complex phenotypes. However, reliable methods to identify a larger proportion of single nucleotide polymorphisms (SNPs) that impact disease risk are currently lacking. Here, we use a genetic pleiotropy-informed conditional false discovery rate (FDR) method on GWAS summary statistics data to identify new loci associated with schizophrenia (SCZ) and bipolar disorders (BD), two highly heritable disorders with significant missing heritability. Epidemiological and clinical evidence suggest similar disease characteristics and overlapping genes between SCZ and BD. Here, we computed conditional Q–Q curves of data from the Psychiatric Genome Consortium (SCZ; n = 9,379 cases and n = 7,736 controls; BD: n = 6,990 cases and n = 4,820 controls) to show enrichment of SNPs associated with SCZ as a function of association with BD and vice versa with a corresponding reduction in FDR. Applying the conditional FDR method, we identified 58 loci associated with SCZ and 35 loci associated with BD below the conditional FDR level of 0.05. Of these, 14 loci were associated with both SCZ and BD (conjunction FDR). Together, these findings show the feasibility of genetic pleiotropy-informed methods to improve gene discovery in SCZ and BD and indicate overlapping genetic mechanisms between these two disorders.
Author Summary
Genome-wide association studies (GWAS) have thus far identified only a small fraction of the heritability of common complex disorders, such as severe mental disorders. We used a conditional false discovery rate approach for analysis of GWAS data, exploiting “genetic pleiotropy” to increase discovery of common gene variants associated with schizophrenia and bipolar disorders. Leveraging the increased power from combining GWAS of two associated phenotypes, we found a striking overlap in polygenic signals, allowing for the discovery of several new common gene variants associated with bipolar disorder and schizophrenia that were not identified in the original analysis using traditional GWAS methods. Some of the gene variants have been identified in other studies with large targeted replication samples, validating the present findings. Our pleiotropy-informed method may be of significant importance for detecting effects that are below the traditional genome-wide significance level in GWAS, particularly in highly polygenic, complex phenotypes, such as schizophrenia and bipolar disorder, where most of the genetic signal is missing (i.e., “missing heritability”). The findings also offer insights into mechanistic relationships between bipolar disorder and schizophrenia pathogenesis.
doi:10.1371/journal.pgen.1003455
PMCID: PMC3636100  PMID: 23637625
5.  Enrichment and Stratification for Predementia Alzheimer Disease Clinical Trials 
PLoS ONE  2012;7(10):e47739.
The tau and amyloid pathobiological processes underlying Alzheimer disease (AD) progresses slowly over periods of decades before clinical manifestation as mild cognitive impairment (MCI), then more rapidly to dementia, and eventually to end-stage organ failure. The failure of clinical trials of candidate disease modifying therapies to slow disease progression in patients already diagnosed with early AD has led to increased interest in exploring the possibility of early intervention and prevention trials, targeting MCI and cognitively healthy (HC) populations. Here, we stratify MCI individuals based on cerebrospinal fluid (CSF) biomarkers and structural atrophy risk factors for the disease. We also stratify HC individuals into risk groups on the basis of CSF biomarkers for the two hallmark AD pathologies. Results show that the broad category of MCI can be decomposed into subsets of individuals with significantly different average regional atrophy rates. By thus selectively identifying individuals, combinations of these biomarkers and risk factors could enable significant reductions in sample size requirements for clinical trials of investigational AD-modifying therapies, and provide stratification mechanisms to more finely assess response to therapy. Power is sufficiently high that detecting efficacy in MCI cohorts should not be a limiting factor in AD therapeutics research. In contrast, we show that sample size estimates for clinical trials aimed at the preclinical stage of the disorder (HCs with evidence of AD pathology) are prohibitively large. Longer natural history studies are needed to inform design of trials aimed at the presymptomatic stage.
doi:10.1371/journal.pone.0047739
PMCID: PMC3474753  PMID: 23082203
6.  Amyloid-β associated volume loss occurs only in the presence of phospho-tau 
Annals of Neurology  2011;70(4):657-661.
The relationship between neurodegeneration and the two hallmark proteins of Alzheimer's disease, amyloid-β (Aβ) and tau, is still unclear. Here, we examined 286 non-demented participants (107 cognitively normal older adults and 179 memory impaired individuals) who underwent longitudinal MR imaging and lumbar puncture. Using mixed effects models, we investigated the relationship between longitudinal entorhinal cortex atrophy, CSF p-tau181p and CSF Aβ1-42. We found a significant relationship between elevated entorhinal cortex atrophy and decreased CSF Aβ1-42 only with elevated CSF p-tau181p. Our findings indicate that Aβ-associated volume loss occurs only in the presence of phospho-tauin humans at risk for dementia.
doi:10.1002/ana.22509
PMCID: PMC3368003  PMID: 22002658
7.  Amyloid-β associated clinical decline occurs only in the presence of elevated p-tau 
Archives of neurology  2012;69(6):709-713.
Objective
To elucidate the relationship between the two hallmark proteins of Alzheimer's disease (AD), amyloid-β (Aβ) and tau, and clinical decline over time among cognitively normal older individuals.
Design
A longitudinal cohort of clinically and cognitively normal older individuals assessed with baseline lumbar puncture and longitudinal clinical assessments.
Setting
Research centers across the United States and Canada.
Patients
We examined one hundred seven participants with a Clinical Dementia Rating (CDR) of 0 at baseline examination.
Main Outcome Measures
Using linear mixed effects models, we investigated the relationship between CSF p-tau181p, CSF Aβ1-42 and clinical decline as assessed using longitudinal change in global CDR, CDR-Sum of Boxes (CDR-SB), and the Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog).
Results
We found a significant relationship between decreased CSF Aβ1-42 and longitudinal change in global CDR, CDR-SB, and ADAS-cog in individuals with elevated CSF p-tau181p. In the absence of CSF p-tau181p, the effect of CSF Aβ1-42 on longitudinal clinical decline was not significantly different from zero.
Conclusions
In cognitively normal older individuals, Aβ-associated clinical decline over a mean of three years may occur only in the presence of ongoing, “downstream” neurodegeneration.
doi:10.1001/archneurol.2011.3354
PMCID: PMC3423526  PMID: 22529247
8.  Rates of Decline in Alzheimer Disease Decrease with Age 
PLoS ONE  2012;7(8):e42325.
Age is the strongest risk factor for sporadic Alzheimer disease (AD), yet the effects of age on rates of clinical decline and brain atrophy in AD have been largely unexplored. Here, we examined longitudinal rates of change as a function of baseline age for measures of clinical decline and structural MRI-based regional brain atrophy, in cohorts of AD, mild cognitive impairment (MCI), and cognitively healthy (HC) individuals aged 65 to 90 years (total n = 723). The effect of age was modeled using mixed effects linear regression. There was pronounced reduction in rates of clinical decline and atrophy with age for AD and MCI individuals, whereas HCs showed increased rates of clinical decline and atrophy with age. This resulted in convergence in rates of change for HCs and patients with advancing age for several measures. Baseline cerebrospinal fluid densities of AD-relevant proteins, Aβ1–42, tau, and phospho-tau181p (ptau), showed a similar pattern of convergence with advanced age across cohorts, particularly for ptau. In contrast, baseline clinical measures did not differ by age, indicating uniformity of clinical severity at baseline. These results imply that the phenotypic expression of AD is relatively mild in individuals older than approximately 85 years, and this may affect the ability to distinguish AD from normal aging in the very old. Our findings show that inclusion of older individuals in clinical trials will substantially reduce the power to detect disease-modifying therapeutic effects, leading to dramatic increases in required clinical trial sample sizes with age of study sample.
doi:10.1371/journal.pone.0042325
PMCID: PMC3410919  PMID: 22876315
9.  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
10.  Automated MRI measures predict progression to Alzheimer's disease 
Neurobiology of aging  2010;31(8):1364-1374.
The prediction of individuals with mild cognitive impairment (MCI) destined to develop Alzheimer's disease (AD) is of increasing clinical importance. In this study, using baseline T1-weighted MRI scans of 324 MCI individuals from two cohorts and automated software tools, we employed factor analyses and Cox proportional hazards models to identify a set of neuroanatomic measures that best predicted the time to progress from MCI to AD. For comparison, cerebrospinal fluid (CSF) assessments of cellular pathology and positron emission tomography (PET) measures of metabolic activity were additionally examined. By three years follow-up, 60 MCI individuals from the first cohort and 58 MCI individuals from the second cohort had progressed to a diagnosis of AD. Cox models on the first cohort demonstrated significant effects for the medial temporal factor [Hazards Ratio (HR) =0.43{95% Confidence Interval (CI), 0.32-0.55}, p < 0.0001], the fronto-parietoccipital factor [HR=0.59{95% CI, 0.48-0.80}, p < 0.001], and the lateral temporal factor [HR=0.67 {95% CI, 0.52-0.87}, p < 0.01]. When applied to the second cohort, these Cox models showed significant effects for the medial temporal factor [HR=0.44 {0.32-0.61}, p < 0.001] and lateral temporal factor [HR=0.49 {0.38-0.62}, p < 0.001]. In a combined Cox model, consisting of individual CSF, PET, and MRI measures that best predicted disease progression, only the medial temporal factor [HR=0.53 {95% CI, 0.34-0.81}, p < 0.001] demonstrated a significant effect. These findings illustrate that automated MRI measures of the medial temporal cortex accurately and reliably predict time to disease progression, outperform cellular and metabolic measures as predictors of clinical decline, and can potentially serve as a predictive marker for AD.
doi:10.1016/j.neurobiolaging.2010.04.023
PMCID: PMC2902697  PMID: 20570399
computational MRI; AD; MCI; clinical biomarker
11.  Genetic Variation and Neuroimaging Measures in Alzheimer Disease 
Archives of neurology  2010;67(6):677-685.
Objective
To investigate whether genome-wide association study (GWAS)–validated and GWAS-promising candidate loci influence magnetic resonance imaging measures and clinical Alzheimer’s disease (AD) status.
Design
Multicenter case-control study of genetic and neuroimaging data from the Alzheimer’s Disease Neuroimaging Initiative.
Setting
Multicenter GWAS.
Patients
A total of 168 individuals with probable AD, 357 with mild cognitive impairment, and 215 cognitively normal control individuals recruited from more than 50 Alzheimer’s Disease Neuroimaging Initiative centers in the United States and Canada. All study participants had APOE and genome-wide genetic data available.
Main Outcome Measures
We investigated the influence of GWAS-validated and GWAS-promising novel AD loci on hippocampal volume, amygdala volume, white matter lesion volume, entorhinal cortex thickness, parahippocampal gyrus thickness, and temporal pole cortex thickness.
Results
Markers at the APOE locus were associated with all phenotypes except white matter lesion volume (all false discovery rate–corrected P values < .001). Novel and established AD loci identified by prior GWASs showed a significant cumulative score–based effect (false discovery rate P=.04) on all analyzed neuroimaging measures. The GWAS-validated variants at the CR1 and PICALM loci and markers at 2 novel loci (BIN1 and CNTN5) showed association with multiple magnetic resonance imaging characteristics (false discovery rate P <.05).
Conclusions
Loci associated with AD also influence neuroimaging correlates of this disease. Furthermore, neuroimaging analysis identified 2 additional loci of high interest for further study.
doi:10.1001/archneurol.2010.108
PMCID: PMC2956757  PMID: 20558387
12.  Selective Disruption of the Cerebral Neocortex in Alzheimer's Disease 
PLoS ONE  2010;5(9):e12853.
Background
Alzheimer's disease (AD) and its transitional state mild cognitive impairment (MCI) are characterized by amyloid plaque and tau neurofibrillary tangle (NFT) deposition within the cerebral neocortex and neuronal loss within the hippocampal formation. However, the precise relationship between pathologic changes in neocortical regions and hippocampal atrophy is largely unknown.
Methodology/Principal Findings
In this study, combining structural MRI scans and automated image analysis tools with reduced cerebrospinal fluid (CSF) Aß levels, a surrogate for intra-cranial amyloid plaques and elevated CSF phosphorylated tau (p-tau) levels, a surrogate for neocortical NFTs, we examined the relationship between the presence of Alzheimer's pathology, gray matter thickness of select neocortical regions, and hippocampal volume in cognitively normal older participants and individuals with MCI and AD (n = 724). Amongst all 3 groups, only select heteromodal cortical regions significantly correlated with hippocampal volume. Amongst MCI and AD individuals, gray matter thickness of the entorhinal cortex and inferior temporal gyrus significantly predicted longitudinal hippocampal volume loss in both amyloid positive and p-tau positive individuals. Amongst cognitively normal older adults, thinning only within the medial portion of the orbital frontal cortex significantly differentiated amyloid positive from amyloid negative individuals whereas thinning only within the entorhinal cortex significantly discriminated p-tau positive from p-tau negative individuals.
Conclusions/Significance
Cortical Aβ and tau pathology affects gray matter thinning within select neocortical regions and potentially contributes to downstream hippocampal degeneration. Neocortical Alzheimer's pathology is evident even amongst older asymptomatic individuals suggesting the existence of a preclinical phase of dementia.
doi:10.1371/journal.pone.0012853
PMCID: PMC2944799  PMID: 20886094
13.  Effects of Registration Regularization and Atlas Sharpness on Segmentation Accuracy 
In this paper, we propose a unified framework for computing atlases from manually labeled data at various degrees of “sharpness” and the joint registration-segmentation of a new brain with these atlases. In non-rigid registration, the tradeoff between warp regularization and image fidelity is typically set empirically. In segmentation, this leads to a probabilistic atlas of arbitrary “sharpness”: weak regularization results in well-aligned training images and a “sharp” atlas; strong regularization yields a “blurry” atlas. We study the effects of this tradeoff in the context of cortical surface parcellation by comparing three special cases of our framework, namely: progressive registration-segmentation of a new brain to increasingly “sharp” atlases with increasingly flexible warps; secondly, progressive registration to a single atlas with increasingly flexible warps; and thirdly, registration to a single atlas with fixed constrained warps. The optimal parcellation in all three cases corresponds to a unique balance of atlas “sharpness” and warp regularization that yield statistically significant improvements over the previously demonstrated parcellation results.
PMCID: PMC2858002  PMID: 18051118
Registration; Segmentation; Parcellation; Multiple Atlases; Markov Random Field; Regularization
14.  Effects of Registration Regularization and Atlas Sharpness on Segmentation Accuracy 
Medical image analysis  2008;12(5):603-615.
In non-rigid registration, the tradeoff between warp regularization and image fidelity is typically determined empirically. In atlas-based segmentation, this leads to a probabilistic atlas of arbitrary sharpness: weak regularization results in well-aligned training images and a sharp atlas; strong regularization yields a “blurry” atlas.
In this paper, we employ a generative model for the joint registration and segmentation of images. The atlas construction process arises naturally as estimation of the model parameters. This framework allows the computation of unbiased atlases from manually labeled data at various degrees of “sharpness”, as well as the joint registration and segmentation of a novel brain in a consistent manner.
We study the effects of the tradeoff of atlas sharpness and warp smoothness in the context of cortical surface parcellation. This is an important question because of the increasingly availability of atlases in public databases and the development of registration algorithms separate from the atlas construction process. We find that the optimal segmentation (parcellation) corresponds to a unique balance of atlas sharpness and warp regularization, yielding statistically significant improvements over the FreeSurfer parcellation algorithm. Furthermore, we conclude that one can simply use a single atlas computed at an optimal sharpness for the registration-segmentation of a new subject with a pre-determined, fixed, optimal warp constraint. The optimal atlas sharpness and warp smoothness can be determined by probing the segmentation performance on available training data. Our experiments also suggest that segmentation accuracy is tolerant up to a small mismatch between atlas sharpness and warp smoothness.
doi:10.1016/j.media.2008.06.005
PMCID: PMC2615799  PMID: 18667352
Generative Model; Registration; Segmentation; Parcellation; Multiple Atlases; Markov Random Field; Regularization
15.  Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease* 
Brain  2009;132(8):2048-2057.
Mild cognitive impairment can represent a transitional state between normal ageing and Alzheimer's disease. Non-invasive diagnostic methods are needed to identify mild cognitive impairment individuals for early therapeutic interventions. Our objective was to determine whether automated magnetic resonance imaging-based measures could identify mild cognitive impairment individuals with a high degree of accuracy. Baseline volumetric T1-weighted magnetic resonance imaging scans of 313 individuals from two independent cohorts were examined using automated software tools to identify the volume and mean thickness of 34 neuroanatomic regions. The first cohort included 49 older controls and 48 individuals with mild cognitive impairment, while the second cohort included 94 older controls and 57 mild cognitive impairment individuals. Sixty-five patients with probable Alzheimer's disease were also included for comparison. For the discrimination of mild cognitive impairment, entorhinal cortex thickness, hippocampal volume and supramarginal gyrus thickness demonstrated an area under the curve of 0.91 (specificity 94%, sensitivity 74%, positive likelihood ratio 12.12, negative likelihood ratio 0.29) for the first cohort and an area under the curve of 0.95 (specificity 91%, sensitivity 90%, positive likelihood ratio 10.0, negative likelihood ratio 0.11) for the second cohort. For the discrimination of Alzheimer's disease, these three measures demonstrated an area under the curve of 1.0. The three magnetic resonance imaging measures demonstrated significant correlations with clinical and neuropsychological assessments as well as with cerebrospinal fluid levels of tau, hyperphosphorylated tau and abeta 42 proteins. These results demonstrate that automated magnetic resonance imaging measures can serve as an in vivo surrogate for disease severity, underlying neuropathology and as a non-invasive diagnostic method for mild cognitive impairment and Alzheimer's disease.
doi:10.1093/brain/awp123
PMCID: PMC2714061  PMID: 19460794
MRI; mild cognitive impairment; Alzheimer's disease; diagnostic marker
16.  Temporoparietal MRI Measures of Atrophy in Subjects with Mild Cognitive Impairment that Predict Subsequent Diagnosis of Alzheimer’s Disease 
Background and Purpose
Mild cognitive impairment (MCI) represents a transitional state between normal aging and Alzheimer’s disease (AD). Our goal was to determine if specific temporoparietal regions can predict the time to progress from MCI to AD.
Methods
MRI scans from 129 individuals with MCI were analyzed to identify the volume of 14 neocortical and 2 non-neocortical brain regions, comprising the temporal and parietal lobes. In addition, three neuropsychological test scores were included to determine whether they would provide independent information. After a mean follow-up time of 5 years, 44 of these individuals had progressed to a diagnosis of AD.
Results
Cox proportional hazards models demonstrated significant effects for six MRI regions with the greatest differences being: entorhinal cortex (HR=0.54, p < 0.001), inferior parietal lobule (HR=0.64, p <0.005), and middle temporal gyrus (HR=0.64, p < 0.004), indicating decreased risk with larger volumes. A multivariable model showed that a combination of the entorhinal cortex (HR = 0.60, p < 0.001) and inferior parietal lobule (HR = 0.62, p < 0.01) was the ‘best’ predictor of time to progress to AD. A multivariable model re-iterated the importance of included both MRI and neuropsychological variables in the final model.
Conclusion
These findings reaffirm the importance of the entorhinal cortex and present evidence for the importance of the inferior parietal lobule as a predictor of time to progress from MCI to AD. The inclusion of neuropsychological performance in the final model continues to highlight the importance of using these measures in a complementary fashion.
doi:10.3174/ajnr.A1397
PMCID: PMC2656417  PMID: 19112067
MRI; prodromal AD; MCI; temporal lobe; parietal lobe

Results 1-16 (16)